From 1bba167deabf2a4ac61acd82b57eb97185ba8d49 Mon Sep 17 00:00:00 2001
From: Quarto GHA Workflow Runner <quarto-github-actions-publish@example.com>
Date: Tue, 2 Apr 2024 00:04:32 +0000
Subject: [PATCH] Built site for gh-pages

---
 .nojekyll                     |   2 +-
 Projects/project1.html        |  24 +-
 Projects/project2.html        |  26 +-
 Projects/project3.html        | 435 +++++++++++++++++++++++++++++++++-
 Projects/project4.html        |  34 +--
 Projects/project5.html        |  30 +--
 Templates/DS250_Template.html |  14 +-
 search.json                   |  56 ++++-
 sitemap.xml                   |  32 +--
 9 files changed, 558 insertions(+), 95 deletions(-)

diff --git a/.nojekyll b/.nojekyll
index ead4d8f..76c7fb0 100644
--- a/.nojekyll
+++ b/.nojekyll
@@ -1 +1 @@
-8b3fa635
\ No newline at end of file
+e6969d9b
\ No newline at end of file
diff --git a/Projects/project1.html b/Projects/project1.html
index 3af2f99..54dfe76 100644
--- a/Projects/project1.html
+++ b/Projects/project1.html
@@ -4887,7 +4887,7 @@ <h2 class="anchored" data-anchor-id="elevator-pitch">Elevator pitch</h2>
 <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
 <p><strong>How does your name at your birth year compare to its use historically?</strong></p>
 <p>My name, Bethany was most popular from 1980 to 2000. Before and after that there were only a couple hundred people were given that name. However, at its height about 2,000 babies were given that name. I was born in 2004, right when the popularity of the name was dropping off.</p>
-<div id="6ba51cb8" class="cell" data-execution_count="3">
+<div id="8846e0f7" class="cell" data-execution_count="3">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
@@ -4915,9 +4915,9 @@ <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
 <span id="cb2-23"><a href="#cb2-23" aria-hidden="true" tabindex="-1"></a>bethany_plot.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="94de1b27-5c5f-4c0d-b5d8-4119b89259e0" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("94de1b27-5c5f-4c0d-b5d8-4119b89259e0")) {                    Plotly.newPlot(                        "94de1b27-5c5f-4c0d-b5d8-4119b89259e0",                        [{"hovertemplate":"year=%{x}\u003cbr\u003eNumber of babies born with the name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"","orientation":"v","showlegend":false,"x":[1920,1921,1923,1925,1926,1927,1929,1931,1932,1933,1934,1935,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015],"xaxis":"x","y":[5.0,5.0,7.0,10.0,5.0,5.0,6.0,10.0,6.0,8.0,8.0,8.0,8.0,19.0,5.0,7.0,21.0,15.0,15.0,10.0,23.0,15.0,46.0,54.0,72.0,87.0,80.0,78.0,115.0,135.0,103.0,101.0,95.0,162.0,159.0,179.0,202.0,288.0,314.0,351.0,392.0,435.0,468.0,583.0,662.0,622.0,756.0,1012.0,1161.0,1112.0,1274.0,1506.0,1760.0,2084.0,2495.0,2689.0,2709.0,2766.0,2978.0,2951.0,3076.0,3294.0,3266.0,3079.0,3228.0,3107.0,2923.0,2836.0,2773.0,2740.0,2692.0,2622.0,2485.0,2296.0,2184.0,2016.0,1787.0,1600.0,1614.0,1487.0,1385.0,1142.0,1039.0,943.0,836.0,903.0,878.0,769.0,796.0,730.0],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"year"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Number of babies born with the name"}},"legend":{"tracegroupgap":0},"title":{"text":"Popularity of the name Bethany over the years"},"shapes":[{"line":{"color":"red","dash":"dash"},"type":"line","x0":2004,"x1":2004,"xref":"x","y0":0,"y1":1,"yref":"y domain"}],"annotations":[{"showarrow":false,"text":"My birth year","x":2004,"xanchor":"right","xref":"x","y":0,"yanchor":"bottom","yref":"y domain"}]},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="bf2c00f7-9cb6-495c-aa19-d55ffc331149" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("bf2c00f7-9cb6-495c-aa19-d55ffc331149")) {                    Plotly.newPlot(                        "bf2c00f7-9cb6-495c-aa19-d55ffc331149",                        [{"hovertemplate":"year=%{x}\u003cbr\u003eNumber of babies born with the name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"","orientation":"v","showlegend":false,"x":[1920,1921,1923,1925,1926,1927,1929,1931,1932,1933,1934,1935,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015],"xaxis":"x","y":[5.0,5.0,7.0,10.0,5.0,5.0,6.0,10.0,6.0,8.0,8.0,8.0,8.0,19.0,5.0,7.0,21.0,15.0,15.0,10.0,23.0,15.0,46.0,54.0,72.0,87.0,80.0,78.0,115.0,135.0,103.0,101.0,95.0,162.0,159.0,179.0,202.0,288.0,314.0,351.0,392.0,435.0,468.0,583.0,662.0,622.0,756.0,1012.0,1161.0,1112.0,1274.0,1506.0,1760.0,2084.0,2495.0,2689.0,2709.0,2766.0,2978.0,2951.0,3076.0,3294.0,3266.0,3079.0,3228.0,3107.0,2923.0,2836.0,2773.0,2740.0,2692.0,2622.0,2485.0,2296.0,2184.0,2016.0,1787.0,1600.0,1614.0,1487.0,1385.0,1142.0,1039.0,943.0,836.0,903.0,878.0,769.0,796.0,730.0],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"year"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Number of babies born with the name"}},"legend":{"tracegroupgap":0},"title":{"text":"Popularity of the name Bethany over the years"},"shapes":[{"line":{"color":"red","dash":"dash"},"type":"line","x0":2004,"x1":2004,"xref":"x","y0":0,"y1":1,"yref":"y domain"}],"annotations":[{"showarrow":false,"text":"My birth year","x":2004,"xanchor":"right","xref":"x","y":0,"yanchor":"bottom","yref":"y domain"}]},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('94de1b27-5c5f-4c0d-b5d8-4119b89259e0');
+var gd = document.getElementById('bf2c00f7-9cb6-495c-aa19-d55ffc331149');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -4951,7 +4951,7 @@ <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
 <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <p><strong>If you talked to someone named Brittany on the phone, what is your guess of his or her age? What ages would you not guess?</strong></p>
 <p>I would guess based on probability that someone named Brittany would be born between 1985 and 1995, which would mean that as of 2024 they would be between the ages of 39 and 29. Before these years there were only about 500 babies given that name per year and after those years there were only about a thousand babies given that name per year. This may seem like a lot, but between 1985 and 1995 it was more like 30,000 per year.</p>
-<div id="385ef8c4" class="cell" data-execution_count="4">
+<div id="893a3f83" class="cell" data-execution_count="4">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
@@ -4976,9 +4976,9 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <span id="cb3-20"><a href="#cb3-20" aria-hidden="true" tabindex="-1"></a>Brittany_plot.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="2ebdb05b-05d2-4b0f-8b00-fac1a4ada359" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("2ebdb05b-05d2-4b0f-8b00-fac1a4ada359")) {                    Plotly.newPlot(                        "2ebdb05b-05d2-4b0f-8b00-fac1a4ada359",                        [{"hovertemplate":"year=%{x}\u003cbr\u003eNumber of babies born with the name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"","orientation":"v","showlegend":false,"x":[1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015],"xaxis":"x","y":[5.0,12.0,32.0,81.0,158.0,166.0,198.0,277.0,304.0,448.0,592.0,764.0,1383.0,1701.0,3093.0,4377.0,7664.0,14010.0,17856.5,18825.5,21952.0,30848.0,32562.5,26963.5,23416.5,21728.0,17808.5,15875.5,13796.0,11527.0,9843.0,7942.0,5183.0,2915.0,1912.0,1559.0,1323.5,1168.0,1009.0,891.0,749.0,644.0,698.0,717.0,745.0,699.0,660.0,636.0],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"year"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Number of babies born with the name"}},"legend":{"tracegroupgap":0},"title":{"text":"Popularity of the name Brittany over the years"}},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="3fbd734e-f46d-42ff-86dc-c72cc203996e" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("3fbd734e-f46d-42ff-86dc-c72cc203996e")) {                    Plotly.newPlot(                        "3fbd734e-f46d-42ff-86dc-c72cc203996e",                        [{"hovertemplate":"year=%{x}\u003cbr\u003eNumber of babies born with the name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"","orientation":"v","showlegend":false,"x":[1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015],"xaxis":"x","y":[5.0,12.0,32.0,81.0,158.0,166.0,198.0,277.0,304.0,448.0,592.0,764.0,1383.0,1701.0,3093.0,4377.0,7664.0,14010.0,17856.5,18825.5,21952.0,30848.0,32562.5,26963.5,23416.5,21728.0,17808.5,15875.5,13796.0,11527.0,9843.0,7942.0,5183.0,2915.0,1912.0,1559.0,1323.5,1168.0,1009.0,891.0,749.0,644.0,698.0,717.0,745.0,699.0,660.0,636.0],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"year"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Number of babies born with the name"}},"legend":{"tracegroupgap":0},"title":{"text":"Popularity of the name Brittany over the years"}},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('2ebdb05b-05d2-4b0f-8b00-fac1a4ada359');
+var gd = document.getElementById('3fbd734e-f46d-42ff-86dc-c72cc203996e');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -5013,7 +5013,7 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <p><strong>Mary, Martha, Peter, and Paul are all Christian names. From 1920 - 2000, compare the name usage of each of the four names. What trends do you notice?</strong></p>
 <p>The most apparent trend is that the popularity of all of these biblical names went down substantially in the 1970s. Another notable trend is that all of these names were most popular in the 1950s. Of these names Mary was the most popular at about 54,000 at its height of popularity, followed shortly by Paul, with about 25,000 at its height. However, both Martha and Peter were never as popular at about 11,000 at their height.</p>
-<div id="d5779861" class="cell" data-execution_count="5">
+<div id="8d6d3f4c" class="cell" data-execution_count="5">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
@@ -5045,9 +5045,9 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <span id="cb4-27"><a href="#cb4-27" aria-hidden="true" tabindex="-1"></a>fig.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="93a78750-b3de-4a34-b91d-68820b756dd3" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("93a78750-b3de-4a34-b91d-68820b756dd3")) {                    Plotly.newPlot(                        "93a78750-b3de-4a34-b91d-68820b756dd3",                        [{"hovertemplate":"name=Martha\u003cbr\u003eyear=%{x}\u003cbr\u003eTotal number of babies born with name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Martha","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Martha","orientation":"v","showlegend":true,"x":[1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000],"xaxis":"x","y":[8705.0,9254.0,9018.0,8731.0,9163.0,8757.0,8557.0,8088.5,8245.0,7381.5,7830.0,7248.5,7329.5,6905.0,7603.0,7383.5,7176.5,7645.0,8017.5,7956.5,8204.0,8250.5,9514.0,9700.0,9329.0,8744.0,9763.0,10651.0,10006.0,9508.0,9840.0,9598.0,9699.0,9262.0,8585.0,7930.0,7703.0,7365.0,6393.5,6439.0,5504.5,5712.0,5164.0,4879.0,4448.0,3793.0,3267.0,2708.0,2557.0,2399.0,2346.0,2167.0,1718.0,1698.0,1811.0,1768.0,1580.0,1572.0,1469.0,1420.0,1525.0,1549.0,1270.5,1166.0,969.5,1057.0,1134.0,1117.0,969.0,1049.5,1222.0,1096.0,955.5,1027.0,928.0,887.0,849.0,830.0,737.0,693.0,741.0],"yaxis":"y","type":"scatter"},{"hovertemplate":"name=Mary\u003cbr\u003eyear=%{x}\u003cbr\u003eTotal number of babies born with name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Mary","line":{"color":"#EF553B","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Mary","orientation":"v","showlegend":true,"x":[1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000],"xaxis":"x","y":[45928.5,49070.0,48514.0,45749.5,44981.0,45006.5,42416.5,43645.5,37597.5,36396.5,38872.5,34680.0,35923.5,32867.5,34809.5,32865.5,31045.0,33171.5,34026.5,32546.0,35422.5,35127.0,37619.0,40505.5,39509.5,38813.0,45337.5,51053.0,50828.0,47835.0,53791.0,48928.5,49898.5,45603.0,48678.5,46351.0,45111.0,43334.0,39392.0,39242.0,36910.5,33353.5,31908.5,31314.5,29094.0,25823.0,23328.5,20413.5,18096.5,16045.0,15333.0,14606.5,12914.5,11429.5,11398.0,9916.0,9941.5,9936.5,9057.5,9605.0,10730.5,10692.0,9912.5,9345.0,8916.5,8269.5,7938.5,7402.5,7992.5,8127.5,8308.0,8400.0,8454.0,7891.5,7746.0,7438.0,6946.0,6627.0,6434.0,6360.0,6184.0],"yaxis":"y","type":"scatter"},{"hovertemplate":"name=Paul\u003cbr\u003eyear=%{x}\u003cbr\u003eTotal number of babies born with name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Paul","line":{"color":"#00cc96","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Paul","orientation":"v","showlegend":true,"x":[1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000],"xaxis":"x","y":[10958.5,11251.5,10907.0,11341.5,11553.5,12626.5,12262.0,11203.0,9650.5,10022.5,10493.0,9812.0,11379.0,11324.5,10642.0,12450.5,11121.5,12269.0,12690.5,12685.5,13382.0,13725.5,15335.0,16520.5,16654.0,16997.0,16823.5,18934.0,17120.5,20309.0,21763.0,21399.0,22197.5,25497.0,25662.5,24818.5,24852.0,24897.5,21623.5,21464.5,21377.0,20980.5,20155.0,21904.5,19928.5,20051.5,18978.5,19168.5,18531.0,16884.0,17193.0,13902.0,13123.5,11327.5,9951.5,9554.0,9980.0,10191.0,9725.5,10428.5,10898.5,10694.5,9129.5,8733.0,9284.5,8774.5,8454.0,8112.0,8238.0,7494.5,7705.5,7150.5,6522.0,6477.0,5796.0,5413.0,4879.0,4748.0,4319.0,4015.0,3786.0],"yaxis":"y","type":"scatter"},{"hovertemplate":"name=Peter\u003cbr\u003eyear=%{x}\u003cbr\u003eTotal number of babies born with name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Peter","line":{"color":"#ab63fa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Peter","orientation":"v","showlegend":true,"x":[1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000],"xaxis":"x","y":[3479.0,3530.0,3143.5,3403.0,3510.0,3369.0,3355.0,2883.0,2858.5,3201.0,3251.0,3093.0,2694.5,3120.0,2865.0,3413.0,3706.0,3283.5,4289.0,4633.0,5039.0,5608.0,6582.0,5920.0,5450.0,5604.0,6449.0,8591.0,8050.0,7180.0,8366.0,9004.0,9581.0,8561.0,10073.0,9689.5,11321.0,10284.5,9555.0,10028.5,9545.0,9225.5,9577.0,8571.5,9907.0,8364.5,7626.5,8087.0,8133.0,7170.0,6854.0,5995.5,6479.0,5918.0,5128.5,5707.0,4721.0,5323.0,5425.5,6076.0,5296.0,5551.0,5611.0,4760.5,4743.5,5285.5,5018.0,5161.0,5042.5,4620.5,4866.5,4956.0,3934.5,4532.0,3928.5,3817.5,4069.0,3821.0,3377.0,3430.0,3137.0],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Year"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Total number of babies born with name"}},"legend":{"title":{"text":"Names"},"tracegroupgap":0},"title":{"text":"Showing trends of biblical names popularity dropping in the 1970s and other trends (1920-2000)"}},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="bf5ee11a-2530-422e-8b97-bf35a789b760" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("bf5ee11a-2530-422e-8b97-bf35a789b760")) {                    Plotly.newPlot(                        "bf5ee11a-2530-422e-8b97-bf35a789b760",                        [{"hovertemplate":"name=Martha\u003cbr\u003eyear=%{x}\u003cbr\u003eTotal number of babies born with name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Martha","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Martha","orientation":"v","showlegend":true,"x":[1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000],"xaxis":"x","y":[8705.0,9254.0,9018.0,8731.0,9163.0,8757.0,8557.0,8088.5,8245.0,7381.5,7830.0,7248.5,7329.5,6905.0,7603.0,7383.5,7176.5,7645.0,8017.5,7956.5,8204.0,8250.5,9514.0,9700.0,9329.0,8744.0,9763.0,10651.0,10006.0,9508.0,9840.0,9598.0,9699.0,9262.0,8585.0,7930.0,7703.0,7365.0,6393.5,6439.0,5504.5,5712.0,5164.0,4879.0,4448.0,3793.0,3267.0,2708.0,2557.0,2399.0,2346.0,2167.0,1718.0,1698.0,1811.0,1768.0,1580.0,1572.0,1469.0,1420.0,1525.0,1549.0,1270.5,1166.0,969.5,1057.0,1134.0,1117.0,969.0,1049.5,1222.0,1096.0,955.5,1027.0,928.0,887.0,849.0,830.0,737.0,693.0,741.0],"yaxis":"y","type":"scatter"},{"hovertemplate":"name=Mary\u003cbr\u003eyear=%{x}\u003cbr\u003eTotal number of babies born with name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Mary","line":{"color":"#EF553B","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Mary","orientation":"v","showlegend":true,"x":[1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000],"xaxis":"x","y":[45928.5,49070.0,48514.0,45749.5,44981.0,45006.5,42416.5,43645.5,37597.5,36396.5,38872.5,34680.0,35923.5,32867.5,34809.5,32865.5,31045.0,33171.5,34026.5,32546.0,35422.5,35127.0,37619.0,40505.5,39509.5,38813.0,45337.5,51053.0,50828.0,47835.0,53791.0,48928.5,49898.5,45603.0,48678.5,46351.0,45111.0,43334.0,39392.0,39242.0,36910.5,33353.5,31908.5,31314.5,29094.0,25823.0,23328.5,20413.5,18096.5,16045.0,15333.0,14606.5,12914.5,11429.5,11398.0,9916.0,9941.5,9936.5,9057.5,9605.0,10730.5,10692.0,9912.5,9345.0,8916.5,8269.5,7938.5,7402.5,7992.5,8127.5,8308.0,8400.0,8454.0,7891.5,7746.0,7438.0,6946.0,6627.0,6434.0,6360.0,6184.0],"yaxis":"y","type":"scatter"},{"hovertemplate":"name=Paul\u003cbr\u003eyear=%{x}\u003cbr\u003eTotal number of babies born with name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Paul","line":{"color":"#00cc96","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Paul","orientation":"v","showlegend":true,"x":[1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000],"xaxis":"x","y":[10958.5,11251.5,10907.0,11341.5,11553.5,12626.5,12262.0,11203.0,9650.5,10022.5,10493.0,9812.0,11379.0,11324.5,10642.0,12450.5,11121.5,12269.0,12690.5,12685.5,13382.0,13725.5,15335.0,16520.5,16654.0,16997.0,16823.5,18934.0,17120.5,20309.0,21763.0,21399.0,22197.5,25497.0,25662.5,24818.5,24852.0,24897.5,21623.5,21464.5,21377.0,20980.5,20155.0,21904.5,19928.5,20051.5,18978.5,19168.5,18531.0,16884.0,17193.0,13902.0,13123.5,11327.5,9951.5,9554.0,9980.0,10191.0,9725.5,10428.5,10898.5,10694.5,9129.5,8733.0,9284.5,8774.5,8454.0,8112.0,8238.0,7494.5,7705.5,7150.5,6522.0,6477.0,5796.0,5413.0,4879.0,4748.0,4319.0,4015.0,3786.0],"yaxis":"y","type":"scatter"},{"hovertemplate":"name=Peter\u003cbr\u003eyear=%{x}\u003cbr\u003eTotal number of babies born with name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Peter","line":{"color":"#ab63fa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Peter","orientation":"v","showlegend":true,"x":[1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000],"xaxis":"x","y":[3479.0,3530.0,3143.5,3403.0,3510.0,3369.0,3355.0,2883.0,2858.5,3201.0,3251.0,3093.0,2694.5,3120.0,2865.0,3413.0,3706.0,3283.5,4289.0,4633.0,5039.0,5608.0,6582.0,5920.0,5450.0,5604.0,6449.0,8591.0,8050.0,7180.0,8366.0,9004.0,9581.0,8561.0,10073.0,9689.5,11321.0,10284.5,9555.0,10028.5,9545.0,9225.5,9577.0,8571.5,9907.0,8364.5,7626.5,8087.0,8133.0,7170.0,6854.0,5995.5,6479.0,5918.0,5128.5,5707.0,4721.0,5323.0,5425.5,6076.0,5296.0,5551.0,5611.0,4760.5,4743.5,5285.5,5018.0,5161.0,5042.5,4620.5,4866.5,4956.0,3934.5,4532.0,3928.5,3817.5,4069.0,3821.0,3377.0,3430.0,3137.0],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Year"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Total number of babies born with name"}},"legend":{"title":{"text":"Names"},"tracegroupgap":0},"title":{"text":"Showing trends of biblical names popularity dropping in the 1970s and other trends (1920-2000)"}},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('93a78750-b3de-4a34-b91d-68820b756dd3');
+var gd = document.getElementById('bf5ee11a-2530-422e-8b97-bf35a789b760');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -5083,7 +5083,7 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <h2 class="anchored" data-anchor-id="questiontask-4">QUESTION|TASK 4</h2>
 <p><strong>Think of a unique name from a famous movie. Plot the usage of that name and see how changes line up with the movie release. Does it look like the movie had an effect on usage?</strong></p>
 <p>It is hard to say if the movie had an effect on the name’s popularity. The popularity was already going up when the movie came out, but the overall trend of the name being more popular did stay higher. However, in 1997, the year average age of the children who watched that show when it first came out were having children there first children, it was a little lower than before the movie came out. However, in the early 2000s, it picked up significantly. It is hard to say without more information if the movie caused this spick or if it was something else.</p>
-<div id="44b06776" class="cell" data-execution_count="6">
+<div id="7f2a6741" class="cell" data-execution_count="6">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
@@ -5110,9 +5110,9 @@ <h2 class="anchored" data-anchor-id="questiontask-4">QUESTION|TASK 4</h2>
 <span id="cb5-22"><a href="#cb5-22" aria-hidden="true" tabindex="-1"></a>Elliott_plot.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="e3252fc5-9b43-4acb-ac81-8f406556f589" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("e3252fc5-9b43-4acb-ac81-8f406556f589")) {                    Plotly.newPlot(                        "e3252fc5-9b43-4acb-ac81-8f406556f589",                        [{"hovertemplate":"year=%{x}\u003cbr\u003eNumber of babies born with the name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"","orientation":"v","showlegend":false,"x":[1910,1911,1912,1913,1914,1915,1916,1917,1918,1919,1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015],"xaxis":"x","y":[10.0,23.0,43.0,60.0,70.0,117.0,106.0,99.0,79.0,119.0,139.0,187.0,152.0,131.0,158.0,145.0,167.0,163.0,129.0,126.0,130.0,90.0,96.0,148.0,154.0,147.0,92.0,109.0,113.0,142.0,161.0,146.0,206.0,189.0,182.0,240.0,210.0,315.0,299.0,256.0,199.0,207.0,204.0,209.0,220.0,177.0,204.0,183.0,151.0,185.0,222.0,256.0,221.0,220.0,169.0,213.0,176.0,153.0,163.0,187.0,189.0,192.0,141.0,177.0,156.0,147.0,184.0,230.0,179.0,255.0,291.0,244.0,432.0,547.0,485.0,411.0,416.0,398.0,485.0,626.0,632.0,542.0,525.0,550.0,432.0,396.0,360.0,346.0,383.0,344.0,370.0,348.0,372.0,416.0,480.0,534.5,652.5,652.5,604.5,675.0,729.0,786.5,874.5,958.0,1058.5,1224.0],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"year"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Number of babies born with the name"}},"legend":{"tracegroupgap":0},"title":{"text":"Popularity of the name Elliott over the years in relation to the movie ET"},"shapes":[{"line":{"color":"red","dash":"dash"},"type":"line","x0":1982,"x1":1982,"xref":"x","y0":0,"y1":1,"yref":"y domain"}],"annotations":[{"showarrow":false,"text":"Release of E.T.","x":1982,"xanchor":"left","xref":"x","y":0,"yanchor":"bottom","yref":"y domain"}]},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="5c357180-1134-422a-a7a7-93eb04bc66ce" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("5c357180-1134-422a-a7a7-93eb04bc66ce")) {                    Plotly.newPlot(                        "5c357180-1134-422a-a7a7-93eb04bc66ce",                        [{"hovertemplate":"year=%{x}\u003cbr\u003eNumber of babies born with the name=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"","orientation":"v","showlegend":false,"x":[1910,1911,1912,1913,1914,1915,1916,1917,1918,1919,1920,1921,1922,1923,1924,1925,1926,1927,1928,1929,1930,1931,1932,1933,1934,1935,1936,1937,1938,1939,1940,1941,1942,1943,1944,1945,1946,1947,1948,1949,1950,1951,1952,1953,1954,1955,1956,1957,1958,1959,1960,1961,1962,1963,1964,1965,1966,1967,1968,1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980,1981,1982,1983,1984,1985,1986,1987,1988,1989,1990,1991,1992,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015],"xaxis":"x","y":[10.0,23.0,43.0,60.0,70.0,117.0,106.0,99.0,79.0,119.0,139.0,187.0,152.0,131.0,158.0,145.0,167.0,163.0,129.0,126.0,130.0,90.0,96.0,148.0,154.0,147.0,92.0,109.0,113.0,142.0,161.0,146.0,206.0,189.0,182.0,240.0,210.0,315.0,299.0,256.0,199.0,207.0,204.0,209.0,220.0,177.0,204.0,183.0,151.0,185.0,222.0,256.0,221.0,220.0,169.0,213.0,176.0,153.0,163.0,187.0,189.0,192.0,141.0,177.0,156.0,147.0,184.0,230.0,179.0,255.0,291.0,244.0,432.0,547.0,485.0,411.0,416.0,398.0,485.0,626.0,632.0,542.0,525.0,550.0,432.0,396.0,360.0,346.0,383.0,344.0,370.0,348.0,372.0,416.0,480.0,534.5,652.5,652.5,604.5,675.0,729.0,786.5,874.5,958.0,1058.5,1224.0],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"year"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Number of babies born with the name"}},"legend":{"tracegroupgap":0},"title":{"text":"Popularity of the name Elliott over the years in relation to the movie ET"},"shapes":[{"line":{"color":"red","dash":"dash"},"type":"line","x0":1982,"x1":1982,"xref":"x","y0":0,"y1":1,"yref":"y domain"}],"annotations":[{"showarrow":false,"text":"Release of E.T.","x":1982,"xanchor":"left","xref":"x","y":0,"yanchor":"bottom","yref":"y domain"}]},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('e3252fc5-9b43-4acb-ac81-8f406556f589');
+var gd = document.getElementById('5c357180-1134-422a-a7a7-93eb04bc66ce');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
diff --git a/Projects/project2.html b/Projects/project2.html
index dd6d8b4..527d9ea 100644
--- a/Projects/project2.html
+++ b/Projects/project2.html
@@ -4888,7 +4888,7 @@ <h2 class="anchored" data-anchor-id="elevator-pitch">Elevator pitch</h2>
 <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
 <p>Fix all of the varied missing data types in the data to be consistent (all missing values should be displayed as “NaN”). In your report include one record example (one row) from your new data, in the raw JSON format. Your example should display the “NaN” for at least one missing value.</p>
 <p>The data was corrected, per the specifications of the task.</p>
-<div id="39cc15b4" class="cell" data-execution_count="3">
+<div id="838fb77f" class="cell" data-execution_count="3">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co">#replaces missing or &quot;bad&quot; data with &quot;good&quot; data.</span></span>
@@ -5010,7 +5010,7 @@ <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
 <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <p>Which airport has the worst delays? Discuss the metric you chose, and why you chose it to determine the “worst” airport. Your answer should include a summary table that lists (for each airport) the total number of flights, total number of delayed flights, proportion of delayed flights, and average delay time in hours.</p>
 <p>From my analysis, the Chicago airport has the worst delays. It on average has the worst delays as far as average minutes delayed. It is about second when it is fairly comparable with the Atlanta airport when you compare the total number of flights to the number of delays no matter how long. Adding these two variables together clearly shows that the Chicago airport is the worst when it comes to delays.</p>
-<div id="bcab810e" class="cell" data-execution_count="4">
+<div id="e2b30f3d" class="cell" data-execution_count="4">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="co"># mean of num_of_delays_total: 3437</span></span>
@@ -5053,9 +5053,9 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <span id="cb3-38"><a href="#cb3-38" aria-hidden="true" tabindex="-1"></a>fig.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="8d7c444e-c3d8-4088-9a17-4c08a70c927e" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("8d7c444e-c3d8-4088-9a17-4c08a70c927e")) {                    Plotly.newPlot(                        "8d7c444e-c3d8-4088-9a17-4c08a70c927e",                        [{"hovertemplate":"airport_name=Atlanta, GA\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Atlanta, GA","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"Atlanta, GA","orientation":"v","showlegend":true,"x":[8355,9195,9431,5748,5813,10986,13699,12861,4731,7493,7140,9899,8109,8013,7870,7104,7534,8470,8836,9726,11991,13124,8290,6606,6653,6802,6341,5796,5471,10622,11931,10970,6862,9107,5914,10483,6570,8657,10144,5217,7670,9817,7673,4556,6603,7851,11791,8463,5636,11059,8923,10324,7967,10482,9980,8260,10016,6669,9660,5908,6557,7275,4227,7247,8254,8448,7704,4713,5161,5411,6986,5391,4979,7637,6694,5838,8192,5705,4413,4062,3957,4283,4638,3509,5331,3124,4740,4993,7465,6190,3780,4825,4472,4345,5479,5384,5480,9474,10827,6985,3940,3668,4714,7524,7528,4884,6001,5240,6226,4685,4944,5801,4762,3770,4331,4662,5181,4356,4446,6031,5258,5145,3134,3098,4060,5474],"xaxis":"x","y":[35048,33702,37806,36881,38076,37209,37584,37886,33631,35282,33063,33632,33274,30438,34988,33251,34291,33787,35419,35276,32927,34692,33691,32795,32266,29766,34033,32891,34178,35978,36992,37284,34271,36942,34674,34592,33881,32357,36089,34572,35413,36434,35578,33099,34700,33872,33903,33320,30762,35669,34417,35135,36343,38241,37499,34017,35768,33915,34122,33729,31253,35186,34177,34856,35143,36074,36128,34266,35494,33850,34440,32013,29034,33855,32549,34077,34134,34781,31729,33298,31322,31207,31351,29757,33669,32653,33882,34227,34915,34724,31593,31019,32355,29447,34682,33654,34412,34436,35541,35139,32046,33810,31466,31894,30784,27982,32702,31117,30945,31798,31608,30198,31613,30000,29492,27366,32775,31383,32425,32739,33735,33725,31331,32594,30903,31030],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=Denver, CO\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Denver, CO","marker":{"color":"#EF553B","symbol":"circle"},"mode":"markers","name":"Denver, CO","orientation":"v","showlegend":true,"x":[3153,1788,2062,1476,2174,3310,3323,2682,1632,1876,1913,4293,2958,3839,4622,2744,3114,4082,4157,3708,3547,4163,2866,4774,5790,5241,3869,3641,4156,5018,4857,5048,2571,3144,7484,4540,4474,4508,3488,4782,5585,4311,4221,2241,2189,2265,6338,3863,3356,3063,2975,5962,4674,3312,2089,4433,4442,2680,2758,2840,2537,3825,2903,2455,2698,3975,3545,3687,3229,3316,3611,3790,4521,3334,2267,2081,3741,2570,2792,2662,2379,2518,3843,4666,3514,2289,2904,2100,4747,3602,3948,4330,3636,4650,4832,3667,3459,2848,6423,5218,4532,4145,3072,4224,4810,4826,4033,2881,2990,3317,4411,3885,3742,3156,3024,3480,4773,4171,3304,1802,2200,3610],"xaxis":"x","y":[12687,11480,12979,12275,16211,16953,17989,17827,16297,16498,15317,16404,17971,16751,19193,18308,19932,20096,20934,21498,19568,19935,18580,19599,20057,18321,20757,19579,20240,20269,21356,21412,19261,19334,20208,19482,18667,20604,19664,20765,21335,22040,21762,19141,19609,18588,19813,19447,20593,19127,19761,20995,21627,21343,18901,19403,19064,18999,17813,20229,19059,20444,21473,20422,19148,19848,19283,17755,20562,19247,20188,21465,22447,22524,19819,18515,19779,18986,18177,20347,19158,19607,20862,22168,21763,18795,19305,17851,18601,17809,19520,18451,19060,19536,20254,18823,19405,17962,19028,17955,16179,18996,17455,18997,19708,20773,20184,18907,19411,17296,18206,17059,15638,18617,17472,18072,18684,19083,18871,17393,18125,18001],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#00cc96","symbol":"circle"},"mode":"markers","name":"","orientation":"v","showlegend":false,"x":[2430,1947,1095,2203,1822,1365,8364,1704,3084,1693,8945,2282,7157,11952,4861,1966,728,898,847,1494,2669,2528,837,1074,1188,7340,826,1294,3165,7489,3913,1874,809,966,1543,8046,1577,1372,770,2225,941,1357,4728,657,4852,2923,3196,4306,2294,5135,5724,3420,1152,2421,7889,3076],"xaxis":"x","y":[12381,12404,7091,13860,8572,7824,32047,12015,19967,6411,30085,12685,34623,30542,12304,12202,10617,6917,10095,5845,10948,17977,5558,6824,17964,25716,5843,6248,19890,26671,21407,19817,6876,6169,6677,35052,6733,6621,6167,19813,9106,7035,15716,8871,33102,31061,16616,20027,13289,31799,24905,29296,8457,13431,27590,17120],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=Chicago, IL\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Chicago, IL","marker":{"color":"#ab63fa","symbol":"circle"},"mode":"markers","name":"Chicago, IL","orientation":"v","showlegend":true,"x":[9178,5269,6544,3786,5195,7643,7641,5533,4717,3538,6466,9479,7177,6545,9608,7637,8995,8121,8457,8769,9052,10412,7536,11592,10628,10968,10591,9673,7340,9438,10068,5906,7030,7107,12652,11387,11011,7461,7113,8600,5713,6008,4157,4108,9506,6255,3696,4835,4587,4002,5672,4241,5442,2868,5469,1991,5164,5123,4990,4323,6396,5861,4666,3117,3216,3384,6026,5260,5768,4951,7254,6760,6146,6737,5079,4233,3281,4790,3556,3896,3164,4823,3200,4543,4513,6860,5696,4680,5817,3466,5166,5310,5942,5149,7097,6550,8585,6767,5596,3473,4510,4045,7446,6509,5332,5293,5456,7137,9004,6148,8217,9148,5093,4763,6551,6606,5374,4364,4789,6130,5110,3879,3236,3962,4233],"xaxis":"x","y":[28194,25665,28785,27634,28523,27756,28283,28662,27474,29083,28453,29229,30828,28150,31685,30698,31976,31286,31890,32338,30768,32244,30537,31399,31839,28988,32447,31292,32385,31528,32483,30436,32012,30041,30253,29936,27987,30003,30757,31602,30773,28251,28834,25294,26388,25985,23916,26964,25871,26509,26907,27567,27575,25917,26759,24925,25460,23737,27054,25754,26479,27581,27822,26339,27106,24538,24870,23866,23295,27287,26422,27227,27667,28508,28451,25661,26324,24395,24656,24791,23697,25618,25810,26746,27161,27657,28106,25694,27000,24620,23741,23878,22179,25505,26046,27023,27274,27970,27714,25285,26539,24033,23086,21529,19812,22922,23234,24634,25381,25885,25717,26310,23564,23484,23515,21814,26122,25845,26909,28183,28128,26169,27608,26063,25568],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=San Diego, CA\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"San Diego, CA","marker":{"color":"#FFA15A","symbol":"circle"},"mode":"markers","name":"San Diego, CA","orientation":"v","showlegend":true,"x":[1952,1635,1324,1117,1661,1769,1629,1286,1321,976,1810,1251,1740,1897,1667,1343,1656,1790,1633,1391,1698,1332,1688,1579,1683,1379,1273,1905,1931,1930,1300,1607,1582,2325,2165,1891,1715,1491,1996,2325,1516,1437,710,765,2265,1127,1257,1268,1002,1755,1448,1128,664,1555,508,1530,963,947,929,1185,1304,1306,995,820,1169,1136,1941,1230,1402,1488,1460,1265,1398,1088,1038,911,919,819,804,709,981,863,832,1197,1277,974,1216,893,1596,886,776,1096,1317,1016,1693,1510,1489,1171,1232,1023,1751,1566,1515,1326,1292,1342,1779,1658,1351,946,1002,983,1746,1030,1119,1039,1176,1266,1479,1564,1212,722,661,997,1383],"xaxis":"x","y":[7283,6543,7298,7512,7574,7862,7946,7451,7641,7239,7590,7598,6962,7882,7468,7896,7893,8173,8231,7593,7912,7519,7788,7674,6920,7440,7925,8339,8718,8854,8389,8660,8202,8357,8031,7478,8080,8005,8350,8350,8613,8346,7131,7364,7085,6919,6325,7052,7178,7296,7553,7382,6636,6832,6371,6561,6338,6615,6493,6953,6981,7133,6991,6262,6521,6149,6372,6294,5737,6532,6200,6518,6623,6865,6779,6324,5980,6316,6119,5878,6527,6329,6575,6772,6867,6185,6427,6087,6324,6120,5609,6496,6393,6612,6763,7015,6850,6166,6383,6029,6243,6086,5485,6430,6255,6450,6742,7193,6928,6228,6528,6068,6339,6084,5478,6589,6422,6595,6763,7031,6876,6173,6207,5965,6231],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=San Francisco, CA\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"San Francisco, CA","marker":{"color":"#19d3f3","symbol":"circle"},"mode":"markers","name":"San Francisco, CA","orientation":"v","showlegend":true,"x":[2816,2122,2148,1470,2217,2978,2548,2638,2212,2134,2495,4307,2693,3048,4117,3413,2347,3107,2561,3212,2472,2894,3052,3398,2599,3589,2011,2509,2893,3601,3904,3820,2893,3672,3108,4358,5131,3611,3010,2573,3266,3904,3234,1976,2098,2321,4277,3599,2892,2406,3481,3754,3186,2862,1594,3458,1138,3168,3555,3177,2423,2356,3008,3372,2974,3539,2595,2901,2285,4703,2811,2639,4092,2884,3037,3793,4069,3907,2542,3192,3235,2170,3179,2290,3976,2992,3285,4345,4877,4493,4876,3359,4514,2136,2038,2989,3679,3318,4940,5688,5411,3488,2844,3138,3387,4516,3335,2908,3704,4560,4358,3705,3429,3362,3578,5721,2850,2929,2496,3753,3135,3684,3149,1913,2096,2189,4465],"xaxis":"x","y":[10274,9327,10532,10210,10954,11089,11579,11598,10765,11104,10584,10972,10727,9742,10964,10824,11105,11128,11625,11850,10821,11231,10723,11065,10928,9938,11223,10976,11548,11856,12345,12456,11567,12042,11603,11940,11560,10817,11810,11542,12115,12842,12646,11323,11657,10753,11210,10016,11296,10990,11491,12033,12516,12470,11217,11663,10936,11402,11279,10307,11534,11236,11738,12025,12451,12557,11675,12034,11396,11792,11486,10454,11968,11470,11873,12381,12953,13190,12531,12905,12099,12412,13437,12663,14067,13952,14448,14937,15711,14184,14756,13645,13823,13214,12026,13871,13715,14300,14768,15401,15478,13903,14295,13809,13539,12081,13846,13734,14164,14372,14951,14766,13871,14489,13243,13827,12883,11555,13015,13520,13844,14435,14605,13318,14170,13527,13833],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=Salt Lake City, UT\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Salt Lake City, UT","marker":{"color":"#FF6692","symbol":"circle"},"mode":"markers","name":"Salt Lake City, UT","orientation":"v","showlegend":true,"x":[2525,2426,1546,1480,2257,2206,1641,1446,1947,2644,1954,2200,2636,1486,1163,1926,1799,1742,1650,1856,1722,2890,3618,2780,1914,1245,1304,2639,2913,2614,1648,1293,4286,3497,2615,1315,1256,1547,1390,677,3216,1840,1200,1470,1188,942,2177,1824,1509,943,2021,593,2748,1554,1211,1146,1281,1430,1677,1757,1642,1578,1436,2106,3114,1942,1552,1702,1639,1184,1287,1344,1078,697,736,871,957,898,1006,726,683,978,1266,1126,1024,827,1684,1686,1085,1292,1299,1017,1393,1473,1228,970,897,809,2265,1671,1295,1254,1022,1034,1391,1361,1254,906,876,1546,1191,1108,1135,1042,921,1305,1298,1157,671,652,981,1745],"xaxis":"x","y":[12000,14115,13398,13822,14472,14630,13720,13962,12970,11469,11423,10375,11997,11402,11783,12155,12847,12942,11784,11997,11383,12174,12187,11011,12661,11715,11625,12934,13570,13564,12282,11871,12354,12364,11681,11653,11584,12476,12382,10479,10859,11051,9995,11207,10741,10956,11972,12642,12268,10298,10457,9912,10334,10452,9507,10594,9940,10277,10982,11267,11371,10082,9895,9856,10486,10174,9319,10817,9845,10045,10460,11002,10753,9456,9536,8806,9246,8660,9833,9052,9050,9479,9844,9821,9164,8551,8872,9058,8262,10092,9425,9378,9994,10328,10402,9137,9264,8510,8737,8676,7807,9371,8728,8804,9503,10031,10043,9108,9233,8825,8626,7866,9475,8845,8757,8975,9502,9502,8406,8764,8435,8804],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=Washington, DC\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Washington, DC","marker":{"color":"#B6E880","symbol":"circle"},"mode":"markers","name":"Washington, DC","orientation":"v","showlegend":true,"x":[1639,1921,1508,2020,2926,3245,2133,1134,1447,1021,1466,1458,1233,1353,1389,1525,2188,2292,1750,1640,1865,2069,2067,2087,2231,1971,1695,2258,2040,1882,1023,1410,1233,2172,1597,1630,1415,1215,2200,1859,1413,1146,848,858,980,703,989,1081,1311,1114,1113,647,784,667,1120,1098,953,710,1004,1348,1236,1087,839,622,1333,1044,1058,1363,1676,1293,980,757,793,916,613,1333,808,1339,1424,1907,1554,1155,970,777,1200,918,988,1179,1193,1532,1835,1834,1217,926,915,901,1356,1198,818,973,897,1076,1308,1107,1010,870,1064,712,937,855,656,548,438,548,893,669,576,397,352,320,443],"xaxis":"x","y":[10042,11249,10997,11189,10743,11152,11064,9398,9262,7408,7494,6917,7078,8256,7963,8085,7838,8018,8330,7744,8451,8621,8710,7691,8672,8239,8233,7511,7334,7345,6679,6954,6895,6906,6792,6886,6396,6521,6501,6764,6559,5814,5914,5619,5556,5057,5775,5644,5962,6170,6055,5116,5282,5042,5362,5738,5441,6245,6528,6697,7000,7035,6482,6256,6565,6085,6964,6674,7034,5801,6109,5832,6185,5781,5636,6467,6221,6696,6429,6532,6506,6577,6873,6207,6197,6024,5366,6231,6160,6482,6527,6559,6509,6118,6513,5887,5789,4688,4222,5215,4987,5105,4936,5128,5060,4857,5055,4412,4320,3700,2998,3033,2955,3244,3382,3334,3228,2925,3000,2684,2799],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"num_of_delays_total"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"num_of_flights_total"}},"legend":{"title":{"text":"airport_name"},"tracegroupgap":0},"title":{"text":"Airport Delays Summary"}},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="c1a7fb7c-0f92-4943-8115-39f24f38bd23" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("c1a7fb7c-0f92-4943-8115-39f24f38bd23")) {                    Plotly.newPlot(                        "c1a7fb7c-0f92-4943-8115-39f24f38bd23",                        [{"hovertemplate":"airport_name=Atlanta, GA\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Atlanta, GA","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"Atlanta, GA","orientation":"v","showlegend":true,"x":[8355,9195,9431,5748,5813,10986,13699,12861,4731,7493,7140,9899,8109,8013,7870,7104,7534,8470,8836,9726,11991,13124,8290,6606,6653,6802,6341,5796,5471,10622,11931,10970,6862,9107,5914,10483,6570,8657,10144,5217,7670,9817,7673,4556,6603,7851,11791,8463,5636,11059,8923,10324,7967,10482,9980,8260,10016,6669,9660,5908,6557,7275,4227,7247,8254,8448,7704,4713,5161,5411,6986,5391,4979,7637,6694,5838,8192,5705,4413,4062,3957,4283,4638,3509,5331,3124,4740,4993,7465,6190,3780,4825,4472,4345,5479,5384,5480,9474,10827,6985,3940,3668,4714,7524,7528,4884,6001,5240,6226,4685,4944,5801,4762,3770,4331,4662,5181,4356,4446,6031,5258,5145,3134,3098,4060,5474],"xaxis":"x","y":[35048,33702,37806,36881,38076,37209,37584,37886,33631,35282,33063,33632,33274,30438,34988,33251,34291,33787,35419,35276,32927,34692,33691,32795,32266,29766,34033,32891,34178,35978,36992,37284,34271,36942,34674,34592,33881,32357,36089,34572,35413,36434,35578,33099,34700,33872,33903,33320,30762,35669,34417,35135,36343,38241,37499,34017,35768,33915,34122,33729,31253,35186,34177,34856,35143,36074,36128,34266,35494,33850,34440,32013,29034,33855,32549,34077,34134,34781,31729,33298,31322,31207,31351,29757,33669,32653,33882,34227,34915,34724,31593,31019,32355,29447,34682,33654,34412,34436,35541,35139,32046,33810,31466,31894,30784,27982,32702,31117,30945,31798,31608,30198,31613,30000,29492,27366,32775,31383,32425,32739,33735,33725,31331,32594,30903,31030],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=Denver, CO\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Denver, CO","marker":{"color":"#EF553B","symbol":"circle"},"mode":"markers","name":"Denver, CO","orientation":"v","showlegend":true,"x":[3153,1788,2062,1476,2174,3310,3323,2682,1632,1876,1913,4293,2958,3839,4622,2744,3114,4082,4157,3708,3547,4163,2866,4774,5790,5241,3869,3641,4156,5018,4857,5048,2571,3144,7484,4540,4474,4508,3488,4782,5585,4311,4221,2241,2189,2265,6338,3863,3356,3063,2975,5962,4674,3312,2089,4433,4442,2680,2758,2840,2537,3825,2903,2455,2698,3975,3545,3687,3229,3316,3611,3790,4521,3334,2267,2081,3741,2570,2792,2662,2379,2518,3843,4666,3514,2289,2904,2100,4747,3602,3948,4330,3636,4650,4832,3667,3459,2848,6423,5218,4532,4145,3072,4224,4810,4826,4033,2881,2990,3317,4411,3885,3742,3156,3024,3480,4773,4171,3304,1802,2200,3610],"xaxis":"x","y":[12687,11480,12979,12275,16211,16953,17989,17827,16297,16498,15317,16404,17971,16751,19193,18308,19932,20096,20934,21498,19568,19935,18580,19599,20057,18321,20757,19579,20240,20269,21356,21412,19261,19334,20208,19482,18667,20604,19664,20765,21335,22040,21762,19141,19609,18588,19813,19447,20593,19127,19761,20995,21627,21343,18901,19403,19064,18999,17813,20229,19059,20444,21473,20422,19148,19848,19283,17755,20562,19247,20188,21465,22447,22524,19819,18515,19779,18986,18177,20347,19158,19607,20862,22168,21763,18795,19305,17851,18601,17809,19520,18451,19060,19536,20254,18823,19405,17962,19028,17955,16179,18996,17455,18997,19708,20773,20184,18907,19411,17296,18206,17059,15638,18617,17472,18072,18684,19083,18871,17393,18125,18001],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#00cc96","symbol":"circle"},"mode":"markers","name":"","orientation":"v","showlegend":false,"x":[2430,1947,1095,2203,1822,1365,8364,1704,3084,1693,8945,2282,7157,11952,4861,1966,728,898,847,1494,2669,2528,837,1074,1188,7340,826,1294,3165,7489,3913,1874,809,966,1543,8046,1577,1372,770,2225,941,1357,4728,657,4852,2923,3196,4306,2294,5135,5724,3420,1152,2421,7889,3076],"xaxis":"x","y":[12381,12404,7091,13860,8572,7824,32047,12015,19967,6411,30085,12685,34623,30542,12304,12202,10617,6917,10095,5845,10948,17977,5558,6824,17964,25716,5843,6248,19890,26671,21407,19817,6876,6169,6677,35052,6733,6621,6167,19813,9106,7035,15716,8871,33102,31061,16616,20027,13289,31799,24905,29296,8457,13431,27590,17120],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=Chicago, IL\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Chicago, IL","marker":{"color":"#ab63fa","symbol":"circle"},"mode":"markers","name":"Chicago, IL","orientation":"v","showlegend":true,"x":[9178,5269,6544,3786,5195,7643,7641,5533,4717,3538,6466,9479,7177,6545,9608,7637,8995,8121,8457,8769,9052,10412,7536,11592,10628,10968,10591,9673,7340,9438,10068,5906,7030,7107,12652,11387,11011,7461,7113,8600,5713,6008,4157,4108,9506,6255,3696,4835,4587,4002,5672,4241,5442,2868,5469,1991,5164,5123,4990,4323,6396,5861,4666,3117,3216,3384,6026,5260,5768,4951,7254,6760,6146,6737,5079,4233,3281,4790,3556,3896,3164,4823,3200,4543,4513,6860,5696,4680,5817,3466,5166,5310,5942,5149,7097,6550,8585,6767,5596,3473,4510,4045,7446,6509,5332,5293,5456,7137,9004,6148,8217,9148,5093,4763,6551,6606,5374,4364,4789,6130,5110,3879,3236,3962,4233],"xaxis":"x","y":[28194,25665,28785,27634,28523,27756,28283,28662,27474,29083,28453,29229,30828,28150,31685,30698,31976,31286,31890,32338,30768,32244,30537,31399,31839,28988,32447,31292,32385,31528,32483,30436,32012,30041,30253,29936,27987,30003,30757,31602,30773,28251,28834,25294,26388,25985,23916,26964,25871,26509,26907,27567,27575,25917,26759,24925,25460,23737,27054,25754,26479,27581,27822,26339,27106,24538,24870,23866,23295,27287,26422,27227,27667,28508,28451,25661,26324,24395,24656,24791,23697,25618,25810,26746,27161,27657,28106,25694,27000,24620,23741,23878,22179,25505,26046,27023,27274,27970,27714,25285,26539,24033,23086,21529,19812,22922,23234,24634,25381,25885,25717,26310,23564,23484,23515,21814,26122,25845,26909,28183,28128,26169,27608,26063,25568],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=San Diego, CA\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"San Diego, CA","marker":{"color":"#FFA15A","symbol":"circle"},"mode":"markers","name":"San Diego, CA","orientation":"v","showlegend":true,"x":[1952,1635,1324,1117,1661,1769,1629,1286,1321,976,1810,1251,1740,1897,1667,1343,1656,1790,1633,1391,1698,1332,1688,1579,1683,1379,1273,1905,1931,1930,1300,1607,1582,2325,2165,1891,1715,1491,1996,2325,1516,1437,710,765,2265,1127,1257,1268,1002,1755,1448,1128,664,1555,508,1530,963,947,929,1185,1304,1306,995,820,1169,1136,1941,1230,1402,1488,1460,1265,1398,1088,1038,911,919,819,804,709,981,863,832,1197,1277,974,1216,893,1596,886,776,1096,1317,1016,1693,1510,1489,1171,1232,1023,1751,1566,1515,1326,1292,1342,1779,1658,1351,946,1002,983,1746,1030,1119,1039,1176,1266,1479,1564,1212,722,661,997,1383],"xaxis":"x","y":[7283,6543,7298,7512,7574,7862,7946,7451,7641,7239,7590,7598,6962,7882,7468,7896,7893,8173,8231,7593,7912,7519,7788,7674,6920,7440,7925,8339,8718,8854,8389,8660,8202,8357,8031,7478,8080,8005,8350,8350,8613,8346,7131,7364,7085,6919,6325,7052,7178,7296,7553,7382,6636,6832,6371,6561,6338,6615,6493,6953,6981,7133,6991,6262,6521,6149,6372,6294,5737,6532,6200,6518,6623,6865,6779,6324,5980,6316,6119,5878,6527,6329,6575,6772,6867,6185,6427,6087,6324,6120,5609,6496,6393,6612,6763,7015,6850,6166,6383,6029,6243,6086,5485,6430,6255,6450,6742,7193,6928,6228,6528,6068,6339,6084,5478,6589,6422,6595,6763,7031,6876,6173,6207,5965,6231],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=San Francisco, CA\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"San Francisco, CA","marker":{"color":"#19d3f3","symbol":"circle"},"mode":"markers","name":"San Francisco, CA","orientation":"v","showlegend":true,"x":[2816,2122,2148,1470,2217,2978,2548,2638,2212,2134,2495,4307,2693,3048,4117,3413,2347,3107,2561,3212,2472,2894,3052,3398,2599,3589,2011,2509,2893,3601,3904,3820,2893,3672,3108,4358,5131,3611,3010,2573,3266,3904,3234,1976,2098,2321,4277,3599,2892,2406,3481,3754,3186,2862,1594,3458,1138,3168,3555,3177,2423,2356,3008,3372,2974,3539,2595,2901,2285,4703,2811,2639,4092,2884,3037,3793,4069,3907,2542,3192,3235,2170,3179,2290,3976,2992,3285,4345,4877,4493,4876,3359,4514,2136,2038,2989,3679,3318,4940,5688,5411,3488,2844,3138,3387,4516,3335,2908,3704,4560,4358,3705,3429,3362,3578,5721,2850,2929,2496,3753,3135,3684,3149,1913,2096,2189,4465],"xaxis":"x","y":[10274,9327,10532,10210,10954,11089,11579,11598,10765,11104,10584,10972,10727,9742,10964,10824,11105,11128,11625,11850,10821,11231,10723,11065,10928,9938,11223,10976,11548,11856,12345,12456,11567,12042,11603,11940,11560,10817,11810,11542,12115,12842,12646,11323,11657,10753,11210,10016,11296,10990,11491,12033,12516,12470,11217,11663,10936,11402,11279,10307,11534,11236,11738,12025,12451,12557,11675,12034,11396,11792,11486,10454,11968,11470,11873,12381,12953,13190,12531,12905,12099,12412,13437,12663,14067,13952,14448,14937,15711,14184,14756,13645,13823,13214,12026,13871,13715,14300,14768,15401,15478,13903,14295,13809,13539,12081,13846,13734,14164,14372,14951,14766,13871,14489,13243,13827,12883,11555,13015,13520,13844,14435,14605,13318,14170,13527,13833],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=Salt Lake City, UT\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Salt Lake City, UT","marker":{"color":"#FF6692","symbol":"circle"},"mode":"markers","name":"Salt Lake City, UT","orientation":"v","showlegend":true,"x":[2525,2426,1546,1480,2257,2206,1641,1446,1947,2644,1954,2200,2636,1486,1163,1926,1799,1742,1650,1856,1722,2890,3618,2780,1914,1245,1304,2639,2913,2614,1648,1293,4286,3497,2615,1315,1256,1547,1390,677,3216,1840,1200,1470,1188,942,2177,1824,1509,943,2021,593,2748,1554,1211,1146,1281,1430,1677,1757,1642,1578,1436,2106,3114,1942,1552,1702,1639,1184,1287,1344,1078,697,736,871,957,898,1006,726,683,978,1266,1126,1024,827,1684,1686,1085,1292,1299,1017,1393,1473,1228,970,897,809,2265,1671,1295,1254,1022,1034,1391,1361,1254,906,876,1546,1191,1108,1135,1042,921,1305,1298,1157,671,652,981,1745],"xaxis":"x","y":[12000,14115,13398,13822,14472,14630,13720,13962,12970,11469,11423,10375,11997,11402,11783,12155,12847,12942,11784,11997,11383,12174,12187,11011,12661,11715,11625,12934,13570,13564,12282,11871,12354,12364,11681,11653,11584,12476,12382,10479,10859,11051,9995,11207,10741,10956,11972,12642,12268,10298,10457,9912,10334,10452,9507,10594,9940,10277,10982,11267,11371,10082,9895,9856,10486,10174,9319,10817,9845,10045,10460,11002,10753,9456,9536,8806,9246,8660,9833,9052,9050,9479,9844,9821,9164,8551,8872,9058,8262,10092,9425,9378,9994,10328,10402,9137,9264,8510,8737,8676,7807,9371,8728,8804,9503,10031,10043,9108,9233,8825,8626,7866,9475,8845,8757,8975,9502,9502,8406,8764,8435,8804],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=Washington, DC\u003cbr\u003enum_of_delays_total=%{x}\u003cbr\u003enum_of_flights_total=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Washington, DC","marker":{"color":"#B6E880","symbol":"circle"},"mode":"markers","name":"Washington, DC","orientation":"v","showlegend":true,"x":[1639,1921,1508,2020,2926,3245,2133,1134,1447,1021,1466,1458,1233,1353,1389,1525,2188,2292,1750,1640,1865,2069,2067,2087,2231,1971,1695,2258,2040,1882,1023,1410,1233,2172,1597,1630,1415,1215,2200,1859,1413,1146,848,858,980,703,989,1081,1311,1114,1113,647,784,667,1120,1098,953,710,1004,1348,1236,1087,839,622,1333,1044,1058,1363,1676,1293,980,757,793,916,613,1333,808,1339,1424,1907,1554,1155,970,777,1200,918,988,1179,1193,1532,1835,1834,1217,926,915,901,1356,1198,818,973,897,1076,1308,1107,1010,870,1064,712,937,855,656,548,438,548,893,669,576,397,352,320,443],"xaxis":"x","y":[10042,11249,10997,11189,10743,11152,11064,9398,9262,7408,7494,6917,7078,8256,7963,8085,7838,8018,8330,7744,8451,8621,8710,7691,8672,8239,8233,7511,7334,7345,6679,6954,6895,6906,6792,6886,6396,6521,6501,6764,6559,5814,5914,5619,5556,5057,5775,5644,5962,6170,6055,5116,5282,5042,5362,5738,5441,6245,6528,6697,7000,7035,6482,6256,6565,6085,6964,6674,7034,5801,6109,5832,6185,5781,5636,6467,6221,6696,6429,6532,6506,6577,6873,6207,6197,6024,5366,6231,6160,6482,6527,6559,6509,6118,6513,5887,5789,4688,4222,5215,4987,5105,4936,5128,5060,4857,5055,4412,4320,3700,2998,3033,2955,3244,3382,3334,3228,2925,3000,2684,2799],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"num_of_delays_total"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"num_of_flights_total"}},"legend":{"title":{"text":"airport_name"},"tracegroupgap":0},"title":{"text":"Airport Delays Summary"}},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('8d7c444e-c3d8-4088-9a17-4c08a70c927e');
+var gd = document.getElementById('c1a7fb7c-0f92-4943-8115-39f24f38bd23');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -5080,9 +5080,9 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
                         })                };                });            </script>        </div>
 </div>
 <div class="cell-output cell-output-display">
-<div>                            <div id="b53957e7-ad38-444a-8ed4-b3c84b6bde89" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("b53957e7-ad38-444a-8ed4-b3c84b6bde89")) {                    Plotly.newPlot(                        "b53957e7-ad38-444a-8ed4-b3c84b6bde89",                        [{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"","orientation":"v","showlegend":false,"x":[""],"xaxis":"x","y":[1186.1127976190476],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Atlanta, GA","marker":{"color":"#EF553B","symbol":"circle"},"mode":"markers","name":"Atlanta, GA","orientation":"v","showlegend":true,"x":["Atlanta, GA"],"xaxis":"x","y":[2274.1649470899474],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Chicago, IL","marker":{"color":"#00cc96","symbol":"circle"},"mode":"markers","name":"Chicago, IL","orientation":"v","showlegend":true,"x":["Chicago, IL"],"xaxis":"x","y":[2423.112666666667],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Denver, CO","marker":{"color":"#ab63fa","symbol":"circle"},"mode":"markers","name":"Denver, CO","orientation":"v","showlegend":true,"x":["Denver, CO"],"xaxis":"x","y":[1424.2275956284152],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Salt Lake City, UT","marker":{"color":"#FFA15A","symbol":"circle"},"mode":"markers","name":"Salt Lake City, UT","orientation":"v","showlegend":true,"x":["Salt Lake City, UT"],"xaxis":"x","y":[552.0758196721312],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"San Diego, CA","marker":{"color":"#19d3f3","symbol":"circle"},"mode":"markers","name":"San Diego, CA","orientation":"v","showlegend":true,"x":["San Diego, CA"],"xaxis":"x","y":[479.82453333333336],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"San Francisco, CA","marker":{"color":"#FF6692","symbol":"circle"},"mode":"markers","name":"San Francisco, CA","orientation":"v","showlegend":true,"x":["San Francisco, CA"],"xaxis":"x","y":[1065.4108923884514],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Washington, DC","marker":{"color":"#B6E880","symbol":"circle"},"mode":"markers","name":"Washington, DC","orientation":"v","showlegend":true,"x":["Washington, DC"],"xaxis":"x","y":[583.7506887052342],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"airport_name"},"categoryorder":"array","categoryarray":["","Atlanta, GA","Chicago, IL","Denver, CO","Salt Lake City, UT","San Diego, CA","San Francisco, CA","Washington, DC"]},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Average Delay Time (hours)"}},"legend":{"title":{"text":"airport_name"},"tracegroupgap":0},"title":{"text":"Average Delay Time at Airports"}},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="6961b69b-3156-4a44-a4b6-4402f10d7e1e" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("6961b69b-3156-4a44-a4b6-4402f10d7e1e")) {                    Plotly.newPlot(                        "6961b69b-3156-4a44-a4b6-4402f10d7e1e",                        [{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"","orientation":"v","showlegend":false,"x":[""],"xaxis":"x","y":[1186.1127976190476],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Atlanta, GA","marker":{"color":"#EF553B","symbol":"circle"},"mode":"markers","name":"Atlanta, GA","orientation":"v","showlegend":true,"x":["Atlanta, GA"],"xaxis":"x","y":[2274.1649470899474],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Chicago, IL","marker":{"color":"#00cc96","symbol":"circle"},"mode":"markers","name":"Chicago, IL","orientation":"v","showlegend":true,"x":["Chicago, IL"],"xaxis":"x","y":[2423.112666666667],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Denver, CO","marker":{"color":"#ab63fa","symbol":"circle"},"mode":"markers","name":"Denver, CO","orientation":"v","showlegend":true,"x":["Denver, CO"],"xaxis":"x","y":[1424.2275956284152],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Salt Lake City, UT","marker":{"color":"#FFA15A","symbol":"circle"},"mode":"markers","name":"Salt Lake City, UT","orientation":"v","showlegend":true,"x":["Salt Lake City, UT"],"xaxis":"x","y":[552.0758196721312],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"San Diego, CA","marker":{"color":"#19d3f3","symbol":"circle"},"mode":"markers","name":"San Diego, CA","orientation":"v","showlegend":true,"x":["San Diego, CA"],"xaxis":"x","y":[479.82453333333336],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"San Francisco, CA","marker":{"color":"#FF6692","symbol":"circle"},"mode":"markers","name":"San Francisco, CA","orientation":"v","showlegend":true,"x":["San Francisco, CA"],"xaxis":"x","y":[1065.4108923884514],"yaxis":"y","type":"scatter"},{"hovertemplate":"airport_name=%{x}\u003cbr\u003eAverage Delay Time (hours)=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"Washington, DC","marker":{"color":"#B6E880","symbol":"circle"},"mode":"markers","name":"Washington, DC","orientation":"v","showlegend":true,"x":["Washington, DC"],"xaxis":"x","y":[583.7506887052342],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"airport_name"},"categoryorder":"array","categoryarray":["","Atlanta, GA","Chicago, IL","Denver, CO","Salt Lake City, UT","San Diego, CA","San Francisco, CA","Washington, DC"]},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Average Delay Time (hours)"}},"legend":{"title":{"text":"airport_name"},"tracegroupgap":0},"title":{"text":"Average Delay Time at Airports"}},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('b53957e7-ad38-444a-8ed4-b3c84b6bde89');
+var gd = document.getElementById('6961b69b-3156-4a44-a4b6-4402f10d7e1e');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -5125,7 +5125,7 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <p>What is the best month to fly if you want to avoid delays of any length? Discuss the metric you chose and why you chose it to calculate your answer. Include one chart to help support your answer, with the x-axis ordered by month. (To answer this question, you will need to remove any rows that are missing the Month variable.)</p>
 <p>The best month to travel if you want no delays is November, closely followed by September. To figure this out I found the average number of carrier delays compared it to each month. Finding the average for each month I found makes it much clearer and easier to see the full picture of what is happening. This also helps with reader bias when they see outliers.</p>
-<div id="4d187627" class="cell" data-execution_count="5">
+<div id="6c9983bf" class="cell" data-execution_count="5">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Replace &#39;n/a&#39; with NaN</span></span>
@@ -5159,9 +5159,9 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <span id="cb4-29"><a href="#cb4-29" aria-hidden="true" tabindex="-1"></a>fig.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="09ee530f-4cfe-437a-a31d-3495f294e4fb" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("09ee530f-4cfe-437a-a31d-3495f294e4fb")) {                    Plotly.newPlot(                        "09ee530f-4cfe-437a-a31d-3495f294e4fb",                        [{"hovertemplate":"Month=%{x}\u003cbr\u003eAverage Number of Carrier Delays=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"","orientation":"v","showlegend":false,"x":["January","March","April","May","June","July","August","September","October","November","December",null],"xaxis":"x","y":[796.5068493150685,789.4929577464789,678.6233766233767,712.6986301369863,911.6,901.6753246753246,836.9333333333333,614.1486486486486,658.0649350649351,591.9868421052631,899.931506849315,699.0394736842105],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Month"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Average Number of Carrier Delays"}},"legend":{"tracegroupgap":0},"title":{"text":"Average Number of Carrier Delays by Month"}},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="0ef078f6-b2dd-43ea-a70b-ba8fb74394e2" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("0ef078f6-b2dd-43ea-a70b-ba8fb74394e2")) {                    Plotly.newPlot(                        "0ef078f6-b2dd-43ea-a70b-ba8fb74394e2",                        [{"hovertemplate":"Month=%{x}\u003cbr\u003eAverage Number of Carrier Delays=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","line":{"color":"#636efa","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"","orientation":"v","showlegend":false,"x":["January","March","April","May","June","July","August","September","October","November","December",null],"xaxis":"x","y":[796.5068493150685,789.4929577464789,678.6233766233767,712.6986301369863,911.6,901.6753246753246,836.9333333333333,614.1486486486486,658.0649350649351,591.9868421052631,899.931506849315,699.0394736842105],"yaxis":"y","type":"scatter"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Month"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Average Number of Carrier Delays"}},"legend":{"tracegroupgap":0},"title":{"text":"Average Number of Carrier Delays by Month"}},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('09ee530f-4cfe-437a-a31d-3495f294e4fb');
+var gd = document.getElementById('0ef078f6-b2dd-43ea-a70b-ba8fb74394e2');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -5200,7 +5200,7 @@ <h2 class="anchored" data-anchor-id="questiontask-4">QUESTION|TASK 4</h2>
 
 From April to August, 40% of delayed flights in the NAS category are due to weather. The rest of the months, the proportion rises to 65%.</code></pre>
 <p>All data has been corrected according to the desired rules given.</p>
-<div id="00248b55" class="cell" data-execution_count="6">
+<div id="d8f42f73" class="cell" data-execution_count="6">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="co">#cleans up data</span></span>
@@ -5369,7 +5369,7 @@ <h2 class="anchored" data-anchor-id="questiontask-4">QUESTION|TASK 4</h2>
 <h2 class="anchored" data-anchor-id="questiontask-5">QUESTION|TASK 5</h2>
 <p>Using the new weather variable calculated above, create a barplot showing the proportion of all flights that are delayed by weather at each airport. Discuss what you learn from this graph.</p>
 <p>This graph shows that overall, not many of the flights are delayed by weather. The highest percentage is SFO at a little under 0.03% of their flights are delayed by weather, and ATL as low as 0.018%. Overall weather doesn’t effect plane travel in the grand scheme of things.</p>
-<div id="256fd14c" class="cell" data-execution_count="7">
+<div id="c92da9ad" class="cell" data-execution_count="7">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>lookup <span class="op">=</span> {</span>
@@ -5414,9 +5414,9 @@ <h2 class="anchored" data-anchor-id="questiontask-5">QUESTION|TASK 5</h2>
 <span id="cb7-40"><a href="#cb7-40" aria-hidden="true" tabindex="-1"></a>fig.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="b1d44c66-553f-4b4f-9ebb-bd6d5eab3aec" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("b1d44c66-553f-4b4f-9ebb-bd6d5eab3aec")) {                    Plotly.newPlot(                        "b1d44c66-553f-4b4f-9ebb-bd6d5eab3aec",                        [{"alignmentgroup":"True","hovertemplate":"Airport Code=%{x}\u003cbr\u003ePercentage of Flights Delayed by Weather=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"v","showlegend":false,"textposition":"auto","x":["SFO","IAD","SAN","ORD","DEN","SLC","ATL"],"xaxis":"x","y":[0.029114925617954507,0.02854632265261376,0.027706020470969064,0.027662891073072723,0.02689752306589155,0.02188468452694065,0.018019988067589678],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Airport Code"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Percentage of Flights Delayed by Weather"}},"legend":{"tracegroupgap":0},"title":{"text":"Proportion of Flights Delayed by Weather at Each Airport"},"barmode":"relative"},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="f01496f5-23d4-4183-814b-ff510f86abf2" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("f01496f5-23d4-4183-814b-ff510f86abf2")) {                    Plotly.newPlot(                        "f01496f5-23d4-4183-814b-ff510f86abf2",                        [{"alignmentgroup":"True","hovertemplate":"Airport Code=%{x}\u003cbr\u003ePercentage of Flights Delayed by Weather=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"v","showlegend":false,"textposition":"auto","x":["SFO","IAD","SAN","ORD","DEN","SLC","ATL"],"xaxis":"x","y":[0.029114925617954507,0.02854632265261376,0.027706020470969064,0.027662891073072723,0.02689752306589155,0.02188468452694065,0.018019988067589678],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Airport Code"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Percentage of Flights Delayed by Weather"}},"legend":{"tracegroupgap":0},"title":{"text":"Proportion of Flights Delayed by Weather at Each Airport"},"barmode":"relative"},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('b1d44c66-553f-4b4f-9ebb-bd6d5eab3aec');
+var gd = document.getElementById('f01496f5-23d4-4183-814b-ff510f86abf2');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
diff --git a/Projects/project3.html b/Projects/project3.html
index 10c1ec1..2b131a1 100644
--- a/Projects/project3.html
+++ b/Projects/project3.html
@@ -6,9 +6,9 @@
 
 <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
 
-<meta name="author" content="[STUDENT NAME]">
+<meta name="author" content="Bethany Ball">
 
-<title>Bethany Ball Data Science Portfolio - Client Report - [Insert Project Title]</title>
+<title>Bethany Ball Data Science Portfolio - Finding Relationships in Baseball - Project 3</title>
 <style>
 code{white-space: pre-wrap;}
 span.smallcaps{font-variant: small-caps;}
@@ -20,10 +20,46 @@
 width: 0.8em;
 margin: 0 0.8em 0.2em -1em;  vertical-align: middle;
 }
+
+pre > code.sourceCode { white-space: pre; position: relative; }
+pre > code.sourceCode > span { line-height: 1.25; }
+pre > code.sourceCode > span:empty { height: 1.2em; }
+.sourceCode { overflow: visible; }
+code.sourceCode > span { color: inherit; text-decoration: inherit; }
+div.sourceCode { margin: 1em 0; }
+pre.sourceCode { margin: 0; }
+@media screen {
+div.sourceCode { overflow: auto; }
+}
+@media print {
+pre > code.sourceCode { white-space: pre-wrap; }
+pre > code.sourceCode > span { text-indent: -5em; padding-left: 5em; }
+}
+pre.numberSource code
+{ counter-reset: source-line 0; }
+pre.numberSource code > span
+{ position: relative; left: -4em; counter-increment: source-line; }
+pre.numberSource code > span > a:first-child::before
+{ content: counter(source-line);
+position: relative; left: -1em; text-align: right; vertical-align: baseline;
+border: none; display: inline-block;
+-webkit-touch-callout: none; -webkit-user-select: none;
+-khtml-user-select: none; -moz-user-select: none;
+-ms-user-select: none; user-select: none;
+padding: 0 4px; width: 4em;
+}
+pre.numberSource { margin-left: 3em; padding-left: 4px; }
+div.sourceCode
+{ }
+@media screen {
+pre > code.sourceCode > span > a:first-child::before { text-decoration: underline; }
+}
 </style>
 
 
-<script>const headroomChanged = new CustomEvent("quarto-hrChanged", {
+<script>/*! jQuery v3.5.1 | (c) JS Foundation and other contributors | jquery.org/license */
+!function(e,t){"use strict";"object"==typeof module&&"object"==typeof module.exports?module.exports=e.document?t(e,!0):function(e){if(!e.document)throw new Error("jQuery requires a window with a document");return t(e)}:t(e)}("undefined"!=typeof window?window:this,function(C,e){"use strict";var t=[],r=Object.getPrototypeOf,s=t.slice,g=t.flat?function(e){return t.flat.call(e)}:function(e){return t.concat.apply([],e)},u=t.push,i=t.indexOf,n={},o=n.toString,v=n.hasOwnProperty,a=v.toString,l=a.call(Object),y={},m=function(e){return"function"==typeof e&&"number"!=typeof e.nodeType},x=function(e){return null!=e&&e===e.window},E=C.document,c={type:!0,src:!0,nonce:!0,noModule:!0};function b(e,t,n){var r,i,o=(n=n||E).createElement("script");if(o.text=e,t)for(r in c)(i=t[r]||t.getAttribute&&t.getAttribute(r))&&o.setAttribute(r,i);n.head.appendChild(o).parentNode.removeChild(o)}function w(e){return null==e?e+"":"object"==typeof e||"function"==typeof e?n[o.call(e)]||"object":typeof e}var f="3.5.1",S=function(e,t){return new S.fn.init(e,t)};function p(e){var t=!!e&&"length"in e&&e.length,n=w(e);return!m(e)&&!x(e)&&("array"===n||0===t||"number"==typeof t&&0<t&&t-1 in e)}S.fn=S.prototype={jquery:f,constructor:S,length:0,toArray:function(){return s.call(this)},get:function(e){return null==e?s.call(this):e<0?this[e+this.length]:this[e]},pushStack:function(e){var t=S.merge(this.constructor(),e);return t.prevObject=this,t},each:function(e){return S.each(this,e)},map:function(n){return this.pushStack(S.map(this,function(e,t){return n.call(e,t,e)}))},slice:function(){return this.pushStack(s.apply(this,arguments))},first:function(){return this.eq(0)},last:function(){return this.eq(-1)},even:function(){return this.pushStack(S.grep(this,function(e,t){return(t+1)%2}))},odd:function(){return this.pushStack(S.grep(this,function(e,t){return t%2}))},eq:function(e){var t=this.length,n=+e+(e<0?t:0);return this.pushStack(0<=n&&n<t?[this[n]]:[])},end:function(){return this.prevObject||this.constructor()},push:u,sort:t.sort,splice:t.splice},S.extend=S.fn.extend=function(){var e,t,n,r,i,o,a=arguments[0]||{},s=1,u=arguments.length,l=!1;for("boolean"==typeof a&&(l=a,a=arguments[s]||{},s++),"object"==typeof a||m(a)||(a={}),s===u&&(a=this,s--);s<u;s++)if(null!=(e=arguments[s]))for(t in e)r=e[t],"__proto__"!==t&&a!==r&&(l&&r&&(S.isPlainObject(r)||(i=Array.isArray(r)))?(n=a[t],o=i&&!Array.isArray(n)?[]:i||S.isPlainObject(n)?n:{},i=!1,a[t]=S.extend(l,o,r)):void 0!==r&&(a[t]=r));return a},S.extend({expando:"jQuery"+(f+Math.random()).replace(/\D/g,""),isReady:!0,error:function(e){throw new Error(e)},noop:function(){},isPlainObject:function(e){var t,n;return!(!e||"[object Object]"!==o.call(e))&&(!(t=r(e))||"function"==typeof(n=v.call(t,"constructor")&&t.constructor)&&a.call(n)===l)},isEmptyObject:function(e){var t;for(t in e)return!1;return!0},globalEval:function(e,t,n){b(e,{nonce:t&&t.nonce},n)},each:function(e,t){var n,r=0;if(p(e)){for(n=e.length;r<n;r++)if(!1===t.call(e[r],r,e[r]))break}else for(r in e)if(!1===t.call(e[r],r,e[r]))break;return e},makeArray:function(e,t){var n=t||[];return null!=e&&(p(Object(e))?S.merge(n,"string"==typeof e?[e]:e):u.call(n,e)),n},inArray:function(e,t,n){return null==t?-1:i.call(t,e,n)},merge:function(e,t){for(var n=+t.length,r=0,i=e.length;r<n;r++)e[i++]=t[r];return e.length=i,e},grep:function(e,t,n){for(var r=[],i=0,o=e.length,a=!n;i<o;i++)!t(e[i],i)!==a&&r.push(e[i]);return r},map:function(e,t,n){var r,i,o=0,a=[];if(p(e))for(r=e.length;o<r;o++)null!=(i=t(e[o],o,n))&&a.push(i);else for(o in e)null!=(i=t(e[o],o,n))&&a.push(i);return g(a)},guid:1,support:y}),"function"==typeof Symbol&&(S.fn[Symbol.iterator]=t[Symbol.iterator]),S.each("Boolean Number String Function Array Date RegExp Object Error Symbol".split(" "),function(e,t){n["[object "+t+"]"]=t.toLowerCase()});var d=function(n){var e,d,b,o,i,h,f,g,w,u,l,T,C,a,E,v,s,c,y,S="sizzle"+1*new Date,p=n.document,k=0,r=0,m=ue(),x=ue(),A=ue(),N=ue(),D=function(e,t){return e===t&&(l=!0),0},j={}.hasOwnProperty,t=[],q=t.pop,L=t.push,H=t.push,O=t.slice,P=function(e,t){for(var n=0,r=e.length;n<r;n++)if(e[n]===t)return n;return-1},R="checked|selected|async|autofocus|autoplay|controls|defer|disabled|hidden|ismap|loop|multiple|open|readonly|required|scoped",M="[\\x20\\t\\r\\n\\f]",I="(?:\\\\[\\da-fA-F]{1,6}"+M+"?|\\\\[^\\r\\n\\f]|[\\w-]|[^\0-\\x7f])+",W="\\["+M+"*("+I+")(?:"+M+"*([*^$|!~]?=)"+M+"*(?:'((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\"|("+I+"))|)"+M+"*\\]",F=":("+I+")(?:\\((('((?:\\\\.|[^\\\\'])*)'|\"((?:\\\\.|[^\\\\\"])*)\")|((?:\\\\.|[^\\\\()[\\]]|"+W+")*)|.*)\\)|)",B=new RegExp(M+"+","g"),$=new RegExp("^"+M+"+|((?:^|[^\\\\])(?:\\\\.)*)"+M+"+$","g"),_=new RegExp("^"+M+"*,"+M+"*"),z=new RegExp("^"+M+"*([>+~]|"+M+")"+M+"*"),U=new RegExp(M+"|>"),X=new RegExp(F),V=new RegExp("^"+I+"$"),G={ID:new RegExp("^#("+I+")"),CLASS:new RegExp("^\\.("+I+")"),TAG:new RegExp("^("+I+"|[*])"),ATTR:new RegExp("^"+W),PSEUDO:new RegExp("^"+F),CHILD:new RegExp("^:(only|first|last|nth|nth-last)-(child|of-type)(?:\\("+M+"*(even|odd|(([+-]|)(\\d*)n|)"+M+"*(?:([+-]|)"+M+"*(\\d+)|))"+M+"*\\)|)","i"),bool:new RegExp("^(?:"+R+")$","i"),needsContext:new RegExp("^"+M+"*[>+~]|:(even|odd|eq|gt|lt|nth|first|last)(?:\\("+M+"*((?:-\\d)?\\d*)"+M+"*\\)|)(?=[^-]|$)","i")},Y=/HTML$/i,Q=/^(?:input|select|textarea|button)$/i,J=/^h\d$/i,K=/^[^{]+\{\s*\[native \w/,Z=/^(?:#([\w-]+)|(\w+)|\.([\w-]+))$/,ee=/[+~]/,te=new RegExp("\\\\[\\da-fA-F]{1,6}"+M+"?|\\\\([^\\r\\n\\f])","g"),ne=function(e,t){var n="0x"+e.slice(1)-65536;return t||(n<0?String.fromCharCode(n+65536):String.fromCharCode(n>>10|55296,1023&n|56320))},re=/([\0-\x1f\x7f]|^-?\d)|^-$|[^\0-\x1f\x7f-\uFFFF\w-]/g,ie=function(e,t){return t?"\0"===e?"\ufffd":e.slice(0,-1)+"\\"+e.charCodeAt(e.length-1).toString(16)+" ":"\\"+e},oe=function(){T()},ae=be(function(e){return!0===e.disabled&&"fieldset"===e.nodeName.toLowerCase()},{dir:"parentNode",next:"legend"});try{H.apply(t=O.call(p.childNodes),p.childNodes),t[p.childNodes.length].nodeType}catch(e){H={apply:t.length?function(e,t){L.apply(e,O.call(t))}:function(e,t){var n=e.length,r=0;while(e[n++]=t[r++]);e.length=n-1}}}function se(t,e,n,r){var i,o,a,s,u,l,c,f=e&&e.ownerDocument,p=e?e.nodeType:9;if(n=n||[],"string"!=typeof t||!t||1!==p&&9!==p&&11!==p)return n;if(!r&&(T(e),e=e||C,E)){if(11!==p&&(u=Z.exec(t)))if(i=u[1]){if(9===p){if(!(a=e.getElementById(i)))return n;if(a.id===i)return n.push(a),n}else if(f&&(a=f.getElementById(i))&&y(e,a)&&a.id===i)return n.push(a),n}else{if(u[2])return H.apply(n,e.getElementsByTagName(t)),n;if((i=u[3])&&d.getElementsByClassName&&e.getElementsByClassName)return H.apply(n,e.getElementsByClassName(i)),n}if(d.qsa&&!N[t+" "]&&(!v||!v.test(t))&&(1!==p||"object"!==e.nodeName.toLowerCase())){if(c=t,f=e,1===p&&(U.test(t)||z.test(t))){(f=ee.test(t)&&ye(e.parentNode)||e)===e&&d.scope||((s=e.getAttribute("id"))?s=s.replace(re,ie):e.setAttribute("id",s=S)),o=(l=h(t)).length;while(o--)l[o]=(s?"#"+s:":scope")+" "+xe(l[o]);c=l.join(",")}try{return H.apply(n,f.querySelectorAll(c)),n}catch(e){N(t,!0)}finally{s===S&&e.removeAttribute("id")}}}return g(t.replace($,"$1"),e,n,r)}function ue(){var r=[];return function e(t,n){return r.push(t+" ")>b.cacheLength&&delete e[r.shift()],e[t+" "]=n}}function le(e){return e[S]=!0,e}function ce(e){var t=C.createElement("fieldset");try{return!!e(t)}catch(e){return!1}finally{t.parentNode&&t.parentNode.removeChild(t),t=null}}function fe(e,t){var n=e.split("|"),r=n.length;while(r--)b.attrHandle[n[r]]=t}function pe(e,t){var n=t&&e,r=n&&1===e.nodeType&&1===t.nodeType&&e.sourceIndex-t.sourceIndex;if(r)return r;if(n)while(n=n.nextSibling)if(n===t)return-1;return e?1:-1}function de(t){return function(e){return"input"===e.nodeName.toLowerCase()&&e.type===t}}function he(n){return function(e){var t=e.nodeName.toLowerCase();return("input"===t||"button"===t)&&e.type===n}}function ge(t){return function(e){return"form"in e?e.parentNode&&!1===e.disabled?"label"in e?"label"in e.parentNode?e.parentNode.disabled===t:e.disabled===t:e.isDisabled===t||e.isDisabled!==!t&&ae(e)===t:e.disabled===t:"label"in e&&e.disabled===t}}function ve(a){return le(function(o){return o=+o,le(function(e,t){var n,r=a([],e.length,o),i=r.length;while(i--)e[n=r[i]]&&(e[n]=!(t[n]=e[n]))})})}function ye(e){return e&&"undefined"!=typeof e.getElementsByTagName&&e}for(e in d=se.support={},i=se.isXML=function(e){var t=e.namespaceURI,n=(e.ownerDocument||e).documentElement;return!Y.test(t||n&&n.nodeName||"HTML")},T=se.setDocument=function(e){var t,n,r=e?e.ownerDocument||e:p;return r!=C&&9===r.nodeType&&r.documentElement&&(a=(C=r).documentElement,E=!i(C),p!=C&&(n=C.defaultView)&&n.top!==n&&(n.addEventListener?n.addEventListener("unload",oe,!1):n.attachEvent&&n.attachEvent("onunload",oe)),d.scope=ce(function(e){return a.appendChild(e).appendChild(C.createElement("div")),"undefined"!=typeof e.querySelectorAll&&!e.querySelectorAll(":scope fieldset div").length}),d.attributes=ce(function(e){return e.className="i",!e.getAttribute("className")}),d.getElementsByTagName=ce(function(e){return e.appendChild(C.createComment("")),!e.getElementsByTagName("*").length}),d.getElementsByClassName=K.test(C.getElementsByClassName),d.getById=ce(function(e){return a.appendChild(e).id=S,!C.getElementsByName||!C.getElementsByName(S).length}),d.getById?(b.filter.ID=function(e){var t=e.replace(te,ne);return function(e){return e.getAttribute("id")===t}},b.find.ID=function(e,t){if("undefined"!=typeof t.getElementById&&E){var n=t.getElementById(e);return n?[n]:[]}}):(b.filter.ID=function(e){var n=e.replace(te,ne);return function(e){var t="undefined"!=typeof e.getAttributeNode&&e.getAttributeNode("id");return t&&t.value===n}},b.find.ID=function(e,t){if("undefined"!=typeof t.getElementById&&E){var n,r,i,o=t.getElementById(e);if(o){if((n=o.getAttributeNode("id"))&&n.value===e)return[o];i=t.getElementsByName(e),r=0;while(o=i[r++])if((n=o.getAttributeNode("id"))&&n.value===e)return[o]}return[]}}),b.find.TAG=d.getElementsByTagName?function(e,t){return"undefined"!=typeof t.getElementsByTagName?t.getElementsByTagName(e):d.qsa?t.querySelectorAll(e):void 0}:function(e,t){var n,r=[],i=0,o=t.getElementsByTagName(e);if("*"===e){while(n=o[i++])1===n.nodeType&&r.push(n);return r}return o},b.find.CLASS=d.getElementsByClassName&&function(e,t){if("undefined"!=typeof t.getElementsByClassName&&E)return t.getElementsByClassName(e)},s=[],v=[],(d.qsa=K.test(C.querySelectorAll))&&(ce(function(e){var t;a.appendChild(e).innerHTML="<a id='"+S+"'></a><select id='"+S+"-\r\\' msallowcapture=''><option selected=''></option></select>",e.querySelectorAll("[msallowcapture^='']").length&&v.push("[*^$]="+M+"*(?:''|\"\")"),e.querySelectorAll("[selected]").length||v.push("\\["+M+"*(?:value|"+R+")"),e.querySelectorAll("[id~="+S+"-]").length||v.push("~="),(t=C.createElement("input")).setAttribute("name",""),e.appendChild(t),e.querySelectorAll("[name='']").length||v.push("\\["+M+"*name"+M+"*="+M+"*(?:''|\"\")"),e.querySelectorAll(":checked").length||v.push(":checked"),e.querySelectorAll("a#"+S+"+*").length||v.push(".#.+[+~]"),e.querySelectorAll("\\\f"),v.push("[\\r\\n\\f]")}),ce(function(e){e.innerHTML="<a href='' disabled='disabled'></a><select disabled='disabled'><option/></select>";var t=C.createElement("input");t.setAttribute("type","hidden"),e.appendChild(t).setAttribute("name","D"),e.querySelectorAll("[name=d]").length&&v.push("name"+M+"*[*^$|!~]?="),2!==e.querySelectorAll(":enabled").length&&v.push(":enabled",":disabled"),a.appendChild(e).disabled=!0,2!==e.querySelectorAll(":disabled").length&&v.push(":enabled",":disabled"),e.querySelectorAll("*,:x"),v.push(",.*:")})),(d.matchesSelector=K.test(c=a.matches||a.webkitMatchesSelector||a.mozMatchesSelector||a.oMatchesSelector||a.msMatchesSelector))&&ce(function(e){d.disconnectedMatch=c.call(e,"*"),c.call(e,"[s!='']:x"),s.push("!=",F)}),v=v.length&&new RegExp(v.join("|")),s=s.length&&new RegExp(s.join("|")),t=K.test(a.compareDocumentPosition),y=t||K.test(a.contains)?function(e,t){var n=9===e.nodeType?e.documentElement:e,r=t&&t.parentNode;return e===r||!(!r||1!==r.nodeType||!(n.contains?n.contains(r):e.compareDocumentPosition&&16&e.compareDocumentPosition(r)))}:function(e,t){if(t)while(t=t.parentNode)if(t===e)return!0;return!1},D=t?function(e,t){if(e===t)return l=!0,0;var n=!e.compareDocumentPosition-!t.compareDocumentPosition;return n||(1&(n=(e.ownerDocument||e)==(t.ownerDocument||t)?e.compareDocumentPosition(t):1)||!d.sortDetached&&t.compareDocumentPosition(e)===n?e==C||e.ownerDocument==p&&y(p,e)?-1:t==C||t.ownerDocument==p&&y(p,t)?1:u?P(u,e)-P(u,t):0:4&n?-1:1)}:function(e,t){if(e===t)return l=!0,0;var n,r=0,i=e.parentNode,o=t.parentNode,a=[e],s=[t];if(!i||!o)return e==C?-1:t==C?1:i?-1:o?1:u?P(u,e)-P(u,t):0;if(i===o)return pe(e,t);n=e;while(n=n.parentNode)a.unshift(n);n=t;while(n=n.parentNode)s.unshift(n);while(a[r]===s[r])r++;return r?pe(a[r],s[r]):a[r]==p?-1:s[r]==p?1:0}),C},se.matches=function(e,t){return se(e,null,null,t)},se.matchesSelector=function(e,t){if(T(e),d.matchesSelector&&E&&!N[t+" "]&&(!s||!s.test(t))&&(!v||!v.test(t)))try{var n=c.call(e,t);if(n||d.disconnectedMatch||e.document&&11!==e.document.nodeType)return n}catch(e){N(t,!0)}return 0<se(t,C,null,[e]).length},se.contains=function(e,t){return(e.ownerDocument||e)!=C&&T(e),y(e,t)},se.attr=function(e,t){(e.ownerDocument||e)!=C&&T(e);var n=b.attrHandle[t.toLowerCase()],r=n&&j.call(b.attrHandle,t.toLowerCase())?n(e,t,!E):void 0;return void 0!==r?r:d.attributes||!E?e.getAttribute(t):(r=e.getAttributeNode(t))&&r.specified?r.value:null},se.escape=function(e){return(e+"").replace(re,ie)},se.error=function(e){throw new Error("Syntax error, unrecognized expression: "+e)},se.uniqueSort=function(e){var t,n=[],r=0,i=0;if(l=!d.detectDuplicates,u=!d.sortStable&&e.slice(0),e.sort(D),l){while(t=e[i++])t===e[i]&&(r=n.push(i));while(r--)e.splice(n[r],1)}return u=null,e},o=se.getText=function(e){var t,n="",r=0,i=e.nodeType;if(i){if(1===i||9===i||11===i){if("string"==typeof e.textContent)return e.textContent;for(e=e.firstChild;e;e=e.nextSibling)n+=o(e)}else if(3===i||4===i)return e.nodeValue}else while(t=e[r++])n+=o(t);return n},(b=se.selectors={cacheLength:50,createPseudo:le,match:G,attrHandle:{},find:{},relative:{">":{dir:"parentNode",first:!0}," ":{dir:"parentNode"},"+":{dir:"previousSibling",first:!0},"~":{dir:"previousSibling"}},preFilter:{ATTR:function(e){return e[1]=e[1].replace(te,ne),e[3]=(e[3]||e[4]||e[5]||"").replace(te,ne),"~="===e[2]&&(e[3]=" "+e[3]+" "),e.slice(0,4)},CHILD:function(e){return e[1]=e[1].toLowerCase(),"nth"===e[1].slice(0,3)?(e[3]||se.error(e[0]),e[4]=+(e[4]?e[5]+(e[6]||1):2*("even"===e[3]||"odd"===e[3])),e[5]=+(e[7]+e[8]||"odd"===e[3])):e[3]&&se.error(e[0]),e},PSEUDO:function(e){var t,n=!e[6]&&e[2];return G.CHILD.test(e[0])?null:(e[3]?e[2]=e[4]||e[5]||"":n&&X.test(n)&&(t=h(n,!0))&&(t=n.indexOf(")",n.length-t)-n.length)&&(e[0]=e[0].slice(0,t),e[2]=n.slice(0,t)),e.slice(0,3))}},filter:{TAG:function(e){var t=e.replace(te,ne).toLowerCase();return"*"===e?function(){return!0}:function(e){return e.nodeName&&e.nodeName.toLowerCase()===t}},CLASS:function(e){var t=m[e+" "];return t||(t=new RegExp("(^|"+M+")"+e+"("+M+"|$)"))&&m(e,function(e){return t.test("string"==typeof e.className&&e.className||"undefined"!=typeof e.getAttribute&&e.getAttribute("class")||"")})},ATTR:function(n,r,i){return function(e){var t=se.attr(e,n);return null==t?"!="===r:!r||(t+="","="===r?t===i:"!="===r?t!==i:"^="===r?i&&0===t.indexOf(i):"*="===r?i&&-1<t.indexOf(i):"$="===r?i&&t.slice(-i.length)===i:"~="===r?-1<(" "+t.replace(B," ")+" ").indexOf(i):"|="===r&&(t===i||t.slice(0,i.length+1)===i+"-"))}},CHILD:function(h,e,t,g,v){var y="nth"!==h.slice(0,3),m="last"!==h.slice(-4),x="of-type"===e;return 1===g&&0===v?function(e){return!!e.parentNode}:function(e,t,n){var r,i,o,a,s,u,l=y!==m?"nextSibling":"previousSibling",c=e.parentNode,f=x&&e.nodeName.toLowerCase(),p=!n&&!x,d=!1;if(c){if(y){while(l){a=e;while(a=a[l])if(x?a.nodeName.toLowerCase()===f:1===a.nodeType)return!1;u=l="only"===h&&!u&&"nextSibling"}return!0}if(u=[m?c.firstChild:c.lastChild],m&&p){d=(s=(r=(i=(o=(a=c)[S]||(a[S]={}))[a.uniqueID]||(o[a.uniqueID]={}))[h]||[])[0]===k&&r[1])&&r[2],a=s&&c.childNodes[s];while(a=++s&&a&&a[l]||(d=s=0)||u.pop())if(1===a.nodeType&&++d&&a===e){i[h]=[k,s,d];break}}else if(p&&(d=s=(r=(i=(o=(a=e)[S]||(a[S]={}))[a.uniqueID]||(o[a.uniqueID]={}))[h]||[])[0]===k&&r[1]),!1===d)while(a=++s&&a&&a[l]||(d=s=0)||u.pop())if((x?a.nodeName.toLowerCase()===f:1===a.nodeType)&&++d&&(p&&((i=(o=a[S]||(a[S]={}))[a.uniqueID]||(o[a.uniqueID]={}))[h]=[k,d]),a===e))break;return(d-=v)===g||d%g==0&&0<=d/g}}},PSEUDO:function(e,o){var t,a=b.pseudos[e]||b.setFilters[e.toLowerCase()]||se.error("unsupported pseudo: "+e);return a[S]?a(o):1<a.length?(t=[e,e,"",o],b.setFilters.hasOwnProperty(e.toLowerCase())?le(function(e,t){var n,r=a(e,o),i=r.length;while(i--)e[n=P(e,r[i])]=!(t[n]=r[i])}):function(e){return a(e,0,t)}):a}},pseudos:{not:le(function(e){var r=[],i=[],s=f(e.replace($,"$1"));return s[S]?le(function(e,t,n,r){var i,o=s(e,null,r,[]),a=e.length;while(a--)(i=o[a])&&(e[a]=!(t[a]=i))}):function(e,t,n){return r[0]=e,s(r,null,n,i),r[0]=null,!i.pop()}}),has:le(function(t){return function(e){return 0<se(t,e).length}}),contains:le(function(t){return t=t.replace(te,ne),function(e){return-1<(e.textContent||o(e)).indexOf(t)}}),lang:le(function(n){return V.test(n||"")||se.error("unsupported lang: "+n),n=n.replace(te,ne).toLowerCase(),function(e){var t;do{if(t=E?e.lang:e.getAttribute("xml:lang")||e.getAttribute("lang"))return(t=t.toLowerCase())===n||0===t.indexOf(n+"-")}while((e=e.parentNode)&&1===e.nodeType);return!1}}),target:function(e){var t=n.location&&n.location.hash;return t&&t.slice(1)===e.id},root:function(e){return e===a},focus:function(e){return e===C.activeElement&&(!C.hasFocus||C.hasFocus())&&!!(e.type||e.href||~e.tabIndex)},enabled:ge(!1),disabled:ge(!0),checked:function(e){var t=e.nodeName.toLowerCase();return"input"===t&&!!e.checked||"option"===t&&!!e.selected},selected:function(e){return e.parentNode&&e.parentNode.selectedIndex,!0===e.selected},empty:function(e){for(e=e.firstChild;e;e=e.nextSibling)if(e.nodeType<6)return!1;return!0},parent:function(e){return!b.pseudos.empty(e)},header:function(e){return J.test(e.nodeName)},input:function(e){return Q.test(e.nodeName)},button:function(e){var t=e.nodeName.toLowerCase();return"input"===t&&"button"===e.type||"button"===t},text:function(e){var t;return"input"===e.nodeName.toLowerCase()&&"text"===e.type&&(null==(t=e.getAttribute("type"))||"text"===t.toLowerCase())},first:ve(function(){return[0]}),last:ve(function(e,t){return[t-1]}),eq:ve(function(e,t,n){return[n<0?n+t:n]}),even:ve(function(e,t){for(var n=0;n<t;n+=2)e.push(n);return e}),odd:ve(function(e,t){for(var n=1;n<t;n+=2)e.push(n);return e}),lt:ve(function(e,t,n){for(var r=n<0?n+t:t<n?t:n;0<=--r;)e.push(r);return e}),gt:ve(function(e,t,n){for(var r=n<0?n+t:n;++r<t;)e.push(r);return e})}}).pseudos.nth=b.pseudos.eq,{radio:!0,checkbox:!0,file:!0,password:!0,image:!0})b.pseudos[e]=de(e);for(e in{submit:!0,reset:!0})b.pseudos[e]=he(e);function me(){}function xe(e){for(var t=0,n=e.length,r="";t<n;t++)r+=e[t].value;return r}function be(s,e,t){var u=e.dir,l=e.next,c=l||u,f=t&&"parentNode"===c,p=r++;return e.first?function(e,t,n){while(e=e[u])if(1===e.nodeType||f)return s(e,t,n);return!1}:function(e,t,n){var r,i,o,a=[k,p];if(n){while(e=e[u])if((1===e.nodeType||f)&&s(e,t,n))return!0}else while(e=e[u])if(1===e.nodeType||f)if(i=(o=e[S]||(e[S]={}))[e.uniqueID]||(o[e.uniqueID]={}),l&&l===e.nodeName.toLowerCase())e=e[u]||e;else{if((r=i[c])&&r[0]===k&&r[1]===p)return a[2]=r[2];if((i[c]=a)[2]=s(e,t,n))return!0}return!1}}function we(i){return 1<i.length?function(e,t,n){var r=i.length;while(r--)if(!i[r](e,t,n))return!1;return!0}:i[0]}function Te(e,t,n,r,i){for(var o,a=[],s=0,u=e.length,l=null!=t;s<u;s++)(o=e[s])&&(n&&!n(o,r,i)||(a.push(o),l&&t.push(s)));return a}function Ce(d,h,g,v,y,e){return v&&!v[S]&&(v=Ce(v)),y&&!y[S]&&(y=Ce(y,e)),le(function(e,t,n,r){var i,o,a,s=[],u=[],l=t.length,c=e||function(e,t,n){for(var r=0,i=t.length;r<i;r++)se(e,t[r],n);return n}(h||"*",n.nodeType?[n]:n,[]),f=!d||!e&&h?c:Te(c,s,d,n,r),p=g?y||(e?d:l||v)?[]:t:f;if(g&&g(f,p,n,r),v){i=Te(p,u),v(i,[],n,r),o=i.length;while(o--)(a=i[o])&&(p[u[o]]=!(f[u[o]]=a))}if(e){if(y||d){if(y){i=[],o=p.length;while(o--)(a=p[o])&&i.push(f[o]=a);y(null,p=[],i,r)}o=p.length;while(o--)(a=p[o])&&-1<(i=y?P(e,a):s[o])&&(e[i]=!(t[i]=a))}}else p=Te(p===t?p.splice(l,p.length):p),y?y(null,t,p,r):H.apply(t,p)})}function Ee(e){for(var i,t,n,r=e.length,o=b.relative[e[0].type],a=o||b.relative[" "],s=o?1:0,u=be(function(e){return e===i},a,!0),l=be(function(e){return-1<P(i,e)},a,!0),c=[function(e,t,n){var r=!o&&(n||t!==w)||((i=t).nodeType?u(e,t,n):l(e,t,n));return i=null,r}];s<r;s++)if(t=b.relative[e[s].type])c=[be(we(c),t)];else{if((t=b.filter[e[s].type].apply(null,e[s].matches))[S]){for(n=++s;n<r;n++)if(b.relative[e[n].type])break;return Ce(1<s&&we(c),1<s&&xe(e.slice(0,s-1).concat({value:" "===e[s-2].type?"*":""})).replace($,"$1"),t,s<n&&Ee(e.slice(s,n)),n<r&&Ee(e=e.slice(n)),n<r&&xe(e))}c.push(t)}return we(c)}return me.prototype=b.filters=b.pseudos,b.setFilters=new me,h=se.tokenize=function(e,t){var n,r,i,o,a,s,u,l=x[e+" "];if(l)return t?0:l.slice(0);a=e,s=[],u=b.preFilter;while(a){for(o in n&&!(r=_.exec(a))||(r&&(a=a.slice(r[0].length)||a),s.push(i=[])),n=!1,(r=z.exec(a))&&(n=r.shift(),i.push({value:n,type:r[0].replace($," ")}),a=a.slice(n.length)),b.filter)!(r=G[o].exec(a))||u[o]&&!(r=u[o](r))||(n=r.shift(),i.push({value:n,type:o,matches:r}),a=a.slice(n.length));if(!n)break}return t?a.length:a?se.error(e):x(e,s).slice(0)},f=se.compile=function(e,t){var n,v,y,m,x,r,i=[],o=[],a=A[e+" "];if(!a){t||(t=h(e)),n=t.length;while(n--)(a=Ee(t[n]))[S]?i.push(a):o.push(a);(a=A(e,(v=o,m=0<(y=i).length,x=0<v.length,r=function(e,t,n,r,i){var o,a,s,u=0,l="0",c=e&&[],f=[],p=w,d=e||x&&b.find.TAG("*",i),h=k+=null==p?1:Math.random()||.1,g=d.length;for(i&&(w=t==C||t||i);l!==g&&null!=(o=d[l]);l++){if(x&&o){a=0,t||o.ownerDocument==C||(T(o),n=!E);while(s=v[a++])if(s(o,t||C,n)){r.push(o);break}i&&(k=h)}m&&((o=!s&&o)&&u--,e&&c.push(o))}if(u+=l,m&&l!==u){a=0;while(s=y[a++])s(c,f,t,n);if(e){if(0<u)while(l--)c[l]||f[l]||(f[l]=q.call(r));f=Te(f)}H.apply(r,f),i&&!e&&0<f.length&&1<u+y.length&&se.uniqueSort(r)}return i&&(k=h,w=p),c},m?le(r):r))).selector=e}return a},g=se.select=function(e,t,n,r){var i,o,a,s,u,l="function"==typeof e&&e,c=!r&&h(e=l.selector||e);if(n=n||[],1===c.length){if(2<(o=c[0]=c[0].slice(0)).length&&"ID"===(a=o[0]).type&&9===t.nodeType&&E&&b.relative[o[1].type]){if(!(t=(b.find.ID(a.matches[0].replace(te,ne),t)||[])[0]))return n;l&&(t=t.parentNode),e=e.slice(o.shift().value.length)}i=G.needsContext.test(e)?0:o.length;while(i--){if(a=o[i],b.relative[s=a.type])break;if((u=b.find[s])&&(r=u(a.matches[0].replace(te,ne),ee.test(o[0].type)&&ye(t.parentNode)||t))){if(o.splice(i,1),!(e=r.length&&xe(o)))return H.apply(n,r),n;break}}}return(l||f(e,c))(r,t,!E,n,!t||ee.test(e)&&ye(t.parentNode)||t),n},d.sortStable=S.split("").sort(D).join("")===S,d.detectDuplicates=!!l,T(),d.sortDetached=ce(function(e){return 1&e.compareDocumentPosition(C.createElement("fieldset"))}),ce(function(e){return e.innerHTML="<a href='#'></a>","#"===e.firstChild.getAttribute("href")})||fe("type|href|height|width",function(e,t,n){if(!n)return e.getAttribute(t,"type"===t.toLowerCase()?1:2)}),d.attributes&&ce(function(e){return e.innerHTML="<input/>",e.firstChild.setAttribute("value",""),""===e.firstChild.getAttribute("value")})||fe("value",function(e,t,n){if(!n&&"input"===e.nodeName.toLowerCase())return e.defaultValue}),ce(function(e){return null==e.getAttribute("disabled")})||fe(R,function(e,t,n){var r;if(!n)return!0===e[t]?t.toLowerCase():(r=e.getAttributeNode(t))&&r.specified?r.value:null}),se}(C);S.find=d,S.expr=d.selectors,S.expr[":"]=S.expr.pseudos,S.uniqueSort=S.unique=d.uniqueSort,S.text=d.getText,S.isXMLDoc=d.isXML,S.contains=d.contains,S.escapeSelector=d.escape;var h=function(e,t,n){var r=[],i=void 0!==n;while((e=e[t])&&9!==e.nodeType)if(1===e.nodeType){if(i&&S(e).is(n))break;r.push(e)}return r},T=function(e,t){for(var n=[];e;e=e.nextSibling)1===e.nodeType&&e!==t&&n.push(e);return n},k=S.expr.match.needsContext;function A(e,t){return e.nodeName&&e.nodeName.toLowerCase()===t.toLowerCase()}var N=/^<([a-z][^\/\0>:\x20\t\r\n\f]*)[\x20\t\r\n\f]*\/?>(?:<\/\1>|)$/i;function D(e,n,r){return m(n)?S.grep(e,function(e,t){return!!n.call(e,t,e)!==r}):n.nodeType?S.grep(e,function(e){return e===n!==r}):"string"!=typeof n?S.grep(e,function(e){return-1<i.call(n,e)!==r}):S.filter(n,e,r)}S.filter=function(e,t,n){var r=t[0];return n&&(e=":not("+e+")"),1===t.length&&1===r.nodeType?S.find.matchesSelector(r,e)?[r]:[]:S.find.matches(e,S.grep(t,function(e){return 1===e.nodeType}))},S.fn.extend({find:function(e){var t,n,r=this.length,i=this;if("string"!=typeof e)return this.pushStack(S(e).filter(function(){for(t=0;t<r;t++)if(S.contains(i[t],this))return!0}));for(n=this.pushStack([]),t=0;t<r;t++)S.find(e,i[t],n);return 1<r?S.uniqueSort(n):n},filter:function(e){return this.pushStack(D(this,e||[],!1))},not:function(e){return this.pushStack(D(this,e||[],!0))},is:function(e){return!!D(this,"string"==typeof e&&k.test(e)?S(e):e||[],!1).length}});var j,q=/^(?:\s*(<[\w\W]+>)[^>]*|#([\w-]+))$/;(S.fn.init=function(e,t,n){var r,i;if(!e)return this;if(n=n||j,"string"==typeof e){if(!(r="<"===e[0]&&">"===e[e.length-1]&&3<=e.length?[null,e,null]:q.exec(e))||!r[1]&&t)return!t||t.jquery?(t||n).find(e):this.constructor(t).find(e);if(r[1]){if(t=t instanceof S?t[0]:t,S.merge(this,S.parseHTML(r[1],t&&t.nodeType?t.ownerDocument||t:E,!0)),N.test(r[1])&&S.isPlainObject(t))for(r in t)m(this[r])?this[r](t[r]):this.attr(r,t[r]);return this}return(i=E.getElementById(r[2]))&&(this[0]=i,this.length=1),this}return e.nodeType?(this[0]=e,this.length=1,this):m(e)?void 0!==n.ready?n.ready(e):e(S):S.makeArray(e,this)}).prototype=S.fn,j=S(E);var L=/^(?:parents|prev(?:Until|All))/,H={children:!0,contents:!0,next:!0,prev:!0};function O(e,t){while((e=e[t])&&1!==e.nodeType);return e}S.fn.extend({has:function(e){var t=S(e,this),n=t.length;return this.filter(function(){for(var e=0;e<n;e++)if(S.contains(this,t[e]))return!0})},closest:function(e,t){var n,r=0,i=this.length,o=[],a="string"!=typeof e&&S(e);if(!k.test(e))for(;r<i;r++)for(n=this[r];n&&n!==t;n=n.parentNode)if(n.nodeType<11&&(a?-1<a.index(n):1===n.nodeType&&S.find.matchesSelector(n,e))){o.push(n);break}return this.pushStack(1<o.length?S.uniqueSort(o):o)},index:function(e){return e?"string"==typeof e?i.call(S(e),this[0]):i.call(this,e.jquery?e[0]:e):this[0]&&this[0].parentNode?this.first().prevAll().length:-1},add:function(e,t){return this.pushStack(S.uniqueSort(S.merge(this.get(),S(e,t))))},addBack:function(e){return this.add(null==e?this.prevObject:this.prevObject.filter(e))}}),S.each({parent:function(e){var t=e.parentNode;return t&&11!==t.nodeType?t:null},parents:function(e){return h(e,"parentNode")},parentsUntil:function(e,t,n){return h(e,"parentNode",n)},next:function(e){return O(e,"nextSibling")},prev:function(e){return O(e,"previousSibling")},nextAll:function(e){return h(e,"nextSibling")},prevAll:function(e){return h(e,"previousSibling")},nextUntil:function(e,t,n){return h(e,"nextSibling",n)},prevUntil:function(e,t,n){return h(e,"previousSibling",n)},siblings:function(e){return T((e.parentNode||{}).firstChild,e)},children:function(e){return T(e.firstChild)},contents:function(e){return null!=e.contentDocument&&r(e.contentDocument)?e.contentDocument:(A(e,"template")&&(e=e.content||e),S.merge([],e.childNodes))}},function(r,i){S.fn[r]=function(e,t){var n=S.map(this,i,e);return"Until"!==r.slice(-5)&&(t=e),t&&"string"==typeof t&&(n=S.filter(t,n)),1<this.length&&(H[r]||S.uniqueSort(n),L.test(r)&&n.reverse()),this.pushStack(n)}});var P=/[^\x20\t\r\n\f]+/g;function R(e){return e}function M(e){throw e}function I(e,t,n,r){var i;try{e&&m(i=e.promise)?i.call(e).done(t).fail(n):e&&m(i=e.then)?i.call(e,t,n):t.apply(void 0,[e].slice(r))}catch(e){n.apply(void 0,[e])}}S.Callbacks=function(r){var e,n;r="string"==typeof r?(e=r,n={},S.each(e.match(P)||[],function(e,t){n[t]=!0}),n):S.extend({},r);var i,t,o,a,s=[],u=[],l=-1,c=function(){for(a=a||r.once,o=i=!0;u.length;l=-1){t=u.shift();while(++l<s.length)!1===s[l].apply(t[0],t[1])&&r.stopOnFalse&&(l=s.length,t=!1)}r.memory||(t=!1),i=!1,a&&(s=t?[]:"")},f={add:function(){return s&&(t&&!i&&(l=s.length-1,u.push(t)),function n(e){S.each(e,function(e,t){m(t)?r.unique&&f.has(t)||s.push(t):t&&t.length&&"string"!==w(t)&&n(t)})}(arguments),t&&!i&&c()),this},remove:function(){return S.each(arguments,function(e,t){var n;while(-1<(n=S.inArray(t,s,n)))s.splice(n,1),n<=l&&l--}),this},has:function(e){return e?-1<S.inArray(e,s):0<s.length},empty:function(){return s&&(s=[]),this},disable:function(){return a=u=[],s=t="",this},disabled:function(){return!s},lock:function(){return a=u=[],t||i||(s=t=""),this},locked:function(){return!!a},fireWith:function(e,t){return a||(t=[e,(t=t||[]).slice?t.slice():t],u.push(t),i||c()),this},fire:function(){return f.fireWith(this,arguments),this},fired:function(){return!!o}};return f},S.extend({Deferred:function(e){var o=[["notify","progress",S.Callbacks("memory"),S.Callbacks("memory"),2],["resolve","done",S.Callbacks("once memory"),S.Callbacks("once memory"),0,"resolved"],["reject","fail",S.Callbacks("once memory"),S.Callbacks("once memory"),1,"rejected"]],i="pending",a={state:function(){return i},always:function(){return s.done(arguments).fail(arguments),this},"catch":function(e){return a.then(null,e)},pipe:function(){var i=arguments;return S.Deferred(function(r){S.each(o,function(e,t){var n=m(i[t[4]])&&i[t[4]];s[t[1]](function(){var e=n&&n.apply(this,arguments);e&&m(e.promise)?e.promise().progress(r.notify).done(r.resolve).fail(r.reject):r[t[0]+"With"](this,n?[e]:arguments)})}),i=null}).promise()},then:function(t,n,r){var u=0;function l(i,o,a,s){return function(){var n=this,r=arguments,e=function(){var e,t;if(!(i<u)){if((e=a.apply(n,r))===o.promise())throw new TypeError("Thenable self-resolution");t=e&&("object"==typeof e||"function"==typeof e)&&e.then,m(t)?s?t.call(e,l(u,o,R,s),l(u,o,M,s)):(u++,t.call(e,l(u,o,R,s),l(u,o,M,s),l(u,o,R,o.notifyWith))):(a!==R&&(n=void 0,r=[e]),(s||o.resolveWith)(n,r))}},t=s?e:function(){try{e()}catch(e){S.Deferred.exceptionHook&&S.Deferred.exceptionHook(e,t.stackTrace),u<=i+1&&(a!==M&&(n=void 0,r=[e]),o.rejectWith(n,r))}};i?t():(S.Deferred.getStackHook&&(t.stackTrace=S.Deferred.getStackHook()),C.setTimeout(t))}}return S.Deferred(function(e){o[0][3].add(l(0,e,m(r)?r:R,e.notifyWith)),o[1][3].add(l(0,e,m(t)?t:R)),o[2][3].add(l(0,e,m(n)?n:M))}).promise()},promise:function(e){return null!=e?S.extend(e,a):a}},s={};return S.each(o,function(e,t){var n=t[2],r=t[5];a[t[1]]=n.add,r&&n.add(function(){i=r},o[3-e][2].disable,o[3-e][3].disable,o[0][2].lock,o[0][3].lock),n.add(t[3].fire),s[t[0]]=function(){return s[t[0]+"With"](this===s?void 0:this,arguments),this},s[t[0]+"With"]=n.fireWith}),a.promise(s),e&&e.call(s,s),s},when:function(e){var n=arguments.length,t=n,r=Array(t),i=s.call(arguments),o=S.Deferred(),a=function(t){return function(e){r[t]=this,i[t]=1<arguments.length?s.call(arguments):e,--n||o.resolveWith(r,i)}};if(n<=1&&(I(e,o.done(a(t)).resolve,o.reject,!n),"pending"===o.state()||m(i[t]&&i[t].then)))return o.then();while(t--)I(i[t],a(t),o.reject);return o.promise()}});var W=/^(Eval|Internal|Range|Reference|Syntax|Type|URI)Error$/;S.Deferred.exceptionHook=function(e,t){C.console&&C.console.warn&&e&&W.test(e.name)&&C.console.warn("jQuery.Deferred exception: "+e.message,e.stack,t)},S.readyException=function(e){C.setTimeout(function(){throw e})};var F=S.Deferred();function B(){E.removeEventListener("DOMContentLoaded",B),C.removeEventListener("load",B),S.ready()}S.fn.ready=function(e){return F.then(e)["catch"](function(e){S.readyException(e)}),this},S.extend({isReady:!1,readyWait:1,ready:function(e){(!0===e?--S.readyWait:S.isReady)||(S.isReady=!0)!==e&&0<--S.readyWait||F.resolveWith(E,[S])}}),S.ready.then=F.then,"complete"===E.readyState||"loading"!==E.readyState&&!E.documentElement.doScroll?C.setTimeout(S.ready):(E.addEventListener("DOMContentLoaded",B),C.addEventListener("load",B));var $=function(e,t,n,r,i,o,a){var s=0,u=e.length,l=null==n;if("object"===w(n))for(s in i=!0,n)$(e,t,s,n[s],!0,o,a);else if(void 0!==r&&(i=!0,m(r)||(a=!0),l&&(a?(t.call(e,r),t=null):(l=t,t=function(e,t,n){return l.call(S(e),n)})),t))for(;s<u;s++)t(e[s],n,a?r:r.call(e[s],s,t(e[s],n)));return i?e:l?t.call(e):u?t(e[0],n):o},_=/^-ms-/,z=/-([a-z])/g;function U(e,t){return t.toUpperCase()}function X(e){return e.replace(_,"ms-").replace(z,U)}var V=function(e){return 1===e.nodeType||9===e.nodeType||!+e.nodeType};function G(){this.expando=S.expando+G.uid++}G.uid=1,G.prototype={cache:function(e){var t=e[this.expando];return t||(t={},V(e)&&(e.nodeType?e[this.expando]=t:Object.defineProperty(e,this.expando,{value:t,configurable:!0}))),t},set:function(e,t,n){var r,i=this.cache(e);if("string"==typeof t)i[X(t)]=n;else for(r in t)i[X(r)]=t[r];return i},get:function(e,t){return void 0===t?this.cache(e):e[this.expando]&&e[this.expando][X(t)]},access:function(e,t,n){return void 0===t||t&&"string"==typeof t&&void 0===n?this.get(e,t):(this.set(e,t,n),void 0!==n?n:t)},remove:function(e,t){var n,r=e[this.expando];if(void 0!==r){if(void 0!==t){n=(t=Array.isArray(t)?t.map(X):(t=X(t))in r?[t]:t.match(P)||[]).length;while(n--)delete r[t[n]]}(void 0===t||S.isEmptyObject(r))&&(e.nodeType?e[this.expando]=void 0:delete e[this.expando])}},hasData:function(e){var t=e[this.expando];return void 0!==t&&!S.isEmptyObject(t)}};var Y=new G,Q=new G,J=/^(?:\{[\w\W]*\}|\[[\w\W]*\])$/,K=/[A-Z]/g;function Z(e,t,n){var r,i;if(void 0===n&&1===e.nodeType)if(r="data-"+t.replace(K,"-$&").toLowerCase(),"string"==typeof(n=e.getAttribute(r))){try{n="true"===(i=n)||"false"!==i&&("null"===i?null:i===+i+""?+i:J.test(i)?JSON.parse(i):i)}catch(e){}Q.set(e,t,n)}else n=void 0;return n}S.extend({hasData:function(e){return Q.hasData(e)||Y.hasData(e)},data:function(e,t,n){return Q.access(e,t,n)},removeData:function(e,t){Q.remove(e,t)},_data:function(e,t,n){return Y.access(e,t,n)},_removeData:function(e,t){Y.remove(e,t)}}),S.fn.extend({data:function(n,e){var t,r,i,o=this[0],a=o&&o.attributes;if(void 0===n){if(this.length&&(i=Q.get(o),1===o.nodeType&&!Y.get(o,"hasDataAttrs"))){t=a.length;while(t--)a[t]&&0===(r=a[t].name).indexOf("data-")&&(r=X(r.slice(5)),Z(o,r,i[r]));Y.set(o,"hasDataAttrs",!0)}return i}return"object"==typeof n?this.each(function(){Q.set(this,n)}):$(this,function(e){var t;if(o&&void 0===e)return void 0!==(t=Q.get(o,n))?t:void 0!==(t=Z(o,n))?t:void 0;this.each(function(){Q.set(this,n,e)})},null,e,1<arguments.length,null,!0)},removeData:function(e){return this.each(function(){Q.remove(this,e)})}}),S.extend({queue:function(e,t,n){var r;if(e)return t=(t||"fx")+"queue",r=Y.get(e,t),n&&(!r||Array.isArray(n)?r=Y.access(e,t,S.makeArray(n)):r.push(n)),r||[]},dequeue:function(e,t){t=t||"fx";var n=S.queue(e,t),r=n.length,i=n.shift(),o=S._queueHooks(e,t);"inprogress"===i&&(i=n.shift(),r--),i&&("fx"===t&&n.unshift("inprogress"),delete o.stop,i.call(e,function(){S.dequeue(e,t)},o)),!r&&o&&o.empty.fire()},_queueHooks:function(e,t){var n=t+"queueHooks";return Y.get(e,n)||Y.access(e,n,{empty:S.Callbacks("once memory").add(function(){Y.remove(e,[t+"queue",n])})})}}),S.fn.extend({queue:function(t,n){var e=2;return"string"!=typeof t&&(n=t,t="fx",e--),arguments.length<e?S.queue(this[0],t):void 0===n?this:this.each(function(){var e=S.queue(this,t,n);S._queueHooks(this,t),"fx"===t&&"inprogress"!==e[0]&&S.dequeue(this,t)})},dequeue:function(e){return this.each(function(){S.dequeue(this,e)})},clearQueue:function(e){return this.queue(e||"fx",[])},promise:function(e,t){var n,r=1,i=S.Deferred(),o=this,a=this.length,s=function(){--r||i.resolveWith(o,[o])};"string"!=typeof e&&(t=e,e=void 0),e=e||"fx";while(a--)(n=Y.get(o[a],e+"queueHooks"))&&n.empty&&(r++,n.empty.add(s));return s(),i.promise(t)}});var ee=/[+-]?(?:\d*\.|)\d+(?:[eE][+-]?\d+|)/.source,te=new RegExp("^(?:([+-])=|)("+ee+")([a-z%]*)$","i"),ne=["Top","Right","Bottom","Left"],re=E.documentElement,ie=function(e){return S.contains(e.ownerDocument,e)},oe={composed:!0};re.getRootNode&&(ie=function(e){return S.contains(e.ownerDocument,e)||e.getRootNode(oe)===e.ownerDocument});var ae=function(e,t){return"none"===(e=t||e).style.display||""===e.style.display&&ie(e)&&"none"===S.css(e,"display")};function se(e,t,n,r){var i,o,a=20,s=r?function(){return r.cur()}:function(){return S.css(e,t,"")},u=s(),l=n&&n[3]||(S.cssNumber[t]?"":"px"),c=e.nodeType&&(S.cssNumber[t]||"px"!==l&&+u)&&te.exec(S.css(e,t));if(c&&c[3]!==l){u/=2,l=l||c[3],c=+u||1;while(a--)S.style(e,t,c+l),(1-o)*(1-(o=s()/u||.5))<=0&&(a=0),c/=o;c*=2,S.style(e,t,c+l),n=n||[]}return n&&(c=+c||+u||0,i=n[1]?c+(n[1]+1)*n[2]:+n[2],r&&(r.unit=l,r.start=c,r.end=i)),i}var ue={};function le(e,t){for(var n,r,i,o,a,s,u,l=[],c=0,f=e.length;c<f;c++)(r=e[c]).style&&(n=r.style.display,t?("none"===n&&(l[c]=Y.get(r,"display")||null,l[c]||(r.style.display="")),""===r.style.display&&ae(r)&&(l[c]=(u=a=o=void 0,a=(i=r).ownerDocument,s=i.nodeName,(u=ue[s])||(o=a.body.appendChild(a.createElement(s)),u=S.css(o,"display"),o.parentNode.removeChild(o),"none"===u&&(u="block"),ue[s]=u)))):"none"!==n&&(l[c]="none",Y.set(r,"display",n)));for(c=0;c<f;c++)null!=l[c]&&(e[c].style.display=l[c]);return e}S.fn.extend({show:function(){return le(this,!0)},hide:function(){return le(this)},toggle:function(e){return"boolean"==typeof e?e?this.show():this.hide():this.each(function(){ae(this)?S(this).show():S(this).hide()})}});var ce,fe,pe=/^(?:checkbox|radio)$/i,de=/<([a-z][^\/\0>\x20\t\r\n\f]*)/i,he=/^$|^module$|\/(?:java|ecma)script/i;ce=E.createDocumentFragment().appendChild(E.createElement("div")),(fe=E.createElement("input")).setAttribute("type","radio"),fe.setAttribute("checked","checked"),fe.setAttribute("name","t"),ce.appendChild(fe),y.checkClone=ce.cloneNode(!0).cloneNode(!0).lastChild.checked,ce.innerHTML="<textarea>x</textarea>",y.noCloneChecked=!!ce.cloneNode(!0).lastChild.defaultValue,ce.innerHTML="<option></option>",y.option=!!ce.lastChild;var ge={thead:[1,"<table>","</table>"],col:[2,"<table><colgroup>","</colgroup></table>"],tr:[2,"<table><tbody>","</tbody></table>"],td:[3,"<table><tbody><tr>","</tr></tbody></table>"],_default:[0,"",""]};function ve(e,t){var n;return n="undefined"!=typeof e.getElementsByTagName?e.getElementsByTagName(t||"*"):"undefined"!=typeof e.querySelectorAll?e.querySelectorAll(t||"*"):[],void 0===t||t&&A(e,t)?S.merge([e],n):n}function ye(e,t){for(var n=0,r=e.length;n<r;n++)Y.set(e[n],"globalEval",!t||Y.get(t[n],"globalEval"))}ge.tbody=ge.tfoot=ge.colgroup=ge.caption=ge.thead,ge.th=ge.td,y.option||(ge.optgroup=ge.option=[1,"<select multiple='multiple'>","</select>"]);var me=/<|&#?\w+;/;function xe(e,t,n,r,i){for(var o,a,s,u,l,c,f=t.createDocumentFragment(),p=[],d=0,h=e.length;d<h;d++)if((o=e[d])||0===o)if("object"===w(o))S.merge(p,o.nodeType?[o]:o);else if(me.test(o)){a=a||f.appendChild(t.createElement("div")),s=(de.exec(o)||["",""])[1].toLowerCase(),u=ge[s]||ge._default,a.innerHTML=u[1]+S.htmlPrefilter(o)+u[2],c=u[0];while(c--)a=a.lastChild;S.merge(p,a.childNodes),(a=f.firstChild).textContent=""}else p.push(t.createTextNode(o));f.textContent="",d=0;while(o=p[d++])if(r&&-1<S.inArray(o,r))i&&i.push(o);else if(l=ie(o),a=ve(f.appendChild(o),"script"),l&&ye(a),n){c=0;while(o=a[c++])he.test(o.type||"")&&n.push(o)}return f}var be=/^key/,we=/^(?:mouse|pointer|contextmenu|drag|drop)|click/,Te=/^([^.]*)(?:\.(.+)|)/;function Ce(){return!0}function Ee(){return!1}function Se(e,t){return e===function(){try{return E.activeElement}catch(e){}}()==("focus"===t)}function ke(e,t,n,r,i,o){var a,s;if("object"==typeof t){for(s in"string"!=typeof n&&(r=r||n,n=void 0),t)ke(e,s,n,r,t[s],o);return e}if(null==r&&null==i?(i=n,r=n=void 0):null==i&&("string"==typeof n?(i=r,r=void 0):(i=r,r=n,n=void 0)),!1===i)i=Ee;else if(!i)return e;return 1===o&&(a=i,(i=function(e){return S().off(e),a.apply(this,arguments)}).guid=a.guid||(a.guid=S.guid++)),e.each(function(){S.event.add(this,t,i,r,n)})}function Ae(e,i,o){o?(Y.set(e,i,!1),S.event.add(e,i,{namespace:!1,handler:function(e){var t,n,r=Y.get(this,i);if(1&e.isTrigger&&this[i]){if(r.length)(S.event.special[i]||{}).delegateType&&e.stopPropagation();else if(r=s.call(arguments),Y.set(this,i,r),t=o(this,i),this[i](),r!==(n=Y.get(this,i))||t?Y.set(this,i,!1):n={},r!==n)return e.stopImmediatePropagation(),e.preventDefault(),n.value}else r.length&&(Y.set(this,i,{value:S.event.trigger(S.extend(r[0],S.Event.prototype),r.slice(1),this)}),e.stopImmediatePropagation())}})):void 0===Y.get(e,i)&&S.event.add(e,i,Ce)}S.event={global:{},add:function(t,e,n,r,i){var o,a,s,u,l,c,f,p,d,h,g,v=Y.get(t);if(V(t)){n.handler&&(n=(o=n).handler,i=o.selector),i&&S.find.matchesSelector(re,i),n.guid||(n.guid=S.guid++),(u=v.events)||(u=v.events=Object.create(null)),(a=v.handle)||(a=v.handle=function(e){return"undefined"!=typeof S&&S.event.triggered!==e.type?S.event.dispatch.apply(t,arguments):void 0}),l=(e=(e||"").match(P)||[""]).length;while(l--)d=g=(s=Te.exec(e[l])||[])[1],h=(s[2]||"").split(".").sort(),d&&(f=S.event.special[d]||{},d=(i?f.delegateType:f.bindType)||d,f=S.event.special[d]||{},c=S.extend({type:d,origType:g,data:r,handler:n,guid:n.guid,selector:i,needsContext:i&&S.expr.match.needsContext.test(i),namespace:h.join(".")},o),(p=u[d])||((p=u[d]=[]).delegateCount=0,f.setup&&!1!==f.setup.call(t,r,h,a)||t.addEventListener&&t.addEventListener(d,a)),f.add&&(f.add.call(t,c),c.handler.guid||(c.handler.guid=n.guid)),i?p.splice(p.delegateCount++,0,c):p.push(c),S.event.global[d]=!0)}},remove:function(e,t,n,r,i){var o,a,s,u,l,c,f,p,d,h,g,v=Y.hasData(e)&&Y.get(e);if(v&&(u=v.events)){l=(t=(t||"").match(P)||[""]).length;while(l--)if(d=g=(s=Te.exec(t[l])||[])[1],h=(s[2]||"").split(".").sort(),d){f=S.event.special[d]||{},p=u[d=(r?f.delegateType:f.bindType)||d]||[],s=s[2]&&new RegExp("(^|\\.)"+h.join("\\.(?:.*\\.|)")+"(\\.|$)"),a=o=p.length;while(o--)c=p[o],!i&&g!==c.origType||n&&n.guid!==c.guid||s&&!s.test(c.namespace)||r&&r!==c.selector&&("**"!==r||!c.selector)||(p.splice(o,1),c.selector&&p.delegateCount--,f.remove&&f.remove.call(e,c));a&&!p.length&&(f.teardown&&!1!==f.teardown.call(e,h,v.handle)||S.removeEvent(e,d,v.handle),delete u[d])}else for(d in u)S.event.remove(e,d+t[l],n,r,!0);S.isEmptyObject(u)&&Y.remove(e,"handle events")}},dispatch:function(e){var t,n,r,i,o,a,s=new Array(arguments.length),u=S.event.fix(e),l=(Y.get(this,"events")||Object.create(null))[u.type]||[],c=S.event.special[u.type]||{};for(s[0]=u,t=1;t<arguments.length;t++)s[t]=arguments[t];if(u.delegateTarget=this,!c.preDispatch||!1!==c.preDispatch.call(this,u)){a=S.event.handlers.call(this,u,l),t=0;while((i=a[t++])&&!u.isPropagationStopped()){u.currentTarget=i.elem,n=0;while((o=i.handlers[n++])&&!u.isImmediatePropagationStopped())u.rnamespace&&!1!==o.namespace&&!u.rnamespace.test(o.namespace)||(u.handleObj=o,u.data=o.data,void 0!==(r=((S.event.special[o.origType]||{}).handle||o.handler).apply(i.elem,s))&&!1===(u.result=r)&&(u.preventDefault(),u.stopPropagation()))}return c.postDispatch&&c.postDispatch.call(this,u),u.result}},handlers:function(e,t){var n,r,i,o,a,s=[],u=t.delegateCount,l=e.target;if(u&&l.nodeType&&!("click"===e.type&&1<=e.button))for(;l!==this;l=l.parentNode||this)if(1===l.nodeType&&("click"!==e.type||!0!==l.disabled)){for(o=[],a={},n=0;n<u;n++)void 0===a[i=(r=t[n]).selector+" "]&&(a[i]=r.needsContext?-1<S(i,this).index(l):S.find(i,this,null,[l]).length),a[i]&&o.push(r);o.length&&s.push({elem:l,handlers:o})}return l=this,u<t.length&&s.push({elem:l,handlers:t.slice(u)}),s},addProp:function(t,e){Object.defineProperty(S.Event.prototype,t,{enumerable:!0,configurable:!0,get:m(e)?function(){if(this.originalEvent)return e(this.originalEvent)}:function(){if(this.originalEvent)return this.originalEvent[t]},set:function(e){Object.defineProperty(this,t,{enumerable:!0,configurable:!0,writable:!0,value:e})}})},fix:function(e){return e[S.expando]?e:new S.Event(e)},special:{load:{noBubble:!0},click:{setup:function(e){var t=this||e;return pe.test(t.type)&&t.click&&A(t,"input")&&Ae(t,"click",Ce),!1},trigger:function(e){var t=this||e;return pe.test(t.type)&&t.click&&A(t,"input")&&Ae(t,"click"),!0},_default:function(e){var t=e.target;return pe.test(t.type)&&t.click&&A(t,"input")&&Y.get(t,"click")||A(t,"a")}},beforeunload:{postDispatch:function(e){void 0!==e.result&&e.originalEvent&&(e.originalEvent.returnValue=e.result)}}}},S.removeEvent=function(e,t,n){e.removeEventListener&&e.removeEventListener(t,n)},S.Event=function(e,t){if(!(this instanceof S.Event))return new S.Event(e,t);e&&e.type?(this.originalEvent=e,this.type=e.type,this.isDefaultPrevented=e.defaultPrevented||void 0===e.defaultPrevented&&!1===e.returnValue?Ce:Ee,this.target=e.target&&3===e.target.nodeType?e.target.parentNode:e.target,this.currentTarget=e.currentTarget,this.relatedTarget=e.relatedTarget):this.type=e,t&&S.extend(this,t),this.timeStamp=e&&e.timeStamp||Date.now(),this[S.expando]=!0},S.Event.prototype={constructor:S.Event,isDefaultPrevented:Ee,isPropagationStopped:Ee,isImmediatePropagationStopped:Ee,isSimulated:!1,preventDefault:function(){var e=this.originalEvent;this.isDefaultPrevented=Ce,e&&!this.isSimulated&&e.preventDefault()},stopPropagation:function(){var e=this.originalEvent;this.isPropagationStopped=Ce,e&&!this.isSimulated&&e.stopPropagation()},stopImmediatePropagation:function(){var e=this.originalEvent;this.isImmediatePropagationStopped=Ce,e&&!this.isSimulated&&e.stopImmediatePropagation(),this.stopPropagation()}},S.each({altKey:!0,bubbles:!0,cancelable:!0,changedTouches:!0,ctrlKey:!0,detail:!0,eventPhase:!0,metaKey:!0,pageX:!0,pageY:!0,shiftKey:!0,view:!0,"char":!0,code:!0,charCode:!0,key:!0,keyCode:!0,button:!0,buttons:!0,clientX:!0,clientY:!0,offsetX:!0,offsetY:!0,pointerId:!0,pointerType:!0,screenX:!0,screenY:!0,targetTouches:!0,toElement:!0,touches:!0,which:function(e){var t=e.button;return null==e.which&&be.test(e.type)?null!=e.charCode?e.charCode:e.keyCode:!e.which&&void 0!==t&&we.test(e.type)?1&t?1:2&t?3:4&t?2:0:e.which}},S.event.addProp),S.each({focus:"focusin",blur:"focusout"},function(e,t){S.event.special[e]={setup:function(){return Ae(this,e,Se),!1},trigger:function(){return Ae(this,e),!0},delegateType:t}}),S.each({mouseenter:"mouseover",mouseleave:"mouseout",pointerenter:"pointerover",pointerleave:"pointerout"},function(e,i){S.event.special[e]={delegateType:i,bindType:i,handle:function(e){var t,n=e.relatedTarget,r=e.handleObj;return n&&(n===this||S.contains(this,n))||(e.type=r.origType,t=r.handler.apply(this,arguments),e.type=i),t}}}),S.fn.extend({on:function(e,t,n,r){return ke(this,e,t,n,r)},one:function(e,t,n,r){return ke(this,e,t,n,r,1)},off:function(e,t,n){var r,i;if(e&&e.preventDefault&&e.handleObj)return r=e.handleObj,S(e.delegateTarget).off(r.namespace?r.origType+"."+r.namespace:r.origType,r.selector,r.handler),this;if("object"==typeof e){for(i in e)this.off(i,t,e[i]);return this}return!1!==t&&"function"!=typeof t||(n=t,t=void 0),!1===n&&(n=Ee),this.each(function(){S.event.remove(this,e,n,t)})}});var Ne=/<script|<style|<link/i,De=/checked\s*(?:[^=]|=\s*.checked.)/i,je=/^\s*<!(?:\[CDATA\[|--)|(?:\]\]|--)>\s*$/g;function qe(e,t){return A(e,"table")&&A(11!==t.nodeType?t:t.firstChild,"tr")&&S(e).children("tbody")[0]||e}function Le(e){return e.type=(null!==e.getAttribute("type"))+"/"+e.type,e}function He(e){return"true/"===(e.type||"").slice(0,5)?e.type=e.type.slice(5):e.removeAttribute("type"),e}function Oe(e,t){var n,r,i,o,a,s;if(1===t.nodeType){if(Y.hasData(e)&&(s=Y.get(e).events))for(i in Y.remove(t,"handle events"),s)for(n=0,r=s[i].length;n<r;n++)S.event.add(t,i,s[i][n]);Q.hasData(e)&&(o=Q.access(e),a=S.extend({},o),Q.set(t,a))}}function Pe(n,r,i,o){r=g(r);var e,t,a,s,u,l,c=0,f=n.length,p=f-1,d=r[0],h=m(d);if(h||1<f&&"string"==typeof d&&!y.checkClone&&De.test(d))return n.each(function(e){var t=n.eq(e);h&&(r[0]=d.call(this,e,t.html())),Pe(t,r,i,o)});if(f&&(t=(e=xe(r,n[0].ownerDocument,!1,n,o)).firstChild,1===e.childNodes.length&&(e=t),t||o)){for(s=(a=S.map(ve(e,"script"),Le)).length;c<f;c++)u=e,c!==p&&(u=S.clone(u,!0,!0),s&&S.merge(a,ve(u,"script"))),i.call(n[c],u,c);if(s)for(l=a[a.length-1].ownerDocument,S.map(a,He),c=0;c<s;c++)u=a[c],he.test(u.type||"")&&!Y.access(u,"globalEval")&&S.contains(l,u)&&(u.src&&"module"!==(u.type||"").toLowerCase()?S._evalUrl&&!u.noModule&&S._evalUrl(u.src,{nonce:u.nonce||u.getAttribute("nonce")},l):b(u.textContent.replace(je,""),u,l))}return n}function Re(e,t,n){for(var r,i=t?S.filter(t,e):e,o=0;null!=(r=i[o]);o++)n||1!==r.nodeType||S.cleanData(ve(r)),r.parentNode&&(n&&ie(r)&&ye(ve(r,"script")),r.parentNode.removeChild(r));return e}S.extend({htmlPrefilter:function(e){return e},clone:function(e,t,n){var r,i,o,a,s,u,l,c=e.cloneNode(!0),f=ie(e);if(!(y.noCloneChecked||1!==e.nodeType&&11!==e.nodeType||S.isXMLDoc(e)))for(a=ve(c),r=0,i=(o=ve(e)).length;r<i;r++)s=o[r],u=a[r],void 0,"input"===(l=u.nodeName.toLowerCase())&&pe.test(s.type)?u.checked=s.checked:"input"!==l&&"textarea"!==l||(u.defaultValue=s.defaultValue);if(t)if(n)for(o=o||ve(e),a=a||ve(c),r=0,i=o.length;r<i;r++)Oe(o[r],a[r]);else Oe(e,c);return 0<(a=ve(c,"script")).length&&ye(a,!f&&ve(e,"script")),c},cleanData:function(e){for(var t,n,r,i=S.event.special,o=0;void 0!==(n=e[o]);o++)if(V(n)){if(t=n[Y.expando]){if(t.events)for(r in t.events)i[r]?S.event.remove(n,r):S.removeEvent(n,r,t.handle);n[Y.expando]=void 0}n[Q.expando]&&(n[Q.expando]=void 0)}}}),S.fn.extend({detach:function(e){return Re(this,e,!0)},remove:function(e){return Re(this,e)},text:function(e){return $(this,function(e){return void 0===e?S.text(this):this.empty().each(function(){1!==this.nodeType&&11!==this.nodeType&&9!==this.nodeType||(this.textContent=e)})},null,e,arguments.length)},append:function(){return Pe(this,arguments,function(e){1!==this.nodeType&&11!==this.nodeType&&9!==this.nodeType||qe(this,e).appendChild(e)})},prepend:function(){return Pe(this,arguments,function(e){if(1===this.nodeType||11===this.nodeType||9===this.nodeType){var t=qe(this,e);t.insertBefore(e,t.firstChild)}})},before:function(){return Pe(this,arguments,function(e){this.parentNode&&this.parentNode.insertBefore(e,this)})},after:function(){return Pe(this,arguments,function(e){this.parentNode&&this.parentNode.insertBefore(e,this.nextSibling)})},empty:function(){for(var e,t=0;null!=(e=this[t]);t++)1===e.nodeType&&(S.cleanData(ve(e,!1)),e.textContent="");return this},clone:function(e,t){return e=null!=e&&e,t=null==t?e:t,this.map(function(){return S.clone(this,e,t)})},html:function(e){return $(this,function(e){var t=this[0]||{},n=0,r=this.length;if(void 0===e&&1===t.nodeType)return t.innerHTML;if("string"==typeof e&&!Ne.test(e)&&!ge[(de.exec(e)||["",""])[1].toLowerCase()]){e=S.htmlPrefilter(e);try{for(;n<r;n++)1===(t=this[n]||{}).nodeType&&(S.cleanData(ve(t,!1)),t.innerHTML=e);t=0}catch(e){}}t&&this.empty().append(e)},null,e,arguments.length)},replaceWith:function(){var n=[];return Pe(this,arguments,function(e){var t=this.parentNode;S.inArray(this,n)<0&&(S.cleanData(ve(this)),t&&t.replaceChild(e,this))},n)}}),S.each({appendTo:"append",prependTo:"prepend",insertBefore:"before",insertAfter:"after",replaceAll:"replaceWith"},function(e,a){S.fn[e]=function(e){for(var t,n=[],r=S(e),i=r.length-1,o=0;o<=i;o++)t=o===i?this:this.clone(!0),S(r[o])[a](t),u.apply(n,t.get());return this.pushStack(n)}});var Me=new RegExp("^("+ee+")(?!px)[a-z%]+$","i"),Ie=function(e){var t=e.ownerDocument.defaultView;return t&&t.opener||(t=C),t.getComputedStyle(e)},We=function(e,t,n){var r,i,o={};for(i in t)o[i]=e.style[i],e.style[i]=t[i];for(i in r=n.call(e),t)e.style[i]=o[i];return r},Fe=new RegExp(ne.join("|"),"i");function Be(e,t,n){var r,i,o,a,s=e.style;return(n=n||Ie(e))&&(""!==(a=n.getPropertyValue(t)||n[t])||ie(e)||(a=S.style(e,t)),!y.pixelBoxStyles()&&Me.test(a)&&Fe.test(t)&&(r=s.width,i=s.minWidth,o=s.maxWidth,s.minWidth=s.maxWidth=s.width=a,a=n.width,s.width=r,s.minWidth=i,s.maxWidth=o)),void 0!==a?a+"":a}function $e(e,t){return{get:function(){if(!e())return(this.get=t).apply(this,arguments);delete this.get}}}!function(){function e(){if(l){u.style.cssText="position:absolute;left:-11111px;width:60px;margin-top:1px;padding:0;border:0",l.style.cssText="position:relative;display:block;box-sizing:border-box;overflow:scroll;margin:auto;border:1px;padding:1px;width:60%;top:1%",re.appendChild(u).appendChild(l);var e=C.getComputedStyle(l);n="1%"!==e.top,s=12===t(e.marginLeft),l.style.right="60%",o=36===t(e.right),r=36===t(e.width),l.style.position="absolute",i=12===t(l.offsetWidth/3),re.removeChild(u),l=null}}function t(e){return Math.round(parseFloat(e))}var n,r,i,o,a,s,u=E.createElement("div"),l=E.createElement("div");l.style&&(l.style.backgroundClip="content-box",l.cloneNode(!0).style.backgroundClip="",y.clearCloneStyle="content-box"===l.style.backgroundClip,S.extend(y,{boxSizingReliable:function(){return e(),r},pixelBoxStyles:function(){return e(),o},pixelPosition:function(){return e(),n},reliableMarginLeft:function(){return e(),s},scrollboxSize:function(){return e(),i},reliableTrDimensions:function(){var e,t,n,r;return null==a&&(e=E.createElement("table"),t=E.createElement("tr"),n=E.createElement("div"),e.style.cssText="position:absolute;left:-11111px",t.style.height="1px",n.style.height="9px",re.appendChild(e).appendChild(t).appendChild(n),r=C.getComputedStyle(t),a=3<parseInt(r.height),re.removeChild(e)),a}}))}();var _e=["Webkit","Moz","ms"],ze=E.createElement("div").style,Ue={};function Xe(e){var t=S.cssProps[e]||Ue[e];return t||(e in ze?e:Ue[e]=function(e){var t=e[0].toUpperCase()+e.slice(1),n=_e.length;while(n--)if((e=_e[n]+t)in ze)return e}(e)||e)}var Ve=/^(none|table(?!-c[ea]).+)/,Ge=/^--/,Ye={position:"absolute",visibility:"hidden",display:"block"},Qe={letterSpacing:"0",fontWeight:"400"};function Je(e,t,n){var r=te.exec(t);return r?Math.max(0,r[2]-(n||0))+(r[3]||"px"):t}function Ke(e,t,n,r,i,o){var a="width"===t?1:0,s=0,u=0;if(n===(r?"border":"content"))return 0;for(;a<4;a+=2)"margin"===n&&(u+=S.css(e,n+ne[a],!0,i)),r?("content"===n&&(u-=S.css(e,"padding"+ne[a],!0,i)),"margin"!==n&&(u-=S.css(e,"border"+ne[a]+"Width",!0,i))):(u+=S.css(e,"padding"+ne[a],!0,i),"padding"!==n?u+=S.css(e,"border"+ne[a]+"Width",!0,i):s+=S.css(e,"border"+ne[a]+"Width",!0,i));return!r&&0<=o&&(u+=Math.max(0,Math.ceil(e["offset"+t[0].toUpperCase()+t.slice(1)]-o-u-s-.5))||0),u}function Ze(e,t,n){var r=Ie(e),i=(!y.boxSizingReliable()||n)&&"border-box"===S.css(e,"boxSizing",!1,r),o=i,a=Be(e,t,r),s="offset"+t[0].toUpperCase()+t.slice(1);if(Me.test(a)){if(!n)return a;a="auto"}return(!y.boxSizingReliable()&&i||!y.reliableTrDimensions()&&A(e,"tr")||"auto"===a||!parseFloat(a)&&"inline"===S.css(e,"display",!1,r))&&e.getClientRects().length&&(i="border-box"===S.css(e,"boxSizing",!1,r),(o=s in e)&&(a=e[s])),(a=parseFloat(a)||0)+Ke(e,t,n||(i?"border":"content"),o,r,a)+"px"}function et(e,t,n,r,i){return new et.prototype.init(e,t,n,r,i)}S.extend({cssHooks:{opacity:{get:function(e,t){if(t){var n=Be(e,"opacity");return""===n?"1":n}}}},cssNumber:{animationIterationCount:!0,columnCount:!0,fillOpacity:!0,flexGrow:!0,flexShrink:!0,fontWeight:!0,gridArea:!0,gridColumn:!0,gridColumnEnd:!0,gridColumnStart:!0,gridRow:!0,gridRowEnd:!0,gridRowStart:!0,lineHeight:!0,opacity:!0,order:!0,orphans:!0,widows:!0,zIndex:!0,zoom:!0},cssProps:{},style:function(e,t,n,r){if(e&&3!==e.nodeType&&8!==e.nodeType&&e.style){var i,o,a,s=X(t),u=Ge.test(t),l=e.style;if(u||(t=Xe(s)),a=S.cssHooks[t]||S.cssHooks[s],void 0===n)return a&&"get"in a&&void 0!==(i=a.get(e,!1,r))?i:l[t];"string"===(o=typeof n)&&(i=te.exec(n))&&i[1]&&(n=se(e,t,i),o="number"),null!=n&&n==n&&("number"!==o||u||(n+=i&&i[3]||(S.cssNumber[s]?"":"px")),y.clearCloneStyle||""!==n||0!==t.indexOf("background")||(l[t]="inherit"),a&&"set"in a&&void 0===(n=a.set(e,n,r))||(u?l.setProperty(t,n):l[t]=n))}},css:function(e,t,n,r){var i,o,a,s=X(t);return Ge.test(t)||(t=Xe(s)),(a=S.cssHooks[t]||S.cssHooks[s])&&"get"in a&&(i=a.get(e,!0,n)),void 0===i&&(i=Be(e,t,r)),"normal"===i&&t in Qe&&(i=Qe[t]),""===n||n?(o=parseFloat(i),!0===n||isFinite(o)?o||0:i):i}}),S.each(["height","width"],function(e,u){S.cssHooks[u]={get:function(e,t,n){if(t)return!Ve.test(S.css(e,"display"))||e.getClientRects().length&&e.getBoundingClientRect().width?Ze(e,u,n):We(e,Ye,function(){return Ze(e,u,n)})},set:function(e,t,n){var r,i=Ie(e),o=!y.scrollboxSize()&&"absolute"===i.position,a=(o||n)&&"border-box"===S.css(e,"boxSizing",!1,i),s=n?Ke(e,u,n,a,i):0;return a&&o&&(s-=Math.ceil(e["offset"+u[0].toUpperCase()+u.slice(1)]-parseFloat(i[u])-Ke(e,u,"border",!1,i)-.5)),s&&(r=te.exec(t))&&"px"!==(r[3]||"px")&&(e.style[u]=t,t=S.css(e,u)),Je(0,t,s)}}}),S.cssHooks.marginLeft=$e(y.reliableMarginLeft,function(e,t){if(t)return(parseFloat(Be(e,"marginLeft"))||e.getBoundingClientRect().left-We(e,{marginLeft:0},function(){return e.getBoundingClientRect().left}))+"px"}),S.each({margin:"",padding:"",border:"Width"},function(i,o){S.cssHooks[i+o]={expand:function(e){for(var t=0,n={},r="string"==typeof e?e.split(" "):[e];t<4;t++)n[i+ne[t]+o]=r[t]||r[t-2]||r[0];return n}},"margin"!==i&&(S.cssHooks[i+o].set=Je)}),S.fn.extend({css:function(e,t){return $(this,function(e,t,n){var r,i,o={},a=0;if(Array.isArray(t)){for(r=Ie(e),i=t.length;a<i;a++)o[t[a]]=S.css(e,t[a],!1,r);return o}return void 0!==n?S.style(e,t,n):S.css(e,t)},e,t,1<arguments.length)}}),((S.Tween=et).prototype={constructor:et,init:function(e,t,n,r,i,o){this.elem=e,this.prop=n,this.easing=i||S.easing._default,this.options=t,this.start=this.now=this.cur(),this.end=r,this.unit=o||(S.cssNumber[n]?"":"px")},cur:function(){var e=et.propHooks[this.prop];return e&&e.get?e.get(this):et.propHooks._default.get(this)},run:function(e){var t,n=et.propHooks[this.prop];return this.options.duration?this.pos=t=S.easing[this.easing](e,this.options.duration*e,0,1,this.options.duration):this.pos=t=e,this.now=(this.end-this.start)*t+this.start,this.options.step&&this.options.step.call(this.elem,this.now,this),n&&n.set?n.set(this):et.propHooks._default.set(this),this}}).init.prototype=et.prototype,(et.propHooks={_default:{get:function(e){var t;return 1!==e.elem.nodeType||null!=e.elem[e.prop]&&null==e.elem.style[e.prop]?e.elem[e.prop]:(t=S.css(e.elem,e.prop,""))&&"auto"!==t?t:0},set:function(e){S.fx.step[e.prop]?S.fx.step[e.prop](e):1!==e.elem.nodeType||!S.cssHooks[e.prop]&&null==e.elem.style[Xe(e.prop)]?e.elem[e.prop]=e.now:S.style(e.elem,e.prop,e.now+e.unit)}}}).scrollTop=et.propHooks.scrollLeft={set:function(e){e.elem.nodeType&&e.elem.parentNode&&(e.elem[e.prop]=e.now)}},S.easing={linear:function(e){return e},swing:function(e){return.5-Math.cos(e*Math.PI)/2},_default:"swing"},S.fx=et.prototype.init,S.fx.step={};var tt,nt,rt,it,ot=/^(?:toggle|show|hide)$/,at=/queueHooks$/;function st(){nt&&(!1===E.hidden&&C.requestAnimationFrame?C.requestAnimationFrame(st):C.setTimeout(st,S.fx.interval),S.fx.tick())}function ut(){return C.setTimeout(function(){tt=void 0}),tt=Date.now()}function lt(e,t){var n,r=0,i={height:e};for(t=t?1:0;r<4;r+=2-t)i["margin"+(n=ne[r])]=i["padding"+n]=e;return t&&(i.opacity=i.width=e),i}function ct(e,t,n){for(var r,i=(ft.tweeners[t]||[]).concat(ft.tweeners["*"]),o=0,a=i.length;o<a;o++)if(r=i[o].call(n,t,e))return r}function ft(o,e,t){var n,a,r=0,i=ft.prefilters.length,s=S.Deferred().always(function(){delete u.elem}),u=function(){if(a)return!1;for(var e=tt||ut(),t=Math.max(0,l.startTime+l.duration-e),n=1-(t/l.duration||0),r=0,i=l.tweens.length;r<i;r++)l.tweens[r].run(n);return s.notifyWith(o,[l,n,t]),n<1&&i?t:(i||s.notifyWith(o,[l,1,0]),s.resolveWith(o,[l]),!1)},l=s.promise({elem:o,props:S.extend({},e),opts:S.extend(!0,{specialEasing:{},easing:S.easing._default},t),originalProperties:e,originalOptions:t,startTime:tt||ut(),duration:t.duration,tweens:[],createTween:function(e,t){var n=S.Tween(o,l.opts,e,t,l.opts.specialEasing[e]||l.opts.easing);return l.tweens.push(n),n},stop:function(e){var t=0,n=e?l.tweens.length:0;if(a)return this;for(a=!0;t<n;t++)l.tweens[t].run(1);return e?(s.notifyWith(o,[l,1,0]),s.resolveWith(o,[l,e])):s.rejectWith(o,[l,e]),this}}),c=l.props;for(!function(e,t){var n,r,i,o,a;for(n in e)if(i=t[r=X(n)],o=e[n],Array.isArray(o)&&(i=o[1],o=e[n]=o[0]),n!==r&&(e[r]=o,delete e[n]),(a=S.cssHooks[r])&&"expand"in a)for(n in o=a.expand(o),delete e[r],o)n in e||(e[n]=o[n],t[n]=i);else t[r]=i}(c,l.opts.specialEasing);r<i;r++)if(n=ft.prefilters[r].call(l,o,c,l.opts))return m(n.stop)&&(S._queueHooks(l.elem,l.opts.queue).stop=n.stop.bind(n)),n;return S.map(c,ct,l),m(l.opts.start)&&l.opts.start.call(o,l),l.progress(l.opts.progress).done(l.opts.done,l.opts.complete).fail(l.opts.fail).always(l.opts.always),S.fx.timer(S.extend(u,{elem:o,anim:l,queue:l.opts.queue})),l}S.Animation=S.extend(ft,{tweeners:{"*":[function(e,t){var n=this.createTween(e,t);return se(n.elem,e,te.exec(t),n),n}]},tweener:function(e,t){m(e)?(t=e,e=["*"]):e=e.match(P);for(var n,r=0,i=e.length;r<i;r++)n=e[r],ft.tweeners[n]=ft.tweeners[n]||[],ft.tweeners[n].unshift(t)},prefilters:[function(e,t,n){var r,i,o,a,s,u,l,c,f="width"in t||"height"in t,p=this,d={},h=e.style,g=e.nodeType&&ae(e),v=Y.get(e,"fxshow");for(r in n.queue||(null==(a=S._queueHooks(e,"fx")).unqueued&&(a.unqueued=0,s=a.empty.fire,a.empty.fire=function(){a.unqueued||s()}),a.unqueued++,p.always(function(){p.always(function(){a.unqueued--,S.queue(e,"fx").length||a.empty.fire()})})),t)if(i=t[r],ot.test(i)){if(delete t[r],o=o||"toggle"===i,i===(g?"hide":"show")){if("show"!==i||!v||void 0===v[r])continue;g=!0}d[r]=v&&v[r]||S.style(e,r)}if((u=!S.isEmptyObject(t))||!S.isEmptyObject(d))for(r in f&&1===e.nodeType&&(n.overflow=[h.overflow,h.overflowX,h.overflowY],null==(l=v&&v.display)&&(l=Y.get(e,"display")),"none"===(c=S.css(e,"display"))&&(l?c=l:(le([e],!0),l=e.style.display||l,c=S.css(e,"display"),le([e]))),("inline"===c||"inline-block"===c&&null!=l)&&"none"===S.css(e,"float")&&(u||(p.done(function(){h.display=l}),null==l&&(c=h.display,l="none"===c?"":c)),h.display="inline-block")),n.overflow&&(h.overflow="hidden",p.always(function(){h.overflow=n.overflow[0],h.overflowX=n.overflow[1],h.overflowY=n.overflow[2]})),u=!1,d)u||(v?"hidden"in v&&(g=v.hidden):v=Y.access(e,"fxshow",{display:l}),o&&(v.hidden=!g),g&&le([e],!0),p.done(function(){for(r in g||le([e]),Y.remove(e,"fxshow"),d)S.style(e,r,d[r])})),u=ct(g?v[r]:0,r,p),r in v||(v[r]=u.start,g&&(u.end=u.start,u.start=0))}],prefilter:function(e,t){t?ft.prefilters.unshift(e):ft.prefilters.push(e)}}),S.speed=function(e,t,n){var r=e&&"object"==typeof e?S.extend({},e):{complete:n||!n&&t||m(e)&&e,duration:e,easing:n&&t||t&&!m(t)&&t};return S.fx.off?r.duration=0:"number"!=typeof r.duration&&(r.duration in S.fx.speeds?r.duration=S.fx.speeds[r.duration]:r.duration=S.fx.speeds._default),null!=r.queue&&!0!==r.queue||(r.queue="fx"),r.old=r.complete,r.complete=function(){m(r.old)&&r.old.call(this),r.queue&&S.dequeue(this,r.queue)},r},S.fn.extend({fadeTo:function(e,t,n,r){return this.filter(ae).css("opacity",0).show().end().animate({opacity:t},e,n,r)},animate:function(t,e,n,r){var i=S.isEmptyObject(t),o=S.speed(e,n,r),a=function(){var e=ft(this,S.extend({},t),o);(i||Y.get(this,"finish"))&&e.stop(!0)};return a.finish=a,i||!1===o.queue?this.each(a):this.queue(o.queue,a)},stop:function(i,e,o){var a=function(e){var t=e.stop;delete e.stop,t(o)};return"string"!=typeof i&&(o=e,e=i,i=void 0),e&&this.queue(i||"fx",[]),this.each(function(){var e=!0,t=null!=i&&i+"queueHooks",n=S.timers,r=Y.get(this);if(t)r[t]&&r[t].stop&&a(r[t]);else for(t in r)r[t]&&r[t].stop&&at.test(t)&&a(r[t]);for(t=n.length;t--;)n[t].elem!==this||null!=i&&n[t].queue!==i||(n[t].anim.stop(o),e=!1,n.splice(t,1));!e&&o||S.dequeue(this,i)})},finish:function(a){return!1!==a&&(a=a||"fx"),this.each(function(){var e,t=Y.get(this),n=t[a+"queue"],r=t[a+"queueHooks"],i=S.timers,o=n?n.length:0;for(t.finish=!0,S.queue(this,a,[]),r&&r.stop&&r.stop.call(this,!0),e=i.length;e--;)i[e].elem===this&&i[e].queue===a&&(i[e].anim.stop(!0),i.splice(e,1));for(e=0;e<o;e++)n[e]&&n[e].finish&&n[e].finish.call(this);delete t.finish})}}),S.each(["toggle","show","hide"],function(e,r){var i=S.fn[r];S.fn[r]=function(e,t,n){return null==e||"boolean"==typeof e?i.apply(this,arguments):this.animate(lt(r,!0),e,t,n)}}),S.each({slideDown:lt("show"),slideUp:lt("hide"),slideToggle:lt("toggle"),fadeIn:{opacity:"show"},fadeOut:{opacity:"hide"},fadeToggle:{opacity:"toggle"}},function(e,r){S.fn[e]=function(e,t,n){return this.animate(r,e,t,n)}}),S.timers=[],S.fx.tick=function(){var e,t=0,n=S.timers;for(tt=Date.now();t<n.length;t++)(e=n[t])()||n[t]!==e||n.splice(t--,1);n.length||S.fx.stop(),tt=void 0},S.fx.timer=function(e){S.timers.push(e),S.fx.start()},S.fx.interval=13,S.fx.start=function(){nt||(nt=!0,st())},S.fx.stop=function(){nt=null},S.fx.speeds={slow:600,fast:200,_default:400},S.fn.delay=function(r,e){return r=S.fx&&S.fx.speeds[r]||r,e=e||"fx",this.queue(e,function(e,t){var n=C.setTimeout(e,r);t.stop=function(){C.clearTimeout(n)}})},rt=E.createElement("input"),it=E.createElement("select").appendChild(E.createElement("option")),rt.type="checkbox",y.checkOn=""!==rt.value,y.optSelected=it.selected,(rt=E.createElement("input")).value="t",rt.type="radio",y.radioValue="t"===rt.value;var pt,dt=S.expr.attrHandle;S.fn.extend({attr:function(e,t){return $(this,S.attr,e,t,1<arguments.length)},removeAttr:function(e){return this.each(function(){S.removeAttr(this,e)})}}),S.extend({attr:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return"undefined"==typeof e.getAttribute?S.prop(e,t,n):(1===o&&S.isXMLDoc(e)||(i=S.attrHooks[t.toLowerCase()]||(S.expr.match.bool.test(t)?pt:void 0)),void 0!==n?null===n?void S.removeAttr(e,t):i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:(e.setAttribute(t,n+""),n):i&&"get"in i&&null!==(r=i.get(e,t))?r:null==(r=S.find.attr(e,t))?void 0:r)},attrHooks:{type:{set:function(e,t){if(!y.radioValue&&"radio"===t&&A(e,"input")){var n=e.value;return e.setAttribute("type",t),n&&(e.value=n),t}}}},removeAttr:function(e,t){var n,r=0,i=t&&t.match(P);if(i&&1===e.nodeType)while(n=i[r++])e.removeAttribute(n)}}),pt={set:function(e,t,n){return!1===t?S.removeAttr(e,n):e.setAttribute(n,n),n}},S.each(S.expr.match.bool.source.match(/\w+/g),function(e,t){var a=dt[t]||S.find.attr;dt[t]=function(e,t,n){var r,i,o=t.toLowerCase();return n||(i=dt[o],dt[o]=r,r=null!=a(e,t,n)?o:null,dt[o]=i),r}});var ht=/^(?:input|select|textarea|button)$/i,gt=/^(?:a|area)$/i;function vt(e){return(e.match(P)||[]).join(" ")}function yt(e){return e.getAttribute&&e.getAttribute("class")||""}function mt(e){return Array.isArray(e)?e:"string"==typeof e&&e.match(P)||[]}S.fn.extend({prop:function(e,t){return $(this,S.prop,e,t,1<arguments.length)},removeProp:function(e){return this.each(function(){delete this[S.propFix[e]||e]})}}),S.extend({prop:function(e,t,n){var r,i,o=e.nodeType;if(3!==o&&8!==o&&2!==o)return 1===o&&S.isXMLDoc(e)||(t=S.propFix[t]||t,i=S.propHooks[t]),void 0!==n?i&&"set"in i&&void 0!==(r=i.set(e,n,t))?r:e[t]=n:i&&"get"in i&&null!==(r=i.get(e,t))?r:e[t]},propHooks:{tabIndex:{get:function(e){var t=S.find.attr(e,"tabindex");return t?parseInt(t,10):ht.test(e.nodeName)||gt.test(e.nodeName)&&e.href?0:-1}}},propFix:{"for":"htmlFor","class":"className"}}),y.optSelected||(S.propHooks.selected={get:function(e){var t=e.parentNode;return t&&t.parentNode&&t.parentNode.selectedIndex,null},set:function(e){var t=e.parentNode;t&&(t.selectedIndex,t.parentNode&&t.parentNode.selectedIndex)}}),S.each(["tabIndex","readOnly","maxLength","cellSpacing","cellPadding","rowSpan","colSpan","useMap","frameBorder","contentEditable"],function(){S.propFix[this.toLowerCase()]=this}),S.fn.extend({addClass:function(t){var e,n,r,i,o,a,s,u=0;if(m(t))return this.each(function(e){S(this).addClass(t.call(this,e,yt(this)))});if((e=mt(t)).length)while(n=this[u++])if(i=yt(n),r=1===n.nodeType&&" "+vt(i)+" "){a=0;while(o=e[a++])r.indexOf(" "+o+" ")<0&&(r+=o+" ");i!==(s=vt(r))&&n.setAttribute("class",s)}return this},removeClass:function(t){var e,n,r,i,o,a,s,u=0;if(m(t))return this.each(function(e){S(this).removeClass(t.call(this,e,yt(this)))});if(!arguments.length)return this.attr("class","");if((e=mt(t)).length)while(n=this[u++])if(i=yt(n),r=1===n.nodeType&&" "+vt(i)+" "){a=0;while(o=e[a++])while(-1<r.indexOf(" "+o+" "))r=r.replace(" "+o+" "," ");i!==(s=vt(r))&&n.setAttribute("class",s)}return this},toggleClass:function(i,t){var o=typeof i,a="string"===o||Array.isArray(i);return"boolean"==typeof t&&a?t?this.addClass(i):this.removeClass(i):m(i)?this.each(function(e){S(this).toggleClass(i.call(this,e,yt(this),t),t)}):this.each(function(){var e,t,n,r;if(a){t=0,n=S(this),r=mt(i);while(e=r[t++])n.hasClass(e)?n.removeClass(e):n.addClass(e)}else void 0!==i&&"boolean"!==o||((e=yt(this))&&Y.set(this,"__className__",e),this.setAttribute&&this.setAttribute("class",e||!1===i?"":Y.get(this,"__className__")||""))})},hasClass:function(e){var t,n,r=0;t=" "+e+" ";while(n=this[r++])if(1===n.nodeType&&-1<(" "+vt(yt(n))+" ").indexOf(t))return!0;return!1}});var xt=/\r/g;S.fn.extend({val:function(n){var r,e,i,t=this[0];return arguments.length?(i=m(n),this.each(function(e){var t;1===this.nodeType&&(null==(t=i?n.call(this,e,S(this).val()):n)?t="":"number"==typeof t?t+="":Array.isArray(t)&&(t=S.map(t,function(e){return null==e?"":e+""})),(r=S.valHooks[this.type]||S.valHooks[this.nodeName.toLowerCase()])&&"set"in r&&void 0!==r.set(this,t,"value")||(this.value=t))})):t?(r=S.valHooks[t.type]||S.valHooks[t.nodeName.toLowerCase()])&&"get"in r&&void 0!==(e=r.get(t,"value"))?e:"string"==typeof(e=t.value)?e.replace(xt,""):null==e?"":e:void 0}}),S.extend({valHooks:{option:{get:function(e){var t=S.find.attr(e,"value");return null!=t?t:vt(S.text(e))}},select:{get:function(e){var t,n,r,i=e.options,o=e.selectedIndex,a="select-one"===e.type,s=a?null:[],u=a?o+1:i.length;for(r=o<0?u:a?o:0;r<u;r++)if(((n=i[r]).selected||r===o)&&!n.disabled&&(!n.parentNode.disabled||!A(n.parentNode,"optgroup"))){if(t=S(n).val(),a)return t;s.push(t)}return s},set:function(e,t){var n,r,i=e.options,o=S.makeArray(t),a=i.length;while(a--)((r=i[a]).selected=-1<S.inArray(S.valHooks.option.get(r),o))&&(n=!0);return n||(e.selectedIndex=-1),o}}}}),S.each(["radio","checkbox"],function(){S.valHooks[this]={set:function(e,t){if(Array.isArray(t))return e.checked=-1<S.inArray(S(e).val(),t)}},y.checkOn||(S.valHooks[this].get=function(e){return null===e.getAttribute("value")?"on":e.value})}),y.focusin="onfocusin"in C;var bt=/^(?:focusinfocus|focusoutblur)$/,wt=function(e){e.stopPropagation()};S.extend(S.event,{trigger:function(e,t,n,r){var i,o,a,s,u,l,c,f,p=[n||E],d=v.call(e,"type")?e.type:e,h=v.call(e,"namespace")?e.namespace.split("."):[];if(o=f=a=n=n||E,3!==n.nodeType&&8!==n.nodeType&&!bt.test(d+S.event.triggered)&&(-1<d.indexOf(".")&&(d=(h=d.split(".")).shift(),h.sort()),u=d.indexOf(":")<0&&"on"+d,(e=e[S.expando]?e:new S.Event(d,"object"==typeof e&&e)).isTrigger=r?2:3,e.namespace=h.join("."),e.rnamespace=e.namespace?new RegExp("(^|\\.)"+h.join("\\.(?:.*\\.|)")+"(\\.|$)"):null,e.result=void 0,e.target||(e.target=n),t=null==t?[e]:S.makeArray(t,[e]),c=S.event.special[d]||{},r||!c.trigger||!1!==c.trigger.apply(n,t))){if(!r&&!c.noBubble&&!x(n)){for(s=c.delegateType||d,bt.test(s+d)||(o=o.parentNode);o;o=o.parentNode)p.push(o),a=o;a===(n.ownerDocument||E)&&p.push(a.defaultView||a.parentWindow||C)}i=0;while((o=p[i++])&&!e.isPropagationStopped())f=o,e.type=1<i?s:c.bindType||d,(l=(Y.get(o,"events")||Object.create(null))[e.type]&&Y.get(o,"handle"))&&l.apply(o,t),(l=u&&o[u])&&l.apply&&V(o)&&(e.result=l.apply(o,t),!1===e.result&&e.preventDefault());return e.type=d,r||e.isDefaultPrevented()||c._default&&!1!==c._default.apply(p.pop(),t)||!V(n)||u&&m(n[d])&&!x(n)&&((a=n[u])&&(n[u]=null),S.event.triggered=d,e.isPropagationStopped()&&f.addEventListener(d,wt),n[d](),e.isPropagationStopped()&&f.removeEventListener(d,wt),S.event.triggered=void 0,a&&(n[u]=a)),e.result}},simulate:function(e,t,n){var r=S.extend(new S.Event,n,{type:e,isSimulated:!0});S.event.trigger(r,null,t)}}),S.fn.extend({trigger:function(e,t){return this.each(function(){S.event.trigger(e,t,this)})},triggerHandler:function(e,t){var n=this[0];if(n)return S.event.trigger(e,t,n,!0)}}),y.focusin||S.each({focus:"focusin",blur:"focusout"},function(n,r){var i=function(e){S.event.simulate(r,e.target,S.event.fix(e))};S.event.special[r]={setup:function(){var e=this.ownerDocument||this.document||this,t=Y.access(e,r);t||e.addEventListener(n,i,!0),Y.access(e,r,(t||0)+1)},teardown:function(){var e=this.ownerDocument||this.document||this,t=Y.access(e,r)-1;t?Y.access(e,r,t):(e.removeEventListener(n,i,!0),Y.remove(e,r))}}});var Tt=C.location,Ct={guid:Date.now()},Et=/\?/;S.parseXML=function(e){var t;if(!e||"string"!=typeof e)return null;try{t=(new C.DOMParser).parseFromString(e,"text/xml")}catch(e){t=void 0}return t&&!t.getElementsByTagName("parsererror").length||S.error("Invalid XML: "+e),t};var St=/\[\]$/,kt=/\r?\n/g,At=/^(?:submit|button|image|reset|file)$/i,Nt=/^(?:input|select|textarea|keygen)/i;function Dt(n,e,r,i){var t;if(Array.isArray(e))S.each(e,function(e,t){r||St.test(n)?i(n,t):Dt(n+"["+("object"==typeof t&&null!=t?e:"")+"]",t,r,i)});else if(r||"object"!==w(e))i(n,e);else for(t in e)Dt(n+"["+t+"]",e[t],r,i)}S.param=function(e,t){var n,r=[],i=function(e,t){var n=m(t)?t():t;r[r.length]=encodeURIComponent(e)+"="+encodeURIComponent(null==n?"":n)};if(null==e)return"";if(Array.isArray(e)||e.jquery&&!S.isPlainObject(e))S.each(e,function(){i(this.name,this.value)});else for(n in e)Dt(n,e[n],t,i);return r.join("&")},S.fn.extend({serialize:function(){return S.param(this.serializeArray())},serializeArray:function(){return this.map(function(){var e=S.prop(this,"elements");return e?S.makeArray(e):this}).filter(function(){var e=this.type;return this.name&&!S(this).is(":disabled")&&Nt.test(this.nodeName)&&!At.test(e)&&(this.checked||!pe.test(e))}).map(function(e,t){var n=S(this).val();return null==n?null:Array.isArray(n)?S.map(n,function(e){return{name:t.name,value:e.replace(kt,"\r\n")}}):{name:t.name,value:n.replace(kt,"\r\n")}}).get()}});var jt=/%20/g,qt=/#.*$/,Lt=/([?&])_=[^&]*/,Ht=/^(.*?):[ \t]*([^\r\n]*)$/gm,Ot=/^(?:GET|HEAD)$/,Pt=/^\/\//,Rt={},Mt={},It="*/".concat("*"),Wt=E.createElement("a");function Ft(o){return function(e,t){"string"!=typeof e&&(t=e,e="*");var n,r=0,i=e.toLowerCase().match(P)||[];if(m(t))while(n=i[r++])"+"===n[0]?(n=n.slice(1)||"*",(o[n]=o[n]||[]).unshift(t)):(o[n]=o[n]||[]).push(t)}}function Bt(t,i,o,a){var s={},u=t===Mt;function l(e){var r;return s[e]=!0,S.each(t[e]||[],function(e,t){var n=t(i,o,a);return"string"!=typeof n||u||s[n]?u?!(r=n):void 0:(i.dataTypes.unshift(n),l(n),!1)}),r}return l(i.dataTypes[0])||!s["*"]&&l("*")}function $t(e,t){var n,r,i=S.ajaxSettings.flatOptions||{};for(n in t)void 0!==t[n]&&((i[n]?e:r||(r={}))[n]=t[n]);return r&&S.extend(!0,e,r),e}Wt.href=Tt.href,S.extend({active:0,lastModified:{},etag:{},ajaxSettings:{url:Tt.href,type:"GET",isLocal:/^(?:about|app|app-storage|.+-extension|file|res|widget):$/.test(Tt.protocol),global:!0,processData:!0,async:!0,contentType:"application/x-www-form-urlencoded; charset=UTF-8",accepts:{"*":It,text:"text/plain",html:"text/html",xml:"application/xml, text/xml",json:"application/json, text/javascript"},contents:{xml:/\bxml\b/,html:/\bhtml/,json:/\bjson\b/},responseFields:{xml:"responseXML",text:"responseText",json:"responseJSON"},converters:{"* text":String,"text html":!0,"text json":JSON.parse,"text xml":S.parseXML},flatOptions:{url:!0,context:!0}},ajaxSetup:function(e,t){return t?$t($t(e,S.ajaxSettings),t):$t(S.ajaxSettings,e)},ajaxPrefilter:Ft(Rt),ajaxTransport:Ft(Mt),ajax:function(e,t){"object"==typeof e&&(t=e,e=void 0),t=t||{};var c,f,p,n,d,r,h,g,i,o,v=S.ajaxSetup({},t),y=v.context||v,m=v.context&&(y.nodeType||y.jquery)?S(y):S.event,x=S.Deferred(),b=S.Callbacks("once memory"),w=v.statusCode||{},a={},s={},u="canceled",T={readyState:0,getResponseHeader:function(e){var t;if(h){if(!n){n={};while(t=Ht.exec(p))n[t[1].toLowerCase()+" "]=(n[t[1].toLowerCase()+" "]||[]).concat(t[2])}t=n[e.toLowerCase()+" "]}return null==t?null:t.join(", ")},getAllResponseHeaders:function(){return h?p:null},setRequestHeader:function(e,t){return null==h&&(e=s[e.toLowerCase()]=s[e.toLowerCase()]||e,a[e]=t),this},overrideMimeType:function(e){return null==h&&(v.mimeType=e),this},statusCode:function(e){var t;if(e)if(h)T.always(e[T.status]);else for(t in e)w[t]=[w[t],e[t]];return this},abort:function(e){var t=e||u;return c&&c.abort(t),l(0,t),this}};if(x.promise(T),v.url=((e||v.url||Tt.href)+"").replace(Pt,Tt.protocol+"//"),v.type=t.method||t.type||v.method||v.type,v.dataTypes=(v.dataType||"*").toLowerCase().match(P)||[""],null==v.crossDomain){r=E.createElement("a");try{r.href=v.url,r.href=r.href,v.crossDomain=Wt.protocol+"//"+Wt.host!=r.protocol+"//"+r.host}catch(e){v.crossDomain=!0}}if(v.data&&v.processData&&"string"!=typeof v.data&&(v.data=S.param(v.data,v.traditional)),Bt(Rt,v,t,T),h)return T;for(i in(g=S.event&&v.global)&&0==S.active++&&S.event.trigger("ajaxStart"),v.type=v.type.toUpperCase(),v.hasContent=!Ot.test(v.type),f=v.url.replace(qt,""),v.hasContent?v.data&&v.processData&&0===(v.contentType||"").indexOf("application/x-www-form-urlencoded")&&(v.data=v.data.replace(jt,"+")):(o=v.url.slice(f.length),v.data&&(v.processData||"string"==typeof v.data)&&(f+=(Et.test(f)?"&":"?")+v.data,delete v.data),!1===v.cache&&(f=f.replace(Lt,"$1"),o=(Et.test(f)?"&":"?")+"_="+Ct.guid+++o),v.url=f+o),v.ifModified&&(S.lastModified[f]&&T.setRequestHeader("If-Modified-Since",S.lastModified[f]),S.etag[f]&&T.setRequestHeader("If-None-Match",S.etag[f])),(v.data&&v.hasContent&&!1!==v.contentType||t.contentType)&&T.setRequestHeader("Content-Type",v.contentType),T.setRequestHeader("Accept",v.dataTypes[0]&&v.accepts[v.dataTypes[0]]?v.accepts[v.dataTypes[0]]+("*"!==v.dataTypes[0]?", "+It+"; q=0.01":""):v.accepts["*"]),v.headers)T.setRequestHeader(i,v.headers[i]);if(v.beforeSend&&(!1===v.beforeSend.call(y,T,v)||h))return T.abort();if(u="abort",b.add(v.complete),T.done(v.success),T.fail(v.error),c=Bt(Mt,v,t,T)){if(T.readyState=1,g&&m.trigger("ajaxSend",[T,v]),h)return T;v.async&&0<v.timeout&&(d=C.setTimeout(function(){T.abort("timeout")},v.timeout));try{h=!1,c.send(a,l)}catch(e){if(h)throw e;l(-1,e)}}else l(-1,"No Transport");function l(e,t,n,r){var i,o,a,s,u,l=t;h||(h=!0,d&&C.clearTimeout(d),c=void 0,p=r||"",T.readyState=0<e?4:0,i=200<=e&&e<300||304===e,n&&(s=function(e,t,n){var r,i,o,a,s=e.contents,u=e.dataTypes;while("*"===u[0])u.shift(),void 0===r&&(r=e.mimeType||t.getResponseHeader("Content-Type"));if(r)for(i in s)if(s[i]&&s[i].test(r)){u.unshift(i);break}if(u[0]in n)o=u[0];else{for(i in n){if(!u[0]||e.converters[i+" "+u[0]]){o=i;break}a||(a=i)}o=o||a}if(o)return o!==u[0]&&u.unshift(o),n[o]}(v,T,n)),!i&&-1<S.inArray("script",v.dataTypes)&&(v.converters["text script"]=function(){}),s=function(e,t,n,r){var i,o,a,s,u,l={},c=e.dataTypes.slice();if(c[1])for(a in e.converters)l[a.toLowerCase()]=e.converters[a];o=c.shift();while(o)if(e.responseFields[o]&&(n[e.responseFields[o]]=t),!u&&r&&e.dataFilter&&(t=e.dataFilter(t,e.dataType)),u=o,o=c.shift())if("*"===o)o=u;else if("*"!==u&&u!==o){if(!(a=l[u+" "+o]||l["* "+o]))for(i in l)if((s=i.split(" "))[1]===o&&(a=l[u+" "+s[0]]||l["* "+s[0]])){!0===a?a=l[i]:!0!==l[i]&&(o=s[0],c.unshift(s[1]));break}if(!0!==a)if(a&&e["throws"])t=a(t);else try{t=a(t)}catch(e){return{state:"parsererror",error:a?e:"No conversion from "+u+" to "+o}}}return{state:"success",data:t}}(v,s,T,i),i?(v.ifModified&&((u=T.getResponseHeader("Last-Modified"))&&(S.lastModified[f]=u),(u=T.getResponseHeader("etag"))&&(S.etag[f]=u)),204===e||"HEAD"===v.type?l="nocontent":304===e?l="notmodified":(l=s.state,o=s.data,i=!(a=s.error))):(a=l,!e&&l||(l="error",e<0&&(e=0))),T.status=e,T.statusText=(t||l)+"",i?x.resolveWith(y,[o,l,T]):x.rejectWith(y,[T,l,a]),T.statusCode(w),w=void 0,g&&m.trigger(i?"ajaxSuccess":"ajaxError",[T,v,i?o:a]),b.fireWith(y,[T,l]),g&&(m.trigger("ajaxComplete",[T,v]),--S.active||S.event.trigger("ajaxStop")))}return T},getJSON:function(e,t,n){return S.get(e,t,n,"json")},getScript:function(e,t){return S.get(e,void 0,t,"script")}}),S.each(["get","post"],function(e,i){S[i]=function(e,t,n,r){return m(t)&&(r=r||n,n=t,t=void 0),S.ajax(S.extend({url:e,type:i,dataType:r,data:t,success:n},S.isPlainObject(e)&&e))}}),S.ajaxPrefilter(function(e){var t;for(t in e.headers)"content-type"===t.toLowerCase()&&(e.contentType=e.headers[t]||"")}),S._evalUrl=function(e,t,n){return S.ajax({url:e,type:"GET",dataType:"script",cache:!0,async:!1,global:!1,converters:{"text script":function(){}},dataFilter:function(e){S.globalEval(e,t,n)}})},S.fn.extend({wrapAll:function(e){var t;return this[0]&&(m(e)&&(e=e.call(this[0])),t=S(e,this[0].ownerDocument).eq(0).clone(!0),this[0].parentNode&&t.insertBefore(this[0]),t.map(function(){var e=this;while(e.firstElementChild)e=e.firstElementChild;return e}).append(this)),this},wrapInner:function(n){return m(n)?this.each(function(e){S(this).wrapInner(n.call(this,e))}):this.each(function(){var e=S(this),t=e.contents();t.length?t.wrapAll(n):e.append(n)})},wrap:function(t){var n=m(t);return this.each(function(e){S(this).wrapAll(n?t.call(this,e):t)})},unwrap:function(e){return this.parent(e).not("body").each(function(){S(this).replaceWith(this.childNodes)}),this}}),S.expr.pseudos.hidden=function(e){return!S.expr.pseudos.visible(e)},S.expr.pseudos.visible=function(e){return!!(e.offsetWidth||e.offsetHeight||e.getClientRects().length)},S.ajaxSettings.xhr=function(){try{return new C.XMLHttpRequest}catch(e){}};var _t={0:200,1223:204},zt=S.ajaxSettings.xhr();y.cors=!!zt&&"withCredentials"in zt,y.ajax=zt=!!zt,S.ajaxTransport(function(i){var o,a;if(y.cors||zt&&!i.crossDomain)return{send:function(e,t){var n,r=i.xhr();if(r.open(i.type,i.url,i.async,i.username,i.password),i.xhrFields)for(n in i.xhrFields)r[n]=i.xhrFields[n];for(n in i.mimeType&&r.overrideMimeType&&r.overrideMimeType(i.mimeType),i.crossDomain||e["X-Requested-With"]||(e["X-Requested-With"]="XMLHttpRequest"),e)r.setRequestHeader(n,e[n]);o=function(e){return function(){o&&(o=a=r.onload=r.onerror=r.onabort=r.ontimeout=r.onreadystatechange=null,"abort"===e?r.abort():"error"===e?"number"!=typeof r.status?t(0,"error"):t(r.status,r.statusText):t(_t[r.status]||r.status,r.statusText,"text"!==(r.responseType||"text")||"string"!=typeof r.responseText?{binary:r.response}:{text:r.responseText},r.getAllResponseHeaders()))}},r.onload=o(),a=r.onerror=r.ontimeout=o("error"),void 0!==r.onabort?r.onabort=a:r.onreadystatechange=function(){4===r.readyState&&C.setTimeout(function(){o&&a()})},o=o("abort");try{r.send(i.hasContent&&i.data||null)}catch(e){if(o)throw e}},abort:function(){o&&o()}}}),S.ajaxPrefilter(function(e){e.crossDomain&&(e.contents.script=!1)}),S.ajaxSetup({accepts:{script:"text/javascript, application/javascript, application/ecmascript, application/x-ecmascript"},contents:{script:/\b(?:java|ecma)script\b/},converters:{"text script":function(e){return S.globalEval(e),e}}}),S.ajaxPrefilter("script",function(e){void 0===e.cache&&(e.cache=!1),e.crossDomain&&(e.type="GET")}),S.ajaxTransport("script",function(n){var r,i;if(n.crossDomain||n.scriptAttrs)return{send:function(e,t){r=S("<script>").attr(n.scriptAttrs||{}).prop({charset:n.scriptCharset,src:n.url}).on("load error",i=function(e){r.remove(),i=null,e&&t("error"===e.type?404:200,e.type)}),E.head.appendChild(r[0])},abort:function(){i&&i()}}});var Ut,Xt=[],Vt=/(=)\?(?=&|$)|\?\?/;S.ajaxSetup({jsonp:"callback",jsonpCallback:function(){var e=Xt.pop()||S.expando+"_"+Ct.guid++;return this[e]=!0,e}}),S.ajaxPrefilter("json jsonp",function(e,t,n){var r,i,o,a=!1!==e.jsonp&&(Vt.test(e.url)?"url":"string"==typeof e.data&&0===(e.contentType||"").indexOf("application/x-www-form-urlencoded")&&Vt.test(e.data)&&"data");if(a||"jsonp"===e.dataTypes[0])return r=e.jsonpCallback=m(e.jsonpCallback)?e.jsonpCallback():e.jsonpCallback,a?e[a]=e[a].replace(Vt,"$1"+r):!1!==e.jsonp&&(e.url+=(Et.test(e.url)?"&":"?")+e.jsonp+"="+r),e.converters["script json"]=function(){return o||S.error(r+" was not called"),o[0]},e.dataTypes[0]="json",i=C[r],C[r]=function(){o=arguments},n.always(function(){void 0===i?S(C).removeProp(r):C[r]=i,e[r]&&(e.jsonpCallback=t.jsonpCallback,Xt.push(r)),o&&m(i)&&i(o[0]),o=i=void 0}),"script"}),y.createHTMLDocument=((Ut=E.implementation.createHTMLDocument("").body).innerHTML="<form></form><form></form>",2===Ut.childNodes.length),S.parseHTML=function(e,t,n){return"string"!=typeof e?[]:("boolean"==typeof t&&(n=t,t=!1),t||(y.createHTMLDocument?((r=(t=E.implementation.createHTMLDocument("")).createElement("base")).href=E.location.href,t.head.appendChild(r)):t=E),o=!n&&[],(i=N.exec(e))?[t.createElement(i[1])]:(i=xe([e],t,o),o&&o.length&&S(o).remove(),S.merge([],i.childNodes)));var r,i,o},S.fn.load=function(e,t,n){var r,i,o,a=this,s=e.indexOf(" ");return-1<s&&(r=vt(e.slice(s)),e=e.slice(0,s)),m(t)?(n=t,t=void 0):t&&"object"==typeof t&&(i="POST"),0<a.length&&S.ajax({url:e,type:i||"GET",dataType:"html",data:t}).done(function(e){o=arguments,a.html(r?S("<div>").append(S.parseHTML(e)).find(r):e)}).always(n&&function(e,t){a.each(function(){n.apply(this,o||[e.responseText,t,e])})}),this},S.expr.pseudos.animated=function(t){return S.grep(S.timers,function(e){return t===e.elem}).length},S.offset={setOffset:function(e,t,n){var r,i,o,a,s,u,l=S.css(e,"position"),c=S(e),f={};"static"===l&&(e.style.position="relative"),s=c.offset(),o=S.css(e,"top"),u=S.css(e,"left"),("absolute"===l||"fixed"===l)&&-1<(o+u).indexOf("auto")?(a=(r=c.position()).top,i=r.left):(a=parseFloat(o)||0,i=parseFloat(u)||0),m(t)&&(t=t.call(e,n,S.extend({},s))),null!=t.top&&(f.top=t.top-s.top+a),null!=t.left&&(f.left=t.left-s.left+i),"using"in t?t.using.call(e,f):("number"==typeof f.top&&(f.top+="px"),"number"==typeof f.left&&(f.left+="px"),c.css(f))}},S.fn.extend({offset:function(t){if(arguments.length)return void 0===t?this:this.each(function(e){S.offset.setOffset(this,t,e)});var e,n,r=this[0];return r?r.getClientRects().length?(e=r.getBoundingClientRect(),n=r.ownerDocument.defaultView,{top:e.top+n.pageYOffset,left:e.left+n.pageXOffset}):{top:0,left:0}:void 0},position:function(){if(this[0]){var e,t,n,r=this[0],i={top:0,left:0};if("fixed"===S.css(r,"position"))t=r.getBoundingClientRect();else{t=this.offset(),n=r.ownerDocument,e=r.offsetParent||n.documentElement;while(e&&(e===n.body||e===n.documentElement)&&"static"===S.css(e,"position"))e=e.parentNode;e&&e!==r&&1===e.nodeType&&((i=S(e).offset()).top+=S.css(e,"borderTopWidth",!0),i.left+=S.css(e,"borderLeftWidth",!0))}return{top:t.top-i.top-S.css(r,"marginTop",!0),left:t.left-i.left-S.css(r,"marginLeft",!0)}}},offsetParent:function(){return this.map(function(){var e=this.offsetParent;while(e&&"static"===S.css(e,"position"))e=e.offsetParent;return e||re})}}),S.each({scrollLeft:"pageXOffset",scrollTop:"pageYOffset"},function(t,i){var o="pageYOffset"===i;S.fn[t]=function(e){return $(this,function(e,t,n){var r;if(x(e)?r=e:9===e.nodeType&&(r=e.defaultView),void 0===n)return r?r[i]:e[t];r?r.scrollTo(o?r.pageXOffset:n,o?n:r.pageYOffset):e[t]=n},t,e,arguments.length)}}),S.each(["top","left"],function(e,n){S.cssHooks[n]=$e(y.pixelPosition,function(e,t){if(t)return t=Be(e,n),Me.test(t)?S(e).position()[n]+"px":t})}),S.each({Height:"height",Width:"width"},function(a,s){S.each({padding:"inner"+a,content:s,"":"outer"+a},function(r,o){S.fn[o]=function(e,t){var n=arguments.length&&(r||"boolean"!=typeof e),i=r||(!0===e||!0===t?"margin":"border");return $(this,function(e,t,n){var r;return x(e)?0===o.indexOf("outer")?e["inner"+a]:e.document.documentElement["client"+a]:9===e.nodeType?(r=e.documentElement,Math.max(e.body["scroll"+a],r["scroll"+a],e.body["offset"+a],r["offset"+a],r["client"+a])):void 0===n?S.css(e,t,i):S.style(e,t,n,i)},s,n?e:void 0,n)}})}),S.each(["ajaxStart","ajaxStop","ajaxComplete","ajaxError","ajaxSuccess","ajaxSend"],function(e,t){S.fn[t]=function(e){return this.on(t,e)}}),S.fn.extend({bind:function(e,t,n){return this.on(e,null,t,n)},unbind:function(e,t){return this.off(e,null,t)},delegate:function(e,t,n,r){return this.on(t,e,n,r)},undelegate:function(e,t,n){return 1===arguments.length?this.off(e,"**"):this.off(t,e||"**",n)},hover:function(e,t){return this.mouseenter(e).mouseleave(t||e)}}),S.each("blur focus focusin focusout resize scroll click dblclick mousedown mouseup mousemove mouseover mouseout mouseenter mouseleave change select submit keydown keypress keyup contextmenu".split(" "),function(e,n){S.fn[n]=function(e,t){return 0<arguments.length?this.on(n,null,e,t):this.trigger(n)}});var Gt=/^[\s\uFEFF\xA0]+|[\s\uFEFF\xA0]+$/g;S.proxy=function(e,t){var n,r,i;if("string"==typeof t&&(n=e[t],t=e,e=n),m(e))return r=s.call(arguments,2),(i=function(){return e.apply(t||this,r.concat(s.call(arguments)))}).guid=e.guid=e.guid||S.guid++,i},S.holdReady=function(e){e?S.readyWait++:S.ready(!0)},S.isArray=Array.isArray,S.parseJSON=JSON.parse,S.nodeName=A,S.isFunction=m,S.isWindow=x,S.camelCase=X,S.type=w,S.now=Date.now,S.isNumeric=function(e){var t=S.type(e);return("number"===t||"string"===t)&&!isNaN(e-parseFloat(e))},S.trim=function(e){return null==e?"":(e+"").replace(Gt,"")},"function"==typeof define&&define.amd&&define("jquery",[],function(){return S});var Yt=C.jQuery,Qt=C.$;return S.noConflict=function(e){return C.$===S&&(C.$=Qt),e&&C.jQuery===S&&(C.jQuery=Yt),S},"undefined"==typeof e&&(C.jQuery=C.$=S),S});
+</script><script>const headroomChanged = new CustomEvent("quarto-hrChanged", {
   detail: {},
   bubbles: true,
   cancelable: false,
@@ -4659,6 +4695,25 @@
     "search-label": "Search"
   }
 }</script>
+<script>var requirejs,require,define;!function(global,setTimeout){var req,s,head,baseElement,dataMain,src,interactiveScript,currentlyAddingScript,mainScript,subPath,version="2.3.6",commentRegExp=/\/\*[\s\S]*?\*\/|([^:"'=]|^)\/\/.*$/gm,cjsRequireRegExp=/[^.]\s*require\s*\(\s*["']([^'"\s]+)["']\s*\)/g,jsSuffixRegExp=/\.js$/,currDirRegExp=/^\.\//,op=Object.prototype,ostring=op.toString,hasOwn=op.hasOwnProperty,isBrowser=!("undefined"==typeof window||"undefined"==typeof navigator||!window.document),isWebWorker=!isBrowser&&"undefined"!=typeof importScripts,readyRegExp=isBrowser&&"PLAYSTATION 3"===navigator.platform?/^complete$/:/^(complete|loaded)$/,defContextName="_",isOpera="undefined"!=typeof opera&&"[object Opera]"===opera.toString(),contexts={},cfg={},globalDefQueue=[],useInteractive=!1;function commentReplace(e,t){return t||""}function isFunction(e){return"[object Function]"===ostring.call(e)}function isArray(e){return"[object Array]"===ostring.call(e)}function each(e,t){var i;if(e)for(i=0;i<e.length&&(!e[i]||!t(e[i],i,e));i+=1);}function eachReverse(e,t){var i;if(e)for(i=e.length-1;-1<i&&(!e[i]||!t(e[i],i,e));i-=1);}function hasProp(e,t){return hasOwn.call(e,t)}function getOwn(e,t){return hasProp(e,t)&&e[t]}function eachProp(e,t){var i;for(i in e)if(hasProp(e,i)&&t(e[i],i))break}function mixin(i,e,r,n){return e&&eachProp(e,function(e,t){!r&&hasProp(i,t)||(!n||"object"!=typeof e||!e||isArray(e)||isFunction(e)||e instanceof RegExp?i[t]=e:(i[t]||(i[t]={}),mixin(i[t],e,r,n)))}),i}function bind(e,t){return function(){return t.apply(e,arguments)}}function scripts(){return document.getElementsByTagName("script")}function defaultOnError(e){throw e}function getGlobal(e){if(!e)return e;var t=global;return each(e.split("."),function(e){t=t[e]}),t}function makeError(e,t,i,r){var n=new Error(t+"\nhttps://requirejs.org/docs/errors.html#"+e);return n.requireType=e,n.requireModules=r,i&&(n.originalError=i),n}if(void 0===define){if(void 0!==requirejs){if(isFunction(requirejs))return;cfg=requirejs,requirejs=void 0}void 0===require||isFunction(require)||(cfg=require,require=void 0),req=requirejs=function(e,t,i,r){var n,o,a=defContextName;return isArray(e)||"string"==typeof e||(o=e,isArray(t)?(e=t,t=i,i=r):e=[]),o&&o.context&&(a=o.context),(n=getOwn(contexts,a))||(n=contexts[a]=req.s.newContext(a)),o&&n.configure(o),n.require(e,t,i)},req.config=function(e){return req(e)},req.nextTick=void 0!==setTimeout?function(e){setTimeout(e,4)}:function(e){e()},require||(require=req),req.version=version,req.jsExtRegExp=/^\/|:|\?|\.js$/,req.isBrowser=isBrowser,s=req.s={contexts:contexts,newContext:newContext},req({}),each(["toUrl","undef","defined","specified"],function(t){req[t]=function(){var e=contexts[defContextName];return e.require[t].apply(e,arguments)}}),isBrowser&&(head=s.head=document.getElementsByTagName("head")[0],baseElement=document.getElementsByTagName("base")[0],baseElement&&(head=s.head=baseElement.parentNode)),req.onError=defaultOnError,req.createNode=function(e,t,i){var r=e.xhtml?document.createElementNS("http://www.w3.org/1999/xhtml","html:script"):document.createElement("script");return r.type=e.scriptType||"text/javascript",r.charset="utf-8",r.async=!0,r},req.load=function(t,i,r){var e,n=t&&t.config||{};if(isBrowser)return(e=req.createNode(n,i,r)).setAttribute("data-requirecontext",t.contextName),e.setAttribute("data-requiremodule",i),!e.attachEvent||e.attachEvent.toString&&e.attachEvent.toString().indexOf("[native code")<0||isOpera?(e.addEventListener("load",t.onScriptLoad,!1),e.addEventListener("error",t.onScriptError,!1)):(useInteractive=!0,e.attachEvent("onreadystatechange",t.onScriptLoad)),e.src=r,n.onNodeCreated&&n.onNodeCreated(e,n,i,r),currentlyAddingScript=e,baseElement?head.insertBefore(e,baseElement):head.appendChild(e),currentlyAddingScript=null,e;if(isWebWorker)try{setTimeout(function(){},0),importScripts(r),t.completeLoad(i)}catch(e){t.onError(makeError("importscripts","importScripts failed for "+i+" at "+r,e,[i]))}},isBrowser&&!cfg.skipDataMain&&eachReverse(scripts(),function(e){if(head||(head=e.parentNode),dataMain=e.getAttribute("data-main"))return mainScript=dataMain,cfg.baseUrl||-1!==mainScript.indexOf("!")||(mainScript=(src=mainScript.split("/")).pop(),subPath=src.length?src.join("/")+"/":"./",cfg.baseUrl=subPath),mainScript=mainScript.replace(jsSuffixRegExp,""),req.jsExtRegExp.test(mainScript)&&(mainScript=dataMain),cfg.deps=cfg.deps?cfg.deps.concat(mainScript):[mainScript],!0}),define=function(e,i,t){var r,n;"string"!=typeof e&&(t=i,i=e,e=null),isArray(i)||(t=i,i=null),!i&&isFunction(t)&&(i=[],t.length&&(t.toString().replace(commentRegExp,commentReplace).replace(cjsRequireRegExp,function(e,t){i.push(t)}),i=(1===t.length?["require"]:["require","exports","module"]).concat(i))),useInteractive&&(r=currentlyAddingScript||getInteractiveScript())&&(e||(e=r.getAttribute("data-requiremodule")),n=contexts[r.getAttribute("data-requirecontext")]),n?(n.defQueue.push([e,i,t]),n.defQueueMap[e]=!0):globalDefQueue.push([e,i,t])},define.amd={jQuery:!0},req.exec=function(text){return eval(text)},req(cfg)}function newContext(u){var i,e,l,c,d,g={waitSeconds:7,baseUrl:"./",paths:{},bundles:{},pkgs:{},shim:{},config:{}},p={},f={},r={},h=[],m={},n={},v={},x=1,b=1;function q(e,t,i){var r,n,o,a,s,u,c,d,p,f,l=t&&t.split("/"),h=g.map,m=h&&h["*"];if(e&&(u=(e=e.split("/")).length-1,g.nodeIdCompat&&jsSuffixRegExp.test(e[u])&&(e[u]=e[u].replace(jsSuffixRegExp,"")),"."===e[0].charAt(0)&&l&&(e=l.slice(0,l.length-1).concat(e)),function(e){var t,i;for(t=0;t<e.length;t++)if("."===(i=e[t]))e.splice(t,1),t-=1;else if(".."===i){if(0===t||1===t&&".."===e[2]||".."===e[t-1])continue;0<t&&(e.splice(t-1,2),t-=2)}}(e),e=e.join("/")),i&&h&&(l||m)){e:for(o=(n=e.split("/")).length;0<o;o-=1){if(s=n.slice(0,o).join("/"),l)for(a=l.length;0<a;a-=1)if((r=getOwn(h,l.slice(0,a).join("/")))&&(r=getOwn(r,s))){c=r,d=o;break e}!p&&m&&getOwn(m,s)&&(p=getOwn(m,s),f=o)}!c&&p&&(c=p,d=f),c&&(n.splice(0,d,c),e=n.join("/"))}return getOwn(g.pkgs,e)||e}function E(t){isBrowser&&each(scripts(),function(e){if(e.getAttribute("data-requiremodule")===t&&e.getAttribute("data-requirecontext")===l.contextName)return e.parentNode.removeChild(e),!0})}function w(e){var t=getOwn(g.paths,e);if(t&&isArray(t)&&1<t.length)return t.shift(),l.require.undef(e),l.makeRequire(null,{skipMap:!0})([e]),!0}function y(e){var t,i=e?e.indexOf("!"):-1;return-1<i&&(t=e.substring(0,i),e=e.substring(i+1,e.length)),[t,e]}function S(e,t,i,r){var n,o,a,s,u=null,c=t?t.name:null,d=e,p=!0,f="";return e||(p=!1,e="_@r"+(x+=1)),u=(s=y(e))[0],e=s[1],u&&(u=q(u,c,r),o=getOwn(m,u)),e&&(u?f=i?e:o&&o.normalize?o.normalize(e,function(e){return q(e,c,r)}):-1===e.indexOf("!")?q(e,c,r):e:(u=(s=y(f=q(e,c,r)))[0],f=s[1],i=!0,n=l.nameToUrl(f))),{prefix:u,name:f,parentMap:t,unnormalized:!!(a=!u||o||i?"":"_unnormalized"+(b+=1)),url:n,originalName:d,isDefine:p,id:(u?u+"!"+f:f)+a}}function k(e){var t=e.id,i=getOwn(p,t);return i||(i=p[t]=new l.Module(e)),i}function M(e,t,i){var r=e.id,n=getOwn(p,r);!hasProp(m,r)||n&&!n.defineEmitComplete?(n=k(e)).error&&"error"===t?i(n.error):n.on(t,i):"defined"===t&&i(m[r])}function O(i,e){var t=i.requireModules,r=!1;e?e(i):(each(t,function(e){var t=getOwn(p,e);t&&(t.error=i,t.events.error&&(r=!0,t.emit("error",i)))}),r||req.onError(i))}function j(){globalDefQueue.length&&(each(globalDefQueue,function(e){var t=e[0];"string"==typeof t&&(l.defQueueMap[t]=!0),h.push(e)}),globalDefQueue=[])}function P(e){delete p[e],delete f[e]}function R(){var e,r,t=1e3*g.waitSeconds,n=t&&l.startTime+t<(new Date).getTime(),o=[],a=[],s=!1,u=!0;if(!i){if(i=!0,eachProp(f,function(e){var t=e.map,i=t.id;if(e.enabled&&(t.isDefine||a.push(e),!e.error))if(!e.inited&&n)w(i)?s=r=!0:(o.push(i),E(i));else if(!e.inited&&e.fetched&&t.isDefine&&(s=!0,!t.prefix))return u=!1}),n&&o.length)return(e=makeError("timeout","Load timeout for modules: "+o,null,o)).contextName=l.contextName,O(e);u&&each(a,function(e){!function n(o,a,s){var e=o.map.id;o.error?o.emit("error",o.error):(a[e]=!0,each(o.depMaps,function(e,t){var i=e.id,r=getOwn(p,i);!r||o.depMatched[t]||s[i]||(getOwn(a,i)?(o.defineDep(t,m[i]),o.check()):n(r,a,s))}),s[e]=!0)}(e,{},{})}),n&&!r||!s||!isBrowser&&!isWebWorker||d||(d=setTimeout(function(){d=0,R()},50)),i=!1}}function a(e){hasProp(m,e[0])||k(S(e[0],null,!0)).init(e[1],e[2])}function o(e,t,i,r){e.detachEvent&&!isOpera?r&&e.detachEvent(r,t):e.removeEventListener(i,t,!1)}function s(e){var t=e.currentTarget||e.srcElement;return o(t,l.onScriptLoad,"load","onreadystatechange"),o(t,l.onScriptError,"error"),{node:t,id:t&&t.getAttribute("data-requiremodule")}}function T(){var e;for(j();h.length;){if(null===(e=h.shift())[0])return O(makeError("mismatch","Mismatched anonymous define() module: "+e[e.length-1]));a(e)}l.defQueueMap={}}return c={require:function(e){return e.require?e.require:e.require=l.makeRequire(e.map)},exports:function(e){if(e.usingExports=!0,e.map.isDefine)return e.exports?m[e.map.id]=e.exports:e.exports=m[e.map.id]={}},module:function(e){return e.module?e.module:e.module={id:e.map.id,uri:e.map.url,config:function(){return getOwn(g.config,e.map.id)||{}},exports:e.exports||(e.exports={})}}},(e=function(e){this.events=getOwn(r,e.id)||{},this.map=e,this.shim=getOwn(g.shim,e.id),this.depExports=[],this.depMaps=[],this.depMatched=[],this.pluginMaps={},this.depCount=0}).prototype={init:function(e,t,i,r){r=r||{},this.inited||(this.factory=t,i?this.on("error",i):this.events.error&&(i=bind(this,function(e){this.emit("error",e)})),this.depMaps=e&&e.slice(0),this.errback=i,this.inited=!0,this.ignore=r.ignore,r.enabled||this.enabled?this.enable():this.check())},defineDep:function(e,t){this.depMatched[e]||(this.depMatched[e]=!0,this.depCount-=1,this.depExports[e]=t)},fetch:function(){if(!this.fetched){this.fetched=!0,l.startTime=(new Date).getTime();var e=this.map;if(!this.shim)return e.prefix?this.callPlugin():this.load();l.makeRequire(this.map,{enableBuildCallback:!0})(this.shim.deps||[],bind(this,function(){return e.prefix?this.callPlugin():this.load()}))}},load:function(){var e=this.map.url;n[e]||(n[e]=!0,l.load(this.map.id,e))},check:function(){if(this.enabled&&!this.enabling){var t,e,i=this.map.id,r=this.depExports,n=this.exports,o=this.factory;if(this.inited){if(this.error)this.emit("error",this.error);else if(!this.defining){if(this.defining=!0,this.depCount<1&&!this.defined){if(isFunction(o)){if(this.events.error&&this.map.isDefine||req.onError!==defaultOnError)try{n=l.execCb(i,o,r,n)}catch(e){t=e}else n=l.execCb(i,o,r,n);if(this.map.isDefine&&void 0===n&&((e=this.module)?n=e.exports:this.usingExports&&(n=this.exports)),t)return t.requireMap=this.map,t.requireModules=this.map.isDefine?[this.map.id]:null,t.requireType=this.map.isDefine?"define":"require",O(this.error=t)}else n=o;if(this.exports=n,this.map.isDefine&&!this.ignore&&(m[i]=n,req.onResourceLoad)){var a=[];each(this.depMaps,function(e){a.push(e.normalizedMap||e)}),req.onResourceLoad(l,this.map,a)}P(i),this.defined=!0}this.defining=!1,this.defined&&!this.defineEmitted&&(this.defineEmitted=!0,this.emit("defined",this.exports),this.defineEmitComplete=!0)}}else hasProp(l.defQueueMap,i)||this.fetch()}},callPlugin:function(){var u=this.map,c=u.id,e=S(u.prefix);this.depMaps.push(e),M(e,"defined",bind(this,function(e){var o,t,i,r=getOwn(v,this.map.id),n=this.map.name,a=this.map.parentMap?this.map.parentMap.name:null,s=l.makeRequire(u.parentMap,{enableBuildCallback:!0});return this.map.unnormalized?(e.normalize&&(n=e.normalize(n,function(e){return q(e,a,!0)})||""),M(t=S(u.prefix+"!"+n,this.map.parentMap,!0),"defined",bind(this,function(e){this.map.normalizedMap=t,this.init([],function(){return e},null,{enabled:!0,ignore:!0})})),void((i=getOwn(p,t.id))&&(this.depMaps.push(t),this.events.error&&i.on("error",bind(this,function(e){this.emit("error",e)})),i.enable()))):r?(this.map.url=l.nameToUrl(r),void this.load()):((o=bind(this,function(e){this.init([],function(){return e},null,{enabled:!0})})).error=bind(this,function(e){this.inited=!0,(this.error=e).requireModules=[c],eachProp(p,function(e){0===e.map.id.indexOf(c+"_unnormalized")&&P(e.map.id)}),O(e)}),o.fromText=bind(this,function(e,t){var i=u.name,r=S(i),n=useInteractive;t&&(e=t),n&&(useInteractive=!1),k(r),hasProp(g.config,c)&&(g.config[i]=g.config[c]);try{req.exec(e)}catch(e){return O(makeError("fromtexteval","fromText eval for "+c+" failed: "+e,e,[c]))}n&&(useInteractive=!0),this.depMaps.push(r),l.completeLoad(i),s([i],o)}),void e.load(u.name,s,o,g))})),l.enable(e,this),this.pluginMaps[e.id]=e},enable:function(){(f[this.map.id]=this).enabled=!0,this.enabling=!0,each(this.depMaps,bind(this,function(e,t){var i,r,n;if("string"==typeof e){if(e=S(e,this.map.isDefine?this.map:this.map.parentMap,!1,!this.skipMap),this.depMaps[t]=e,n=getOwn(c,e.id))return void(this.depExports[t]=n(this));this.depCount+=1,M(e,"defined",bind(this,function(e){this.undefed||(this.defineDep(t,e),this.check())})),this.errback?M(e,"error",bind(this,this.errback)):this.events.error&&M(e,"error",bind(this,function(e){this.emit("error",e)}))}i=e.id,r=p[i],hasProp(c,i)||!r||r.enabled||l.enable(e,this)})),eachProp(this.pluginMaps,bind(this,function(e){var t=getOwn(p,e.id);t&&!t.enabled&&l.enable(e,this)})),this.enabling=!1,this.check()},on:function(e,t){var i=this.events[e];i||(i=this.events[e]=[]),i.push(t)},emit:function(e,t){each(this.events[e],function(e){e(t)}),"error"===e&&delete this.events[e]}},(l={config:g,contextName:u,registry:p,defined:m,urlFetched:n,defQueue:h,defQueueMap:{},Module:e,makeModuleMap:S,nextTick:req.nextTick,onError:O,configure:function(e){if(e.baseUrl&&"/"!==e.baseUrl.charAt(e.baseUrl.length-1)&&(e.baseUrl+="/"),"string"==typeof e.urlArgs){var i=e.urlArgs;e.urlArgs=function(e,t){return(-1===t.indexOf("?")?"?":"&")+i}}var r=g.shim,n={paths:!0,bundles:!0,config:!0,map:!0};eachProp(e,function(e,t){n[t]?(g[t]||(g[t]={}),mixin(g[t],e,!0,!0)):g[t]=e}),e.bundles&&eachProp(e.bundles,function(e,t){each(e,function(e){e!==t&&(v[e]=t)})}),e.shim&&(eachProp(e.shim,function(e,t){isArray(e)&&(e={deps:e}),!e.exports&&!e.init||e.exportsFn||(e.exportsFn=l.makeShimExports(e)),r[t]=e}),g.shim=r),e.packages&&each(e.packages,function(e){var t;t=(e="string"==typeof e?{name:e}:e).name,e.location&&(g.paths[t]=e.location),g.pkgs[t]=e.name+"/"+(e.main||"main").replace(currDirRegExp,"").replace(jsSuffixRegExp,"")}),eachProp(p,function(e,t){e.inited||e.map.unnormalized||(e.map=S(t,null,!0))}),(e.deps||e.callback)&&l.require(e.deps||[],e.callback)},makeShimExports:function(t){return function(){var e;return t.init&&(e=t.init.apply(global,arguments)),e||t.exports&&getGlobal(t.exports)}},makeRequire:function(o,a){function s(e,t,i){var r,n;return a.enableBuildCallback&&t&&isFunction(t)&&(t.__requireJsBuild=!0),"string"==typeof e?isFunction(t)?O(makeError("requireargs","Invalid require call"),i):o&&hasProp(c,e)?c[e](p[o.id]):req.get?req.get(l,e,o,s):(r=S(e,o,!1,!0).id,hasProp(m,r)?m[r]:O(makeError("notloaded",'Module name "'+r+'" has not been loaded yet for context: '+u+(o?"":". Use require([])")))):(T(),l.nextTick(function(){T(),(n=k(S(null,o))).skipMap=a.skipMap,n.init(e,t,i,{enabled:!0}),R()}),s)}return a=a||{},mixin(s,{isBrowser:isBrowser,toUrl:function(e){var t,i=e.lastIndexOf("."),r=e.split("/")[0];return-1!==i&&(!("."===r||".."===r)||1<i)&&(t=e.substring(i,e.length),e=e.substring(0,i)),l.nameToUrl(q(e,o&&o.id,!0),t,!0)},defined:function(e){return hasProp(m,S(e,o,!1,!0).id)},specified:function(e){return e=S(e,o,!1,!0).id,hasProp(m,e)||hasProp(p,e)}}),o||(s.undef=function(i){j();var e=S(i,o,!0),t=getOwn(p,i);t.undefed=!0,E(i),delete m[i],delete n[e.url],delete r[i],eachReverse(h,function(e,t){e[0]===i&&h.splice(t,1)}),delete l.defQueueMap[i],t&&(t.events.defined&&(r[i]=t.events),P(i))}),s},enable:function(e){getOwn(p,e.id)&&k(e).enable()},completeLoad:function(e){var t,i,r,n=getOwn(g.shim,e)||{},o=n.exports;for(j();h.length;){if(null===(i=h.shift())[0]){if(i[0]=e,t)break;t=!0}else i[0]===e&&(t=!0);a(i)}if(l.defQueueMap={},r=getOwn(p,e),!t&&!hasProp(m,e)&&r&&!r.inited){if(!(!g.enforceDefine||o&&getGlobal(o)))return w(e)?void 0:O(makeError("nodefine","No define call for "+e,null,[e]));a([e,n.deps||[],n.exportsFn])}R()},nameToUrl:function(e,t,i){var r,n,o,a,s,u,c=getOwn(g.pkgs,e);if(c&&(e=c),u=getOwn(v,e))return l.nameToUrl(u,t,i);if(req.jsExtRegExp.test(e))a=e+(t||"");else{for(r=g.paths,o=(n=e.split("/")).length;0<o;o-=1)if(s=getOwn(r,n.slice(0,o).join("/"))){isArray(s)&&(s=s[0]),n.splice(0,o,s);break}a=n.join("/"),a=("/"===(a+=t||(/^data\:|^blob\:|\?/.test(a)||i?"":".js")).charAt(0)||a.match(/^[\w\+\.\-]+:/)?"":g.baseUrl)+a}return g.urlArgs&&!/^blob\:/.test(a)?a+g.urlArgs(e,a):a},load:function(e,t){req.load(l,e,t)},execCb:function(e,t,i,r){return t.apply(r,i)},onScriptLoad:function(e){if("load"===e.type||readyRegExp.test((e.currentTarget||e.srcElement).readyState)){interactiveScript=null;var t=s(e);l.completeLoad(t.id)}},onScriptError:function(e){var i=s(e);if(!w(i.id)){var r=[];return eachProp(p,function(e,t){0!==t.indexOf("_@r")&&each(e.depMaps,function(e){if(e.id===i.id)return r.push(t),!0})}),O(makeError("scripterror",'Script error for "'+i.id+(r.length?'", needed by: '+r.join(", "):'"'),e,[i.id]))}}}).require=l.makeRequire(),l}function getInteractiveScript(){return interactiveScript&&"interactive"===interactiveScript.readyState||eachReverse(scripts(),function(e){if("interactive"===e.readyState)return interactiveScript=e}),interactiveScript}}(this,"undefined"==typeof setTimeout?void 0:setTimeout);</script>
+
+<script type="application/javascript">define('jquery', [],function() {return window.jQuery;})</script>
+<script type="text/javascript">
+window.PlotlyConfig = {MathJaxConfig: 'local'};
+if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: "STIX-Web"}});}
+if (typeof require !== 'undefined') {
+require.undef("plotly");
+requirejs.config({
+    paths: {
+        'plotly': ['https://cdn.plot.ly/plotly-2.30.0.min']
+    }
+});
+require(['plotly'], function(Plotly) {
+    window._Plotly = Plotly;
+});
+}
+</script>
+
 
 
 <style type="text/css">
@@ -4716,7 +4771,7 @@
 <header id="title-block-header" class="quarto-title-block default page-columns page-full">
   <div class="quarto-title-banner page-columns page-full">
     <div class="quarto-title column-page-right">
-      <h1 class="title">Client Report - [Insert Project Title]</h1>
+      <div class="quarto-title-block"><div><h1 class="title">Finding Relationships in Baseball - Project 3</h1><button type="button" class="btn code-tools-button dropdown-toggle" id="quarto-code-tools-menu" data-bs-toggle="dropdown" aria-expanded="false"><i class="bi"></i> See code</button><ul class="dropdown-menu dropdown-menu-end" aria-labelelledby="quarto-code-tools-menu"><li><a id="quarto-show-all-code" class="dropdown-item" href="javascript:void(0)" role="button">Show All Code</a></li><li><a id="quarto-hide-all-code" class="dropdown-item" href="javascript:void(0)" role="button">Hide All Code</a></li></ul></div></div>
             <p class="subtitle lead">Course DS 250</p>
                       </div>
   </div>
@@ -4727,7 +4782,7 @@ <h1 class="title">Client Report - [Insert Project Title]</h1>
       <div>
       <div class="quarto-title-meta-heading">Author</div>
       <div class="quarto-title-meta-contents">
-               <p>[STUDENT NAME] </p>
+               <p>Bethany Ball </p>
             </div>
     </div>
       
@@ -4810,11 +4865,375 @@ <h1 class="title">Client Report - [Insert Project Title]</h1>
     <h2 id="toc-title">On this page</h2>
    
   <ul>
-  <li><a href="#paste-in-a-template" id="toc-paste-in-a-template">Paste in a template</a></li>
+  <li><a href="#elevator-pitch" id="toc-elevator-pitch">Elevator pitch</a></li>
+  <li><a href="#questiontask-1" id="toc-questiontask-1">QUESTION|TASK 1</a></li>
+  <li><a href="#questiontask-2" id="toc-questiontask-2">QUESTION|TASK 2</a></li>
+  <li><a href="#questiontask-3" id="toc-questiontask-3">QUESTION|TASK 3</a></li>
   </ul>
 </nav>
-<section id="paste-in-a-template" class="level3">
-<h3 class="anchored" data-anchor-id="paste-in-a-template">Paste in a template</h3>
+<section id="elevator-pitch" class="level2">
+<h2 class="anchored" data-anchor-id="elevator-pitch">Elevator pitch</h2>
+<p>Overall this data shows that you have to be careful with averages because if one person did one thing once and succeeded then they will have a perfect average, but that does not mean that they are the best. This data also shows that teams/players that are good usually stay good and that teams/players that are bad usually stay bad. Overall I think this data is a warning to know our data set and which values you don’t want to include because it will just mess with the averages, and how if you don’t have enough information on a player, team, etc you really shouldn’t make averages with thoughts numbers until you have enough data for it too be meaningful.</p>
+<div id="project-data" class="cell" data-execution_count="2">
+<details class="code-fold">
+<summary>Read and format project data</summary>
+<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Include and execute your code here</span></span>
+<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> sqlite3</span>
+<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="co"># Path to your SQLite database file</span></span>
+<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a>db_file <span class="op">=</span> <span class="st">&quot;https://byuistats.github.io/DS250-Course/Data/lahmansbaseballdb.sqlite&quot;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</details>
+</div>
+</section>
+<section id="questiontask-1" class="level2">
+<h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
+<p>Write an SQL query to create a new dataframe about baseball players who attended BYU-Idaho. The new table should contain five columns: playerID, schoolID, salary, and the yearID/teamID associated with each salary. Order the table by salary (highest to lowest) and print out the table in your report.</p>
+<div id="5f2f3164" class="cell" data-execution_count="3">
+<details class="code-fold">
+<summary>Show the code</summary>
+<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Connect to the SQLite database</span></span>
+<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a><span class="bu">file</span> <span class="op">=</span> <span class="st">&#39;lahmansbaseballdb.sqlite&#39;</span></span>
+<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> sqlite3.<span class="ex">connect</span>(<span class="bu">file</span>)</span>
+<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a><span class="co"># Execute the SQL query and store the results in a DataFrame</span></span>
+<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a>query <span class="op">=</span> <span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a><span class="st">SELECT </span></span>
+<span id="cb2-8"><a href="#cb2-8" aria-hidden="true" tabindex="-1"></a><span class="st">    s.playerID,</span></span>
+<span id="cb2-9"><a href="#cb2-9" aria-hidden="true" tabindex="-1"></a><span class="st">    sl.schoolID,</span></span>
+<span id="cb2-10"><a href="#cb2-10" aria-hidden="true" tabindex="-1"></a><span class="st">    s.salary,</span></span>
+<span id="cb2-11"><a href="#cb2-11" aria-hidden="true" tabindex="-1"></a><span class="st">    s.yearID || &#39;/&#39; || s.teamID AS year_team</span></span>
+<span id="cb2-12"><a href="#cb2-12" aria-hidden="true" tabindex="-1"></a><span class="st">FROM </span></span>
+<span id="cb2-13"><a href="#cb2-13" aria-hidden="true" tabindex="-1"></a><span class="st">    schools sl</span></span>
+<span id="cb2-14"><a href="#cb2-14" aria-hidden="true" tabindex="-1"></a><span class="st">JOIN</span></span>
+<span id="cb2-15"><a href="#cb2-15" aria-hidden="true" tabindex="-1"></a><span class="st">    collegeplaying cp ON cp.schoolID = sl.schoolID</span></span>
+<span id="cb2-16"><a href="#cb2-16" aria-hidden="true" tabindex="-1"></a><span class="st">JOIN</span></span>
+<span id="cb2-17"><a href="#cb2-17" aria-hidden="true" tabindex="-1"></a><span class="st">    salaries s ON s.playerID = cp.playerID</span></span>
+<span id="cb2-18"><a href="#cb2-18" aria-hidden="true" tabindex="-1"></a><span class="st">WHERE </span></span>
+<span id="cb2-19"><a href="#cb2-19" aria-hidden="true" tabindex="-1"></a><span class="st">    sl.schoolID = &#39;idbyuid&#39;</span></span>
+<span id="cb2-20"><a href="#cb2-20" aria-hidden="true" tabindex="-1"></a><span class="st">ORDER BY </span></span>
+<span id="cb2-21"><a href="#cb2-21" aria-hidden="true" tabindex="-1"></a><span class="st">    s.salary DESC;</span></span>
+<span id="cb2-22"><a href="#cb2-22" aria-hidden="true" tabindex="-1"></a><span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb2-23"><a href="#cb2-23" aria-hidden="true" tabindex="-1"></a>df <span class="op">=</span> pd.read_sql_query(query, con)</span>
+<span id="cb2-24"><a href="#cb2-24" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb2-25"><a href="#cb2-25" aria-hidden="true" tabindex="-1"></a><span class="co"># Set display options to show all rows and columns</span></span>
+<span id="cb2-26"><a href="#cb2-26" aria-hidden="true" tabindex="-1"></a>pd.set_option(<span class="st">&#39;display.max_rows&#39;</span>, <span class="va">None</span>)</span>
+<span id="cb2-27"><a href="#cb2-27" aria-hidden="true" tabindex="-1"></a>pd.set_option(<span class="st">&#39;display.max_columns&#39;</span>, <span class="va">None</span>)</span>
+<span id="cb2-28"><a href="#cb2-28" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb2-29"><a href="#cb2-29" aria-hidden="true" tabindex="-1"></a><span class="co"># Print the DataFrame</span></span>
+<span id="cb2-30"><a href="#cb2-30" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="st">&quot;DataFrame with the data:&quot;</span>)</span>
+<span id="cb2-31"><a href="#cb2-31" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(df)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</details>
+<div class="cell-output cell-output-stdout">
+<pre><code>DataFrame with the data:
+     playerID schoolID     salary year_team
+0   lindsma01  idbyuid  4000000.0  2014/CHA
+1   lindsma01  idbyuid  4000000.0  2014/CHA
+2   lindsma01  idbyuid  3600000.0  2012/BAL
+3   lindsma01  idbyuid  3600000.0  2012/BAL
+4   lindsma01  idbyuid  2800000.0  2011/COL
+5   lindsma01  idbyuid  2800000.0  2011/COL
+6   lindsma01  idbyuid  2300000.0  2013/CHA
+7   lindsma01  idbyuid  2300000.0  2013/CHA
+8   lindsma01  idbyuid  1625000.0  2010/HOU
+9   lindsma01  idbyuid  1625000.0  2010/HOU
+10  stephga01  idbyuid  1025000.0  2001/SLN
+11  stephga01  idbyuid  1025000.0  2001/SLN
+12  stephga01  idbyuid   900000.0  2002/SLN
+13  stephga01  idbyuid   900000.0  2002/SLN
+14  stephga01  idbyuid   800000.0  2003/SLN
+15  stephga01  idbyuid   800000.0  2003/SLN
+16  stephga01  idbyuid   550000.0  2000/SLN
+17  stephga01  idbyuid   550000.0  2000/SLN
+18  lindsma01  idbyuid   410000.0  2009/FLO
+19  lindsma01  idbyuid   410000.0  2009/FLO
+20  lindsma01  idbyuid   395000.0  2008/FLO
+21  lindsma01  idbyuid   395000.0  2008/FLO
+22  lindsma01  idbyuid   380000.0  2007/FLO
+23  lindsma01  idbyuid   380000.0  2007/FLO
+24  stephga01  idbyuid   215000.0  1999/SLN
+25  stephga01  idbyuid   215000.0  1999/SLN
+26  stephga01  idbyuid   185000.0  1998/PHI
+27  stephga01  idbyuid   185000.0  1998/PHI
+28  stephga01  idbyuid   150000.0  1997/PHI
+29  stephga01  idbyuid   150000.0  1997/PHI</code></pre>
+</div>
+</div>
+<p><strong>Summary/Findings</strong></p>
+<ul>
+<li><p>There are only 2 people in this database who have played for BYU-Idaho baseball.</p></li>
+<li><p>The most money made by either was $4,000,000.00</p></li>
+<li><p>The least amount made by either player was $150,000.00</p></li>
+</ul>
+</section>
+<section id="questiontask-2" class="level2">
+<h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
+<p>This three-part question requires you to calculate batting average (number of hits divided by the number of at-bats)</p>
+<p><strong>QUESTION|TASK 2.1</strong></p>
+<p>Write an SQL query that provides playerID, yearID, and batting average for players with at least 1 at bat that year. Sort the table from highest batting average to lowest, and then by playerid alphabetically. Show the top 5 results in your report.</p>
+<div id="683173f5" class="cell" data-execution_count="4">
+<details class="code-fold">
+<summary>Show the code</summary>
+<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Connect to the SQLite database</span></span>
+<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="bu">file</span> <span class="op">=</span> <span class="st">&#39;lahmansbaseballdb.sqlite&#39;</span></span>
+<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> sqlite3.<span class="ex">connect</span>(<span class="bu">file</span>)</span>
+<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a><span class="co"># Execute the SQL query and store the results in a DataFrame</span></span>
+<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a>query <span class="op">=</span> <span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a><span class="st">SELECT</span></span>
+<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a><span class="st">    playerID,</span></span>
+<span id="cb4-9"><a href="#cb4-9" aria-hidden="true" tabindex="-1"></a><span class="st">    yearID,</span></span>
+<span id="cb4-10"><a href="#cb4-10" aria-hidden="true" tabindex="-1"></a><span class="st">    CAST(H AS REAL) / AB AS batting_average</span></span>
+<span id="cb4-11"><a href="#cb4-11" aria-hidden="true" tabindex="-1"></a><span class="st">FROM</span></span>
+<span id="cb4-12"><a href="#cb4-12" aria-hidden="true" tabindex="-1"></a><span class="st">    Batting</span></span>
+<span id="cb4-13"><a href="#cb4-13" aria-hidden="true" tabindex="-1"></a><span class="st">WHERE</span></span>
+<span id="cb4-14"><a href="#cb4-14" aria-hidden="true" tabindex="-1"></a><span class="st">    AB &gt; 0</span></span>
+<span id="cb4-15"><a href="#cb4-15" aria-hidden="true" tabindex="-1"></a><span class="st">ORDER BY</span></span>
+<span id="cb4-16"><a href="#cb4-16" aria-hidden="true" tabindex="-1"></a><span class="st">    batting_average DESC,</span></span>
+<span id="cb4-17"><a href="#cb4-17" aria-hidden="true" tabindex="-1"></a><span class="st">    playerID DESC</span></span>
+<span id="cb4-18"><a href="#cb4-18" aria-hidden="true" tabindex="-1"></a><span class="st">LIMIT 5;</span></span>
+<span id="cb4-19"><a href="#cb4-19" aria-hidden="true" tabindex="-1"></a><span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb4-20"><a href="#cb4-20" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb4-21"><a href="#cb4-21" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb4-22"><a href="#cb4-22" aria-hidden="true" tabindex="-1"></a>df <span class="op">=</span> pd.read_sql_query(query, con)</span>
+<span id="cb4-23"><a href="#cb4-23" aria-hidden="true" tabindex="-1"></a><span class="co"># Show the data</span></span>
+<span id="cb4-24"><a href="#cb4-24" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(df)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</details>
+<div class="cell-output cell-output-stdout">
+<pre><code>    playerID  yearID  batting_average
+0  zearfda01    1898              1.0
+1  zannido01    1966              1.0
+2  yantzge01    1912              1.0
+3    yanes01    2000              1.0
+4    yanes01    2003              1.0</code></pre>
+</div>
+</div>
+<p><strong>Summary/Findings</strong></p>
+<ul>
+<li><p>Everyone in the top 5 had a 100% average, which means that they probably didn’t bat much.</p></li>
+<li><p>The years don’t seem to show a pattern, at least for the top 5 shown.</p></li>
+</ul>
+<p><strong>QUESTION|TASK 2.2</strong></p>
+<p>Use the same query as above, but only include players with at least 10 at bats that year. Print the top 5 results.</p>
+<div id="503d5e36" class="cell" data-execution_count="5">
+<details class="code-fold">
+<summary>Show the code</summary>
+<div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Connect to the SQLite database</span></span>
+<span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a><span class="bu">file</span> <span class="op">=</span> <span class="st">&#39;lahmansbaseballdb.sqlite&#39;</span></span>
+<span id="cb6-3"><a href="#cb6-3" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> sqlite3.<span class="ex">connect</span>(<span class="bu">file</span>)</span>
+<span id="cb6-4"><a href="#cb6-4" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb6-5"><a href="#cb6-5" aria-hidden="true" tabindex="-1"></a><span class="co"># Execute the SQL query and store the results in a DataFrame</span></span>
+<span id="cb6-6"><a href="#cb6-6" aria-hidden="true" tabindex="-1"></a>query <span class="op">=</span> <span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb6-7"><a href="#cb6-7" aria-hidden="true" tabindex="-1"></a><span class="st">SELECT</span></span>
+<span id="cb6-8"><a href="#cb6-8" aria-hidden="true" tabindex="-1"></a><span class="st">    playerID,</span></span>
+<span id="cb6-9"><a href="#cb6-9" aria-hidden="true" tabindex="-1"></a><span class="st">    yearID,</span></span>
+<span id="cb6-10"><a href="#cb6-10" aria-hidden="true" tabindex="-1"></a><span class="st">    CAST(H AS REAL) / AB AS batting_average</span></span>
+<span id="cb6-11"><a href="#cb6-11" aria-hidden="true" tabindex="-1"></a><span class="st">FROM</span></span>
+<span id="cb6-12"><a href="#cb6-12" aria-hidden="true" tabindex="-1"></a><span class="st">    Batting</span></span>
+<span id="cb6-13"><a href="#cb6-13" aria-hidden="true" tabindex="-1"></a><span class="st">WHERE</span></span>
+<span id="cb6-14"><a href="#cb6-14" aria-hidden="true" tabindex="-1"></a><span class="st">    AB &gt; 9</span></span>
+<span id="cb6-15"><a href="#cb6-15" aria-hidden="true" tabindex="-1"></a><span class="st">ORDER BY</span></span>
+<span id="cb6-16"><a href="#cb6-16" aria-hidden="true" tabindex="-1"></a><span class="st">    batting_average DESC,</span></span>
+<span id="cb6-17"><a href="#cb6-17" aria-hidden="true" tabindex="-1"></a><span class="st">    playerID ASC</span></span>
+<span id="cb6-18"><a href="#cb6-18" aria-hidden="true" tabindex="-1"></a><span class="st">LIMIT 5;</span></span>
+<span id="cb6-19"><a href="#cb6-19" aria-hidden="true" tabindex="-1"></a><span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb6-20"><a href="#cb6-20" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb6-21"><a href="#cb6-21" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb6-22"><a href="#cb6-22" aria-hidden="true" tabindex="-1"></a>df <span class="op">=</span> pd.read_sql_query(query, con)</span>
+<span id="cb6-23"><a href="#cb6-23" aria-hidden="true" tabindex="-1"></a><span class="co"># Show the data</span></span>
+<span id="cb6-24"><a href="#cb6-24" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(df)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</details>
+<div class="cell-output cell-output-stdout">
+<pre><code>    playerID  yearID  batting_average
+0  nymanny01    1974         0.642857
+1  carsoma01    2013         0.636364
+2  altizda01    1910         0.600000
+3  johnsde01    1975         0.600000
+4  silvech01    1948         0.571429</code></pre>
+</div>
+</div>
+<p><strong>Summary/Findings</strong></p>
+<ul>
+<li><p>The batting averages dropped substantially went you exclude the people that have batted less than 10 times that year.</p></li>
+<li><p>All of the top averages are around 60%.</p></li>
+<li><p>Again the years don’t show a clear pattern with the data shown.</p></li>
+</ul>
+<p><strong>QUESTION|TASK 2.3</strong></p>
+<p>Now calculate the batting average for players over their entire careers (all years combined). Only include players with at least 100 at bats, and print the top 5 results.</p>
+<div id="ec0be205" class="cell" data-execution_count="6">
+<details class="code-fold">
+<summary>Show the code</summary>
+<div class="sourceCode cell-code" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Connect to the SQLite database</span></span>
+<span id="cb8-2"><a href="#cb8-2" aria-hidden="true" tabindex="-1"></a><span class="bu">file</span> <span class="op">=</span> <span class="st">&#39;lahmansbaseballdb.sqlite&#39;</span></span>
+<span id="cb8-3"><a href="#cb8-3" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> sqlite3.<span class="ex">connect</span>(<span class="bu">file</span>)</span>
+<span id="cb8-4"><a href="#cb8-4" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb8-5"><a href="#cb8-5" aria-hidden="true" tabindex="-1"></a><span class="co"># Execute the SQL query and store the results in a DataFrame</span></span>
+<span id="cb8-6"><a href="#cb8-6" aria-hidden="true" tabindex="-1"></a>query <span class="op">=</span> <span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb8-7"><a href="#cb8-7" aria-hidden="true" tabindex="-1"></a><span class="st">SELECT</span></span>
+<span id="cb8-8"><a href="#cb8-8" aria-hidden="true" tabindex="-1"></a><span class="st">    s.playerID,</span></span>
+<span id="cb8-9"><a href="#cb8-9" aria-hidden="true" tabindex="-1"></a><span class="st">    SUM(H) AS total_hits,</span></span>
+<span id="cb8-10"><a href="#cb8-10" aria-hidden="true" tabindex="-1"></a><span class="st">    SUM(AB) AS total_at_bats,</span></span>
+<span id="cb8-11"><a href="#cb8-11" aria-hidden="true" tabindex="-1"></a><span class="st">    CAST(SUM(H) AS REAL) / NULLIF(SUM(AB), 0) AS career_batting_average</span></span>
+<span id="cb8-12"><a href="#cb8-12" aria-hidden="true" tabindex="-1"></a><span class="st">FROM</span></span>
+<span id="cb8-13"><a href="#cb8-13" aria-hidden="true" tabindex="-1"></a><span class="st">    Salaries s</span></span>
+<span id="cb8-14"><a href="#cb8-14" aria-hidden="true" tabindex="-1"></a><span class="st">JOIN</span></span>
+<span id="cb8-15"><a href="#cb8-15" aria-hidden="true" tabindex="-1"></a><span class="st">    Batting b ON s.playerID = b.playerID</span></span>
+<span id="cb8-16"><a href="#cb8-16" aria-hidden="true" tabindex="-1"></a><span class="st">GROUP BY</span></span>
+<span id="cb8-17"><a href="#cb8-17" aria-hidden="true" tabindex="-1"></a><span class="st">    s.playerID</span></span>
+<span id="cb8-18"><a href="#cb8-18" aria-hidden="true" tabindex="-1"></a><span class="st">HAVING</span></span>
+<span id="cb8-19"><a href="#cb8-19" aria-hidden="true" tabindex="-1"></a><span class="st">    total_at_bats &gt;= 100</span></span>
+<span id="cb8-20"><a href="#cb8-20" aria-hidden="true" tabindex="-1"></a><span class="st">ORDER BY</span></span>
+<span id="cb8-21"><a href="#cb8-21" aria-hidden="true" tabindex="-1"></a><span class="st">    career_batting_average DESC</span></span>
+<span id="cb8-22"><a href="#cb8-22" aria-hidden="true" tabindex="-1"></a><span class="st">LIMIT 5;</span></span>
+<span id="cb8-23"><a href="#cb8-23" aria-hidden="true" tabindex="-1"></a><span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb8-24"><a href="#cb8-24" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb8-25"><a href="#cb8-25" aria-hidden="true" tabindex="-1"></a>df <span class="op">=</span> pd.read_sql_query(query, con)</span>
+<span id="cb8-26"><a href="#cb8-26" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb8-27"><a href="#cb8-27" aria-hidden="true" tabindex="-1"></a><span class="co"># Show the data</span></span>
+<span id="cb8-28"><a href="#cb8-28" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(df.head())</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</details>
+<div class="cell-output cell-output-stdout">
+<pre><code>    playerID  total_hits  total_at_bats  career_batting_average
+0  kruegbi01          42            105                0.400000
+1  forstte01          62            156                0.397436
+2  mathete01          54            144                0.375000
+3  gwynnto01       53397         157896                0.338178
+4  pemberu01          45            134                0.335821</code></pre>
+</div>
+</div>
+<p><strong>Summary/Findings</strong></p>
+<ul>
+<li><p>The highest batting average is 40%.</p></li>
+<li><p>The most impressive of these top 5 is gwynnto01 (), because he has batted substantially more then all of the others, therefore the average will even out to a more true average taking out outliners, like hitting every time in one game because of a bad pitcher.</p></li>
+<li><p>From the 1st to the 5th it drops quitly, almost 7%.</p></li>
+</ul>
+</section>
+<section id="questiontask-3" class="level2">
+<h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
+<p>Pick any two baseball teams and compare them using a metric of your choice (average salary, home runs, number of wins, etc). Write an SQL query to get the data you need, then make a graph using Plotly Express to visualize the comparison. What do you learn?</p>
+<div id="227f0cfa" class="cell" data-execution_count="7">
+<details class="code-fold">
+<summary>Show the code</summary>
+<div class="sourceCode cell-code" id="cb10"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> sqlite3</span>
+<span id="cb10-2"><a href="#cb10-2" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
+<span id="cb10-3"><a href="#cb10-3" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> plotly.express <span class="im">as</span> px</span>
+<span id="cb10-4"><a href="#cb10-4" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> numpy <span class="im">as</span> np</span>
+<span id="cb10-5"><a href="#cb10-5" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> sklearn.linear_model <span class="im">import</span> LinearRegression</span>
+<span id="cb10-6"><a href="#cb10-6" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-7"><a href="#cb10-7" aria-hidden="true" tabindex="-1"></a><span class="co"># Connect to the SQLite database</span></span>
+<span id="cb10-8"><a href="#cb10-8" aria-hidden="true" tabindex="-1"></a><span class="bu">file</span> <span class="op">=</span> <span class="st">&#39;lahmansbaseballdb.sqlite&#39;</span></span>
+<span id="cb10-9"><a href="#cb10-9" aria-hidden="true" tabindex="-1"></a>con <span class="op">=</span> sqlite3.<span class="ex">connect</span>(<span class="bu">file</span>)</span>
+<span id="cb10-10"><a href="#cb10-10" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-11"><a href="#cb10-11" aria-hidden="true" tabindex="-1"></a><span class="co"># Execute the SQL query and store the results in a DataFrame</span></span>
+<span id="cb10-12"><a href="#cb10-12" aria-hidden="true" tabindex="-1"></a>query <span class="op">=</span> <span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb10-13"><a href="#cb10-13" aria-hidden="true" tabindex="-1"></a><span class="st">SELECT</span></span>
+<span id="cb10-14"><a href="#cb10-14" aria-hidden="true" tabindex="-1"></a><span class="st">    t.W AS wins,</span></span>
+<span id="cb10-15"><a href="#cb10-15" aria-hidden="true" tabindex="-1"></a><span class="st">    t.yearID,</span></span>
+<span id="cb10-16"><a href="#cb10-16" aria-hidden="true" tabindex="-1"></a><span class="st">    s.schoolID</span></span>
+<span id="cb10-17"><a href="#cb10-17" aria-hidden="true" tabindex="-1"></a><span class="st">FROM</span></span>
+<span id="cb10-18"><a href="#cb10-18" aria-hidden="true" tabindex="-1"></a><span class="st">    schools s</span></span>
+<span id="cb10-19"><a href="#cb10-19" aria-hidden="true" tabindex="-1"></a><span class="st">JOIN</span></span>
+<span id="cb10-20"><a href="#cb10-20" aria-hidden="true" tabindex="-1"></a><span class="st">    collegeplaying cp ON s.schoolID = cp.schoolID</span></span>
+<span id="cb10-21"><a href="#cb10-21" aria-hidden="true" tabindex="-1"></a><span class="st">JOIN</span></span>
+<span id="cb10-22"><a href="#cb10-22" aria-hidden="true" tabindex="-1"></a><span class="st">    batting b ON b.playerID = cp.playerID</span></span>
+<span id="cb10-23"><a href="#cb10-23" aria-hidden="true" tabindex="-1"></a><span class="st">JOIN</span></span>
+<span id="cb10-24"><a href="#cb10-24" aria-hidden="true" tabindex="-1"></a><span class="st">    teams t ON t.teamID = b.teamID</span></span>
+<span id="cb10-25"><a href="#cb10-25" aria-hidden="true" tabindex="-1"></a><span class="st">WHERE</span></span>
+<span id="cb10-26"><a href="#cb10-26" aria-hidden="true" tabindex="-1"></a><span class="st">    s.schoolID IN (&#39;weberst&#39;, &#39;sfaustin&#39;)  -- Use IN to specify multiple schools</span></span>
+<span id="cb10-27"><a href="#cb10-27" aria-hidden="true" tabindex="-1"></a><span class="st">ORDER BY</span></span>
+<span id="cb10-28"><a href="#cb10-28" aria-hidden="true" tabindex="-1"></a><span class="st">    t.yearID ASC;  -- Order by yearID in ascending order</span></span>
+<span id="cb10-29"><a href="#cb10-29" aria-hidden="true" tabindex="-1"></a><span class="st">&quot;&quot;&quot;</span></span>
+<span id="cb10-30"><a href="#cb10-30" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-31"><a href="#cb10-31" aria-hidden="true" tabindex="-1"></a>df <span class="op">=</span> pd.read_sql_query(query, con)</span>
+<span id="cb10-32"><a href="#cb10-32" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-33"><a href="#cb10-33" aria-hidden="true" tabindex="-1"></a><span class="co"># Group the data by school and calculate linear regression for each school</span></span>
+<span id="cb10-34"><a href="#cb10-34" aria-hidden="true" tabindex="-1"></a>trendlines <span class="op">=</span> {}</span>
+<span id="cb10-35"><a href="#cb10-35" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span> school, data <span class="kw">in</span> df.groupby(<span class="st">&#39;schoolID&#39;</span>):</span>
+<span id="cb10-36"><a href="#cb10-36" aria-hidden="true" tabindex="-1"></a>    X <span class="op">=</span> data[<span class="st">&#39;yearID&#39;</span>].values.reshape(<span class="op">-</span><span class="dv">1</span>, <span class="dv">1</span>)</span>
+<span id="cb10-37"><a href="#cb10-37" aria-hidden="true" tabindex="-1"></a>    y <span class="op">=</span> data[<span class="st">&#39;wins&#39;</span>].values.reshape(<span class="op">-</span><span class="dv">1</span>, <span class="dv">1</span>)</span>
+<span id="cb10-38"><a href="#cb10-38" aria-hidden="true" tabindex="-1"></a>    model <span class="op">=</span> LinearRegression()</span>
+<span id="cb10-39"><a href="#cb10-39" aria-hidden="true" tabindex="-1"></a>    model.fit(X, y)</span>
+<span id="cb10-40"><a href="#cb10-40" aria-hidden="true" tabindex="-1"></a>    trendlines[school] <span class="op">=</span> model.predict(X)</span>
+<span id="cb10-41"><a href="#cb10-41" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-42"><a href="#cb10-42" aria-hidden="true" tabindex="-1"></a><span class="co"># Create a line plot using Plotly Express</span></span>
+<span id="cb10-43"><a href="#cb10-43" aria-hidden="true" tabindex="-1"></a>fig <span class="op">=</span> px.line(df, x<span class="op">=</span><span class="st">&#39;yearID&#39;</span>, y<span class="op">=</span><span class="st">&#39;wins&#39;</span>, color<span class="op">=</span><span class="st">&#39;schoolID&#39;</span>,</span>
+<span id="cb10-44"><a href="#cb10-44" aria-hidden="true" tabindex="-1"></a>              title<span class="op">=</span><span class="st">&#39;Wins Over Years for Weber State and Stephen F. Austin&#39;</span>,</span>
+<span id="cb10-45"><a href="#cb10-45" aria-hidden="true" tabindex="-1"></a>              color_discrete_map <span class="op">=</span> {<span class="st">&#39;weberst&#39;</span>: <span class="st">&#39;purple&#39;</span>, <span class="st">&#39;sfaustin&#39;</span>: <span class="st">&#39;red&#39;</span>},  labels<span class="op">=</span>{<span class="st">&#39;yearID&#39;</span>: <span class="st">&#39;Year&#39;</span>, <span class="st">&#39;wins&#39;</span>: <span class="st">&#39;Wins&#39;</span>, <span class="st">&#39;schoolID&#39;</span>: <span class="st">&#39;Schools&#39;</span>})</span>
+<span id="cb10-46"><a href="#cb10-46" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-47"><a href="#cb10-47" aria-hidden="true" tabindex="-1"></a><span class="co"># Define colors for trend lines</span></span>
+<span id="cb10-48"><a href="#cb10-48" aria-hidden="true" tabindex="-1"></a>trendline_colors <span class="op">=</span> {<span class="st">&#39;weberst&#39;</span>: <span class="st">&#39;blue&#39;</span>, <span class="st">&#39;sfaustin&#39;</span>: <span class="st">&#39;green&#39;</span>}</span>
+<span id="cb10-49"><a href="#cb10-49" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-50"><a href="#cb10-50" aria-hidden="true" tabindex="-1"></a><span class="co"># Add trend lines to the plot with different colors</span></span>
+<span id="cb10-51"><a href="#cb10-51" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span> school, trendline <span class="kw">in</span> trendlines.items():</span>
+<span id="cb10-52"><a href="#cb10-52" aria-hidden="true" tabindex="-1"></a>    fig.add_scatter(x<span class="op">=</span>df[df[<span class="st">&#39;schoolID&#39;</span>] <span class="op">==</span> school][<span class="st">&#39;yearID&#39;</span>], y<span class="op">=</span>trendline.flatten(), mode<span class="op">=</span><span class="st">&#39;lines&#39;</span>,</span>
+<span id="cb10-53"><a href="#cb10-53" aria-hidden="true" tabindex="-1"></a>                    name<span class="op">=</span><span class="ss">f&#39;Trendline (</span><span class="sc">{</span>school<span class="sc">}</span><span class="ss">)&#39;</span>, line<span class="op">=</span><span class="bu">dict</span>(color<span class="op">=</span>trendline_colors[school], width<span class="op">=</span><span class="dv">3</span>))</span>
+<span id="cb10-54"><a href="#cb10-54" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-55"><a href="#cb10-55" aria-hidden="true" tabindex="-1"></a><span class="co"># Update the opacity of the &quot;normal&quot; lines</span></span>
+<span id="cb10-56"><a href="#cb10-56" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span> trace <span class="kw">in</span> fig.data:</span>
+<span id="cb10-57"><a href="#cb10-57" aria-hidden="true" tabindex="-1"></a>    <span class="cf">if</span> <span class="st">&#39;Trendline&#39;</span> <span class="kw">not</span> <span class="kw">in</span> trace[<span class="st">&#39;name&#39;</span>]:</span>
+<span id="cb10-58"><a href="#cb10-58" aria-hidden="true" tabindex="-1"></a>        trace[<span class="st">&#39;opacity&#39;</span>] <span class="op">=</span> <span class="fl">0.5</span></span>
+<span id="cb10-59"><a href="#cb10-59" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-60"><a href="#cb10-60" aria-hidden="true" tabindex="-1"></a><span class="co"># Define custom legend labels</span></span>
+<span id="cb10-61"><a href="#cb10-61" aria-hidden="true" tabindex="-1"></a>legend_labels <span class="op">=</span> {</span>
+<span id="cb10-62"><a href="#cb10-62" aria-hidden="true" tabindex="-1"></a>    <span class="st">&#39;weberst&#39;</span>: <span class="st">&#39;Weber State&#39;</span>,</span>
+<span id="cb10-63"><a href="#cb10-63" aria-hidden="true" tabindex="-1"></a>    <span class="st">&#39;sfaustin&#39;</span>: <span class="st">&#39;Stephen F. Austin&#39;</span>,</span>
+<span id="cb10-64"><a href="#cb10-64" aria-hidden="true" tabindex="-1"></a>}</span>
+<span id="cb10-65"><a href="#cb10-65" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-66"><a href="#cb10-66" aria-hidden="true" tabindex="-1"></a><span class="co"># Update the legend labels for trendlines</span></span>
+<span id="cb10-67"><a href="#cb10-67" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span> trace <span class="kw">in</span> fig.data:</span>
+<span id="cb10-68"><a href="#cb10-68" aria-hidden="true" tabindex="-1"></a>    <span class="cf">if</span> <span class="st">&#39;Trendline&#39;</span> <span class="kw">in</span> trace[<span class="st">&#39;name&#39;</span>]:</span>
+<span id="cb10-69"><a href="#cb10-69" aria-hidden="true" tabindex="-1"></a>        <span class="co"># Extract the school name from the trace name</span></span>
+<span id="cb10-70"><a href="#cb10-70" aria-hidden="true" tabindex="-1"></a>        school_start_idx <span class="op">=</span> trace[<span class="st">&#39;name&#39;</span>].find(<span class="st">&#39;(&#39;</span>) <span class="op">+</span> <span class="dv">1</span></span>
+<span id="cb10-71"><a href="#cb10-71" aria-hidden="true" tabindex="-1"></a>        school_end_idx <span class="op">=</span> trace[<span class="st">&#39;name&#39;</span>].find(<span class="st">&#39;)&#39;</span>)</span>
+<span id="cb10-72"><a href="#cb10-72" aria-hidden="true" tabindex="-1"></a>        school <span class="op">=</span> trace[<span class="st">&#39;name&#39;</span>][school_start_idx:school_end_idx].lower()</span>
+<span id="cb10-73"><a href="#cb10-73" aria-hidden="true" tabindex="-1"></a>        trace[<span class="st">&#39;legendgroup&#39;</span>] <span class="op">=</span> <span class="ss">f&#39;</span><span class="sc">{</span>school<span class="sc">}</span><span class="ss">_trendline&#39;</span></span>
+<span id="cb10-74"><a href="#cb10-74" aria-hidden="true" tabindex="-1"></a>        trace[<span class="st">&#39;name&#39;</span>] <span class="op">=</span> <span class="ss">f&#39;</span><span class="sc">{</span>legend_labels<span class="sc">.</span>get(school, school)<span class="sc">}</span><span class="ss"> (Trendline)&#39;</span></span>
+<span id="cb10-75"><a href="#cb10-75" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-76"><a href="#cb10-76" aria-hidden="true" tabindex="-1"></a><span class="co"># Update the legend labels for normal lines</span></span>
+<span id="cb10-77"><a href="#cb10-77" aria-hidden="true" tabindex="-1"></a><span class="cf">for</span> trace <span class="kw">in</span> fig.data:</span>
+<span id="cb10-78"><a href="#cb10-78" aria-hidden="true" tabindex="-1"></a>    <span class="cf">if</span> <span class="st">&#39;Trendline&#39;</span> <span class="kw">not</span> <span class="kw">in</span> trace[<span class="st">&#39;name&#39;</span>]:</span>
+<span id="cb10-79"><a href="#cb10-79" aria-hidden="true" tabindex="-1"></a>        school <span class="op">=</span> trace[<span class="st">&#39;name&#39;</span>].split()[<span class="dv">0</span>].lower()</span>
+<span id="cb10-80"><a href="#cb10-80" aria-hidden="true" tabindex="-1"></a>        trace[<span class="st">&#39;legendgroup&#39;</span>] <span class="op">=</span> school</span>
+<span id="cb10-81"><a href="#cb10-81" aria-hidden="true" tabindex="-1"></a>        trace[<span class="st">&#39;name&#39;</span>] <span class="op">=</span> legend_labels.get(school, school)</span>
+<span id="cb10-82"><a href="#cb10-82" aria-hidden="true" tabindex="-1"></a></span>
+<span id="cb10-83"><a href="#cb10-83" aria-hidden="true" tabindex="-1"></a>fig.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</details>
+<div class="cell-output cell-output-display">
+<div>                            <div id="456a5d1c-cd75-4b6a-a083-fddf8aa4f666" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("456a5d1c-cd75-4b6a-a083-fddf8aa4f666")) {                    Plotly.newPlot(                        "456a5d1c-cd75-4b6a-a083-fddf8aa4f666",                        [{"hovertemplate":"Schools=sfaustin\u003cbr\u003eYear=%{x}\u003cbr\u003eWins=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"sfaustin","line":{"color":"red","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Stephen F. Austin","orientation":"v","showlegend":true,"x":[1892,1892,1892,1892,1893,1893,1893,1893,1894,1894,1894,1894,1895,1895,1895,1895,1896,1896,1896,1896,1897,1897,1897,1897,1898,1898,1898,1898,1899,1899,1899,1899,1900,1900,1900,1900,1901,1901,1901,1901,1902,1902,1902,1902,1903,1903,1903,1903,1904,1904,1904,1904,1905,1905,1905,1905,1906,1906,1906,1906,1907,1907,1907,1907,1908,1908,1908,1908,1909,1909,1909,1909,1910,1910,1910,1910,1911,1911,1911,1911,1912,1912,1912,1912,1913,1913,1913,1913,1914,1914,1914,1914,1915,1915,1915,1915,1916,1916,1916,1916,1917,1917,1917,1917,1918,1918,1918,1918,1919,1919,1919,1919,1920,1920,1920,1920,1921,1921,1921,1921,1922,1922,1922,1922,1923,1923,1923,1923,1924,1924,1924,1924,1925,1925,1925,1925,1926,1926,1926,1926,1927,1927,1927,1927,1928,1928,1928,1928,1929,1929,1929,1929,1930,1930,1930,1930,1931,1931,1931,1931,1932,1932,1932,1932,1933,1933,1933,1933,1934,1934,1934,1934,1935,1935,1935,1935,1936,1936,1936,1936,1937,1937,1937,1937,1938,1938,1938,1938,1939,1939,1939,1939,1940,1940,1940,1940,1941,1941,1941,1941,1942,1942,1942,1942,1943,1943,1943,1943,1944,1944,1944,1944,1945,1945,1945,1945,1946,1946,1946,1946,1947,1947,1947,1947,1948,1948,1948,1948,1949,1949,1949,1949,1950,1950,1950,1950,1951,1951,1951,1951,1952,1952,1952,1952,1953,1953,1953,1953,1954,1954,1954,1954,1955,1955,1955,1955,1956,1956,1956,1956,1957,1957,1957,1957,1958,1958,1958,1958,1959,1959,1959,1959,1960,1960,1960,1960,1961,1961,1961,1961,1962,1962,1962,1962,1963,1963,1963,1963,1964,1964,1964,1964,1965,1965,1965,1965,1966,1966,1966,1966,1967,1967,1967,1967,1968,1968,1968,1968,1969,1969,1969,1969,1970,1970,1970,1970,1971,1971,1971,1971,1972,1972,1972,1972,1973,1973,1973,1973,1974,1974,1974,1974,1975,1975,1975,1975,1976,1976,1976,1976,1977,1977,1977,1977,1978,1978,1978,1978,1979,1979,1979,1979,1980,1980,1980,1980,1981,1981,1981,1981,1982,1982,1982,1982,1983,1983,1983,1983,1984,1984,1984,1984,1985,1985,1985,1985,1986,1986,1986,1986,1987,1987,1987,1987,1988,1988,1988,1988,1989,1989,1989,1989,1990,1990,1990,1990,1991,1991,1991,1991,1992,1992,1992,1992,1993,1993,1993,1993,1994,1994,1994,1994,1995,1995,1995,1995,1996,1996,1996,1996,1997,1997,1997,1997,1998,1998,1998,1998,1999,1999,1999,1999,2000,2000,2000,2000,2001,2001,2001,2001,2002,2002,2002,2002,2003,2003,2003,2003,2004,2004,2004,2004,2005,2005,2005,2005,2006,2006,2006,2006,2007,2007,2007,2007,2008,2008,2008,2008,2009,2009,2009,2009,2010,2010,2010,2010,2011,2011,2011,2011,2012,2012,2012,2012,2013,2013,2013,2013,2014,2014,2014,2014,2015,2015,2015,2015,2016,2016,2016,2016,2017,2017,2017,2017,2018,2018,2018,2018,2019,2019,2019,2019],"xaxis":"x","y":[56,56,56,56,57,57,57,57,56,56,56,56,39,39,39,39,40,40,40,40,29,29,29,29,39,39,39,39,84,84,84,84,65,65,65,65,76,76,76,76,56,56,56,56,43,43,43,43,75,75,75,75,58,58,58,58,52,52,52,52,52,52,52,52,49,49,49,49,54,54,54,54,63,63,63,63,75,75,75,75,63,63,63,63,51,51,51,51,81,81,81,81,72,72,72,72,60,60,60,60,82,82,82,82,51,51,51,51,54,54,54,54,75,75,75,75,87,87,87,87,85,85,85,85,79,79,79,79,65,65,65,65,77,77,77,77,89,89,89,89,92,92,92,92,95,95,95,95,78,78,78,78,92,92,92,92,101,101,101,101,72,72,72,72,82,82,82,82,95,95,95,95,96,96,96,96,87,87,87,87,81,81,81,81,71,71,71,71,92,92,92,92,84,84,84,84,97,97,97,97,106,106,106,106,105,105,105,105,105,105,105,105,95,95,95,95,98,98,98,98,89,89,89,89,85,85,85,85,96,96,96,96,78,78,78,78,81,81,81,81,88,88,88,88,83,83,83,83,72,72,72,72,68,68,68,68,76,76,76,76,87,87,87,87,72,72,72,72,71,71,71,71,86,86,86,86,80,80,80,80,84,84,84,84,93,93,93,93,93,93,93,93,80,80,80,80,83,83,83,83,101,101,101,101,97,97,97,97,87,87,87,87,76,76,76,76,90,90,90,90,75,75,75,75,81,81,81,81,86,86,86,86,82,82,82,82,72,72,72,72,83,83,83,83,69,69,69,69,86,86,86,86,74,74,74,74,59,59,59,59,92,92,92,92,79,79,79,79,84,84,84,84,101,101,101,101,79,79,79,79,95,95,95,95,76,76,76,76,86,86,86,86,70,70,70,70,84,84,84,84,83,83,83,83,87,87,87,87,53,53,53,53,62,62,62,62,88,88,88,88,73,73,73,73,83,83,83,83,75,75,75,75,95,95,95,95,93,93,93,93,97,97,97,97,85,85,85,85,105,105,105,105,100,100,100,100,83,83,83,83,78,78,78,78,86,86,86,86,91,91,91,91,86,86,86,86,90,90,90,90,88,88,88,88,97,97,97,97,90,90,90,90,100,100,100,100,86,86,86,86,83,83,83,83,88,88,88,88,91,91,91,91],"yaxis":"y","type":"scatter","opacity":0.5},{"hovertemplate":"Schools=weberst\u003cbr\u003eYear=%{x}\u003cbr\u003eWins=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"weberst","line":{"color":"purple","dash":"solid"},"marker":{"symbol":"circle"},"mode":"lines","name":"Weber State","orientation":"v","showlegend":true,"x":[1901,1901,1902,1902,1903,1903,1904,1904,1905,1905,1906,1906,1907,1907,1908,1908,1909,1909,1910,1910,1911,1911,1912,1912,1913,1913,1914,1914,1915,1915,1916,1916,1917,1917,1918,1918,1919,1919,1920,1920,1921,1921,1922,1922,1923,1923,1924,1924,1925,1925,1926,1926,1927,1927,1928,1928,1929,1929,1930,1930,1931,1931,1932,1932,1933,1933,1934,1934,1935,1935,1936,1936,1937,1937,1938,1938,1939,1939,1940,1940,1941,1941,1942,1942,1943,1943,1944,1944,1945,1945,1946,1946,1947,1947,1948,1948,1949,1949,1950,1950,1951,1951,1952,1952,1953,1953,1954,1954,1955,1955,1956,1956,1957,1957,1958,1958,1959,1959,1960,1960,1961,1961,1962,1962,1963,1963,1964,1964,1965,1965,1966,1966,1967,1967,1968,1968,1969,1969,1970,1970,1971,1971,1972,1972,1973,1973,1974,1974,1975,1975,1976,1976,1977,1977,1978,1978,1979,1979,1980,1980,1981,1981,1982,1982,1983,1983,1984,1984,1985,1985,1986,1986,1987,1987,1988,1988,1989,1989,1990,1990,1991,1991,1992,1992,1993,1993,1994,1994,1995,1995,1996,1996,1997,1997,1998,1998,1999,1999,2000,2000,2001,2001,2002,2002,2003,2003,2004,2004,2005,2005,2006,2006,2007,2007,2008,2008,2009,2009,2010,2010,2011,2011,2012,2012,2013,2013,2014,2014,2015,2015,2016,2016,2017,2017,2018,2018,2019,2019],"xaxis":"x","y":[79,79,77,77,91,91,95,95,78,78,49,49,59,59,75,75,88,88,81,81,78,78,105,105,79,79,91,91,101,101,91,91,90,90,75,75,66,66,72,72,75,75,61,61,61,61,67,67,47,47,46,46,51,51,57,57,58,58,52,52,62,62,43,43,63,63,76,76,78,78,74,74,80,80,88,88,89,89,82,82,84,84,93,93,68,68,77,77,71,71,104,104,83,83,96,96,96,96,94,94,87,87,76,76,84,84,69,69,84,84,84,84,82,82,79,79,75,75,65,65,76,76,76,76,76,76,72,72,62,62,72,72,92,92,86,86,87,87,87,87,85,85,85,85,89,89,84,84,95,95,83,83,97,97,99,99,91,91,83,83,59,59,89,89,78,78,86,86,81,81,95,95,78,78,89,89,83,83,88,88,84,84,73,73,80,80,54,54,86,86,85,85,78,78,92,92,94,94,85,85,82,82,93,93,95,95,98,98,95,95,86,86,96,96,95,95,95,95,89,89,90,90,69,69,97,97,71,71,78,78,93,93,93,93,108,108,84,84],"yaxis":"y","type":"scatter","opacity":0.5},{"line":{"color":"green","width":3},"mode":"lines","name":"Stephen F. Austin (Trendline)","x":[1892,1892,1892,1892,1893,1893,1893,1893,1894,1894,1894,1894,1895,1895,1895,1895,1896,1896,1896,1896,1897,1897,1897,1897,1898,1898,1898,1898,1899,1899,1899,1899,1900,1900,1900,1900,1901,1901,1901,1901,1902,1902,1902,1902,1903,1903,1903,1903,1904,1904,1904,1904,1905,1905,1905,1905,1906,1906,1906,1906,1907,1907,1907,1907,1908,1908,1908,1908,1909,1909,1909,1909,1910,1910,1910,1910,1911,1911,1911,1911,1912,1912,1912,1912,1913,1913,1913,1913,1914,1914,1914,1914,1915,1915,1915,1915,1916,1916,1916,1916,1917,1917,1917,1917,1918,1918,1918,1918,1919,1919,1919,1919,1920,1920,1920,1920,1921,1921,1921,1921,1922,1922,1922,1922,1923,1923,1923,1923,1924,1924,1924,1924,1925,1925,1925,1925,1926,1926,1926,1926,1927,1927,1927,1927,1928,1928,1928,1928,1929,1929,1929,1929,1930,1930,1930,1930,1931,1931,1931,1931,1932,1932,1932,1932,1933,1933,1933,1933,1934,1934,1934,1934,1935,1935,1935,1935,1936,1936,1936,1936,1937,1937,1937,1937,1938,1938,1938,1938,1939,1939,1939,1939,1940,1940,1940,1940,1941,1941,1941,1941,1942,1942,1942,1942,1943,1943,1943,1943,1944,1944,1944,1944,1945,1945,1945,1945,1946,1946,1946,1946,1947,1947,1947,1947,1948,1948,1948,1948,1949,1949,1949,1949,1950,1950,1950,1950,1951,1951,1951,1951,1952,1952,1952,1952,1953,1953,1953,1953,1954,1954,1954,1954,1955,1955,1955,1955,1956,1956,1956,1956,1957,1957,1957,1957,1958,1958,1958,1958,1959,1959,1959,1959,1960,1960,1960,1960,1961,1961,1961,1961,1962,1962,1962,1962,1963,1963,1963,1963,1964,1964,1964,1964,1965,1965,1965,1965,1966,1966,1966,1966,1967,1967,1967,1967,1968,1968,1968,1968,1969,1969,1969,1969,1970,1970,1970,1970,1971,1971,1971,1971,1972,1972,1972,1972,1973,1973,1973,1973,1974,1974,1974,1974,1975,1975,1975,1975,1976,1976,1976,1976,1977,1977,1977,1977,1978,1978,1978,1978,1979,1979,1979,1979,1980,1980,1980,1980,1981,1981,1981,1981,1982,1982,1982,1982,1983,1983,1983,1983,1984,1984,1984,1984,1985,1985,1985,1985,1986,1986,1986,1986,1987,1987,1987,1987,1988,1988,1988,1988,1989,1989,1989,1989,1990,1990,1990,1990,1991,1991,1991,1991,1992,1992,1992,1992,1993,1993,1993,1993,1994,1994,1994,1994,1995,1995,1995,1995,1996,1996,1996,1996,1997,1997,1997,1997,1998,1998,1998,1998,1999,1999,1999,1999,2000,2000,2000,2000,2001,2001,2001,2001,2002,2002,2002,2002,2003,2003,2003,2003,2004,2004,2004,2004,2005,2005,2005,2005,2006,2006,2006,2006,2007,2007,2007,2007,2008,2008,2008,2008,2009,2009,2009,2009,2010,2010,2010,2010,2011,2011,2011,2011,2012,2012,2012,2012,2013,2013,2013,2013,2014,2014,2014,2014,2015,2015,2015,2015,2016,2016,2016,2016,2017,2017,2017,2017,2018,2018,2018,2018,2019,2019,2019,2019],"y":[65.1021075581395,65.1021075581395,65.1021075581395,65.1021075581395,65.3241708249405,65.3241708249405,65.3241708249405,65.3241708249405,65.54623409174144,65.54623409174144,65.54623409174144,65.54623409174144,65.76829735854238,65.76829735854238,65.76829735854238,65.76829735854238,65.99036062534333,65.99036062534333,65.99036062534333,65.99036062534333,66.21242389214427,66.21242389214427,66.21242389214427,66.21242389214427,66.43448715894522,66.43448715894522,66.43448715894522,66.43448715894522,66.65655042574616,66.65655042574616,66.65655042574616,66.65655042574616,66.87861369254716,66.87861369254716,66.87861369254716,66.87861369254716,67.1006769593481,67.1006769593481,67.1006769593481,67.1006769593481,67.32274022614905,67.32274022614905,67.32274022614905,67.32274022614905,67.54480349295,67.54480349295,67.54480349295,67.54480349295,67.76686675975094,67.76686675975094,67.76686675975094,67.76686675975094,67.98893002655188,67.98893002655188,67.98893002655188,67.98893002655188,68.21099329335283,68.21099329335283,68.21099329335283,68.21099329335283,68.43305656015383,68.43305656015383,68.43305656015383,68.43305656015383,68.65511982695477,68.65511982695477,68.65511982695477,68.65511982695477,68.87718309375572,68.87718309375572,68.87718309375572,68.87718309375572,69.09924636055666,69.09924636055666,69.09924636055666,69.09924636055666,69.3213096273576,69.3213096273576,69.3213096273576,69.3213096273576,69.54337289415855,69.54337289415855,69.54337289415855,69.54337289415855,69.7654361609595,69.7654361609595,69.7654361609595,69.7654361609595,69.98749942776044,69.98749942776044,69.98749942776044,69.98749942776044,70.20956269456144,70.20956269456144,70.20956269456144,70.20956269456144,70.43162596136239,70.43162596136239,70.43162596136239,70.43162596136239,70.65368922816333,70.65368922816333,70.65368922816333,70.65368922816333,70.87575249496427,70.87575249496427,70.87575249496427,70.87575249496427,71.09781576176522,71.09781576176522,71.09781576176522,71.09781576176522,71.31987902856616,71.31987902856616,71.31987902856616,71.31987902856616,71.54194229536711,71.54194229536711,71.54194229536711,71.54194229536711,71.76400556216811,71.76400556216811,71.76400556216811,71.76400556216811,71.98606882896905,71.98606882896905,71.98606882896905,71.98606882896905,72.20813209577,72.20813209577,72.20813209577,72.20813209577,72.43019536257094,72.43019536257094,72.43019536257094,72.43019536257094,72.65225862937189,72.65225862937189,72.65225862937189,72.65225862937189,72.87432189617283,72.87432189617283,72.87432189617283,72.87432189617283,73.09638516297377,73.09638516297377,73.09638516297377,73.09638516297377,73.31844842977478,73.31844842977478,73.31844842977478,73.31844842977478,73.54051169657572,73.54051169657572,73.54051169657572,73.54051169657572,73.76257496337666,73.76257496337666,73.76257496337666,73.76257496337666,73.98463823017761,73.98463823017761,73.98463823017761,73.98463823017761,74.20670149697855,74.20670149697855,74.20670149697855,74.20670149697855,74.4287647637795,74.4287647637795,74.4287647637795,74.4287647637795,74.65082803058044,74.65082803058044,74.65082803058044,74.65082803058044,74.87289129738144,74.87289129738144,74.87289129738144,74.87289129738144,75.09495456418239,75.09495456418239,75.09495456418239,75.09495456418239,75.31701783098333,75.31701783098333,75.31701783098333,75.31701783098333,75.53908109778428,75.53908109778428,75.53908109778428,75.53908109778428,75.76114436458522,75.76114436458522,75.76114436458522,75.76114436458522,75.98320763138616,75.98320763138616,75.98320763138616,75.98320763138616,76.20527089818711,76.20527089818711,76.20527089818711,76.20527089818711,76.42733416498805,76.42733416498805,76.42733416498805,76.42733416498805,76.64939743178905,76.64939743178905,76.64939743178905,76.64939743178905,76.87146069859,76.87146069859,76.87146069859,76.87146069859,77.09352396539094,77.09352396539094,77.09352396539094,77.09352396539094,77.31558723219189,77.31558723219189,77.31558723219189,77.31558723219189,77.53765049899283,77.53765049899283,77.53765049899283,77.53765049899283,77.75971376579378,77.75971376579378,77.75971376579378,77.75971376579378,77.98177703259472,77.98177703259472,77.98177703259472,77.98177703259472,78.20384029939572,78.20384029939572,78.20384029939572,78.20384029939572,78.42590356619667,78.42590356619667,78.42590356619667,78.42590356619667,78.64796683299761,78.64796683299761,78.64796683299761,78.64796683299761,78.87003009979856,78.87003009979856,78.87003009979856,78.87003009979856,79.0920933665995,79.0920933665995,79.0920933665995,79.0920933665995,79.31415663340044,79.31415663340044,79.31415663340044,79.31415663340044,79.53621990020139,79.53621990020139,79.53621990020139,79.53621990020139,79.75828316700239,79.75828316700239,79.75828316700239,79.75828316700239,79.98034643380333,79.98034643380333,79.98034643380333,79.98034643380333,80.20240970060428,80.20240970060428,80.20240970060428,80.20240970060428,80.42447296740522,80.42447296740522,80.42447296740522,80.42447296740522,80.64653623420617,80.64653623420617,80.64653623420617,80.64653623420617,80.86859950100711,80.86859950100711,80.86859950100711,80.86859950100711,81.09066276780806,81.09066276780806,81.09066276780806,81.09066276780806,81.31272603460906,81.31272603460906,81.31272603460906,81.31272603460906,81.53478930141,81.53478930141,81.53478930141,81.53478930141,81.75685256821095,81.75685256821095,81.75685256821095,81.75685256821095,81.97891583501189,81.97891583501189,81.97891583501189,81.97891583501189,82.20097910181283,82.20097910181283,82.20097910181283,82.20097910181283,82.42304236861378,82.42304236861378,82.42304236861378,82.42304236861378,82.64510563541472,82.64510563541472,82.64510563541472,82.64510563541472,82.86716890221567,82.86716890221567,82.86716890221567,82.86716890221567,83.08923216901667,83.08923216901667,83.08923216901667,83.08923216901667,83.31129543581761,83.31129543581761,83.31129543581761,83.31129543581761,83.53335870261856,83.53335870261856,83.53335870261856,83.53335870261856,83.7554219694195,83.7554219694195,83.7554219694195,83.7554219694195,83.97748523622045,83.97748523622045,83.97748523622045,83.97748523622045,84.19954850302139,84.19954850302139,84.19954850302139,84.19954850302139,84.42161176982233,84.42161176982233,84.42161176982233,84.42161176982233,84.64367503662334,84.64367503662334,84.64367503662334,84.64367503662334,84.86573830342428,84.86573830342428,84.86573830342428,84.86573830342428,85.08780157022522,85.08780157022522,85.08780157022522,85.08780157022522,85.30986483702617,85.30986483702617,85.30986483702617,85.30986483702617,85.53192810382711,85.53192810382711,85.53192810382711,85.53192810382711,85.75399137062806,85.75399137062806,85.75399137062806,85.75399137062806,85.976054637429,85.976054637429,85.976054637429,85.976054637429,86.19811790423,86.19811790423,86.19811790423,86.19811790423,86.42018117103095,86.42018117103095,86.42018117103095,86.42018117103095,86.64224443783189,86.64224443783189,86.64224443783189,86.64224443783189,86.86430770463284,86.86430770463284,86.86430770463284,86.86430770463284,87.08637097143378,87.08637097143378,87.08637097143378,87.08637097143378,87.30843423823472,87.30843423823472,87.30843423823472,87.30843423823472,87.53049750503567,87.53049750503567,87.53049750503567,87.53049750503567,87.75256077183667,87.75256077183667,87.75256077183667,87.75256077183667,87.97462403863761,87.97462403863761,87.97462403863761,87.97462403863761,88.19668730543856,88.19668730543856,88.19668730543856,88.19668730543856,88.4187505722395,88.4187505722395,88.4187505722395,88.4187505722395,88.64081383904045,88.64081383904045,88.64081383904045,88.64081383904045,88.86287710584139,88.86287710584139,88.86287710584139,88.86287710584139,89.08494037264234,89.08494037264234,89.08494037264234,89.08494037264234,89.30700363944334,89.30700363944334,89.30700363944334,89.30700363944334,89.52906690624428,89.52906690624428,89.52906690624428,89.52906690624428,89.75113017304523,89.75113017304523,89.75113017304523,89.75113017304523,89.97319343984617,89.97319343984617,89.97319343984617,89.97319343984617,90.19525670664711,90.19525670664711,90.19525670664711,90.19525670664711,90.41731997344806,90.41731997344806,90.41731997344806,90.41731997344806,90.639383240249,90.639383240249,90.639383240249,90.639383240249,90.86144650704995,90.86144650704995,90.86144650704995,90.86144650704995,91.08350977385095,91.08350977385095,91.08350977385095,91.08350977385095,91.3055730406519,91.3055730406519,91.3055730406519,91.3055730406519,91.52763630745284,91.52763630745284,91.52763630745284,91.52763630745284,91.74969957425378,91.74969957425378,91.74969957425378,91.74969957425378,91.97176284105473,91.97176284105473,91.97176284105473,91.97176284105473,92.19382610785567,92.19382610785567,92.19382610785567,92.19382610785567,92.41588937465662,92.41588937465662,92.41588937465662,92.41588937465662,92.63795264145762,92.63795264145762,92.63795264145762,92.63795264145762,92.86001590825856,92.86001590825856,92.86001590825856,92.86001590825856,93.0820791750595,93.0820791750595,93.0820791750595,93.0820791750595,93.30414244186045,93.30414244186045,93.30414244186045,93.30414244186045],"type":"scatter","legendgroup":"sfaustin_trendline"},{"line":{"color":"blue","width":3},"mode":"lines","name":"Weber State (Trendline)","x":[1901,1901,1902,1902,1903,1903,1904,1904,1905,1905,1906,1906,1907,1907,1908,1908,1909,1909,1910,1910,1911,1911,1912,1912,1913,1913,1914,1914,1915,1915,1916,1916,1917,1917,1918,1918,1919,1919,1920,1920,1921,1921,1922,1922,1923,1923,1924,1924,1925,1925,1926,1926,1927,1927,1928,1928,1929,1929,1930,1930,1931,1931,1932,1932,1933,1933,1934,1934,1935,1935,1936,1936,1937,1937,1938,1938,1939,1939,1940,1940,1941,1941,1942,1942,1943,1943,1944,1944,1945,1945,1946,1946,1947,1947,1948,1948,1949,1949,1950,1950,1951,1951,1952,1952,1953,1953,1954,1954,1955,1955,1956,1956,1957,1957,1958,1958,1959,1959,1960,1960,1961,1961,1962,1962,1963,1963,1964,1964,1965,1965,1966,1966,1967,1967,1968,1968,1969,1969,1970,1970,1971,1971,1972,1972,1973,1973,1974,1974,1975,1975,1976,1976,1977,1977,1978,1978,1979,1979,1980,1980,1981,1981,1982,1982,1983,1983,1984,1984,1985,1985,1986,1986,1987,1987,1988,1988,1989,1989,1990,1990,1991,1991,1992,1992,1993,1993,1994,1994,1995,1995,1996,1996,1997,1997,1998,1998,1999,1999,2000,2000,2001,2001,2002,2002,2003,2003,2004,2004,2005,2005,2006,2006,2007,2007,2008,2008,2009,2009,2010,2010,2011,2011,2012,2012,2013,2013,2014,2014,2015,2015,2016,2016,2017,2017,2018,2018,2019,2019],"y":[72.30882352941171,72.30882352941171,72.45086170061239,72.45086170061239,72.59289987181307,72.59289987181307,72.73493804301381,72.73493804301381,72.8769762142145,72.8769762142145,73.01901438541518,73.01901438541518,73.16105255661586,73.16105255661586,73.30309072781654,73.30309072781654,73.44512889901722,73.44512889901722,73.5871670702179,73.5871670702179,73.72920524141858,73.72920524141858,73.87124341261926,73.87124341261926,74.01328158381995,74.01328158381995,74.15531975502063,74.15531975502063,74.29735792622131,74.29735792622131,74.43939609742199,74.43939609742199,74.58143426862267,74.58143426862267,74.72347243982335,74.72347243982335,74.86551061102404,74.86551061102404,75.00754878222472,75.00754878222472,75.1495869534254,75.1495869534254,75.29162512462608,75.29162512462608,75.43366329582676,75.43366329582676,75.57570146702744,75.57570146702744,75.71773963822812,75.71773963822812,75.8597778094288,75.8597778094288,76.00181598062949,76.00181598062949,76.14385415183017,76.14385415183017,76.28589232303085,76.28589232303085,76.42793049423159,76.42793049423159,76.56996866543227,76.56996866543227,76.71200683663295,76.71200683663295,76.85404500783363,76.85404500783363,76.99608317903431,76.99608317903431,77.138121350235,77.138121350235,77.28015952143568,77.28015952143568,77.42219769263636,77.42219769263636,77.56423586383704,77.56423586383704,77.70627403503772,77.70627403503772,77.8483122062384,77.8483122062384,77.99035037743909,77.99035037743909,78.13238854863977,78.13238854863977,78.27442671984045,78.27442671984045,78.41646489104113,78.41646489104113,78.55850306224181,78.55850306224181,78.7005412334425,78.7005412334425,78.84257940464317,78.84257940464317,78.98461757584386,78.98461757584386,79.12665574704454,79.12665574704454,79.26869391824522,79.26869391824522,79.4107320894459,79.4107320894459,79.55277026064658,79.55277026064658,79.69480843184726,79.69480843184726,79.83684660304795,79.83684660304795,79.97888477424863,79.97888477424863,80.12092294544931,80.12092294544931,80.26296111665005,80.26296111665005,80.40499928785073,80.40499928785073,80.54703745905141,80.54703745905141,80.68907563025209,80.68907563025209,80.83111380145277,80.83111380145277,80.97315197265345,80.97315197265345,81.11519014385414,81.11519014385414,81.25722831505482,81.25722831505482,81.3992664862555,81.3992664862555,81.54130465745618,81.54130465745618,81.68334282865686,81.68334282865686,81.82538099985754,81.82538099985754,81.96741917105822,81.96741917105822,82.1094573422589,82.1094573422589,82.25149551345959,82.25149551345959,82.39353368466027,82.39353368466027,82.53557185586095,82.53557185586095,82.67761002706163,82.67761002706163,82.81964819826231,82.81964819826231,82.961686369463,82.961686369463,83.10372454066368,83.10372454066368,83.24576271186436,83.24576271186436,83.38780088306504,83.38780088306504,83.52983905426572,83.52983905426572,83.6718772254664,83.6718772254664,83.81391539666708,83.81391539666708,83.95595356786782,83.95595356786782,84.0979917390685,84.0979917390685,84.24002991026919,84.24002991026919,84.38206808146987,84.38206808146987,84.52410625267055,84.52410625267055,84.66614442387123,84.66614442387123,84.80818259507191,84.80818259507191,84.9502207662726,84.9502207662726,85.09225893747328,85.09225893747328,85.23429710867396,85.23429710867396,85.37633527987464,85.37633527987464,85.51837345107532,85.51837345107532,85.660411622276,85.660411622276,85.80244979347668,85.80244979347668,85.94448796467736,85.94448796467736,86.08652613587805,86.08652613587805,86.22856430707873,86.22856430707873,86.37060247827941,86.37060247827941,86.51264064948009,86.51264064948009,86.65467882068077,86.65467882068077,86.79671699188145,86.79671699188145,86.93875516308213,86.93875516308213,87.08079333428282,87.08079333428282,87.2228315054835,87.2228315054835,87.36486967668418,87.36486967668418,87.50690784788486,87.50690784788486,87.6489460190856,87.6489460190856,87.79098419028628,87.79098419028628,87.93302236148696,87.93302236148696,88.07506053268764,88.07506053268764,88.21709870388833,88.21709870388833,88.359136875089,88.359136875089,88.50117504628969,88.50117504628969,88.64321321749037,88.64321321749037,88.78525138869105,88.78525138869105,88.92728955989173,88.92728955989173,89.06932773109241,89.06932773109241],"type":"scatter","legendgroup":"weberst_trendline"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Year"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Wins"}},"legend":{"title":{"text":"Schools"},"tracegroupgap":0},"title":{"text":"Wins Over Years for Weber State and Stephen F. Austin"}},                        {"responsive": true}                    ).then(function(){
+                            
+var gd = document.getElementById('456a5d1c-cd75-4b6a-a083-fddf8aa4f666');
+var x = new MutationObserver(function (mutations, observer) {{
+        var display = window.getComputedStyle(gd).display;
+        if (!display || display === 'none') {{
+            console.log([gd, 'removed!']);
+            Plotly.purge(gd);
+            observer.disconnect();
+        }}
+}});
+
+// Listen for the removal of the full notebook cells
+var notebookContainer = gd.closest('#notebook-container');
+if (notebookContainer) {{
+    x.observe(notebookContainer, {childList: true});
+}}
+
+// Listen for the clearing of the current output cell
+var outputEl = gd.closest('.output');
+if (outputEl) {{
+    x.observe(outputEl, {childList: true});
+}}
+
+                        })                };                });            </script>        </div>
+</div>
+</div>
+<p><strong>Summary/Findings</strong></p>
+<ul>
+<li><p>Stephen F. Austin University is doing better overall as far as wins.</p></li>
+<li><p>These two schools are very well matched to each other, and win about the same amount.</p></li>
+<li><p>They both pass each other frequently in the number of wins year to year.</p></li>
+<li><p>Weber more frequently drops down and jumps in the number of wins.</p></li>
+<li><p>Stephen F. Austin has stayed relatively steady over the years.</p></li>
+<li><p>Both teams are improving although very slowly.</p></li>
+</ul>
 
 
 </section>
diff --git a/Projects/project4.html b/Projects/project4.html
index a969a35..b548e1f 100644
--- a/Projects/project4.html
+++ b/Projects/project4.html
@@ -4887,7 +4887,7 @@ <h2 class="anchored" data-anchor-id="elevator-pitch">Elevator pitch</h2>
 <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
 <p>Create 2-3 charts that evaluate potential relationships between the home variables and before1980. Explain what you learn from the charts that could help a machine learning algorithm.</p>
 <p>Only one of these charts was very useful at helping find if the house was built before 1980, and that was the ‘Year Built’ chart, witch makes seance. Some of the other charts could help but wouldn’t be that accrate.</p>
-<div id="fae4c42b" class="cell" data-execution_count="3">
+<div id="9c40d435" class="cell" data-execution_count="3">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co">#chart one sell price </span></span>
@@ -4911,9 +4911,9 @@ <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
 <span id="cb2-19"><a href="#cb2-19" aria-hidden="true" tabindex="-1"></a>fig.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="0b6d41ef-2f1c-4e74-b6aa-cb27b93d9e98" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("0b6d41ef-2f1c-4e74-b6aa-cb27b93d9e98")) {                    Plotly.newPlot(                        "0b6d41ef-2f1c-4e74-b6aa-cb27b93d9e98",                        [{"hovertemplate":"before1980=%{x}\u003cbr\u003eyrbuilt=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"","showlegend":false,"x":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,0,0,0,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,0,0,1,1,0,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,0,0,0,1,0,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,1,1,0,1,1,0,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,1,0,1,1,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,1,0,0,0,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,1,0,0,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,0,0,1,1,0,1,1,0,0,1,1,1,1,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,0,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,0,1,0,0,1,1,1,1,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,0,1,1,0,0,0,1,0,0,1,1,1,1,1,1,0,1,1,1,0,0,0,1,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,1,1,0,1,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,0,1,0,1,1,1,1,1,0,0,0,1,1,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,0,0,0,1,1,0,0,0,1,0,1,0,1,0,0,1,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,1,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,0,0,1,1,0,0,1,0,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,1,0,1,1,1,1,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,1,0,1,1,1,0,0,0,0,1,0,0,1,0,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,0,1,0,1,1,1,0,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,0,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,1,0,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,0,0,0,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"xaxis":"x","y":[2004,2005,2005,2005,2005,2005,2005,2005,2006,2006,2006,2005,2003,2005,2004,2005,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2005,2005,2005,2005,2005,2005,2005,2005,2005,2004,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2006,2006,2006,2005,2005,2005,2011,2006,2006,2006,2005,2005,2006,2009,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2010,2010,2011,2012,2012,2010,2010,2011,2011,2012,2011,2011,2012,2012,2012,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2012,2012,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2012,2012,2012,2011,2011,2011,2011,2012,2012,2012,2012,2012,2011,2011,2012,2012,2011,2011,2012,2012,2012,2011,2011,2012,2011,2011,2012,2011,2011,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2012,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2012,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2010,2010,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2010,2010,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2011,2011,2010,2011,2011,2010,2010,2011,2011,2012,2012,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2012,2010,2012,2011,2012,2011,2011,2010,2010,2011,2010,2011,2011,2011,2011,2012,2010,2010,2007,2006,2007,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2006,2006,2006,2005,2005,2008,2012,2012,2008,2011,2010,2012,2010,2012,2010,2010,2011,2011,2012,2006,2012,2012,2012,2006,2006,2007,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2012,2012,2012,2012,2012,2012,2012,2012,2013,2002,2002,2002,2003,2003,2003,2003,2003,2003,2003,2004,2006,2005,2005,2005,2004,2004,2004,2004,2004,2004,2004,2004,2003,2003,2002,2003,2003,2003,2003,2003,2002,2002,2005,2005,2005,2005,2006,2006,2006,2006,2006,2006,2006,2010,2010,2012,2005,2005,2005,2005,2005,2005,2006,2006,2006,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2006,2006,2006,2006,2006,2007,2007,2007,2006,2006,2006,2006,2008,2008,2009,2009,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2003,2003,2003,2003,2003,2004,2004,2003,2003,2004,2005,2005,2006,2006,2005,2005,2007,2007,2004,2004,2004,2004,2004,2004,2004,2005,2005,2005,2005,2005,2004,2004,2004,2004,2004,2004,2004,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2006,2006,2006,2006,2006,2006,2006,2006,2006,2007,2007,2007,2007,2007,2007,2006,2006,2006,2007,2006,2006,2006,2008,2006,2006,2006,2006,2006,2006,2006,2007,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2007,2007,2003,2003,2003,2003,2003,2003,2003,2009,2009,2010,2010,2004,2002,2004,2003,2003,2003,2003,2002,2003,2006,2007,2004,2004,2004,2004,2010,2010,2010,2011,2003,2006,2006,2006,2004,2003,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2004,2007,2007,2007,2010,2011,2011,2011,2010,2005,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2005,2005,2005,2005,2005,2011,2011,2005,2004,2004,2004,2004,2004,2011,2005,2005,2004,2004,2006,2004,2004,2006,2007,2011,2011,2012,2011,2011,2011,2005,2006,2005,2005,2005,2005,2004,2004,2007,2006,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2011,2010,2011,2010,2010,2010,2010,2010,2010,2011,2009,2009,2009,2011,2011,2011,2011,2011,2011,2011,2011,2011,2008,2010,2010,2010,2010,2010,2010,2011,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2011,2010,2010,2010,2010,2010,2010,2010,2010,2009,2001,2003,2001,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2003,2003,2003,2003,2002,2002,2003,2004,2006,2006,2006,2006,2006,2005,2005,2005,2005,2005,2005,2004,2006,2007,1999,1999,1999,1999,1999,1999,1999,1999,1999,1998,1998,1999,1999,1999,1999,1999,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2001,2000,2001,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,1971,1971,1971,1972,1972,1972,1972,1972,1972,1972,1973,1973,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1973,1973,1973,1973,1972,1973,1973,1973,1973,1973,1973,1973,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,2005,2004,1999,1999,1999,1999,1998,1999,1999,1999,1999,1998,1998,1999,1999,1998,1998,1998,1998,1998,1999,1999,1999,1999,1999,2000,2000,2000,2000,2000,1999,1999,1999,2000,2000,2000,2000,2000,1999,1999,1999,1999,2000,2000,2000,2000,2000,2000,1975,1975,1974,1973,1973,1973,1973,1973,1974,1974,1974,1974,1974,1974,1974,1976,1973,1973,1974,1973,1973,1973,1973,1973,1974,1974,1974,1980,1981,1981,1980,1981,1983,1983,1981,1981,1982,1982,1981,1981,1981,1979,1979,1979,1979,1976,1976,1976,1976,1976,1997,1996,1996,1995,1983,1993,1993,1975,1975,1983,1983,1983,1983,1998,1998,1999,1999,1999,1999,2000,1999,1999,2000,1999,2000,2000,1999,1999,1999,1999,2000,2000,1999,1986,2001,1986,1986,1986,1987,1984,1984,1984,1984,1984,1984,1984,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1994,1994,1994,1994,1995,1995,1995,1995,1995,1995,1997,1998,1997,1997,1998,1996,1997,1997,1996,1996,1996,1996,1996,1996,1995,1999,1999,1999,2000,1999,1999,1999,1983,1983,1983,1983,1982,1982,1982,1982,1982,1980,1980,1980,1983,1983,1984,1984,1987,1987,1986,1986,1986,1986,1986,1987,1987,1987,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1982,1982,1982,1981,1981,1997,1996,1996,1997,1998,1998,1998,1997,1996,1998,1996,1996,1987,1986,1986,1986,1985,1985,1984,1984,1984,1986,1984,1984,1985,1985,1985,1979,1979,1979,1979,1979,1979,1979,1980,1985,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1979,1979,1979,1979,1979,1979,1980,1979,1979,1979,1979,1979,1979,1984,1979,1982,1980,1980,1981,1982,1983,1982,1982,1982,1983,1983,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1983,1983,1983,2001,2001,2001,2000,2002,2002,2002,2002,2002,2002,2001,2001,2001,2001,2001,2001,2001,2001,2001,2000,2000,2000,2012,1987,1993,1986,1993,1986,1993,1986,1986,1986,1986,1985,1985,1985,1984,1984,1984,1984,1995,1995,1995,1995,1997,1995,1996,1996,1996,1996,1996,1996,1996,1999,1999,1999,2000,2000,2000,2005,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2010,2010,2010,2012,2008,2010,2010,2010,2010,2012,2012,2012,2012,2012,2012,2012,1987,1984,1984,1984,1983,1983,1983,1983,1984,1983,1983,1983,1983,1983,1984,1984,1984,1983,1983,1983,1984,2006,2006,2006,2006,2006,2006,2007,2007,2007,2007,2010,2010,2010,2007,2007,2007,2007,2006,2007,2007,2007,2008,2010,2010,2010,2007,2007,2007,2010,2010,2010,2010,1997,1984,1996,1996,1995,1995,1995,1995,1995,1996,1998,1996,1996,1997,1998,1998,1998,1997,1998,1998,1998,1998,2003,2002,2002,2002,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2004,2004,2004,2003,2003,2003,2003,1994,1994,1993,1993,1993,1993,1993,1994,1994,1994,1994,1994,1994,1994,1994,1994,1994,1994,1997,1997,1997,1997,1997,1998,1998,1998,1998,1998,1998,1999,1999,1999,1998,1998,1998,1999,1999,1999,1998,1998,1998,1998,1999,1999,1999,1999,1998,1999,1999,2002,2002,2003,2002,2002,2002,2002,2003,2003,2003,2001,2001,2002,2002,2002,2001,2001,1984,1984,1984,1984,1984,1986,1986,1985,1985,1985,1985,1985,1985,1985,1986,1986,1986,1986,1992,1991,1991,1992,1987,1992,1991,1991,1990,1990,1990,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1987,1994,1991,1992,2001,2001,2000,2000,2000,2000,2000,2000,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2001,2001,2001,2000,2000,2000,2000,2003,2003,2003,2002,2002,2003,2003,2003,2003,2003,2003,2003,2003,2003,1985,1986,1986,1986,1986,1985,1985,1985,1985,1985,1985,1999,1999,2000,2000,2002,2002,2001,2001,2001,2002,2002,2002,2001,2002,2001,2001,2001,2002,2002,2001,2001,2002,2001,2001,2001,2001,2001,2002,2002,2002,2002,2002,2002,2002,2002,1999,1997,2002,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2002,2000,2000,2000,2000,2000,2000,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2002,2001,2001,2001,2001,2001,2001,2001,2001,2001,2002,2002,2002,2002,2002,2002,1987,1987,1987,1987,1988,1992,1992,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1999,1999,1999,1999,1999,1999,2000,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2001,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,2001,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2003,2002,2002,2002,2002,2002,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,1985,1985,1991,1992,1992,1992,1994,1985,1985,1985,1993,1985,1985,1985,1985,1984,1991,1985,1985,1985,1985,1985,1984,1984,1984,1984,1991,1991,1985,1985,1985,1986,1986,1987,1987,1990,1991,1991,1991,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1971,1968,1968,1967,1967,1968,1970,1969,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1969,1969,1969,1998,1971,1997,1968,1968,1967,1968,1966,1967,1967,1967,1967,1968,1968,1966,1967,1966,1966,1967,1967,1967,1966,1966,1967,1967,1967,1967,2000,1971,1969,1969,1999,1981,1968,1966,1966,1966,1966,1969,1967,1967,1968,1969,1969,1969,1969,1969,1969,1969,1968,1968,1967,1968,1977,1977,1998,1970,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1970,1970,1972,1971,1971,1971,1971,1971,1971,1972,1972,1972,1972,1972,1972,1972,1972,1973,1973,1975,1975,1975,1975,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2007,2004,2004,2004,1977,1978,1978,1980,1978,1978,1979,1979,2007,1999,1980,1980,1980,2000,2000,1998,1998,2000,2000,1998,1997,1983,1983,1983,1983,1983,1983,1983,1985,1985,1983,1983,1999,1999,1999,1998,1999,1999,1999,1998,1999,1999,1999,1999,1999,1998,1999,1999,1999,1999,2000,2000,1999,1999,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2002,2002,2002,2003,2003,2003,2003,2003,2003,2003,2003,2003,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2010,2010,2011,2011,2010,2010,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2011,2011,2011,2011,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2009,2010,2010,2011,2010,2010,2010,2010,2011,2010,2011,2010,2008,2009,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2009,2008,2008,2009,2008,2008,2008,2010,2010,2010,2010,2011,2010,2010,2009,2009,2009,2004,2004,2004,2004,2003,2003,2003,2004,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2006,2006,2006,2005,2005,2005,2006,2005,2010,2011,2011,2011,2011,2011,2011,2006,2006,2006,2006,2006,2006,2006,2005,2005,2005,2006,2006,2008,2006,2005,2005,2007,2006,2005,2005,2005,2006,2005,2010,2005,2004,2004,2005,2005,2005,2005,2005,2005,2005,2006,2005,2005,2005,2006,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2004,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2006,2006,2010,2010,2010,2010,2006,2007,2007,2007,2008,2008,2008,2009,2009,2009,2009,2009,2009,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2006,2006,2006,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2005,2005,2006,2005,2005,2005,2005,2005,2005,2006,2005,2007,2006,2006,2006,2006,2006,2007,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2010,2010,2008,2010,2010,2010,2010,2010,2010,2010,2010,2008,2010,2010,2007,2005,2005,2005,2005,2006,2002,2002,2003,2003,2002,2002,2003,2003,2003,2003,2003,2002,2002,2002,2002,2002,2002,2002,2003,2004,2004,2002,2002,2002,2002,2002,2003,2003,2003,2003,2003,2002,2002,2005,2005,2005,2005,2005,2005,2005,2002,2003,2003,2003,2003,2003,2003,2003,2002,2006,2006,2008,2010,2008,2007,2007,2007,2007,2007,2006,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2002,2003,2003,2003,2003,2003,2003,2003,2003,2002,2002,2003,2003,2003,2003,2002,2003,2003,2003,2003,2003,2002,2003,2003,2003,2003,2003,2003,2003,2003,2002,2003,2003,2003,2004,2004,2004,2004,2004,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2005,2006,2005,2006,2004,2002,2002,2005,2005,2005,2006,2006,2010,2010,2008,2008,2008,2010,2010,2007,2008,2010,2010,2010,2010,2008,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2007,2007,2007,2007,2007,2007,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2008,2008,2011,2011,2011,2011,2011,2011,2010,2008,2010,2010,2008,2011,2011,2011,2011,2011,2011,2011,2011,2007,2007,2007,2007,2007,2008,2009,2010,2010,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2012,2012,2012,2007,2007,2007,2007,2007,2007,2007,2007,2010,2010,2011,2011,2009,2007,2011,2011,2011,2011,2007,2010,2010,2011,2011,2007,2007,2011,2011,2011,2011,2010,2010,2010,2011,2011,2010,2010,2010,2010,2011,2007,2007,2007,2010,2011,2010,2008,2008,2008,2008,2008,2008,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2011,2011,2012,2012,2011,2011,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2011,2011,2012,2011,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,1953,1952,1952,1952,1952,1954,1951,1951,1952,1952,1952,1952,1952,1953,1952,1952,1952,1952,1953,1954,1951,1951,1952,1952,1952,1952,1955,1952,1952,1952,1953,2006,2006,2006,2006,2006,2006,2006,1953,1953,1953,1953,1953,1953,1953,1953,1953,1952,1952,1952,1952,1956,1958,1958,1955,1952,1953,1953,1952,1952,1952,1952,1953,1953,1953,1953,1953,1953,1953,1953,1953,1952,1952,1953,1953,1953,1953,1953,1954,1955,1954,1955,1954,1954,1954,1954,1954,1954,1954,1954,1955,1955,1952,1952,1981,1981,1952,1953,1952,1953,1954,1954,1953,1953,1953,1953,1952,1954,1953,1953,1953,1957,1957,1954,1954,1954,1954,1953,1953,1955,1952,1952,1952,1954,1954,1954,1954,1952,1954,1953,1948,1948,1948,1949,1949,1950,1949,1949,1948,1948,1951,1948,1948,1947,1951,1956,1949,1949,1948,1949,1949,1948,1947,1948,1948,1947,1952,1947,1947,1948,1949,1947,1947,1947,1947,1949,1949,1949,1949,1946,1954,1947,1947,1947,1947,1947,1946,1946,1946,1945,1950,1976,1976,1947,1947,1949,1949,1947,1949,1951,1947,1946,1951,1946,1946,1949,1948,1948,1948,1948,1948,2010,1901,1948,1949,1949,1948,1948,1946,1948,1949,1954,1954,1952,1952,1952,1952,1952,1951,1951,1951,1954,1954,1954,1952,1951,1951,1951,1952,1952,1952,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1950,1950,1951,1951,1950,1950,1950,1950,1950,1949,1950,1949,1951,1949,1949,1949,1949,1952,1952,1949,1949,1949,1947,1947,1949,1949,1947,1947,1947,1948,1952,1948,1964,1964,1954,1954,1954,1956,1956,1956,1955,1953,1954,1955,1954,1954,1954,1954,1954,1955,1955,1955,1953,1951,1953,1953,1953,1952,1952,1951,1952,1952,1955,1954,1954,1954,1954,1954,1954,1954,1955,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1950,1950,1950,1950,1950,1950,1950,1950,1949,1953,1954,1954,1954,1950,1949,1952,2002,2002,2002,2002,2002,2001,1951,1951,1948,1948,1947,1934,1934,1940,1951,1951,1936,1936,1932,1932,1933,1941,1951,1951,1928,1928,1928,1924,1927,1927,1928,1928,1949,1906,1949,1948,2005,1948,1951,1946,1939,1939,1947,1951,1948,1926,1927,1915,1924,1932,1932,1932,1913,1922,1919,1951,1928,1948,1946,1924,1949,1949,1926,1938,1938,1940,1933,1932,1924,1924,1924,1924,1925,1925,1918,1924,1921,1921,1923,1923,1923,1918,1918,1925,1912,1923,1922,1923,1925,1914,1921,1923,1927,1924,1947,1947,1952,1947,1947,1947,1947,1947,1947,1947,2004,1948,1948,1948,1948,1949,1949,1951,1951,1951,1951,1952,1947,1946,1952,1952,1952,1941,1952,1949,1948,1948,1947,1947,1942,1942,2012,2012,1947,1947,1947,1949,1951,1951,1950,1950,1951,1949,1949,1951,1951,1951,1951,1951,1948,1948,1948,1948,1942,1942,1942,1942,1946,1946,1946,1948,1926,1925,1931,1932,1914,1908,1908,1926,1913,1911,1913,1926,1926,1926,1924,1926,1927,1929,1930,1929,1950,1929,1941,2004,1948,1948,1948,1926,1926,1932,1933,1932,1941,1941,1948,1933,1933,1926,1931,1928,1931,1942,1925,1925,1931,1914,1925,2007,1924,1911,1925,1925,1922,1911,1911,1911,1925,1926,1911,1907,1921,1898,1913,2006,1926,1926,1928,1926,2012,1922,1925,1925,1924,1906,1906,2002,1909,2008,1919,1956,1924,1906,2012,1893,1905,1925,1910,1926,1913,1913,1925,1925,1925,1895,1895,1921,1926,1927,1927,1927,1927,1928,1924,1924,2006,1924,1924,1923,1910,1911,1911,1912,1911,1921,1913,1908,1893,2011,1929,1929,1920,1923,1923,1911,1925,1928,1910,1926,1927,1900,1925,1915,1925,1910,1907,1907,1915,1925,1905,1913,1905,1914,1909,1923,1911,1911,1910,1911,1911,1910,1915,1919,1917,1910,1920,1920,1909,1921,1913,1912,1906,1910,1912,1916,1911,1902,1952,1909,1905,1951,1907,1932,1910,1910,1910,1914,1915,1915,1920,1920,1928,1921,1922,1926,1929,1931,1927,1932,1928,1928,1940,1914,1951,1922,1908,1906,1906,1927,1906,1914,1916,1916,1919,1932,1920,1927,1927,1941,1929,1925,1925,1925,1925,1932,1954,1925,1911,1903,1925,1926,1929,1928,1928,1929,1926,1920,1939,1890,1922,1922,1920,1919,1933,1983,1927,1922,1929,1925,1921,1910,1930,1924,1913,1908,1952,1952,1952,1941,1941,1930,1930,1928,1939,1916,1916,1924,1923,1923,1930,1923,1923,1926,1926,1913,1913,1930,1919,1926,1930,1928,1926,1938,1927,1927,1927,1948,1929,1940,1925,1925,1932,1925,1909,1942,1929,1931,1940,1925,1930,1925,1932,1931,1936,1936,1907,1931,1940,1948,1948,1948,1952,1952,1939,1939,1947,1930,1931,1941,1926,1927,1927,1927,1945,1912,1949,1948,1948,1948,1947,1947,1947,1947,1952,1947,1947,1947,1948,1948,1948,1948,1949,1950,1949,1949,1949,1949,1949,1949,1949,1951,1948,1948,1948,1948,1948,1948,1949,1948,1948,1948,1948,1948,1954,1954,1948,1948,1948,1948,1948,1949,1949,1949,1950,1950,1950,1950,1950,1950,1948,1948,1948,1948,1948,1948,1948,1949,1949,1949,1946,1943,1943,1942,1949,1946,1949,1941,1942,1941,1941,1942,1941,1941,1940,1941,1941,1924,1925,1922,1917,1999,1925,1910,1948,1942,1941,1942,1942,1942,1950,1942,1938,1938,1937,1939,1932,1937,1932,1932,1937,1932,1938,1933,1938,1938,1938,1938,1938,1924,1925,2012,2012,2012,1924,1921,1954,1925,1949,1949,1932,1932,1925,1927,1922,1936,1931,1933,1933,1934,1934,1952,1942,1942,1948,1937,1942,1942,1933,1931,1937,1929,1937,1925,1924,1924,1929,1927,1927,1928,1929,1925,1928,1928,1925,1925,1935,1928,1928,1925,1923,1928,1927,1928,1928,1927,1928,1927,1929,1928,1928,1934,1938,1929,1937,1930,1930,1929,1930,1939,1935,1930,1937,1926,1924,1929,1929,1991,1929,1930,1930,1932,1929,1942,1942,1939,1930,1930,1952,1948,1948,1948,1948,1948,1948,1948,1948,1948,1948,1948,1948,1948,1937,2006,2012,1925,1948,1947,1948,1948,1949,1941,1939,1947,1954,1939,1951,1938,1938,1908,1941,1938,1942,1937,1942,1942,1942,1912,1912,1910,1910,1947,1947,1940,1941,1946,1941,1941,1941,1951,1906,1947,1947,1942,1933,1928,1911,1898,2012,1938,2003,1938,1937,1925,2004,2004,2004,2004,2005,2005,2004,2004,2004,2004,2004,2004,2004,2002,2004,2004,2004,2004,2005,2004,2006,2006,2006,2005,2005,2011,2011,2011,2011,2010,2006,2006,2010,2007,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2006,2012,2008,2008,2007,2007,2007,2007,2007,2007,2007,2006,2006,2006,2006,2006,2006,2007,2007,2006,2007,2007,2010,2010,2010,2010,2010,2009,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,1950,1955,1949,1949,1949,1949,1952,1952,1950,1952,1952,1952,1952,1952,2002,2002,2002,2002,2002,2002,2002,2002,2002,2003,2003,2003,2003,2003,2003,2002,2002,2002,2002,2002,2002,2004,2004,2004,2004,2004,2004,2012,2012,2012,2012,2012,2012,2009,2009,2009,2009,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,1947,1925,1946,1941,1948,1947,1946,1946,1947,1949,1945,1945,1945,1946,1946,1941,1918,1927,1942,1942,1942,1941,1941,1942,1941,1925,1925,1942,1942,1942,1942,1942,1942,1942,1942,1941,1941,1941,1948,1923,1947,1947,1948,1948,1939,1954,1901,1949,1947,1947,1926,1924,1940,1924,1948,1929,1925,1940,1925,1962,1959,1959,1962,1951,1948,1949,1948,1948,1957,1925,1948,1952,1952,1952,1952,1983,1939,1950,1931,1951,1951,1942,1942,1942,1942,1942,1951,1948,1914,1951,1951,1951,1951,1951,1933,1933,1947,1947,1947,1947,1947,1947,1948,1947,1924,1953,1954,1934,1956,1951,1951,1954,1948,1948,1940,1948,1948,1947,1947,1947,1947,1947,1949,1949,1947,1947,1965,1953,1953,1953,1947,1949,1950,1949,1949,1950,1950,1950,1950,2004,2005,2005,2005,2004,2004,2004,2004,2004,2004,2005,2004,2004,2004,2004,2005,2005,2004,2004,2005,2005,1894,1962,2002,1982,2005,2005,1928,1889,1927,1924,1940,1948,1940,1938,1954,1947,1947,1953,1953,1926,1953,1921,1947,1947,1947,1953,1956,1953,2003,2003,2003,2003,2003,1894,1947,1921,1914,1922,1937,1891,1943,2000,1932,1915,1890,1901,1940,1939,1939,1890,1948,1947,1949,1949,1948,1949,1949,1949,1947,1948,1948,1948,1948,1948,1948,1948,1948,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1948,1948,1948,1951,1953,1949,1948,1911,1910,1954,1923,1923,1906,1946,1948,1949,1949,1900,1910,1953,1947,1947,1947,1947,1947,1947,1947,1947,1961,1961,1954,1954,1959,1923,1956,1929,1929,1903,1903,1922,1910,1914,1914,1908,1909,1906,1900,1922,1922,1906,1906,1906,1924,1913,1922,1922,1922,1910,1910,1910,1927,1998,1948,1942,1941,1948,1942,1942,1942,1942,1941,1942,1941,1941,1941,1941,1942,1948,1948,1948,1948,1941,1941,1942,1942,1942,1947,1941,1941,1927,1927,1928,1925,1925,1948,1948,1948,1948,1948,1927,1948,1948,1925,1942,1942,1942,1942,1942,1941,1941,1941,1927,1927,1941,1941,1936,1942,1942,1941,1941,1942,1942,1940,1917,1924,1910,2002,1945,1945,1948,1948,1948,1910,1910,2012,2012,2012,2011,1927,1955,1949,1953,1955,1961,2012,1951,1929,1929,1921,2012,2012,1936,1954,1922,1922,1961,1906,1928,2011,2011,2011,2011,1919,1937,1954,1900,1911,1908,1910,1911,1925,1924,1960,1929,1929,1921,1921,1921,1949,1927,1929,1909,1908,1922,1910,1915,1929,1952,1952,1938,1906,1901,1901,1919,1924,1900,1908,1924,1929,1929,1923,1924,1924,1974,1890,1923,1949,1942,1933,1924,1923,1910,1910,1921,1925,1940,1925,1930,1930,1921,1923,1947,1908,1908,1906,1916,1948,1948,1948,1910,1948,1948,1955,1954,1958,1948,1948,1946,1947,1952,1941,1924,1924,1925,1946,1946,1946,1946,1955,1956,1956,1947,1947,1938,1940,2005,1921,1921,1912,2011,2011,1924,1923,1905,1961,1908,1896,1901,2008,1963,1963,2006,1904,1942,2009,2009,1940,1896,1910,1901,1906,1904,1904,1906,2008,2008,2012,2012,1905,1907,1907,1904,1904,1924,1922,1903,1912,1909,1898,1910,1925,1922,1924,1951,1906,1906,1906,1953,1916,2004,2007,1920,1910,1923,1925,1925,1923,1923,1923,1922,1922,1921,1906,1901,2005,2007,2007,2007,2007,2007,2009,2009,2010,2010,2011,2011,2011,2011,2011,2011,2011,1920,1930,1908,1954,1928,1911,1905,2006,2006,1978,1986,1903,1924,1911,1911,1956,2000,1935,1931,1931,1928,1928,1910,2010,2010,1906,1891,2010,2010,1910,1906,1951,1951,2011,2011,1949,1918,2009,1904,1908,1891,1911,1906,1908,1901,1906,1908,1908,2012,1911,1906,2012,1919,1919,1906,1912,1922,1900,1900,1914,2010,2010,1898,2012,2012,1949,1904,1922,1910,2012,1916,2007,2007,1922,1911,1926,1920,1911,1918,1918,2006,2006,2010,2010,1908,1938,1891,1926,1906,1900,1949,1920,1906,1908,1908,1931,1902,1902,2012,1906,2007,2007,2011,2011,1906,2003,2011,2011,1908,1914,1914,1912,1918,1924,1905,1905,1922,2009,1908,1908,2010,2010,2010,1912,1936,1936,1891,1926,1901,1911,1910,1906,1927,1896,1901,1901,1906,1930,1905,1896,1982,1906,1924,1908,1898,2010,2010,1906,2012,2012,1910,1928,1949,1920,1928,1927,1917,1896,1927,1907,1907,1953,1953,2008,2008,2011,1900,1924,1924,1925,1948,1900,1955,1959,1905,2011,2011,1905,1911,1911,2012,2012,1900,1896,1906,1940,2012,2012,2012,2012,1935,1932,1932,1936,1936,1903,1956,1997,1955,2005,1910,1952,1952,1950,1970,2006,1927,1910,1921,1922,1909,1904,1906,1926,1886,1905,1910,1922,1938,1958,1958,1952,1955,1952,1952,1941,1941,1941,1941,1941,1941,1954,1959,1949,1950,1950,1949,1941,1939,1902,1900,1900,1906,1933,1933,1932,1962,1949,1929,1946,1924,1928,1928,1948,1926,1951,1951,1926,1983,1930,1928,1999,1942,1910,1960,1905,1900,1909,1902,1906,1973,1973,1906,1906,2011,2011,1931,1906,1905,1903,1903,1933,1907,1909,1900,1928,1928,1928,1911,1925,1946,1922,1920,1925,1912,1912,1926,1926,1926,1925,1926,1925,1948,1925,1925,1949,1945,1925,1901,1910,1910,1910,1922,1910,1907,1906,1905,1923,1910,1910,1910,1910,1910,1908,1922,1913,1913,1926,1922,1921,1923,1945,1945,1945,1945,1951,1949,1948,1890,1890,1947,1938,1939,1905,1921,1921,1939,1951,1939,1956,1920,1910,1939,1939,1900,2012,2012,2011,2008,1942,1925,1915,1913,1929,1950,1951,1941,1900,1907,1903,1933,1903,1970,1970,1970,1970,1915,1922,1925,1910,1927,1913,1908,1920,1923,1955,1955,1929,1956,1930,1919,1925,1925,1925,1925,2011,2011,2011,1912,1937,2011,1925,1910,1906,1906,1928,1923,1925,1910,1910,1922,1921,1914,1928,1912,1912,1920,1922,1922,1921,1915,1924,1925,1924,1925,1960,1926,1896,1910,1896,1908,1906,1906,1926,1921,1941,1941,1912,1912,1923,1925,1912,1910,1938,1919,1941,1941,1941,1890,1901,1952,1952,1928,1900,1900,1895,1909,1909,1916,1915,2012,1923,1921,1912,1905,1910,1954,1905,1905,1928,1946,1946,1928,1904,1930,1921,1891,1891,2012,2003,1946,1946,1946,1905,1905,1905,1908,1960,1910,1905,1895,1911,1911,1905,1994,1925,1927,1927,1928,1940,1927,1928,1888,1926,1925,2009,2009,1926,1925,1895,1954,1951,1955,1907,1907,1954,1895,1961,1956,1943,1943,1943,1905,1911,1910,1941,1941,1938,1927,1925,1905,1900,1902,1907,1918,1918,1910,1895,1895,1980,1891,2002,1917,1917,1950,1948,1948,1948,1948,1948,1921,1890,1890,1890,1958,2010,1948,1949,1949,1946,1949,1886,1943,1943,1943,1943,1943,1943,1947,1947,1943,1908,1896,1945,1945,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1951,1951,1967,1925,1906,1906,1943,1908,1923,1923,1930,1926,1925,1925,1900,1900,1908,1925,1926,1925,1925,1926,1904,1904,1899,1911,1911,1891,1908,1896,1925,1959,1959,1896,1900,1891,1899,1933,1933,1933,1909,1906,1906,1907,1907,1906,1895,1911,1999,1911,1911,1896,1913,1913,1911,1911,1901,1903,1959,1959,1903,1904,1886,1886,1906,1891,1947,1947,1921,1896,1959,1925,1925,1913,1916,1949,1936,1918,1925,1925,1953,1954,1905,1905,1905,1923,1911,1906,1903,1894,1907,1923,1929,1955,1886,1886,1887,1955,1955,1974,1974,1933,1956,1958,1923,1923,1917,1910,1984,1984,1967,1949,1897,1897,1906,1914,1952,1896,1896,1886,1891,1896,1896,1896,1896,1901,1896,1896,1925,1942,1891,1896,1896,1896,1906,1906,1889,1889,1890,1890,1952,1952,1901,1891,1956,1896,1896,1896,1912,1924,1924,1911,1940,1911,1911,1916,1901,1901,1953,1921,1908,1998,1999,1904,1915,1915,1886,1928,1896,1911,1886,1886,1890,1926,1895,1946,1905,1904,1886,1925,1886,1952,1928,1891,1891,1896,1930,1910,1945,1900,1912,1906,1910,1898,1898,1906,1891,1941,1886,1887,1932,1932,1896,1896,1901,1917,2007,2007,1886,1890,1892,1889,1922,1888,1891,1910,1889,1896,1896,1902,1948,1903,1953,1886,1896,1886,2001,1886,1901,1999,1889,1886,1882,1882,2004,1896,1896,1896,1928,1892,1889,1890,1890,1888,1888,1893,1890,1888,1957,1957,1957,1947,1940,1925,1952,1952,1948,1946,1946,1948,1948,1948,1948,1948,1947,1901,1930,1890,1888,1888,1890,1893,1893,1946,1927,1894,1894,1901,1887,1887,1919,1955,1955,1886,2005,1946,1946,1948,1948,1942,1942,2011,1936,1922,1904,1900,1939,1906,1950,1950,1959,1923,1923,1939,1942,1949,2010,1922,1894,1928,1938,1945,1945,1938,1938,1927,2012,1951,1947,1947,1892,1892,1953,1896,1927,1907,1938,1938,1938,1953,1973,1948,1948,1930,1932,1950,1949,1949,1949,1948,1947,1949,1949,1946,1923,1923,1925,1945,1945,1945,1915,1888,2011,2011,1926,1938,1936,1936,1896,2004,1901,1999,1999,2006,1923,1942,1942,1953,1917,1920,1920,1915,1952,1956,1956,1956,1912,1926,1926,1901,1902,1927,1951,1886,1886,1949,1949,1949,1949,1949,1927,1890,1935,1929,2003,2003,1926,1894,1949,1937,1937,1942,1953,1908,1948,1941,1923,1917,1917,1913,1910,1908,1922,1923,1923,1926,1925,1925,1948,1896,1926,1926,1926,1926,1931,1931,1937,1938,1926,1901,1901,1938,1938,1999,1912,1895,1952,1910,1952,1895,1949,1913,1911,1911,1911,1922,1929,1925,1925,1924,1924,1910,1910,1927,1927,1927,1928,1928,1928,1963,1963,1963,1963,1963,1954,1945,1945,1945,1945,1928,1928,1896,1896,1923,1949,1894,1986,1986,1891,1891,1927,1927,1922,1886,1951,1949,1942,1945,1942,1942,1951,1952,1925,1962,1936,1936,1909,1926,1906,1912,1912,1952,1902,1905,1914,1953,1926,1929,1925,1925,1926,1926,1924,1924,1946,1930,1930,1944,1925,1925,1925,1925,1925,1926,1927,1922,1922,1910,1910,2011,2011,1929,1925,1925,1949,1948,1948,1948,1938,1938,1938,1923,1923,1923,1952,1952,1951,1952,1952,1949,1951,1951,1951,1945,1945,1945,1941,1941,1941,1948,1953,1953,1951,1949,1949,1952,1952,1948,1947,1947,1949,1946,1942,1946,1959,1959,1948,1947,1947,1941,1941,1952,1962,1962,1952,1952,1946,1946,1944,1944,1948,1931,1951,1951,1951,2007,1933,2007,1955,1952,1952,1922,1951,1949,1949,1956,1971,1952,1952,1948,1922,1931,2002,1911,1910,1887,1901,1926,1924,1914,1957,1912,1912,1922,1924,1910,1942,1942,1940,1929,1890,1890,1890,1924,1924,1925,1929,1916,1914,1928,1922,1922,1910,1925,1925,1922,1921,1916,1917,2011,1922,1922,1913,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1921,1924,1896,1896,1939,1924,1890,1899,1899,1899,1890,1886,1886,1908,1896,1886,1890,1887,1890,1887,1890,1886,1986,1986,1892,1886,1910,1910,1910,1910,1902,1886,1886,1905,1905,1896,1896,1900,1907,1907,1908,1906,1905,1905,1888,1890,1890,1890,1890,1909,1909,1886,1911,1888,1900,1900,1890,1890,1890,1890,1888,1888,1888,1890,1890,1890,1890,1890,1910,1910,1885,1885,1904,1904,1895,1900,1890,1904,1904,1888,1888,1888,1888,1887,1886,1888,1888,1906,2010,1892,1896,1896,1998,1882,1882,1901,1896,1896,1886,1886,1886,1894,1894,1894,1885,1886,1886,1887,1889,1897,1886,1886,1886,1880,1890,1888,1888,1890,1886,1886,1886,1900,1888,1886,1886,1969,1886,1890,1886,1886,1886,1886,1886,1909,1909,1909,1909,1909,1888,2002,2002,2002,2002,2002,2002,1894,2006,1884,1901,1893,1887,1890,1885,1895,1886,1886,1905,1886,1890,1885,2003,1898,1895,1890,1903,1911,1900,1895,1890,1890,1890,1890,1895,1890,1873,1896,1896,1896,1896,1890,1883,1900,1900,1900,1900,1926,1926,1971,1890,1971,1890,1910,1955,1886,1907,1909,1896,1884,1884,1906,2003,1896,1896,1888,1907,1908,1923,1908,1907,1907,1907,1910,1923,1923,1923,1910,1910,1890,1890,1908,1946,1910,1910,1981,1981,1908,1908,1906,1954,1954,1907,1904,1905,1907,1904,1906,1904,1910,1906,1908,1905,1905,1890,1890,1906,1906,1910,1906,1926,1911,1910,2012,1908,2008,2012,1910,1908,1908,1906,1911,1911,1911,1906,1912,1912,1909,1909,1886,1886,1913,2005,1915,1905,1906,1888,1909,1909,1909,1909,2002,1885,1885,1885,2002,2002,2002,2002,2002,2002,2005,2005,2005,2005,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,1910,1901,1880,1884,1884,1885,1885,1886,1900,1904,1904,1904,1904,1904,1904,1904,1904,1888,1892,1903,1898,1898,1898,1898,1898,1898,2012,2012,1896,2003,2006,2006,2006,2006,1888,1888,1888,1888,1888,1888,1884,1886,2003,1886,1884,1889,1886,1882,1886,1886,1888,1890,1894,1885,1885,1961,1961,1880,1999,1894,1910,1886,1932,1888,2005,1895,1895,1897,1897,1897,1897,1880,1890,1888,1895,1880,1885,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,1958,1958,1958,2004,2004,2005,2005,1933,1933,1933,1933,2008,1903,1910,1910,1910,2006,2006,2006,2006,2005,2005,2005,2005,2005,2005,2005,1896,1896,1896,1896,1896,1896,1896,1896,1896,1896,1896,1896,1896,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2001,2001,2001,2001,2001,1920,1920,2000,2000,2000,2000,2000,2000,1886,2005,2005,2005,2005,2005,2005,1916,1916,1916,1916,1916,2000,2000,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,1896,1896,1895,1895,1997,1997,1997,1997,1891,1886,1890,1891,1886,1886,1886,2012,2012,1901,2011,1927,2007,2007,2007,2007,2009,2009,1886,1886,2010,1924,2006,1891,1891,1891,1906,1906,1896,1891,1886,1891,1886,2010,2010,1901,1901,1901,1901,1906,2010,2010,2007,1891,1886,1886,2010,2010,1891,1891,1891,1891,2011,1901,1891,1903,1890,1901,1963,2005,2005,1901,1901,1926,1920,1891,1901,1905,1913,1900,1900,1906,1906,1941,1946,1937,1936,1952,1938,1923,1921,1915,1910,1894,1890,1964,2003,1910,2007,1964,1905,1955,1904,1904,1896,1908,2011,2011,1909,2012,2012,1961,1885,2006,1900,1900,2008,2008,1959,1959,2008,2008,1887,1890,1964,1964,2011,2011,1924,1951,1955,2011,2011,2012,1900,1886,1890,1890,1890,1887,2009,2009,2009,2009,2011,2011,2011,2011,1893,1896,2011,2011,1896,1896,2010,2011,2011,1893,1911,1911,1910,2012,2012,2011,2011,2011,2012,2011,2011,2011,2012,2012,1896,1898,2005,2011,2012,1911,1880,2003,2005,2007,1889,2005,1912,1891,1948,2008,1986,1958,1886,2007,1898,1898,1898,1899,1899,1886,1906,1906,1894,1893,1900,2009,2009,2009,2009,1954,1954,2002,2002,2002,2002,2002,2002,2001,2001,2001,2007,2007,2007,2007,1890,1906,1906,1903,1899,2008,2008,2008,2008,2008,2008,2003,1880,1880,1891,2008,2008,2008,2008,2010,2011,2011,2011,1910,1910,1910,1910,2012,2012,2012,2006,2007,2007,2007,2007,2010,2010,2010,2010,2010,2010,2010,2010,2010,2012,1891,2009,2009,1907,1907,2009,2009,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2002,2002,2002,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,1984,1984,1999,1999,1999,1999,1999,1999,2000,2000,2000,2000,1886,2006,2003,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,1908,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,1996,1998,1998,1998,2007,2007,1908,1886,1886,1900,1885,1885,1884,2011,2011,2011,2011,2003,2007,2007,2007,1896,2000,2000,2000,1900,2007,2007,2007,2007,2007,2007,2007,2007,2007,2004,2004,2004,2004,2004,2004,2004,1890,1908,1911,1911,1922,1908,1908,1908,2012,2012,1890,1909,1890,1905,1890,1910,1910,1910,1885,1885,1885,1895,1903,1930,1930,1885,1885,1890,1895,2012,1899,1900,1885,1885,1905,1905,1905,1905,1905,1895,1895,1905,1910,1901,1902,1955,1906,1925,1911,1911,1955,1900,1928,1905,1905,1895,1895,1893,1890,1954,1954,1954,1913,1915,1954,1954,1954,1954,1954,1908,1908,1915,1908,1923,1893,1900,1900,1890,1900,1902,1909,1913,1900,1923,1932,1911,1909,1909,1954,1890,1910,1910,1910,1890,1909,1909,1895,1900,1909,1903,1902,1902,2005,2005,1931,1907,2002,2002,2002,1925,1904,1890,1928,1927,1927,2010,2010,1927,1925,1924,1922,1923,1915,1910,1923,1935,1928,1925,1925,1925,1890,1925,1890,1927,1923,1908,1912,1953,1930,1956,1929,1927,1922,1937,1929,1929,1923,2012,1922,1911,1930,1910,1907,1906,1926,1926,1910,1901,1908,1927,1912,1891,1891,1891,1891,1891,2011,2011,1928,1908,1885,1927,1915,1900,1996,1996,1996,1886,1915,1927,2010,1890,1906,1920,1925,1912,1912,1891,1891,1885,2003,1905,2010,2010,1885,1885,1908,1905,1905,1905,1890,1905,1905,1890,1890,1907,1910,1925,1925,1925,1908,1887,1903,1910,1910,1929,1929,1929,1929,1929,1894,1894,1894,2008,2008,2008,2008,1900,1893,1890,1916,1916,1916,1939,1939,1904,1909,1897,1922,1900,1900,1890,1890,1886,1885,1900,1900,1902,1887,1891,1896,1896,2006,2006,2006,2008,2008,1912,1905,1894,2007,2007,1900,1900,1902,1888,2010,2010,1911,1931,1931,1911,1904,1905,1881,1881,1908,1912,1912,1912,1912,1912,1916,2008,1940,1940,1940,1940,1941,1941,1973,1973,1973,1973,1925,1925,1925,1941,1941,1916,1925,1932,1941,1930,1940,1909,1908,1908,1929,1906,1906,2012,1951,1948,1955,2011,2011,1952,1885,1900,1922,2009,2009,2009,2009,2009,2011,1893,1890,1900,1900,1890,1890,1895,1892,2007,2007,2007,2011,1910,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1913,1886,2002,2002,1911,1911,1912,1906,1891,1906,1891,1891,1896,1896,1890,1890,1909,1904,1929,1899,1926,1940,1940,1930,1930,1932,1932,1932,1926,1931,1931,1931,1949,1910,1891,1891,1891,1951,1896,1896,1937,1901,2000,1906,2010,2010,1953,1927,1906,1906,1931,1937,1934,2012,1937,1930,1911,1931,1930,1931,1930,1931,1885,1928,1928,1930,1929,1929,1947,2008,1922,1911,1928,1921,1925,1925,1910,1906,2007,2010,2010,2010,2012,1910,1936,1889,1889,2008,1897,1906,1913,1910,2007,1926,1906,1953,1953,1925,1924,1922,1913,1913,2007,1941,1938,1907,1924,1924,2010,1924,2010,2010,1891,1908,2006,1892,1928,1929,1890,1900,1900,1906,1916,2003,2003,2003,2003,1912,1926,1926,1927,1914,1955,1924,1956,2008,2008,2008,1910,1925,1953,1959,1899,1899,1954,1954,1912,1929,1952,1957,1952,1925,1953,1953,1953,1952,1952,1946,1946,1924,1996,1952,1952,2011,2011,2011,1906,1906,1954,1901,1953,1891,1910,1906,1906,1952,1952,1949,1930,2010,1968,1968,1968,1924,1924,1947,1952,1952,1952,1929,1910,1925,1896,1897,1922,1952,1889,1957,1906,1954,1953,1941,1896,1926,1926,1949,1891,1891,2009,2009,1927,1952,1952,1952,1941,2006,2006,2012,1948,1937,2005,2005,1949,1896,1924,1949,1949,1949,1921,1921,1929,1999,1999,2001,1999,1999,2001,2001,2000,2001,1999,1999,2003,1940,1940,1950,1942,1936,1937,1937,1955,1937,1938,1952,1949,1951,1959,1932,1932,1927,1924,1890,1890,1947,1947,1919,1949,1948,1940,1909,1951,1951,1951,1940,1925,1907,1937,1893,1999,1949,1925,1922,1924,1938,2011,2011,1951,1949,1952,1911,1957,1923,1921,1931,1927,1983,1952,1890,1951,1953,1890,1952,1953,1951,1951,1951,1921,1952,1955,1949,1943,1952,1952,1952,1951,1992,1950,1946,1961,1943,1943,1943,1943,1949,1947,1942,1949,1921,1952,1952,1913,1900,2006,2007,1895,1905,1888,1926,1908,1904,1954,1954,1954,1900,2005,2005,1953,2008,1940,1940,1935,2006,2006,1933,1938,1935,1912,1905,1910,1910,1910,1947,1949,1949,1890,1893,1910,2006,1952,1951,1951,1944,1944,1951,1890,1906,1900,1961,1953,1953,1939,1939,1900,1940,1940,1940,1939,1939,1940,1939,1939,1954,1949,1923,1949,1949,1949,1951,1927,1927,1928,1942,1918,1952,1951,1951,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1953,1892,1952,1946,1940,1939,1941,1941,1941,1941,1946,1941,1941,1929,1954,1952,1948,1948,1948,1954,1941,1893,1914,1913,1914,1908,1885,1885,1895,1951,1885,1941,1941,1942,1941,1941,1941,1941,1947,1999,1925,1934,1981,1956,1951,1909,1946,1928,1928,1927,1910,1906,1885,1894,1898,1964,1951,2003,1951,1951,1931,2011,2011,1931,1931,1947,1947,1947,1947,1947,1969,1980,1940,1914,1952,1907,2005,2008,1954,2011,2011,2011,2011,1900,2012,2009,2009,2011,2011,1952,2006,2006,1895,1949,2009,1951,1951,2006,2007,2011,2006,2009,1952,1953,1910,2005,1965,1907,1905,1952,1954,1894,1908,2012,2012,1954,1947,1949,1963,1900,1942,1949,1946,1951,1951,1907,1907,1907,1907,1910,1948,1948,1974,1974,1948,1998,1958,2008,2008,2008,2008,1957,1928,1942,1925,1928,1928,1928,1928,1929,1929,1929,1924,1924,1924,1924,1926,1926,1926,1926,1926,1926,1953,1920,1924,1920,1919,1919,1920,1921,1926,2000,2007,2007,1896,1896,1893,1890,1896,1913,1913,1913,1891,1891,1896,1896,1886,1923,2006,1906,2006,2006,1978,1978,1890,1890,2004,2005,1887,1900,1998,2007,2007,2007,2007,2007,2007,2007,2007,2008,2008,2008,2008,2008,2008,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,1907,1910,1908,2007,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1891,1891,1890,1890,2004,1958,1958,1958,1958,1958,1886,1898,1905,1953,1886,1886,1900,1900,1896,1896,1895,1895,2010,2010,2010,1959,1952,1948,1951,1951,1895,1938,1938,1938,1939,2008,2008,1957,1902,1885,1901,1904,1904,1904,1904,1890,1909,1947,1947,1953,1910,1907,1891,1886,1896,1896,1910,1929,2008,1952,1891,1925,1900,1900,1900,1896,1896,1886,1890,1900,1891,1901,1896,1911,1896,1911,1956,1949,1942,1942,1952,1952,1953,2012,2012,1954,1996,1996,1948,1996,1938,1979,1980,1980,1995,1995,1995,1995,1995,1952,1952,1952,1952,1952,1996,1996,1997,1997,1997,1997,1997,1952,1952,1952,1952,2011,2011,1951,1885,1880,1880,1947,1948,1930,1999,1927,1957,2011,1951,1952,1952,1939,1940,1954,1954,1989,1999,1926,1910,1910,1910,1910,1906,1906,1906,1984,2002,2002,1906,1906,1907,1924,1930,1930,2001,2001,2001,1905,1890,1890,1890,1890,1890,1890,1886,1886,1886,2002,2002,2002,2002,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1908,2011,2011,2000,2000,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1886,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1909,1909,1997,1997,1997,1997,1928,1928,1928,1928,1928,1928,1928,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2006,2006,2006,2006,1898,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,1919,1919,1919,1919,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2004,2000,2000,2000,2000,2000,2000,2000,2000,2000,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2007,2007,2007,2007,2007,2007,1896,1896,1907,1907,1907,1981,1981,1981,1885,1885,1880,1884,1985,1985,1985,1881,1902,1888,1948,1896,2007,2007,2007,2007,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1888,1984,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,1890,1885,1901,2008,2008,2008,2008,2008,2008,2008,2004,2004,2007,2007,1886,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2007,2007,2007,2007,2007,2007,2007,1888,1884,1884,1891,1891,1951,1891,1913,1913,1983,1983,1983,1983,1983,1983,1983,1983,1908,1908,1908,2008,2008,2008,2009,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1896,1896,1905,1905,1905,1905,1905,1905,1905,1903,1903,1903,1903,1903,1903,1903,1903,1903,1980,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2006,2006,2006,2006,2006,2003,2003,2003,2003,2003,2003,1910,1910,1892,2001,2001,2001,2001,2001,1886,1999,1999,1999,1967,1998,1998,1998,1998,1897,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2006,1941,1997,1997,1997,1997,1997,1905,1905,1905,1906,1896,1892,1890,1890,1905,1905,1905,1980,1893,1906,1910,1904,1910,1908,1888,1888,1893,1897,1890,1890,1890,1893,1893,1927,1927,1918,1906,1904,1923,1906,1906,1906,1902,1900,1900,1896,1910,1922,1917,1923,1923,1923,1890,1902,1896,1892,1900,1900,1900,1890,1972,1890,1904,1904,1904,1893,1909,1910,1898,1896,1898,1937,1898,1961,1961,1896,1904,1904,1900,1903,1908,1908,1908,1890,1898,1905,1954,1910,1904,1904,1901,1910,1908,1908,2000,1906,1910,1912,1890,1890,1908,1954,1925,1914,1908,1894,1893,1902,1902,1898,1951,1951,1951,1906,2007,1888,2011,1971,1971,1896,1896,1964,1900,1900,2011,1888,1900,1900,1898,2000,1904,1904,1890,1948,2002,2008,2008,2008,1895,1890,2001,1910,1910,1893,1890,1906,1908,1925,1889,1902,1901,1942,1890,1887,1892,1892,1891,1901,1900,1900,1892,1889,1889,1889,1890,1890,1896,1890,1928,1896,1891,1920,1895,1895,1893,1886,1905,1900,1900,2008,2008,2008,2008,2008,1906,1906,1906,1906,1887,1889,2011,1896,1896,2003,2003,2003,2003,1891,1891,1891,1894,1890,1890,1889,1897,1924,2010,1894,1890,1890,1889,1946,1946,1946,1946,1946,1946,1946,1946,1946,1892,1998,1999,1905,2002,2002,2002,2002,2002,2002,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,1890,1890,1890,1890,1930,1930,1930,1890,1890,1886,1894,1890,1890,2006,1999,1886,2003,2003,2003,1896,2005,2005,2005,2005,1901,1901,1901,1901,1901,1901,1901,2001,2001,2001,2001,2001,2003,2003,2003,2003,2003,2003,2003,2003,2003,1997,1886,1889,1999,1999,1900,1890,1890,1890,1902,1902,1909,2005,1908,1908,1909,2005,1912,1966,1966,1966,1930,1890,2005,2003,2003,2003,2003,2003,2011,2011,2011,2011,2011,2011,2011,2011,2011,1904,1904,1893,2005,2003,2003,1899,2003,2003,2003,1937,1893,1906,2005,2005,2005,2005,2005,1906,1904,1904,1922,1922,1916,1916,1916,1962,2006,2006,2006,2006,2006,2006,2006,2006,2006,1890,1889,1978,1978,1901,2002,1892,1900,1906,1890,1890,1936,1925,1908,1908,1930,1901,1896,1890,1890,1894,1893,1906,2000,2000,2000,2000,1909,1909,1912,1890,1909,1918,1918,1916,1937,1944,1944,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1937,1937,1909,1905,1910,1910,2006,2006,2006,2006,2006,1905,1890,1905,1910,1928,1925,1923,1910,1920,1906,1925,1925,1914,1922,1916,1934,1904,1907,1907,1904,1908,1908,1907,1906,1908,1908,1962,1962,1906,1895,1908,1909,1908,1911,1925,1927,1924,1927,1952,1955,1958,1950,1962,1951,1928,1955,1953,1953,1950,1950,1953,1954,1952,1954,1954,1953,1953,1953,1953,1953,1954,1966,1971,1978,1974,1976,2005,1965,1961,1969,1971,1962,1962,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1980,1980,1983,1970,1970,1968,1968,1966,1967,1969,1969,1970,1966,1969,1983,1984,1979,1979,1988,1964,1964,1962,1962,1962,1962,1970,1962,1964,1963,1968,1966,1963,1961,1963,1962,1967,1965,1962,1962,1962,1964,1968,1962,1963,1963,1963,1964,1963,1963,1962,1963,1963,1963,1962,1962,1965,1970,1970,1970,1970,1970,1970,1968,1970,1969,1969,1968,1968,1968,1965,1963,1963,1963,1962,1962,1962,1962,1963,1963,1961,1961,1961,1962,1963,1963,1963,1962,1963,1962,1962,1962,1964,1968,1969,1969,1968,1963,1963,1962,1961,1986,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1979,1979,1979,1979,1979,1979,1979,1984,1984,1986,1979,1979,1979,1979,1980,1980,1980,1983,1982,1982,1982,1983,2003,2003,2003,1914,1910,1922,1910,1911,1912,1908,2008,2008,2008,2008,2008,2008,2008,2008,2008,1906,1906,1906,1905,1892,1908,1906,1906,1906,1981,1906,1908,2001,2001,2001,2001,2001,2001,2001,2001,2001,2005,2005,1902,1970,1970,1970,1914,2000,2003,1911,1911,1910,1909,1914,1914,1966,1966,1966,1966,1966,1985,1924,1924,1964,1964,1964,1964,1964,1964,1924,1924,1924,2012,1947,1927,1924,1946,1924,1930,1923,1923,1926,1891,1910,1910,1910,1923,1925,1908,1908,1908,1908,1915,1915,1906,1911,1927,1908,1910,1910,1908,1910,1914,1910,1910,1910,1910,1920,1922,1920,1910,1907,1993,1908,1959,1923,1920,1922,2007,2007,2007,1968,1968,1908,1927,1914,1908,1910,1900,1900,1900,1891,1901,1908,1899,1898,1968,1892,1901,1891,1911,1910,1975,1975,1975,1906,1882,1891,1920,1966,1966,1966,1968,1968,1968,1968,1900,1906,1916,1892,1884,1892,1892,1901,1915,1915,1915,1914,1908,1908,1910,1908,1908,1928,1928,1928,1928,1938,1908,1923,1898,1908,1908,1904,1963,1963,1911,1902,1962,1962,1962,1962,1962,1906,1965,1965,1930,1898,1905,1890,1901,1901,1901,1901,1901,1901,1901,1931,1931,1931,1919,1919,1918,1918,1896,1896,1906,1961,1906,1903,1953,1922,1909,1905,1902,1910,2005,1906,1906,1924,1925,1925,1903,1922,1927,1925,1922,1919,1919,1908,1904,1900,1974,1974,1974,1974,1974,1974,1974,1939,1915,1915,1910,1919,1910,1925,1923,1948,1922,1903,1903,1905,1900,1923,1922,1923,1909,1909,1911,1923,1915,1916,1923,1925,1922,1918,1920,1920,1928,1922,1922,2012,1924,1924,1923,1923,1923,1922,1930,1922,1922,1922,1924,1924,1925,1923,1923,1924,1922,1922,1908,1921,1924,1924,1922,1921,1920,1923,1889,1926,1922,1920,1920,1920,1923,1920,1919,1916,1914,1919,1920,1922,1941,1923,1922,1920,1920,1927,1920,1927,1924,1924,1926,1924,1923,1923,1923,1929,1926,1925,1925,1925,1937,1937,1924,1925,1949,1926,1924,1924,1937,1924,1932,1919,1922,1921,1917,1919,1919,1918,1917,1919,1919,1911,1994,1989,1910,1900,2007,2008,1988,1988,1988,1988,1998,2002,1924,2001,2000,1900,1943,1999,2001,1983,2000,2005,2007,2007,2007,2007,2007,1999,2007,2006,1942,1942,2000,2007,2007,1923,2003,1922,1920,1920,1914,1913,1913,1917,1912,1913,1913,1922,1923,1918,1911,1923,1905,1927,1922,1922,1926,1920,2007,2012,1981,2004,2012,2011,1928,1951,1951,1975,1962,1962,2005,1998,1998,1998,2000,1990,2005,2000,2000,2000,2000,1908,2007,1993,2010,2010,2010,2010,2010,2010,2010,2010,1894,1894,1894,1894,1896,1896,1896,1896,1930,1890,1900,1896,1935,1902,1929,1929,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1902,1904,1910,1892,1888,1886,1905,1902,1924,1887,1900,1893,1886,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1904,1904,1962,1962,1927,1927,1964,1905,1906,1965,1904,1906,1902,1902,1902,1902,1902,1902,1886,1904,1965,1965,1965,1968,1968,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1892,1892,1901,1969,1969,1969,1969,1969,1965,1960,1960,1960,1960,1960,1960,1993,1993,1969,1969,1969,1969,1969,1969,1969,1981,1981,1981,1981,1981,1980,1980,1980,1980,1980,1976,1976,1976,1976,1968,1968,1968,1901,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1930,1973,1967,1967,1967,1967,1967,1967,1967,1967,1902,1902,1902,1902,1890,1947,1947,1947,1901,1890,1890,1891,1889,1889,1888,1906,1903,1903,1966,1885,1900,1900,1930,1894,1929,1929,1929,1905,1905,1905,1928,1928,1928,1903,1905,1896,1901,1902,1901,1901,1888,1892,1892,1902,1902,1902,1902,1965,1965,1965,1965,1965,1965,1966,1966,1966,1959,1959,1900,1965,1965,1965,1965,1965,1965,1965,1916,1907,1964,1896,1900,1954,1903,1903,1962,2003,2003,1900,1899,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1960,1967,1967,1967,1967,1910,1910,1900,1892,1894,1954,1954,1954,1930,1896,1900,1908,1900,1960,1893,1906,1910,1966,1910,1902,1902,1905,1908,1964,1968,1968,1968,1906,1906,1904,1966,1966,1966,1966,1961,1961,1968,1958,1958,1958,1958,1958,1958,1898,1910,1961,1961,1961,1961,1961,1886,1886,1960,1960,1911,1911,1923,1923,1923,1914,1914,1914,1970,1970,2000,1910,1910,1904,1904,1904,1900,1968,1968,1968,1968,1929,1929,1929,1929,1929,1929,1929,1929,1929,1929,1929,1929,1929,1909,1910,1963,1963,1899,1908,1929,1929,1929,1900,1891,1896,1891,1958,1958,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1900,1902,1902,1902,1898,1906,1910,1923,1923,1923,1928,1910,1910,2006,2006,1911,1900,1927,1941,1908,1908,1908,1906,1904,1905,1940,1940,1940,1908,1908,1996,1996,1996,1973,1973,1973,1905,1893,1893,1905,1922,1923,1923,1905,1900,1907,1923,1905,1912,1906,1923,1908,1921,1926,1912,1912,1921,1910,1925,1925,1984,1908,1908,1908,1895,1922,1924,1920,1908,1908,1906,1911,1918,1925,1921,1921,1918,1999,1999,1999,1923,1923,1958,1958,1958,1958,1913,1913,1929,1959,1924,1910,1910,1910,1926,1961,1961,1961,1905,1908,2005,1886,1904,1904,1879,1884,1892,1941,1956,1956,1956,1956,1956,1956,1956,1956,1956,1915,1915,1915,1915,2006,2006,1893,1910,1896,1896,1903,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1953,1953,1967,1967,1907,1896,1970,1970,1970,1970,1970,1970,1970,1888,2007,2007,2007,1997,1997,2006,2006,2006,2006,2006,2006,2006,2006,1908,1908,1908,1908,1908,1902,1902,1902,1902,1908,1908,1908,1912,1997,1997,1997,1997,1997,1998,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1904,1890,1925,1886,1884,1906,2010,1889,1884,1924,1900,1894,1894,1890,1908,1935,1891,1898,1899,1904,1890,1890,1890,1890,1920,1920,1920,1998,1998,1998,1998,1998,1998,1998,2001,2001,2001,2001,2001,2001,2001,2001,2001,1996,1996,1996,1996,1996,1996,1996,1902,1901,1901,1931,1931,1931,1961,1961,1961,1900,1885,1891,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1951,1951,1968,1981,1938,1890,1941,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,1920,1929,1929,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1974,1974,1977,1977,1977,1977,1977,1909,1910,1925,1925,1925,1925,1925,1974,1974,1974,1898,1966,1958,1958,1958,1958,1958,1958,1958,1958,1958,1958,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1973,1973,1973,1973,1959,1959,1959,1959,1959,1959,1959,1959,1908,1966,1966,1966,1966,1966,1896,1896,1926,1926,1926,1926,1904,1904,1968,1968,1968,1968,1968,1908,1961,1981,1981,1961,1961,1961,1961,1960,1953,1953,1953,1953,1953,1900,1900,1900,1900,1925,1925,2001,2001,2001,1953,1953,1904,1904,1904,1962,1962,1962,1962,1962,1905,1939,1974,1974,1974,1974,1974,1974,1967,1967,1967,1967,1985,1985,1985,1906,1893,1970,1970,1970,1970,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1966,1966,1966,1966,1966,1966,1966,1961,1961,1890,1887,1895,1890,1886,1902,1890,1890,1907,1890,1890,1890,1915,1915,1915,1915,1915,1915,1890,1890,1900,1886,1895,1890,1900,2010,1890,1890,1886,1886,1890,2001,1890,1900,1888,1908,1884,1888,1889,1890,1890,1885,1890,1890,1920,1965,1965,1902,1999,1923,1923,1912,1923,1890,1896,1953,1934,1956,1894,1949,1936,1944,1947,1948,1930,1896,1949,1949,1949,1944,1948,1948,1948,1947,1947,1947,1948,1917,1953,1947,1947,1928,1924,1928,1902,1900,1900,1950,1892,1892,1948,1948,1948,1949,1949,1949,1949,1948,1948,2011,1946,1948,1949,1945,1945,1896,1894,1923,1923,1924,1925,1908,1908,1908,1910,1908,1925,1923,1929,1929,1936,1929,1948,1903,1922,1926,1933,1949,1906,1952,1952,1900,1953,1908,1905,1905,1905,1900,2005,1890,1985,2003,1905,1948,1955,1955,1930,1926,1941,1941,1939,1895,1948,1948,1927,1931,1970,1970,1970,1947,1901,1951,1941,1947,1947,1949,1946,1952,1952,1953,1941,1939,1939,1939,1895,1951,1942,2012,1947,1951,1963,1963,1951,1951,1954,1962,1885,1949,1949,1949,1949,1949,1973,1973,1973,1973,1942,1954,1953,2006,1917,1915,1953,1953,1949,1949,1953,1953,1955,1930,1910,1925,1955,1921,1921,1922,1949,1949,1949,1952,1952,1903,1923,2011,1900,1913,1922,1921,1900,1938,1921,1926,1900,1922,1948,1949,1900,1906,1949,1959,1966,1915,1948,1928,1925,1922,1949,1922,1906,1954,1954,1983,1983,1983,1967,1967,1921,1952,1953,2011,2011,1947,1947,1953,2000,1952,1952,1952,1951,1955,1960,1961,1961,1960,1960,1960,1960,1959,1971,1956,1956,1956,1956,1957,1957,1957,1957,1957,1942,1939,1924,1924,1951,1926,1951,1926,1926,1948,1926,1925,1949,1942,1944,1944,1941,1940,1942,1929,1922,1951,1945,1910,1941,1941,1941,1942,1996,1947,1966,1938,2005,1936,1927,1927,1951,1953,1896,1957,1941,1914,1921,1905,2005,1955,1900,1910,1921,1923,1946,1910,1942,1952,1955,1955,1955,1955,1955,1946,1946,1946,1952,1946,1946,1946,1956,1956,1956,1946,1948,1955,1960,1957,1957,1956,1954,1954,1954,1954,1954,1996,1954,1954,1956,1955,1956,1956,1959,1973,1973,1956,1952,1954,1955,1953,1954,1954,1954,1954,1953,1954,1954,1953,1953,1949,1949,1949,1953,1952,1948,1948,1954,1954,1953,1948,1953,1953,1954,1954,1949,1953,1953,1953,1956,1961,1907,1956,1959,1955,1955,1955,1948,1948,1952,1960,1947,1943,1943,1942,1942,1949,1940,1955,1955,1948,1954,1910,1910,1954,1955,1953,1953,1953,1953,1953,1955,1955,1954,1955,1955,1954,1953,1954,1954,1954,1954,1954,1954,1954,1954,1943,1943,1954,1902,1890,1915,1951,1951,1983,1954,1948,1924,1962,1951,1954,1951,1951,1951,1951,1951,1951,1906,1954,1952,1927,1902,1896,1910,1910,1948,1924,1954,1925,1942,1949,1923,1959,1952,1952,1957,1951,1925,1925,1921,1921,1970,2005,1922,1927,1919,1951,1926,1910,1910,1928,1951,1951,1947,1968,1949,1949,1949,1949,1922,1941,1947,1952,1926,1926,1954,2008,2008,2008,1921,1956,1947,1949,1949,1951,1951,1941,1931,1921,1921,1928,1915,1910,1905,1905,1954,1954,1954,1954,1948,1919,1919,1958,1909,1907,1907,1985,1922,2010,2010,1923,1922,1922,1922,1954,1947,1947,1922,1955,1953,1952,1962,1962,1921,1949,1949,1910,1949,1921,1924,1931,1947,1947,1947,1949,1955,1955,1948,1948,1947,1947,1947,1947,1911,1926,1924,1953,1908,1952,1914,1914,1947,1949,1948,1948,1949,1949,1906,1947,1947,1950,1948,1946,1946,1942,1948,1920,1961,1961,1941,1942,1934,1955,1940,1939,1948,1947,1935,1923,1925,1948,1948,1930,1931,1931,1929,1930,1925,1925,1947,1947,1929,1929,1941,1920,1953,1953,1959,1959,1943,1943,1931,1929,1916,1921,1921,1921,1932,1927,1929,1929,1940,1908,1948,1922,1924,1924,1922,2000,1922,1922,1954,1906,1888,1890,1890,1880,1880,1918,1905,1905,1951,1951,1886,1954,1954,1998,1942,1942,1914,1888,1954,1954,1954,1954,2004,1900,1905,1888,1924,1924,1888,1905,1905,1969,1969,1969,1969,1969,1969,1960,1960,1961,1961,1961,1961,1971,1971,1971,1971,1971,1906,1997,1997,1997,1997,1997,1997,1911,1898,1898,1888,1895,1901,1958,1958,1958,1958,1958,1890,1895,1900,1900,1900,1905,1908,1908,1908,1910,1890,1895,1901,1913,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1898,1898,1952,1952,1964,1964,1964,1900,1896,1886,1886,1890,1936,1890,1886,1886,1886,1890,1896,1883,1890,1894,1886,1886,1890,1896,1890,1890,1887,1886,1886,1890,1886,1890,1888,1888,1900,1889,1893,1890,1886,1896,1900,1906,1999,1916,2006,1890,1886,1884,1890,1904,1890,1890,1982,1982,1890,1890,1890,1986,1986,2007,1885,1885,1885,1885,1890,1887,1905,1905,1905,2012,1888,1888,1894,1923,1890,1888,1888,1888,1896,1910,1910,1914,1903,1890,1889,1889,1890,1895,1900,1900,1926,1880,2000,2000,2000,1890,1890,1890,1906,1906,1900,1894,1906,1910,1910,1926,2005,1890,1895,1900,1900,1888,1890,1896,1890,1888,1890,1890,1888,1890,1895,1890,1974,1890,1896,1896,1903,1903,1911,1888,1905,1891,1984,1984,1984,1890,1890,1890,1890,1953,1900,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1895,1895,1929,1929,1890,1890,1890,1907,1890,2007,1899,1900,1906,1889,1889,1890,1910,1900,1901,1915,1889,1890,1905,1964,1964,1890,1890,1896,1896,1890,1904,1904,1896,1891,1892,1892,1885,1891,1890,1895,1886,1890,1906,1906,1906,1906,1985,1900,1893,1890,1890,1922,1971,1971,1971,1971,1901,1900,1900,1900,1900,1890,1961,1961,1905,1901,1905,1906,1999,1900,1965,1895,1905,1890,1906,1998,1998,1950,1950,1950,1902,1902,1928,1901,1896,1890,1890,1896,1896,1890,1885,1890,1895,1890,1890,1901,1901,1901,1900,1900,1890,1890,1910,1890,1890,1900,1892,1900,2006,1961,1961,1961,1965,1890,1900,1900,1890,1906,1932,1890,1905,1905,1922,1895,1895,1968,1968,1968,1962,1968,1968,1968,1900,1900,1890,1890,1890,1895,1924,1924,1901,1890,1923,1900,1886,1900,1900,1898,1895,1895,1895,1890,1890,1956,1895,1903,1905,1909,1890,2010,2010,2010,2011,2011,2011,1902,1902,1902,1924,2008,2008,1890,1890,1927,1927,1929,1932,1928,1912,1928,2012,2007,1907,1916,1911,1917,1919,1919,1940,1924,1910,1910,2007,1922,1922,1925,1905,1999,2005,1915,1925,1923,1923,1911,1923,1920,1952,1924,1997,1929,1942,1928,1986,1955,1926,1920,1926,1909,1925,1909,1911,1911,1956,1926,1931,1936,1927,1927,1925,1938,1928,1931,1937,1916,1910,1907,1924,2002,1906,1912,1910,1910,1912,1911,1911,1904,1917,1906,1890,1925,1909,1927,1890,1909,1933,1908,1922,1923,1928,1924,1925,1925,1925,1905,1905,1948,1917,1922,1919,1907,1912,1951,1907,1989,1906,1896,2004,1911,1969,1969,1906,1923,1906,1921,1968,1968,1968,1923,1932,1906,1906,1901,1901,1913,1906,1924,1915,2005,1906,1904,1898,1904,1906,1906,1994,1994,1995,1926,1906,1901,2007,2007,1906,1906,1926,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1910,1907,1986,1986,1962,1962,1962,1960,1960,1960,1960,1926,1926,1947,1947,1947,1947,1947,2000,1967,1967,1970,1961,1961,1961,1961,1961,1908,2008,2008,2008,1924,1924,1924,1924,1924,2005,1922,1922,1905,1910,1910,1909,1900,1894,1894,1905,1969,1969,1922,1900,1962,1962,1962,1895,1907,1907,1905,1905,1909,1908,1910,1928,1910,1910,1915,1916,1915,1895,1895,1907,1890,1954,1900,2007,2011,2011,1983,1910,1922,2001,2001,1922,2008,2008,1912,1908,1914,1919,1919,2004,1905,1972,1981,2005,1994,1994,2002,2002,2008,2008,1991,1991,1999,1992,1994,1987,2003,2006,2004,2012,1979,2005,2008,1987,1999,2002,2012,2001,2004,2004,2005,2004,2000,2007,1983,1994,1994,2005,1984,1984,1993,1981,1982,1981,1981,1981,1981,1988,1999,1999,1985,1985,1951,1951,1993,1999,1999,1999,2005,1996,2001,2000,1998,2007,2007,2007,1932,1906,1948,2001,2003,1946,1984,1984,1984,1985,1985,1984,1984,1985,1991,1996,1991,1984,1994,1988,1993,2007,2008,2008,2011,2011,2011,2011,2001,2007,1984,1991,2007,2007,2007,1978,1979,1971,1971,1971,1971,1971,1971,1971,2000,2006,1993,1994,2003,2005,1955,1955,2005,1991,1983,2001,1935,1935,1991,2005,1993,2000,1916,1896,1983,1997,1951,2005,1985,1985,2006,2006,2006,2006,2007,1985,1999,1997,2006,1994,2008,2008,1985,1985,1990,1990,1974,1974,1974,1974,2001,2006,1987,1988,1988,1989,1997,1997,1994,1994,1991,1997,1997,1997,1997,1997,1997,1998,1978,1940,1983,1983,1983,1985,1985,1985,1985,1999,1999,1999,1991,2007,2005,2000,2004,2004,2004,2007,2008,2008,2008,2008,2009,1918,2002,1999,2002,1999,2000,2002,1999,2005,1999,2012,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,1996,1996,1996,1996,1996,1996,1996,1996,1996,1947,1999,1999,2004,2004,1996,1996,1996,1996,1996,1997,1997,1998,1998,1998,2000,2000,1998,1998,1998,1998,1949,2000,2003,2005,2006,2006,2006,2001,2001,2003,2003,2003,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,2000,2001,2002,2002,2002,2003,1999,2004,2004,2006,2007,2007,2007,2007,2007,1924,1986,1998,1998,1995,1985,1985,1994,1994,1997,1999,1999,1999,1999,1996,1996,1998,1998,1999,2000,1998,1998,2000,2000,2000,2000,2000,2000,2006,2006,2006,2000,1948,1996,2001,1985,1985,1985,1994,1994,1994,1994,2000,2000,2000,2000,2000,2001,2001,2001,2001,2001,2001,2006,2006,2006,1955,1954,1955,1955,1956,1967,1999,1954,1955,1955,1962,1961,1962,1957,1985,1990,1990,1993,1994,1994,1991,1982,1994,2008,2012,1943,1969,1968,2011,2011,2006,2008,1961,2000,1988,1978,1983,1978,1978,1978,1979,1978,1978,1978,1987,1987,1982,1978,1978,1981,1978,1978,1978,1984,1994,1995,1995,1949,2012,2012,1949,2002,1952,1948,2005,1947,1942,1952,1952,1955,1931,1924,1937,1937,1940,1923,1942,2004,1999,1946,2004,1949,1949,1949,1949,1940,1938,1940,2005,2007,2006,1937,1929,2012,2012,1946,1928,1942,1947,1941,1940,1940,2005,1942,2002,1967,1939,1938,1948,1937,1937,1940,1956,1929,1938,1955,1930,1930,1924,1940,1926,1940,1939,1936,1933,1938,1938,1939,1942,1950,1940,1938,1938,1939,1946,1942,2009,1941,1942,2010,1942,1951,1951,1946,1956,1954,1956,1952,1952,1953,1953,1952,2012,2012,1951,1948,2012,1952,2012,2012,1950,1952,2011,2011,1933,1954,1954,1953,1955,1953,1954,1951,2007,1942,1942,1942,1950,1947,1942,1911,1951,1952,1951,1951,1951,1952,1951,1952,2011,1993,1992,1928,1928,2008,1912,1933,1949,1928,1892,2004,1922,1905,1927,1913,1919,1926,1917,1917,1926,1926,2012,2005,1916,1916,1922,1919,1920,1919,2011,2012,1928,1928,1925,1928,1928,1938,1946,1932,2012,1930,1928,1937,1929,1929,1929,1928,1928,1929,1932,1929,1911,1929,2007,1927,1927,1915,1885,1927,1926,1926,1922,1925,1925,2012,2012,1925,1929,1919,1919,2012,1928,1925,1929,1930,1930,1930,2007,1926,1927,1927,1929,1928,1928,1936,1932,1932,1970,1970,1970,1970,1911,1923,1922,1926,1896,1926,1917,1927,2004,2012,2012,1925,1910,1964,1910,2009,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1925,1925,1925,1925,1925,1910,1910,1911,1911,1880,1888,1910,2007,2007,1903,1901,1920,1916,2012,1925,1925,1915,1914,1915,1909,1942,1921,1895,1900,1925,1927,2005,1927,1974,1974,1974,1974,1974,1974,1974,1974,1974,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1925,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1997,1997,1910,1923,1930,1910,2004,1922,1946,1950,1950,1925,1924,1922,2004,1925,1924,1922,1922,1925,1924,1900,1928,1924,1905,1908,1920,1924,1926,2008,1924,1922,1920,1920,1923,2005,2006,2007,2007,1923,1923,1906,2006,1920,2002,1920,1926,1921,1911,1913,1917,1906,1924,1923,1922,1920,1920,1924,1924,1924,2010,1890,1925,1922,1896,2004,2011,2012,1918,2008,2011,2011,2012,1913,1906,1955,1924,2011,1911,1911,2005,2010,2010,1911,1911,1911,1911,1911,1906,1922,1911,1922,1906,1906,1906,1906,1909,1909,2011,1949,1925,1911,1924,1911,1929,1910,1939,2006,2007,2007,2012,1921,1926,1927,2011,1931,1928,1928,1929,1926,1926,1926,2011,1925,1926,1929,1926,2004,1931,1931,1924,2012,1925,1893,1924,1922,1922,1903,1924,2012,1924,1921,1921,1922,1922,2005,1925,1926,2010,2007,2011,2008,1924,1924,1923,1928,2012,1925,1929,1925,2008,2006,2005,1926,1925,1925,1927,1927,1921,1921,1924,1936,2012,1921,1921,1921,2007,1912,2011,2010,1912,1911,2012,1912,1910,2007,2007,1915,1920,1909,1937,1960,1940,2011,2012,2012,2011,1914,1882,1997,1915,2010,2010,1900,1925,1940,1940,1922,1925,1908,1908,1895,1895,1895,1922,1925,1922,1922,1923,1908,1891,1899,1906,1900,1904,1903,1891,1904,1895,1925,1885,1893,1907,1902,1888,1905,1917,1900,1951,1901,1901,1900,1894,1900,1903,1896,1896,1890,1936,1936,1900,1905,1904,1904,1895,1895,1895,1924,1904,1893,1909,1909,1890,1890,1909,1930,1904,1901,1918,1905,1905,1900,2007,1906,1908,1900,1890,1904,1904,1906,1927,1900,1902,1890,1897,1905,1927,1898,1898,1896,1900,1910,1901,1905,1907,1902,1890,1910,1906,1908,1901,1905,1904,1904,1921,1921,2006,1923,1885,1905,1906,1907,1907,1923,2005,1905,1890,1912,1900,1893,1905,1926,1907,1901,1907,1919,2006,2008,1925,1925,1893,1906,1890,1905,1903,1927,1927,1902,1905,1901,1900,1929,1929,1925,1922,1905,1926,2008,1885,1927,1890,1890,1898,1908,1908,1911,1909,1909,1909,1906,1908,1904,1905,2007,1905,2010,1910,1890,1906,2008,2008,2008,2010,2010,2010,1909,1923,1903,1903,1907,1909,1900,1903,1905,1905,1910,1909,1910,1910,1905,1929,1905,1907,1908,1933,1905,1911,1911,1910,1908,1997,1951,1949,1949,1952,1910,1910,1910,1953,1953,1953,1953,1952,1954,1949,1908,1921,1911,1905,2012,1888,1927,1925,1925,2012,2004,2004,1951,1900,1951,1910,1954,1954,1954,1949,1950,1950,1949,1949,1951,1951,1951,1951,1951,1951,1951,1951,1957,1957,1950,1951,1950,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1963,1951,1951,1951,1952,1951,1951,1951,1952,1951,1951,1951,1951,1951,1952,1952,1951,1952,1954,1952,1952,1954,1952,1952,1952,1952,1952,1953,1963,1963,1952,1952,1953,1953,1956,1952,1953,1952,1952,1952,1952,1952,1952,1953,1952,1952,1952,1952,1952,1952,1952,1954,1952,1952,1953,1953,1953,1950,1942,1956,1956,1956,1949,1949,1949,1949,1937,1938,1952,1952,1929,1955,1966,1947,1952,1953,1948,1950,1932,1946,1946,1946,1948,1965,1936,1951,1942,1946,1946,1946,1946,1946,1939,1939,1948,1940,1939,1939,1939,1939,1951,1951,1951,1935,1935,1948,1937,1927,1929,1944,1949,1953,1927,1940,1957,1930,1955,1955,1955,1936,1936,1934,1936,1933,2003,2005,2006,1922,1937,1935,1939,1934,1949,1933,1934,1938,1980,1945,1938,1938,1925,1939,1943,1955,1942,1943,1931,1936,1935,1935,2000,2000,2000,1940,1939,2011,2011,1938,1940,1955,1955,1941,1952,1952,1955,1947,1951,2010,2010,1943,1943,1940,1937,1930,1936,1942,1940,1952,1946,1946,1947,1984,1956,1956,1959,1963,1964,1952,1985,1960,1954,1936,1930,1950,1953,1947,1948,1947,1947,1947,1947,1947,1947,1947,1947,1947,1950,1951,1951,1947,1948,1955,1948,1948,1948,1951,1951,1951,1952,1952,1952,1954,1954,1954,1953,1953,1953,1953,1954,1953,1954,1954,1955,1938,1934,1924,1924,1929,1929,1939,1929,1934,1929,1955,1955,1955,1929,1929,1929,1949,1929,1936,1945,1925,1936,1929,1934,1929,1934,1929,1929,2010,1929,1929,1959,1940,1930,1935,1948,1957,1957,1934,1931,1931,1973,1929,1929,2004,1940,1978,1938,1940,1940,2001,1932,1932,1936,1936,1934,1940,1951,1972,1937,1953,2010,1937,1943,1954,1940,1938,1936,2005,1940,1940,1940,2000,1941,2000,1956,1956,1958,1959,1962,1962,1955,1955,1955,2001,2010,2005,2005,2005,2005,1948,2000,1955,1955,1955,1938,1955,1948,1954,1938,1959,2003,1953,1955,1955,1949,1949,1952,1955,1955,1948,1954,1946,1955,1954,1954,1954,1954,1954,1954,1954,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1926,1950,1953,1953,1954,1953,1953,1947,1956,1956,1948,1948,1943,1940,1950,1940,1940,1940,1954,1998,2002,1929,1941,1942,1934,1934,1946,1956,1935,1951,1955,1938,2011,1960,1930,1952,1955,1955,1961,1955,1935,1955,1955,1955,1955,1957,1954,1955,1948,1947,1947,1953,1988,1988,1983,1983,1983,1983,1983,1983,1983,1930,1935,1932,1934,1948,2011,2011,2011,2011,1980,1980,1973,2002,1959,1959,1941,1946,1942,2000,1947,1948,1954,1940,1940,1940,1940,1940,1940,1949,1949,1948,1952,1940,1958,1888,1960,1965,1948,1954,1954,1940,1948,1940,1946,1940,1940,1947,1938,2009,2009,1940,1959,1959,1948,1943,1942,1942,1942,1948,1949,1949,1948,1948,1948,1948,1948,1945,1945,1948,1948,1952,1949,1957,1957,1951,1955,1955,1952,2001,1953,1953,1953,1955,1953,1953,1953,1953,1955,1955,1953,1953,1953,1954,1955,1953,1955,1956,1955,1955,1955,1955,1954,1954,1955,1955,1954,1955,1955,1954,1987,1954,1954,1954,1954,1956,1951,1954,1954,1953,1953,1951,1953,1953,1953,1953,1966,1951,1951,1951,1951,1952,1952,1952,1955,1952,1952,1952,1951,1952,1952,1953,1952,1952,1953,1953,1955,1955,1955,1954,1954,1955,1954,1954,1954,1954,1954,1955,1955,1955,1955,1955,1954,1954,1956,1955,1956,1955,1955,1955,1955,1954,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1954,1955,1955,1955,1955,1955,1954,1957,1956,1955,1957,1957,1960,1959,1952,1952,1952,1952,1955,1952,1952,1952,1953,1952,1954,1953,1953,1953,1953,1953,1953,1952,1953,1955,1955,1955,1955,1957,1955,1954,1954,1954,1955,1954,1954,1956,1954,1954,1954,1954,1954,1954,1952,1952,1952,1952,1952,1952,1954,1955,1955,1955,1956,1955,1957,1957,1958,1957,1956,1957,1955,1950,1955,1955,1956,1958,1984,1942,1937,1959,1978,1956,1956,1954,1954,1954,1954,1954,1954,1954,1956,1954,1954,1955,1955,1955,1954,1955,1954,1954,1955,1955,1955,1954,1954,1954,1954,1954,1954,1954,1954,1954,1956,1955,1956,1999,1937,1954,1959,1959,1961,1955,1955,1955,1955,1959,1959,1959,1952,1962,1929,1953,1955,1954,1955,1955,1954,1958,1955,1948,1955,1941,1941,1939,1953,1954,1954,1960,1960,1957,1984,1984,1984,1984,1956,1974,1974,1929,1962,1961,1961,1956,1955,1940,1947,1964,1948,1948,1950,1953,1953,1953,1953,1953,1953,1955,1954,1954,1955,1955,1955,1954,1954,1954,1984,1984,1984,1984,1986,1986,1994,1995,1996,1995,1996,1995,1959,1999,1959,1963,1964,2004,1954,1954,1954,1955,1955,1955,1956,1956,1956,1956,1954,1959,1957,1957,1957,1956,2005,1955,1955,1956,1956,1955,1955,1943,1943,1958,1957,1957,1958,1958,1958,1958,1958,1958,1958,1958,1959,1959,1950,2006,2006,2006,2006,2006,2006,1955,1952,1950,2002,2002,1940,1957,1957,1957,1960,1961,1977,1953,1953,1953,1954,1954,1953,1954,1954,1954,1954,1954,1953,1954,1954,1954,1953,1954,1954,1954,1954,1954,1954,1954,1953,1953,1955,1955,1955,1956,1953,1954,1954,1954,1954,1954,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1962,1962,1953,1953,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1958,1954,1954,1954,1954,1954,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1955,1953,1953,1954,1954,1954,1953,1953,1954,1954,1954,1954,1954,1906,1922,2006,1929,2012,2012,2012,2012,2008,2008,1908,1908,1910,1908,1910,2009,2009,1927,1926,1926,1900,1908,1893,1910,1902,2006,2006,2006,1910,1905,1927,1909,1926,1890,1904,1927,1927,1927,1955,1955,1955,1955,1902,1907,1912,1924,1910,1910,1900,1905,1922,1914,1914,1914,1914,1905,1910,1910,1910,1910,1910,1900,1930,1890,2006,1925,2008,1910,1905,2004,2005,1892,1900,1900,1904,1905,1910,1895,1888,1936,1885,2007,2007,2009,1926,1885,1885,1988,2000,1926,1993,1897,1890,1890,2003,1910,1910,1929,1890,1890,1890,1999,1925,1929,1910,1928,1939,1933,1910,1921,1929,2011,2011,2011,2011,2007,1896,1907,1924,1891,2012,2001,2009,1896,1925,1907,1926,1908,1910,1911,1896,1904,1904,1889,1896,1891,2008,1896,1906,1900,1903,1890,1919,1919,1914,1921,2001,1908,1923,1941,1913,1926,2000,1922,1922,1906,1954,2007,1891,2012,2012,1911,1912,1928,1925,2009,2011,2011,1955,1911,1911,1890,2009,2009,1909,2007,2010,2010,2011,1900,1922,2001,2001,1990,1927,1921,1999,1912,2010,1904,1911,1926,1926,1946,1923,1913,2012,2011,2011,1928,1928,2010,2010,2010,1922,1922,1922,1921,1924,1920,1920,2011,1922,1919,1920,1917,1920,1917,2010,1907,1921,1925,2012,1911,1925,1922,1911,1939,1920,1921,1929,1928,1927,1927,1903,1917,1910,1926,1925,1930,2011,1912,1912,1910,2009,2006,2006,1923,1907,1926,1928,1926,1926,1926,1896,2012,1916,1976,1923,1932,2012,2011,1927,1928,1926,1925,1925,2007,1922,1922,2011,1925,1924,1953,1922,1931,1925,1925,1952,1928,1922,1922,1923,1951,1928,1926,1896,1906,1904,1926,2005,1960,1956,1956,1924,1935,1935,1927,1928,1929,1956,1956,1956,2007,1994,1928,1938,1950,1921,1921,1932,1969,1896,1922,1968,1925,2002,1928,1909,1938,1942,1945,1928,2006,2000,1937,1928,1928,1938,1924,1928,1947,1947,1926,1942,1924,1926,1935,1910,1910,1934,1934,1938,1937,1941,1912,1908,1908,1962,1908,1922,1891,1930,1908,1928,1926,1925,1925,1925,1931,1941,1924,1929,1929,1925,1925,2008,1926,1946,1923,1923,2006,1929,2007,1954,1952,1976,1975,1976,1976,1955,1957,1968,1967,1967,1962,1937,1927,1924,1948,1938,1930,1928,1926,1925,1930,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1951,1951,1948,1951,1947,1941,1941,1942,1942,1939,2007,2005,1963,1941,1948,1951,2005,2002,1939,1932,2011,2001,1947,1947,1947,1947,1948,1948,1951,1955,1948,1947,1947,1948,1986,1983,1982,1982,1982,1983,1983,1983,1942,1951,1941,1942,2007,1948,2005,1942,1942,2005,2005,1924,1914,1939,1940,1925,2012,1997,1928,1909,1928,1925,1924,1911,1911,1940,1930,1930,1949,1940,1936,1928,1941,1930,1949,2002,2003,1942,1951,2001,2010,2006,2006,2011,2011,2011,1946,1946,1997,1946,1949,2011,1994,1994,1948,1948,1943,2007,1948,1949,1994,1946,2012,1960,1960,2008,2008,2008,1908,2008,2010,1928,1929,1940,1925,1925,1928,2005,1915,1949,1927,2004,2007,2005,1941,2005,1944,2006,1941,2012,2004,2005,2012,1940,1997,2006,2008,2005,1943,2011,2012,1945,2012,2011,2011,2012,1941,1941,2012,1941,1949,2009,1938,1948,1930,2004,2006,2006,2007,2007,2007,1941,1942,1941,1939,1942,1942,1941,1926,1951,1948,1922,1952,1952,1955,1942,1946,1946,1942,1942,1942,2002,1922,2005,2005,1946,1944,2004,1941,1949,1946,2000,1982,1997,1956,2012,1965,1960,1959,1959,1959,2011,2011,2011,1948,1928,1951,1951,2006,1949,1953,2005,1949,2006,1949,1951,1950,1951,1951,1949,1955,1948,1945,1943,1942,1931,1949,1948,1952,1951,1956,1956,1957,1957,1968,1968,1968,1968,1968,1968,1968,1951,2012,2005,2005,2005,1951,2006,1950,1948,2007,1949,1971,2002,1961,1961,1961,1961,1961,1961,2001,2012,2012,2006,2007,2000,1948,1952,2003,1950,1942,1942,1942,1942,1942,1942,1951,2008,1960,1960,1994,1994,2001,2007,2007,2007,2007,2007,1906,2006,2006,1927,1936,1909,1905,1942,1994,1893,1942,1929,1955,1896,1992,1921,1936,2006,2007,1951,1957,2006,2006,2006,2006,2006,2006,1942,1942,1926,1927,2010,2007,1948,2001,2011,1992,2005,1961,1922,2012,2007,2011,2005,2012,2012,2012,2000,1928,2012,2003,2008,2008,1994,2007,1980,1958,1958,2008,2008,2008,2008,2008,2008,2008,2006,2007,1940,2007,2012,2008,2011,1964,2001,1962,1991,1991,2000,1984,2002,1943,1940,1999,1991,1999,1948,1991,1925,2004,1945,2000,2007,1954,2012,2012,2007,2011,1927,1955,1959,1997,1997,1997,1997,1957,1956,1956,1957,1985,1958,1957,1910,1973,1910,1998,2012,1947,2003,2002,1956,1960,1942,1947,1947,1947,2006,2000,1942,1949,1950,1952,1935,2011,2011,2001,2003,1993,2005,2005,1999,1999,1998,1943,1943,1943,2012,2001,2001,2004,2005,1942,1951,2001,2005,1948,1952,2008,2008,2010,2012,2006,1955,2011,2011,2012,2005,2007,1955,2006,1993,2001,2001,2009,1946,2011,2000,2009,1958,2007,1953,2007,1951,2004,1954,2010,1951,2012,2005,2006,1972,1987,1951,1951,2007,1954,1955,1997,1949,2006,1949,1959,1959,1959,1959,1959,1959,1925,1923,1940,1923,1923,1929,1922,1923,1923,2006,2011,1923,1925,1927,1925,1923,1930,2012,2012,1926,1921,1920,1948,1925,1929,1922,1952,1925,1925,1926,1922,1927,2007,2002,1924,1906,1922,1914,1925,1926,1922,1937,1978,1924,1926,1929,1942,1942,2007,2005,2004,1924,1931,1931,1931,1924,1934,1923,1927,1925,2007,1928,1926,1926,1927,1941,1925,1931,1963,1924,1920,1928,1930,1942,1922,1926,1923,1920,1928,1994,1996,1891,1891,1942,1925,1925,1920,1943,1927,1936,1941,1940,1944,1944,1944,1941,2009,1953,1941,1941,1955,1955,1954,1955,1955,1941,1941,1940,1941,1941,1941,1941,1941,1940,1940,1950,1956,1942,1942,1941,1941,1927,1927,1939,2012,1940,1928,1949,1928,1942,1952,2006,2006,2008,2008,1955,1941,1948,1948,1947,1955,2006,1927,1926,2010,2010,2010,1947,2007,1940,1940,1950,1942,1946,1946,1954,1938,1939,1939,1940,2007,1938,1940,1940,2012,2012,2012,1931,1941,2007,1959,1957,1923,1929,1946,2001,2006,1954,1960,1963,1963,1963,1963,1963,1963,1963,1963,1954,1941,1942,1948,1948,1928,2004,2004,1910,1942,1942,1938,1942,1942,1946,1946,1948,1948,1949,1947,1947,1947,1952,1980,1924,1924,2007,2002,2003,2011,2011,2010,1928,2010,2007,2010,2010,1903,1903,2006,2007,2010,2010,2010,2010,1925,1971,1893,1893,2007,2006,2006,2007,1926,1895,2009,2009,2009,2009,1922,1954,1929,2006,2011,1927,1931,1931,1927,1927,1926,1926,1947,1910,2007,1926,1929,1919,1962,1929,1952,1900,1949,1957,1888,1888,2006,1937,1915,1928,1922,1906,2005,2003,1947,1929,1930,1930,1949,2011,2011,1918,2003,1942,1942,2012,1924,1924,1954,1931,1939,1963,1963,1908,1908,1912,1908,1949,1948,2000,2006,2008,2008,1954,1999,1998,1924,1921,1953,1950,1911,1911,1909,1927,1952,1908,1895,1944,1925,1922,1905,1931,1910,1940,1925,1915,1900,1946,1925,1925,1932,1923,1995,1946,1946,1938,1922,1953,1935,1935,1956,1895,1905,1924,1924,1930,1947,1911,1929,1909,1953,1950,1950,1925,1925,1955,1920,1947,1912,1952,1907,1952,1952,1907,1925,1954,1952,2001,1925,1900,1948,1921,1922,1948,1939,1949,1895,1926,1926,1995,1921,1921,2011,1897,1895,1951,1949,1941,1970,2012,2012,2012,2012,1972,1973,1973,1973,1946,1995,1998,1999,1998,1998,1998,1999,1950,1950,1953,1939,1994,2004,1950,1946,2000,2000,1954,1954,1998,1998,1977,2001,1974,2001,1982,1982,1984,1984,1984,1946,1999,1945,2003,1950,1933,1951,1948,1948,1948,1948,1948,1948,1948,1948,1948,1947,1947,1947,1947,1949,1949,1948,1948,1948,1948,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1951,1949,1949,1949,1949,1949,1951,1951,1951,1951,1951,1951,1951,1949,1949,1949,1949,1949,1951,1951,1952,1951,1951,1951,1953,1957,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1952,1952,1952,1952,1952,1952,1952,1953,1952,1953,1952,1952,1953,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1942,1977,1950,1998,1950,1971,1997,1997,1963,1944,1941,1970,2009,1958,1972,1949,1972,1975,1977,1948,1948,1939,2002,1949,1939,1998,1984,1948,1945,1941,2004,1949,1947,1939,1954,1955,1954,1954,1954,1954,1954,1954,1954,1954,1955,1956,1955,1955,1956,1956,1956,1956,1956,1956,1956,1956,1957,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1955,1956,1955,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1955,1961,1954,1954,1954,1957,1958,1958,1958,1957,1957,1958,1955,1956,1956,1955,1955,1955,1955,1965,1956,1955,1958,1957,1959,1956,1956,1955,1955,1957,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1962,1961,1961,1961,1961,2012,1973,1959,1960,1961,1961,1959,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1956,1956,1956,1956,1956,1956,1956,1956,1957,1957,1957,1956,1957,1957,1957,1957,1956,1957,1957,1957,1958,1958,1956,1956,1956,1956,1955,1955,1955,1955,1956,1956,1956,1955,1958,1955,1955,1955,1955,1954,1955,1955,1955,1955,1955,1955,1955,1956,1955,1955,1955,1955,1955,1955,1956,1956,1956,1956,1956,1956,1956,1957,1957,1957,1957,1957,1957,1955,1955,1955,1955,1955,1956,1962,1960,1960,1957,1956,1956,1956,1955,1956,1956,1956,1956,1956,1956,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1958,1958,1958,1958,1958,1958,1959,1959,1959,1958,1958,1958,1958,1958,1958,1958,1957,1957,1957,1958,1958,1957,1957,1957,1957,1957,1957,1957,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1957,1957,1957,1957,1957,1957,1957,1957,1957,1956,1956,1956,1957,1996,1998,1996,1998,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1957,1957,1954,2010,2010,2010,1937,1979,1940,1952,1940,1947,2001,2006,1947,1928,1963,1955,1954,1931,1931,1960,1951,1987,1946,2002,2002,1926,1965,1965,1947,1955,1946,1974,1974,1931,1959,1954,1959,1953,1953,1953,1953,1954,1954,1954,1954,1954,1954,1953,1953,1953,1953,1953,1953,1953,1954,1956,1954,1954,1954,1983,1983,1997,1997,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,1982,1982,1982,1982,1982,1982,1982,1983,1983,1983,1983,1941,1952,1953,1953,1953,1953,1956,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1958,1958,1960,1960,1955,1955,1955,1961,1957,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1959,1957,1956,1958,1958,1957,1956,1956,1961,1962,1963,1966,1963,1963,1941,1941,1949,1941,1953,2010,1953,1953,1958,1944,2012,1942,1941,1940,1939,1938,1952,1952,1951,1951,1951,1951,1951,1957,1957,1951,1951,1952,1953,1951,1953,1952,1951,1953,1954,1953,1938,1938,1952,1953,1952,1954,1953,1953,1952,1951,1953,1952,1952,1954,2009,1952,1952,2004,1952,1952,1951,1955,1953,1953,2004,2008,1953,1954,1955,2006,1955,1955,1954,1954,2006,1957,1956,1956,1956,1955,1956,1956,1956,1957,1956,1956,1959,1959,1960,1960,1960,1961,1958,1978,1974,1974,1978,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1978,1978,1978,1977,1978,1977,1977,1978,1958,1960,1958,1958,1959,1960,1956,1956,1956,1957,1959,1959,1958,1958,1958,1957,1959,1968,1959,1958,1954,1954,1957,1957,1956,1956,1956,1958,1957,1958,1956,1957,1956,1957,1957,1957,1957,1953,1957,1957,1956,1957,1955,1956,1955,1956,1956,1956,1956,1957,1957,1964,1954,1955,1954,1958,1955,1956,1941,1941,1942,1936,1923,1942,1942,1926,1935,1948,1948,1948,1923,1923,1923,1952,1941,1941,1941,1930,1925,1925,1949,1949,1942,1948,1948,1948,2000,1958,1947,1942,1926,1947,1942,1938,1925,1952,1925,1925,1927,1927,1949,1927,1948,1948,1948,1952,1925,1948,1948,1952,1933,1927,1927,1941,1953,1951,1951,1957,2003,2003,2003,1915,1915,1929,1947,1948,1948,1952,1925,1948,1948,1930,1930,1950,1950,1922,2003,1947,1947,1942,1943,1943,1941,1942,1942,1946,1946,1928,1928,1927,1925,1949,1925,1943,1943,1942,1942,1943,1943,1943,1942,1943,1943,1944,1944,1942,1942,1942,1953,1944,1948,1947,1953,1953,1949,1954,1954,1953,1953,1963,1975,1975,1953,2007,2006,2006,2006,2006,2006,2007,2007,2007,2009,2009,2002,2001,2002,2001,2004,2002,2001,2001,2002,2003,2003,2004,2005,2003,2004,2003,2002,2002,2002,2002,2002,2002,2003,2002,2002,2001,2001,2001,2002,2002,2003,2002,2002,2002,2002,2002,2001,2002,2002,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2006,2006,2006,2006,2005,2005,2006,2007,2007,2007,2007,2007,2007,2007,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2005,2004,2004,2004,2004,2005,2008,2008,1948,1905,1948,1940,1956,1956,1956,1956,1956,1956,1942,1942,1930,1941,1941,1941,1958,1916,1942,1949,1952,1948,1909,1952,1930,1930,1928,1941,1941,1955,1941,1927,1919,1941,1941,1932,1928,1940,2004,1920,1948,1952,1887,1949,1949,1954,2001,1952,1948,1949,1948,1951,1952,1951,2004,1952,2001,1946,1940,1932,1929,1929,1929,1929,1947,1940,1948,1948,1948,1946,1940,1940,1940,1941,1940,1906,1998,1949,1951,1946,1946,1941,1942,1942,1948,1942,1985,1951,1951,1940,1940,1951,1939,1949,2007,2006,1945,1945,1945,1945,1945,1945,1945,1942,1942,1942,1942,1942,1942,1942,1950,1942,1951,1942,1951,1951,1952,1951,1951,1951,1946,1946,1942,1939,1947,1950,1948,1948,1941,1942,1948,2011,2011,1951,1948,1950,1950,1951,2007,1942,1942,1944,1944,1944,1956,1956,1947,1940,1938,2006,1941,1948,1949,1948,1995,1996,1996,1996,1997,1997,1997,1997,1997,1954,1941,1939,1947,1948,2012,2012,1949,1940,1954,1946,1946,1948,1949,1963,1951,2011,2012,1947,1949,1947,1947,1947,1942,1942,1948,1946,1948,1938,1938,2005,1949,1941,1925,1949,1951,2007,1942,1947,1948,1943,1948,1947,1941,1941,1941,1941,2006,1949,1949,1949,2012,2012,1951,1938,2005,2007,2009,2009,1946,1946,2008,1938,2011,2011,1946,1951,1940,1941,1939,1949,1951,1994,1984,1984,1985,1985,1984,1984,1946,1946,1945,1947,1947,1947,1942,1930,1938,1940,1940,1916,1910,1952,1952,1945,1945,1945,1952,1948,1923,1947,1932,1939,1948,1948,1947,1947,1972,1949,1949,1950,1950,1950,1950,1949,2006,2006,1914,1891,1958,1952,1948,1940,2005,1947,1952,1952,1952,1951,1896,1948,1952,1955,1954,1931,1931,1931,1931,1955,1936,1937,1925,1928,1931,1933,1937,1927,1937,1924,1905,1931,1926,1952,1927,1927,1928,1927,1924,1924,1927,1949,1925,1931,1932,1932,1929,1928,1938,1938,1938,1937,1937,1938,1932,1932,1937,1952,1940,1940,1947,1947,1947,1954,1954,1938,1938,1951,1942,1938,1941,1941,1948,1940,1942,1930,1939,1948,2002,1952,1947,1951,1947,1954,1954,1949,1949,2005,1942,1941,1945,1939,1940,1926,1915,1915,1923,1941,1938,1938,1938,1940,1939,1916,1914,1924,1924,1924,1949,1949,1949,1980,1942,1942,1926,1925,1918,1910,1926,2011,2011,1937,2004,1906,1926,1930,1938,1938,1927,1929,1929,1927,1929,1929,1927,1933,1932,1932,1955,1931,1938,1932,1948,1948,1948,1948,1939,1928,1940,1953,1959,1959,1959,1959,1959,1959,1959,1939,1939,1939,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1972,1972,1972,1972,1951,1949,1949,1956,1947,1938,1965,1965,1940,1946,1955,1955,1940,1942,1924,1924,1936,1937,1929,1999,2004,2004,1926,1926,1926,1936,1929,1935,1936,1937,1936,1936,1936,1936,2006,1936,1936,1940,1946,1941,1973,1933,1927,1938,1939,1942,2008,1947,1955,1947,1947,1956,1953,1963,1963,1963,1963,1963,1963,1963,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1962,1962,1962,1962,1962,1962,1962,1962,1948,1958,1954,1958,1948,1946,1946,1947,1949,1940,2011,1946,1944,1944,1943,1944,1938,1951,1938,1941,1941,1941,1948,1948,1937,1941,1942,2002,2006,1939,1941,1939,1940,1942,1944,1942,1942,1946,1941,1941,1942,1940,1940,1941,1990,1990,1949,1949,1940,1940,1949,1937,1936,1991,1938,1937,1940,1940,1940,1936,1936,1937,1937,1937,2006,2000,2006,2007,2011,2001,1966,2006,2000,1996,2005,2005,1993,1951,2012,2007,2007,1951,1954,2011,1957,1957,1957,1952,2000,1998,1998,1998,1941,2004,2001,1941,2005,1941,2010,2007,1999,2004,2004,1950,2007,1953,2004,1959,1954,1954,2004,2000,2007,2007,1959,2012,2007,1955,2006,1996,1944,1944,2000,1949,1939,2006,1929,1938,1937,1934,1928,1954,1937,1938,1937,1948,1940,1978,1934,1944,1925,1925,1925,1928,1928,1931,1934,1953,2007,1940,1946,1927,1928,1929,1929,2001,2000,2000,1996,2007,1953,1938,1937,1935,1952,1924,1938,2005,1931,1949,1951,1929,1941,1949,1949,1955,1999,2004,1942,1951,1952,2010,2006,2007,1952,1947,1981,1957,2003,1952,1953,1949,2005,1948,1948,2005,2005,1955,1955,1955,2010,2011,1953,1953,1958,1956,1941,1955,1952,1958,1942,1943,2012,2008,1952,1952,2002,1956,1954,1952,1985,1953,1953,1961,2005,1954,1955,1942,2006,2006,1956,1956,1943,1943,1954,1954,1954,1954,1954,1954,1954,1950,1947,1946,1946,1943,1946,1946,1943,1943,1943,1943,1943,1947,1947,1947,1952,1948,1948,1951,1952,1948,1954,1949,1955,1952,1955,1952,1948,1953,1952,1953,2012,2008,1952,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,1950,2004,2004,2004,1954,1954,1954,1963,1960,1953,1949,1948,1951,1940,1948,1941,2005,1943,1938,1949,1939,1955,1952,1952,1966,2007,1962,1961,1963,1952,1955,1954,1953,1954,1954,1953,1953,2006,1954,2000,2012,2012,1952,2005,1954,1952,1951,1951,1953,2006,2012,2012,2006,1960,1952,1952,1951,1950,1948,1951,1951,2007,1955,2004,1956,1955,1955,2006,1955,1955,2006,1955,1955,1954,1954,1996,1962,1961,1957,1957,2012,1956,1956,1954,1957,1958,1958,1955,1956,1955,1956,1961,1962,1961,1962,1965,1973,2002,2000,1999,2000,2008,1999,2001,1999,2000,2000,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2004,2004,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1940,2004,2005,2005,2005,2006,2006,2004,2002,2002,2002,2002,2002,2003,2003,2004,2005,2006,1998,1998,1998,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1998,1998,1998,2000,1998,1999,1999,2000,1999,1998,1998,1998,1998,1998,1998,1998,1999,2000,2000,2000,1999,2000,1999,1999,2000,2000,1999,1999,2003,2005,2005,2002,2002,2002,2005,2005,2005,2005,2005,2005,2006,2006,2006,2006,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2008,2008,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2010,2011,2010,2011,2010,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2008,2009,2009,2011,2011,2011,2012,2012,2012,2012,2010,2010,2010,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2011,2011,2008,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2010,2010,2011,2010,2010,2011,2010,2011,2011,2009,2010,2010,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1968,1968,1968,1966,1966,1966,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1968,1968,1968,1968,1967,1967,1967,1967,1967,1967,1967,1967,1967,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1973,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1967,1967,1967,1967,1967,1967,1967,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1979,1963,1991,1967,1991,1994,1958,1969,1968,1968,1968,1968,1972,1973,1968,1955,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1980,1980,1980,1980,1980,1980,1980,1980,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1983,1983,1983,1983,1983,1983,1983,1983,1998,1998,1998,1998,1998,1999,1998,1999,2000,2000,2000,2000,2000,2000,2000,2000,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1995,1995,1995,1996,1998,1998,1997,1997,1996,1996,1995,1994,1998,1998,1998,1998,1998,1998,1998,1957,1993,1959,1958,1958,1957,1958,1959,1963,1964,1964,1963,1961,1960,1958,1958,1970,1959,1958,1961,1962,1960,1966,1966,1929,1959,1959,1953,1953,1953,1953,1955,2009,2009,1973,1959,1955,1927,1961,1947,1969,1945,1973,1951,1934,1968,1951,1945,1945,1951,2005,1956,1957,1953,1953,1953,1958,1958,2000,2000,2000,2000,2006,2006,2006,1956,1917,1945,1900,1973,1952,1961,2001,2006,1947,1946,1945,1945,1945,1978,1947,1947,1947,2011,2011,1958,1958,1958,1958,1956,1957,1957,1958,1959,1957,1957,1957,1957,1957,1957,1957,1957,1958,1958,1963,1963,1965,1973,1974,1974,1973,1974,1973,1974,1973,1973,1973,1973,1973,1973,1973,1973,1973,1974,1974,1974,1977,1993,1993,1993,1963,1963,1981,1981,1981,1981,1982,1983,1983,1982,1964,1960,1984,1984,1990,1997,1984,1984,1948,1948,1960,1956,1956,1957,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1959,1959,1959,1959,1960,1960,1960,1960,1960,1961,1961,1959,1960,1960,1959,1959,1959,1959,1998,1998,1998,1998,1998,1998,1952,1952,1953,1952,1952,1952,1952,1952,1952,1952,1952,1951,1951,1953,1952,1953,1947,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1954,1954,1954,1954,1954,1951,1951,1951,1951,1951,1955,1955,1952,1952,1953,1953,1953,1953,1952,1952,1952,1952,1952,1950,1953,1953,1956,1983,1983,1976,1977,1998,1998,1947,1947,1939,1939,1956,1956,1956,1985,1956,1956,1956,1952,1957,1959,1948,1985,1986,1986,1953,1953,1954,1953,1953,1953,1953,1953,1953,2004,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,1954,1955,1955,1955,1953,1955,1954,1954,1954,1954,1953,1953,1954,1954,1961,1961,1963,1981,1973,1969,1969,1969,1965,1949,1960,1960,1955,1955,1955,1956,1920,1956,1954,1955,1956,1955,1955,1921,1955,1955,1955,1954,1954,1954,1956,1956,1956,1956,1956,1956,1956,1957,1957,1959,1958,1958,1958,1958,1954,1954,1954,1954,1954,1954,1953,1953,1953,1953,1953,1953,1954,1954,1954,1960,1964,1963,1964,1965,1966,1966,1965,1966,1965,1966,1966,1966,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1976,1978,1977,1977,1977,1978,1978,1967,1967,1967,1978,1978,1978,1978,1978,1978,1978,1979,1979,1979,1979,1979,1979,1979,1979,1980,1984,1984,1984,1984,1985,1997,1997,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1953,1953,1954,1954,1953,1953,1953,1954,1954,1954,1954,1954,1955,1955,1955,1955,1955,1955,1955,1955,1955,1954,1955,1955,1955,1955,1953,1954,1954,1955,1955,1950,1954,1961,1958,1958,1957,1978,1978,1977,1957,1957,1957,1958,1958,1958,1958,1957,1960,1960,1961,1958,1960,1956,1956,1956,1956,1956,1956,1956,1958,1956,1956,1957,1958,1958,1957,1957,1957,1957,1958,1958,1957,1957,1958,1958,1959,1959,1960,1966,1968,1967,1967,1967,1968,1967,1967,1967,1961,1963,1962,1963,1963,1961,1962,1961,1968,1964,1956,1959,1960,1953,1980,1980,1980,1980,1980,1982,1982,1982,1982,1982,1983,1983,1983,1992,1983,1983,1985,1984,1984,1984,1984,1983,1983,1986,1986,1986,1986,1985,1985,1986,1997,1997,1997,1997,1997,1997,1997,1997,1997,1982,1982,1982,1982,1982,1983,1983,1982,1982,1983,1983,1983,1983,1983,1992,1993,1993,1980,1980,1980,1980,1982,1982,1982,1982,1982,1984,1984,1984,1984,1984,1983,1987,1987,1987,1984,1983,1983,1984,1983,1983,1983,1983,1983,1983,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1986,1983,1983,1984,1988,1985,1986,1996,1996,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1984,1984,1984,1984,1985,1985,1985,1985,1985,1995,1995,1995,1995,1995,1995,1995,1986,1985,1985,1985,1984,1985,1984,1986,1986,1986,1985,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1966,1966,1964,1972,1965,1928,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1976,1976,1976,1976,1977,1977,1977,1977,1974,1974,1974,1974,1974,1977,1977,1960,1970,1962,1962,1960,1960,1972,1972,1972,1972,1966,1966,1966,1967,1966,2003,1970,1970,1970,1970,1970,1970,1970,1971,1963,1966,1963,1964,1963,1963,1963,1974,1992,1970,1964,1968,1964,1964,1964,1964,1964,1965,1965,1965,1965,1965,1965,1965,1968,1968,1967,1967,1968,1968,1968,1968,1967,1978,1978,1972,1972,1972,1972,1972,1973,1973,1972,1972,1973,1973,1956,1957,1955,1955,1956,1955,1955,1956,1960,1955,1956,1970,1970,1970,1970,1970,1970,1970,1970,1963,1963,1963,1962,1963,1963,1963,1963,1960,1956,1957,1955,1953,1961,1961,1927,1927,1956,1984,1984,1985,1962,1962,1962,1962,1962,1959,1959,1955,1955,1955,1956,1956,1953,1953,1955,1953,1953,1953,1953,1954,1953,1953,1953,1953,1953,1953,1954,1953,1953,1955,1955,1954,1956,1955,1955,1982,1952,1951,1952,1952,1952,1952,1952,1953,1952,1952,1952,1952,1951,1951,1952,1951,1951,1951,1951,1952,1952,1952,1952,1952,1952,1967,1952,1952,1952,1951,1952,1951,1951,1951,1951,1951,1952,1951,1951,1951,1951,1951,1951,1952,1951,1952,1951,1952,1952,1952,1953,1952,1952,1955,1955,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1953,1953,1953,1951,1951,1951,1951,1951,1951,1951,1951,1951,1950,1951,1951,2006,1949,1949,1949,1949,1949,1951,1949,2005,1949,2012,1949,2007,2006,2010,2012,2012,2003,2012,2012,1951,1952,1951,1951,2005,1951,2005,1951,1951,1956,1956,1951,1954,2011,1951,1951,2011,2012,2012,1952,1954,1952,2007,1951,1951,2004,1950,1952,2007,1953,1957,1957,1953,1952,1951,2006,2006,1953,2005,1951,1951,1954,1957,1973,1953,1955,1955,2004,2011,2011,1956,2006,1952,2012,2012,1952,1953,1953,1953,1953,1953,1953,1953,1953,1952,1952,1955,1953,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,2007,1953,1953,1952,1952,1952,1951,1953,1952,1952,1953,1953,1953,1953,1953,1953,1954,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1957,1953,1957,1957,1956,1954,1954,1955,1954,1954,1954,1966,1967,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1967,1967,1966,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1973,1973,1973,1973,1964,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1952,1969,1965,1966,1966,1966,1966,1969,1974,1967,1967,1967,1967,1967,1967,1963,1963,1963,1964,1970,1964,1972,1972,1966,1972,1971,1964,1965,1971,1968,1968,1968,1968,1968,1972,1969,1969,1969,1969,1969,1969,1971,1971,1971,1972,1972,1972,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1974,1975,1975,1975,1975,1975,1975,1975,1974,1974,1974,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1965,1964,1964,1964,1965,1973,1965,1965,1966,1966,1966,1968,1967,1966,1967,1967,1966,1967,1967,1967,1968,1969,1970,1968,1968,1968,1974,1974,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1974,1974,1974,1974,1974,1974,1974,1974,1977,1976,1977,1977,1977,1975,1974,1974,1977,1977,1985,1979,1981,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1983,1984,1991,1991,1991,1986,1985,1993,1987,1986,1986,1987,1988,1989,1987,1987,1986,1990,1990,1968,1962,1963,1963,1964,1964,1968,1968,1969,1969,1968,1967,1968,1967,1968,1976,1976,1975,1975,1975,1975,1976,1976,1976,1974,1976,1974,1976,1974,1974,1974,1974,1974,1974,1976,1976,1979,1981,1981,1981,1982,1983,1982,1982,1982,1981,1983,1983,1983,1983,1983,1982,1983,1987,1988,1985,1984,1984,1984,1985,1985,1972,1972,1972,1973,1973,1972,1972,1971,1971,1969,1972,1971,1972,1968,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1962,1962,1962,1967,1963,1963,1962,1962,1962,1967,1966,1966,1964,1962,1964,1964,1971,1969,1972,1972,1972,1972,1969,1970,1969,1971,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1980,1980,1980,1980,1980,1979,1979,1981,1981,1981,1981,1981,1981,1981,1981,1981,1979,1979,1979,1981,1980,1980,1980,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2006,2006,2006,2006,2006,1964,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1984,1984,1984,1985,1986,1997,1997,1997,1997,1997,1997,1997,1997,1974,1973,2012,2011,2011,2012,2012,2012,2011,2011,2011,2010,2011,2011,2011,2011,2011,1963,1963,1965,1963,1963,1963,1963,1970,1970,1968,1963,1963,1963,1969,1970,1970,1970,1970,1970,1969,1969,1970,1969,1968,1968,1968,1968,1968,1968,1969,1964,1969,1969,1967,1967,1967,1969,1969,1968,1968,1968,1968,1968,1968,1970,1970,1970,1970,1969,1973,1972,1972,1972,1973,1973,1973,1973,1973,1973,1973,1972,1972,1972,1972,1972,1972,1969,1969,1969,1969,1969,1969,1970,1970,1970,1970,1970,1971,1971,1970,1971,1971,1971,1971,1971,1972,1971,1971,1971,1971,1971,1971,1970,1970,1971,1969,1969,1963,1963,1963,1963,1968,1968,1973,1973,1968,1974,1968,1969,1964,1964,1964,1964,1964,1964,1964,1964,1972,1972,1972,1972,1972,1973,1973,1973,1973,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1973,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1970,1970,1971,1971,1971,1970,1971,1971,1971,1971,1970,1971,1968,1967,1966,1967,1967,1966,1967,1969,1971,1971,1971,1973,1972,1969,1969,1971,1970,1974,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1969,1965,1965,1966,1966,1966,1964,1965,1963,1971,1971,2002,2004,2004,2004,2004,1962,1964,1964,1963,1964,1965,1965,1972,1963,1963,1963,1963,1962,1964,1962,1963,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1973,1973,1973,1973,1973,1972,1973,1972,1976,1974,1974,1974,1974,1974,1976,1974,1974,1975,1974,1975,1976,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1960,1959,1959,1957,1957,1958,1959,1960,1959,1961,1961,1962,1958,1958,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1956,1957,1957,1956,1956,1956,1956,1956,1956,1956,1956,1956,1979,1979,1979,1979,1998,1998,1998,1998,1998,1998,1998,1998,2006,2003,2012,2012,2003,2003,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1983,1976,1976,1976,1976,1976,1978,1972,1969,1969,1969,1975,1975,1976,1976,1976,1978,1978,1978,1978,1978,1980,1980,1978,1978,1978,1980,1980,1980,1980,1981,1981,1983,1984,1984,1984,1982,1982,1982,1982,1982,1986,1986,1986,1986,1986,1987,1986,1988,1987,1990,1990,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1984,1984,1984,1984,1984,1984,1970,1970,1970,1970,1971,1972,1972,1972,1972,1972,1972,1972,1970,1970,1970,1970,1971,1972,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1999,1998,1998,1998,1998,1998,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1963,1994,1969,1967,1968,1964,1969,1968,1999,1999,1999,1999,1999,1999,1999,1963,1971,1971,1963,1963,1971,1963,1964,1964,1963,1964,1970,1970,1963,1963,1963,1971,1969,1963,1963,1963,1963,1964,1971,1971,1971,1970,1970,1970,1970,1970,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1972,1973,1972,1972,1973,1973,1989,1988,1988,1989,1979,1985,1989,1985,1982,1976,1976,1976,1974,1974,1973,1973,1990,1976,1971,1973,1973,1974,1977,1977,1978,1979,1970,1979,1977,1989,1979,1977,1978,1964,1965,1964,1964,1965,1963,1964,1964,1974,1962,1963,1959,1959,1959,1959,1960,1959,1973,1961,1961,1961,1961,1961,1961,1960,1960,1959,1959,1959,1959,1962,1962,1962,1959,1959,1959,1957,1960,1960,1958,1958,1958,1958,1958,1958,1957,1958,1957,1957,1957,1957,1957,1957,1957,1957,1971,1971,1971,1971,1971,1972,1972,1972,1972,1972,1972,1972,1972,1973,1973,1973,1973,1973,1973,1966,1969,1966,1966,1966,1966,1966,1969,1968,1997,1971,1971,1970,1971,1966,1973,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1976,1976,1976,1976,1977,1976,1976,1976,1977,1988,1994,1972,2004,1973,1973,1973,1973,1973,1975,1975,1972,1973,1973,1973,1973,1978,1978,1978,1979,1983,1995,1996,1994,2000,1993,1993,1994,1997,1978,1979,1979,1979,1979,1979,1979,1980,1980,1978,1995,1995,1995,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2003,2003,2003,2003,2003,1977,2004,2004,1977,1977,1977,1978,1978,1978,1977,1977,1977,1978,1977,1977,1977,1977,1977,1977,1978,1978,1978,1978,1978,1984,1984,1981,1981,1981,1983,1983,1983,1983,1983,1982,1981,1983,1983,1983,1981,1983,1982,1982,1981,1982,1982,1982,1982,1982,1982,1983,1983,1983,1983,1981,1982,1983,1983,1983,1983,1981,1981,1980,1981,1981,1981,1981,1981,1981,1981,1982,1982,1981,1981,1981,1982,1983,1981,1981,1981,1980,1980,1980,1980,1982,1982,1982,1982,1982,1982,1982,1980,1982,1982,1982,1982,1982,1982,1982,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1984,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,1975,1975,1975,1977,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1983,1983,1985,1985,1985,1985,1985,2003,2003,2004,2004,2004,2005,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,1974,1976,1974,1974,1974,1974,1974,1974,1974,1986,1978,1978,1978,1978,1978,1974,1979,1974,1974,1974,1979,1996,1996,1996,1996,1996,1996,1997,1997,1997,1997,1998,1997,1997,1997,1997,1997,1998,1998,1998,1998,1998,1999,1998,1998,1998,1998,1998,1998,1998,1999,1998,1998,1998,1998,1998,1998,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1996,1997,1997,1997,1997,1997,1996,1997,1996,1997,1997,1997,1998,2000,1999,1998,2000,1999,1999,1999,1999,1999,1999,1998,1998,1998,1997,1996,1996,1997,1997,1996,1997,1997,1997,1997,1997,1997,2000,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998],"yaxis":"y","type":"scattergl"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Before 1980 (1: Yes, 0: No)"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Year Built"}},"legend":{"tracegroupgap":0},"title":{"text":"Year built vs. before1980"}},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="aa07b9f5-1121-4ebe-b48a-27144f144782" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("aa07b9f5-1121-4ebe-b48a-27144f144782")) {                    Plotly.newPlot(                        "aa07b9f5-1121-4ebe-b48a-27144f144782",                        [{"hovertemplate":"before1980=%{x}\u003cbr\u003eyrbuilt=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"","showlegend":false,"x":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,0,0,0,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,0,0,1,1,0,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,0,0,0,1,0,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,1,1,0,1,1,0,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,1,0,1,1,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,1,0,0,0,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,1,0,0,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,0,0,1,1,0,1,1,0,0,1,1,1,1,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,0,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,0,1,0,0,1,1,1,1,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,0,1,1,0,0,0,1,0,0,1,1,1,1,1,1,0,1,1,1,0,0,0,1,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,1,1,0,1,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,0,1,0,1,1,1,1,1,0,0,0,1,1,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,0,0,0,1,1,0,0,0,1,0,1,0,1,0,0,1,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,1,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,0,0,1,1,0,0,1,0,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,1,0,1,1,1,1,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,1,0,1,1,1,0,0,0,0,1,0,0,1,0,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,0,1,0,1,1,1,0,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,0,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,1,0,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,0,0,0,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"xaxis":"x","y":[2004,2005,2005,2005,2005,2005,2005,2005,2006,2006,2006,2005,2003,2005,2004,2005,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2005,2005,2005,2005,2005,2005,2005,2005,2005,2004,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2006,2006,2006,2005,2005,2005,2011,2006,2006,2006,2005,2005,2006,2009,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2010,2010,2011,2012,2012,2010,2010,2011,2011,2012,2011,2011,2012,2012,2012,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2012,2012,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2012,2012,2012,2011,2011,2011,2011,2012,2012,2012,2012,2012,2011,2011,2012,2012,2011,2011,2012,2012,2012,2011,2011,2012,2011,2011,2012,2011,2011,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2012,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2012,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2010,2010,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2010,2010,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2011,2011,2010,2011,2011,2010,2010,2011,2011,2012,2012,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2012,2010,2012,2011,2012,2011,2011,2010,2010,2011,2010,2011,2011,2011,2011,2012,2010,2010,2007,2006,2007,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2006,2006,2006,2005,2005,2008,2012,2012,2008,2011,2010,2012,2010,2012,2010,2010,2011,2011,2012,2006,2012,2012,2012,2006,2006,2007,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2012,2012,2012,2012,2012,2012,2012,2012,2013,2002,2002,2002,2003,2003,2003,2003,2003,2003,2003,2004,2006,2005,2005,2005,2004,2004,2004,2004,2004,2004,2004,2004,2003,2003,2002,2003,2003,2003,2003,2003,2002,2002,2005,2005,2005,2005,2006,2006,2006,2006,2006,2006,2006,2010,2010,2012,2005,2005,2005,2005,2005,2005,2006,2006,2006,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2006,2006,2006,2006,2006,2007,2007,2007,2006,2006,2006,2006,2008,2008,2009,2009,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2003,2003,2003,2003,2003,2004,2004,2003,2003,2004,2005,2005,2006,2006,2005,2005,2007,2007,2004,2004,2004,2004,2004,2004,2004,2005,2005,2005,2005,2005,2004,2004,2004,2004,2004,2004,2004,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2006,2006,2006,2006,2006,2006,2006,2006,2006,2007,2007,2007,2007,2007,2007,2006,2006,2006,2007,2006,2006,2006,2008,2006,2006,2006,2006,2006,2006,2006,2007,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2007,2007,2003,2003,2003,2003,2003,2003,2003,2009,2009,2010,2010,2004,2002,2004,2003,2003,2003,2003,2002,2003,2006,2007,2004,2004,2004,2004,2010,2010,2010,2011,2003,2006,2006,2006,2004,2003,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2004,2007,2007,2007,2010,2011,2011,2011,2010,2005,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2005,2005,2005,2005,2005,2011,2011,2005,2004,2004,2004,2004,2004,2011,2005,2005,2004,2004,2006,2004,2004,2006,2007,2011,2011,2012,2011,2011,2011,2005,2006,2005,2005,2005,2005,2004,2004,2007,2006,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2011,2010,2011,2010,2010,2010,2010,2010,2010,2011,2009,2009,2009,2011,2011,2011,2011,2011,2011,2011,2011,2011,2008,2010,2010,2010,2010,2010,2010,2011,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2011,2010,2010,2010,2010,2010,2010,2010,2010,2009,2001,2003,2001,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2003,2003,2003,2003,2002,2002,2003,2004,2006,2006,2006,2006,2006,2005,2005,2005,2005,2005,2005,2004,2006,2007,1999,1999,1999,1999,1999,1999,1999,1999,1999,1998,1998,1999,1999,1999,1999,1999,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2001,2000,2001,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,1971,1971,1971,1972,1972,1972,1972,1972,1972,1972,1973,1973,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1973,1973,1973,1973,1972,1973,1973,1973,1973,1973,1973,1973,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,2005,2004,1999,1999,1999,1999,1998,1999,1999,1999,1999,1998,1998,1999,1999,1998,1998,1998,1998,1998,1999,1999,1999,1999,1999,2000,2000,2000,2000,2000,1999,1999,1999,2000,2000,2000,2000,2000,1999,1999,1999,1999,2000,2000,2000,2000,2000,2000,1975,1975,1974,1973,1973,1973,1973,1973,1974,1974,1974,1974,1974,1974,1974,1976,1973,1973,1974,1973,1973,1973,1973,1973,1974,1974,1974,1980,1981,1981,1980,1981,1983,1983,1981,1981,1982,1982,1981,1981,1981,1979,1979,1979,1979,1976,1976,1976,1976,1976,1997,1996,1996,1995,1983,1993,1993,1975,1975,1983,1983,1983,1983,1998,1998,1999,1999,1999,1999,2000,1999,1999,2000,1999,2000,2000,1999,1999,1999,1999,2000,2000,1999,1986,2001,1986,1986,1986,1987,1984,1984,1984,1984,1984,1984,1984,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1994,1994,1994,1994,1995,1995,1995,1995,1995,1995,1997,1998,1997,1997,1998,1996,1997,1997,1996,1996,1996,1996,1996,1996,1995,1999,1999,1999,2000,1999,1999,1999,1983,1983,1983,1983,1982,1982,1982,1982,1982,1980,1980,1980,1983,1983,1984,1984,1987,1987,1986,1986,1986,1986,1986,1987,1987,1987,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1982,1982,1982,1981,1981,1997,1996,1996,1997,1998,1998,1998,1997,1996,1998,1996,1996,1987,1986,1986,1986,1985,1985,1984,1984,1984,1986,1984,1984,1985,1985,1985,1979,1979,1979,1979,1979,1979,1979,1980,1985,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1979,1979,1979,1979,1979,1979,1980,1979,1979,1979,1979,1979,1979,1984,1979,1982,1980,1980,1981,1982,1983,1982,1982,1982,1983,1983,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1983,1983,1983,2001,2001,2001,2000,2002,2002,2002,2002,2002,2002,2001,2001,2001,2001,2001,2001,2001,2001,2001,2000,2000,2000,2012,1987,1993,1986,1993,1986,1993,1986,1986,1986,1986,1985,1985,1985,1984,1984,1984,1984,1995,1995,1995,1995,1997,1995,1996,1996,1996,1996,1996,1996,1996,1999,1999,1999,2000,2000,2000,2005,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2010,2010,2010,2012,2008,2010,2010,2010,2010,2012,2012,2012,2012,2012,2012,2012,1987,1984,1984,1984,1983,1983,1983,1983,1984,1983,1983,1983,1983,1983,1984,1984,1984,1983,1983,1983,1984,2006,2006,2006,2006,2006,2006,2007,2007,2007,2007,2010,2010,2010,2007,2007,2007,2007,2006,2007,2007,2007,2008,2010,2010,2010,2007,2007,2007,2010,2010,2010,2010,1997,1984,1996,1996,1995,1995,1995,1995,1995,1996,1998,1996,1996,1997,1998,1998,1998,1997,1998,1998,1998,1998,2003,2002,2002,2002,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2004,2004,2004,2003,2003,2003,2003,1994,1994,1993,1993,1993,1993,1993,1994,1994,1994,1994,1994,1994,1994,1994,1994,1994,1994,1997,1997,1997,1997,1997,1998,1998,1998,1998,1998,1998,1999,1999,1999,1998,1998,1998,1999,1999,1999,1998,1998,1998,1998,1999,1999,1999,1999,1998,1999,1999,2002,2002,2003,2002,2002,2002,2002,2003,2003,2003,2001,2001,2002,2002,2002,2001,2001,1984,1984,1984,1984,1984,1986,1986,1985,1985,1985,1985,1985,1985,1985,1986,1986,1986,1986,1992,1991,1991,1992,1987,1992,1991,1991,1990,1990,1990,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1987,1994,1991,1992,2001,2001,2000,2000,2000,2000,2000,2000,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2001,2001,2001,2000,2000,2000,2000,2003,2003,2003,2002,2002,2003,2003,2003,2003,2003,2003,2003,2003,2003,1985,1986,1986,1986,1986,1985,1985,1985,1985,1985,1985,1999,1999,2000,2000,2002,2002,2001,2001,2001,2002,2002,2002,2001,2002,2001,2001,2001,2002,2002,2001,2001,2002,2001,2001,2001,2001,2001,2002,2002,2002,2002,2002,2002,2002,2002,1999,1997,2002,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2002,2000,2000,2000,2000,2000,2000,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2002,2001,2001,2001,2001,2001,2001,2001,2001,2001,2002,2002,2002,2002,2002,2002,1987,1987,1987,1987,1988,1992,1992,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1999,1999,1999,1999,1999,1999,2000,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2001,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,2001,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2003,2002,2002,2002,2002,2002,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,1985,1985,1991,1992,1992,1992,1994,1985,1985,1985,1993,1985,1985,1985,1985,1984,1991,1985,1985,1985,1985,1985,1984,1984,1984,1984,1991,1991,1985,1985,1985,1986,1986,1987,1987,1990,1991,1991,1991,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1971,1968,1968,1967,1967,1968,1970,1969,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1969,1969,1969,1998,1971,1997,1968,1968,1967,1968,1966,1967,1967,1967,1967,1968,1968,1966,1967,1966,1966,1967,1967,1967,1966,1966,1967,1967,1967,1967,2000,1971,1969,1969,1999,1981,1968,1966,1966,1966,1966,1969,1967,1967,1968,1969,1969,1969,1969,1969,1969,1969,1968,1968,1967,1968,1977,1977,1998,1970,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1970,1970,1972,1971,1971,1971,1971,1971,1971,1972,1972,1972,1972,1972,1972,1972,1972,1973,1973,1975,1975,1975,1975,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2007,2004,2004,2004,1977,1978,1978,1980,1978,1978,1979,1979,2007,1999,1980,1980,1980,2000,2000,1998,1998,2000,2000,1998,1997,1983,1983,1983,1983,1983,1983,1983,1985,1985,1983,1983,1999,1999,1999,1998,1999,1999,1999,1998,1999,1999,1999,1999,1999,1998,1999,1999,1999,1999,2000,2000,1999,1999,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2002,2002,2002,2003,2003,2003,2003,2003,2003,2003,2003,2003,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2010,2010,2011,2011,2010,2010,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2011,2011,2011,2011,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2009,2010,2010,2011,2010,2010,2010,2010,2011,2010,2011,2010,2008,2009,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2009,2008,2008,2009,2008,2008,2008,2010,2010,2010,2010,2011,2010,2010,2009,2009,2009,2004,2004,2004,2004,2003,2003,2003,2004,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2006,2006,2006,2005,2005,2005,2006,2005,2010,2011,2011,2011,2011,2011,2011,2006,2006,2006,2006,2006,2006,2006,2005,2005,2005,2006,2006,2008,2006,2005,2005,2007,2006,2005,2005,2005,2006,2005,2010,2005,2004,2004,2005,2005,2005,2005,2005,2005,2005,2006,2005,2005,2005,2006,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2004,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2006,2006,2010,2010,2010,2010,2006,2007,2007,2007,2008,2008,2008,2009,2009,2009,2009,2009,2009,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2006,2006,2006,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2005,2005,2006,2005,2005,2005,2005,2005,2005,2006,2005,2007,2006,2006,2006,2006,2006,2007,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2010,2010,2008,2010,2010,2010,2010,2010,2010,2010,2010,2008,2010,2010,2007,2005,2005,2005,2005,2006,2002,2002,2003,2003,2002,2002,2003,2003,2003,2003,2003,2002,2002,2002,2002,2002,2002,2002,2003,2004,2004,2002,2002,2002,2002,2002,2003,2003,2003,2003,2003,2002,2002,2005,2005,2005,2005,2005,2005,2005,2002,2003,2003,2003,2003,2003,2003,2003,2002,2006,2006,2008,2010,2008,2007,2007,2007,2007,2007,2006,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2002,2003,2003,2003,2003,2003,2003,2003,2003,2002,2002,2003,2003,2003,2003,2002,2003,2003,2003,2003,2003,2002,2003,2003,2003,2003,2003,2003,2003,2003,2002,2003,2003,2003,2004,2004,2004,2004,2004,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2005,2006,2005,2006,2004,2002,2002,2005,2005,2005,2006,2006,2010,2010,2008,2008,2008,2010,2010,2007,2008,2010,2010,2010,2010,2008,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2007,2007,2007,2007,2007,2007,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2008,2008,2011,2011,2011,2011,2011,2011,2010,2008,2010,2010,2008,2011,2011,2011,2011,2011,2011,2011,2011,2007,2007,2007,2007,2007,2008,2009,2010,2010,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2012,2012,2012,2007,2007,2007,2007,2007,2007,2007,2007,2010,2010,2011,2011,2009,2007,2011,2011,2011,2011,2007,2010,2010,2011,2011,2007,2007,2011,2011,2011,2011,2010,2010,2010,2011,2011,2010,2010,2010,2010,2011,2007,2007,2007,2010,2011,2010,2008,2008,2008,2008,2008,2008,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2011,2011,2012,2012,2011,2011,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2011,2011,2012,2011,2011,2011,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,1953,1952,1952,1952,1952,1954,1951,1951,1952,1952,1952,1952,1952,1953,1952,1952,1952,1952,1953,1954,1951,1951,1952,1952,1952,1952,1955,1952,1952,1952,1953,2006,2006,2006,2006,2006,2006,2006,1953,1953,1953,1953,1953,1953,1953,1953,1953,1952,1952,1952,1952,1956,1958,1958,1955,1952,1953,1953,1952,1952,1952,1952,1953,1953,1953,1953,1953,1953,1953,1953,1953,1952,1952,1953,1953,1953,1953,1953,1954,1955,1954,1955,1954,1954,1954,1954,1954,1954,1954,1954,1955,1955,1952,1952,1981,1981,1952,1953,1952,1953,1954,1954,1953,1953,1953,1953,1952,1954,1953,1953,1953,1957,1957,1954,1954,1954,1954,1953,1953,1955,1952,1952,1952,1954,1954,1954,1954,1952,1954,1953,1948,1948,1948,1949,1949,1950,1949,1949,1948,1948,1951,1948,1948,1947,1951,1956,1949,1949,1948,1949,1949,1948,1947,1948,1948,1947,1952,1947,1947,1948,1949,1947,1947,1947,1947,1949,1949,1949,1949,1946,1954,1947,1947,1947,1947,1947,1946,1946,1946,1945,1950,1976,1976,1947,1947,1949,1949,1947,1949,1951,1947,1946,1951,1946,1946,1949,1948,1948,1948,1948,1948,2010,1901,1948,1949,1949,1948,1948,1946,1948,1949,1954,1954,1952,1952,1952,1952,1952,1951,1951,1951,1954,1954,1954,1952,1951,1951,1951,1952,1952,1952,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1950,1950,1951,1951,1950,1950,1950,1950,1950,1949,1950,1949,1951,1949,1949,1949,1949,1952,1952,1949,1949,1949,1947,1947,1949,1949,1947,1947,1947,1948,1952,1948,1964,1964,1954,1954,1954,1956,1956,1956,1955,1953,1954,1955,1954,1954,1954,1954,1954,1955,1955,1955,1953,1951,1953,1953,1953,1952,1952,1951,1952,1952,1955,1954,1954,1954,1954,1954,1954,1954,1955,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1950,1950,1950,1950,1950,1950,1950,1950,1949,1953,1954,1954,1954,1950,1949,1952,2002,2002,2002,2002,2002,2001,1951,1951,1948,1948,1947,1934,1934,1940,1951,1951,1936,1936,1932,1932,1933,1941,1951,1951,1928,1928,1928,1924,1927,1927,1928,1928,1949,1906,1949,1948,2005,1948,1951,1946,1939,1939,1947,1951,1948,1926,1927,1915,1924,1932,1932,1932,1913,1922,1919,1951,1928,1948,1946,1924,1949,1949,1926,1938,1938,1940,1933,1932,1924,1924,1924,1924,1925,1925,1918,1924,1921,1921,1923,1923,1923,1918,1918,1925,1912,1923,1922,1923,1925,1914,1921,1923,1927,1924,1947,1947,1952,1947,1947,1947,1947,1947,1947,1947,2004,1948,1948,1948,1948,1949,1949,1951,1951,1951,1951,1952,1947,1946,1952,1952,1952,1941,1952,1949,1948,1948,1947,1947,1942,1942,2012,2012,1947,1947,1947,1949,1951,1951,1950,1950,1951,1949,1949,1951,1951,1951,1951,1951,1948,1948,1948,1948,1942,1942,1942,1942,1946,1946,1946,1948,1926,1925,1931,1932,1914,1908,1908,1926,1913,1911,1913,1926,1926,1926,1924,1926,1927,1929,1930,1929,1950,1929,1941,2004,1948,1948,1948,1926,1926,1932,1933,1932,1941,1941,1948,1933,1933,1926,1931,1928,1931,1942,1925,1925,1931,1914,1925,2007,1924,1911,1925,1925,1922,1911,1911,1911,1925,1926,1911,1907,1921,1898,1913,2006,1926,1926,1928,1926,2012,1922,1925,1925,1924,1906,1906,2002,1909,2008,1919,1956,1924,1906,2012,1893,1905,1925,1910,1926,1913,1913,1925,1925,1925,1895,1895,1921,1926,1927,1927,1927,1927,1928,1924,1924,2006,1924,1924,1923,1910,1911,1911,1912,1911,1921,1913,1908,1893,2011,1929,1929,1920,1923,1923,1911,1925,1928,1910,1926,1927,1900,1925,1915,1925,1910,1907,1907,1915,1925,1905,1913,1905,1914,1909,1923,1911,1911,1910,1911,1911,1910,1915,1919,1917,1910,1920,1920,1909,1921,1913,1912,1906,1910,1912,1916,1911,1902,1952,1909,1905,1951,1907,1932,1910,1910,1910,1914,1915,1915,1920,1920,1928,1921,1922,1926,1929,1931,1927,1932,1928,1928,1940,1914,1951,1922,1908,1906,1906,1927,1906,1914,1916,1916,1919,1932,1920,1927,1927,1941,1929,1925,1925,1925,1925,1932,1954,1925,1911,1903,1925,1926,1929,1928,1928,1929,1926,1920,1939,1890,1922,1922,1920,1919,1933,1983,1927,1922,1929,1925,1921,1910,1930,1924,1913,1908,1952,1952,1952,1941,1941,1930,1930,1928,1939,1916,1916,1924,1923,1923,1930,1923,1923,1926,1926,1913,1913,1930,1919,1926,1930,1928,1926,1938,1927,1927,1927,1948,1929,1940,1925,1925,1932,1925,1909,1942,1929,1931,1940,1925,1930,1925,1932,1931,1936,1936,1907,1931,1940,1948,1948,1948,1952,1952,1939,1939,1947,1930,1931,1941,1926,1927,1927,1927,1945,1912,1949,1948,1948,1948,1947,1947,1947,1947,1952,1947,1947,1947,1948,1948,1948,1948,1949,1950,1949,1949,1949,1949,1949,1949,1949,1951,1948,1948,1948,1948,1948,1948,1949,1948,1948,1948,1948,1948,1954,1954,1948,1948,1948,1948,1948,1949,1949,1949,1950,1950,1950,1950,1950,1950,1948,1948,1948,1948,1948,1948,1948,1949,1949,1949,1946,1943,1943,1942,1949,1946,1949,1941,1942,1941,1941,1942,1941,1941,1940,1941,1941,1924,1925,1922,1917,1999,1925,1910,1948,1942,1941,1942,1942,1942,1950,1942,1938,1938,1937,1939,1932,1937,1932,1932,1937,1932,1938,1933,1938,1938,1938,1938,1938,1924,1925,2012,2012,2012,1924,1921,1954,1925,1949,1949,1932,1932,1925,1927,1922,1936,1931,1933,1933,1934,1934,1952,1942,1942,1948,1937,1942,1942,1933,1931,1937,1929,1937,1925,1924,1924,1929,1927,1927,1928,1929,1925,1928,1928,1925,1925,1935,1928,1928,1925,1923,1928,1927,1928,1928,1927,1928,1927,1929,1928,1928,1934,1938,1929,1937,1930,1930,1929,1930,1939,1935,1930,1937,1926,1924,1929,1929,1991,1929,1930,1930,1932,1929,1942,1942,1939,1930,1930,1952,1948,1948,1948,1948,1948,1948,1948,1948,1948,1948,1948,1948,1948,1937,2006,2012,1925,1948,1947,1948,1948,1949,1941,1939,1947,1954,1939,1951,1938,1938,1908,1941,1938,1942,1937,1942,1942,1942,1912,1912,1910,1910,1947,1947,1940,1941,1946,1941,1941,1941,1951,1906,1947,1947,1942,1933,1928,1911,1898,2012,1938,2003,1938,1937,1925,2004,2004,2004,2004,2005,2005,2004,2004,2004,2004,2004,2004,2004,2002,2004,2004,2004,2004,2005,2004,2006,2006,2006,2005,2005,2011,2011,2011,2011,2010,2006,2006,2010,2007,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2006,2012,2008,2008,2007,2007,2007,2007,2007,2007,2007,2006,2006,2006,2006,2006,2006,2007,2007,2006,2007,2007,2010,2010,2010,2010,2010,2009,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,1950,1955,1949,1949,1949,1949,1952,1952,1950,1952,1952,1952,1952,1952,2002,2002,2002,2002,2002,2002,2002,2002,2002,2003,2003,2003,2003,2003,2003,2002,2002,2002,2002,2002,2002,2004,2004,2004,2004,2004,2004,2012,2012,2012,2012,2012,2012,2009,2009,2009,2009,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2010,2010,2010,2010,2010,2010,2010,2010,1947,1925,1946,1941,1948,1947,1946,1946,1947,1949,1945,1945,1945,1946,1946,1941,1918,1927,1942,1942,1942,1941,1941,1942,1941,1925,1925,1942,1942,1942,1942,1942,1942,1942,1942,1941,1941,1941,1948,1923,1947,1947,1948,1948,1939,1954,1901,1949,1947,1947,1926,1924,1940,1924,1948,1929,1925,1940,1925,1962,1959,1959,1962,1951,1948,1949,1948,1948,1957,1925,1948,1952,1952,1952,1952,1983,1939,1950,1931,1951,1951,1942,1942,1942,1942,1942,1951,1948,1914,1951,1951,1951,1951,1951,1933,1933,1947,1947,1947,1947,1947,1947,1948,1947,1924,1953,1954,1934,1956,1951,1951,1954,1948,1948,1940,1948,1948,1947,1947,1947,1947,1947,1949,1949,1947,1947,1965,1953,1953,1953,1947,1949,1950,1949,1949,1950,1950,1950,1950,2004,2005,2005,2005,2004,2004,2004,2004,2004,2004,2005,2004,2004,2004,2004,2005,2005,2004,2004,2005,2005,1894,1962,2002,1982,2005,2005,1928,1889,1927,1924,1940,1948,1940,1938,1954,1947,1947,1953,1953,1926,1953,1921,1947,1947,1947,1953,1956,1953,2003,2003,2003,2003,2003,1894,1947,1921,1914,1922,1937,1891,1943,2000,1932,1915,1890,1901,1940,1939,1939,1890,1948,1947,1949,1949,1948,1949,1949,1949,1947,1948,1948,1948,1948,1948,1948,1948,1948,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1947,1948,1948,1948,1951,1953,1949,1948,1911,1910,1954,1923,1923,1906,1946,1948,1949,1949,1900,1910,1953,1947,1947,1947,1947,1947,1947,1947,1947,1961,1961,1954,1954,1959,1923,1956,1929,1929,1903,1903,1922,1910,1914,1914,1908,1909,1906,1900,1922,1922,1906,1906,1906,1924,1913,1922,1922,1922,1910,1910,1910,1927,1998,1948,1942,1941,1948,1942,1942,1942,1942,1941,1942,1941,1941,1941,1941,1942,1948,1948,1948,1948,1941,1941,1942,1942,1942,1947,1941,1941,1927,1927,1928,1925,1925,1948,1948,1948,1948,1948,1927,1948,1948,1925,1942,1942,1942,1942,1942,1941,1941,1941,1927,1927,1941,1941,1936,1942,1942,1941,1941,1942,1942,1940,1917,1924,1910,2002,1945,1945,1948,1948,1948,1910,1910,2012,2012,2012,2011,1927,1955,1949,1953,1955,1961,2012,1951,1929,1929,1921,2012,2012,1936,1954,1922,1922,1961,1906,1928,2011,2011,2011,2011,1919,1937,1954,1900,1911,1908,1910,1911,1925,1924,1960,1929,1929,1921,1921,1921,1949,1927,1929,1909,1908,1922,1910,1915,1929,1952,1952,1938,1906,1901,1901,1919,1924,1900,1908,1924,1929,1929,1923,1924,1924,1974,1890,1923,1949,1942,1933,1924,1923,1910,1910,1921,1925,1940,1925,1930,1930,1921,1923,1947,1908,1908,1906,1916,1948,1948,1948,1910,1948,1948,1955,1954,1958,1948,1948,1946,1947,1952,1941,1924,1924,1925,1946,1946,1946,1946,1955,1956,1956,1947,1947,1938,1940,2005,1921,1921,1912,2011,2011,1924,1923,1905,1961,1908,1896,1901,2008,1963,1963,2006,1904,1942,2009,2009,1940,1896,1910,1901,1906,1904,1904,1906,2008,2008,2012,2012,1905,1907,1907,1904,1904,1924,1922,1903,1912,1909,1898,1910,1925,1922,1924,1951,1906,1906,1906,1953,1916,2004,2007,1920,1910,1923,1925,1925,1923,1923,1923,1922,1922,1921,1906,1901,2005,2007,2007,2007,2007,2007,2009,2009,2010,2010,2011,2011,2011,2011,2011,2011,2011,1920,1930,1908,1954,1928,1911,1905,2006,2006,1978,1986,1903,1924,1911,1911,1956,2000,1935,1931,1931,1928,1928,1910,2010,2010,1906,1891,2010,2010,1910,1906,1951,1951,2011,2011,1949,1918,2009,1904,1908,1891,1911,1906,1908,1901,1906,1908,1908,2012,1911,1906,2012,1919,1919,1906,1912,1922,1900,1900,1914,2010,2010,1898,2012,2012,1949,1904,1922,1910,2012,1916,2007,2007,1922,1911,1926,1920,1911,1918,1918,2006,2006,2010,2010,1908,1938,1891,1926,1906,1900,1949,1920,1906,1908,1908,1931,1902,1902,2012,1906,2007,2007,2011,2011,1906,2003,2011,2011,1908,1914,1914,1912,1918,1924,1905,1905,1922,2009,1908,1908,2010,2010,2010,1912,1936,1936,1891,1926,1901,1911,1910,1906,1927,1896,1901,1901,1906,1930,1905,1896,1982,1906,1924,1908,1898,2010,2010,1906,2012,2012,1910,1928,1949,1920,1928,1927,1917,1896,1927,1907,1907,1953,1953,2008,2008,2011,1900,1924,1924,1925,1948,1900,1955,1959,1905,2011,2011,1905,1911,1911,2012,2012,1900,1896,1906,1940,2012,2012,2012,2012,1935,1932,1932,1936,1936,1903,1956,1997,1955,2005,1910,1952,1952,1950,1970,2006,1927,1910,1921,1922,1909,1904,1906,1926,1886,1905,1910,1922,1938,1958,1958,1952,1955,1952,1952,1941,1941,1941,1941,1941,1941,1954,1959,1949,1950,1950,1949,1941,1939,1902,1900,1900,1906,1933,1933,1932,1962,1949,1929,1946,1924,1928,1928,1948,1926,1951,1951,1926,1983,1930,1928,1999,1942,1910,1960,1905,1900,1909,1902,1906,1973,1973,1906,1906,2011,2011,1931,1906,1905,1903,1903,1933,1907,1909,1900,1928,1928,1928,1911,1925,1946,1922,1920,1925,1912,1912,1926,1926,1926,1925,1926,1925,1948,1925,1925,1949,1945,1925,1901,1910,1910,1910,1922,1910,1907,1906,1905,1923,1910,1910,1910,1910,1910,1908,1922,1913,1913,1926,1922,1921,1923,1945,1945,1945,1945,1951,1949,1948,1890,1890,1947,1938,1939,1905,1921,1921,1939,1951,1939,1956,1920,1910,1939,1939,1900,2012,2012,2011,2008,1942,1925,1915,1913,1929,1950,1951,1941,1900,1907,1903,1933,1903,1970,1970,1970,1970,1915,1922,1925,1910,1927,1913,1908,1920,1923,1955,1955,1929,1956,1930,1919,1925,1925,1925,1925,2011,2011,2011,1912,1937,2011,1925,1910,1906,1906,1928,1923,1925,1910,1910,1922,1921,1914,1928,1912,1912,1920,1922,1922,1921,1915,1924,1925,1924,1925,1960,1926,1896,1910,1896,1908,1906,1906,1926,1921,1941,1941,1912,1912,1923,1925,1912,1910,1938,1919,1941,1941,1941,1890,1901,1952,1952,1928,1900,1900,1895,1909,1909,1916,1915,2012,1923,1921,1912,1905,1910,1954,1905,1905,1928,1946,1946,1928,1904,1930,1921,1891,1891,2012,2003,1946,1946,1946,1905,1905,1905,1908,1960,1910,1905,1895,1911,1911,1905,1994,1925,1927,1927,1928,1940,1927,1928,1888,1926,1925,2009,2009,1926,1925,1895,1954,1951,1955,1907,1907,1954,1895,1961,1956,1943,1943,1943,1905,1911,1910,1941,1941,1938,1927,1925,1905,1900,1902,1907,1918,1918,1910,1895,1895,1980,1891,2002,1917,1917,1950,1948,1948,1948,1948,1948,1921,1890,1890,1890,1958,2010,1948,1949,1949,1946,1949,1886,1943,1943,1943,1943,1943,1943,1947,1947,1943,1908,1896,1945,1945,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1946,1951,1951,1967,1925,1906,1906,1943,1908,1923,1923,1930,1926,1925,1925,1900,1900,1908,1925,1926,1925,1925,1926,1904,1904,1899,1911,1911,1891,1908,1896,1925,1959,1959,1896,1900,1891,1899,1933,1933,1933,1909,1906,1906,1907,1907,1906,1895,1911,1999,1911,1911,1896,1913,1913,1911,1911,1901,1903,1959,1959,1903,1904,1886,1886,1906,1891,1947,1947,1921,1896,1959,1925,1925,1913,1916,1949,1936,1918,1925,1925,1953,1954,1905,1905,1905,1923,1911,1906,1903,1894,1907,1923,1929,1955,1886,1886,1887,1955,1955,1974,1974,1933,1956,1958,1923,1923,1917,1910,1984,1984,1967,1949,1897,1897,1906,1914,1952,1896,1896,1886,1891,1896,1896,1896,1896,1901,1896,1896,1925,1942,1891,1896,1896,1896,1906,1906,1889,1889,1890,1890,1952,1952,1901,1891,1956,1896,1896,1896,1912,1924,1924,1911,1940,1911,1911,1916,1901,1901,1953,1921,1908,1998,1999,1904,1915,1915,1886,1928,1896,1911,1886,1886,1890,1926,1895,1946,1905,1904,1886,1925,1886,1952,1928,1891,1891,1896,1930,1910,1945,1900,1912,1906,1910,1898,1898,1906,1891,1941,1886,1887,1932,1932,1896,1896,1901,1917,2007,2007,1886,1890,1892,1889,1922,1888,1891,1910,1889,1896,1896,1902,1948,1903,1953,1886,1896,1886,2001,1886,1901,1999,1889,1886,1882,1882,2004,1896,1896,1896,1928,1892,1889,1890,1890,1888,1888,1893,1890,1888,1957,1957,1957,1947,1940,1925,1952,1952,1948,1946,1946,1948,1948,1948,1948,1948,1947,1901,1930,1890,1888,1888,1890,1893,1893,1946,1927,1894,1894,1901,1887,1887,1919,1955,1955,1886,2005,1946,1946,1948,1948,1942,1942,2011,1936,1922,1904,1900,1939,1906,1950,1950,1959,1923,1923,1939,1942,1949,2010,1922,1894,1928,1938,1945,1945,1938,1938,1927,2012,1951,1947,1947,1892,1892,1953,1896,1927,1907,1938,1938,1938,1953,1973,1948,1948,1930,1932,1950,1949,1949,1949,1948,1947,1949,1949,1946,1923,1923,1925,1945,1945,1945,1915,1888,2011,2011,1926,1938,1936,1936,1896,2004,1901,1999,1999,2006,1923,1942,1942,1953,1917,1920,1920,1915,1952,1956,1956,1956,1912,1926,1926,1901,1902,1927,1951,1886,1886,1949,1949,1949,1949,1949,1927,1890,1935,1929,2003,2003,1926,1894,1949,1937,1937,1942,1953,1908,1948,1941,1923,1917,1917,1913,1910,1908,1922,1923,1923,1926,1925,1925,1948,1896,1926,1926,1926,1926,1931,1931,1937,1938,1926,1901,1901,1938,1938,1999,1912,1895,1952,1910,1952,1895,1949,1913,1911,1911,1911,1922,1929,1925,1925,1924,1924,1910,1910,1927,1927,1927,1928,1928,1928,1963,1963,1963,1963,1963,1954,1945,1945,1945,1945,1928,1928,1896,1896,1923,1949,1894,1986,1986,1891,1891,1927,1927,1922,1886,1951,1949,1942,1945,1942,1942,1951,1952,1925,1962,1936,1936,1909,1926,1906,1912,1912,1952,1902,1905,1914,1953,1926,1929,1925,1925,1926,1926,1924,1924,1946,1930,1930,1944,1925,1925,1925,1925,1925,1926,1927,1922,1922,1910,1910,2011,2011,1929,1925,1925,1949,1948,1948,1948,1938,1938,1938,1923,1923,1923,1952,1952,1951,1952,1952,1949,1951,1951,1951,1945,1945,1945,1941,1941,1941,1948,1953,1953,1951,1949,1949,1952,1952,1948,1947,1947,1949,1946,1942,1946,1959,1959,1948,1947,1947,1941,1941,1952,1962,1962,1952,1952,1946,1946,1944,1944,1948,1931,1951,1951,1951,2007,1933,2007,1955,1952,1952,1922,1951,1949,1949,1956,1971,1952,1952,1948,1922,1931,2002,1911,1910,1887,1901,1926,1924,1914,1957,1912,1912,1922,1924,1910,1942,1942,1940,1929,1890,1890,1890,1924,1924,1925,1929,1916,1914,1928,1922,1922,1910,1925,1925,1922,1921,1916,1917,2011,1922,1922,1913,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1921,1924,1896,1896,1939,1924,1890,1899,1899,1899,1890,1886,1886,1908,1896,1886,1890,1887,1890,1887,1890,1886,1986,1986,1892,1886,1910,1910,1910,1910,1902,1886,1886,1905,1905,1896,1896,1900,1907,1907,1908,1906,1905,1905,1888,1890,1890,1890,1890,1909,1909,1886,1911,1888,1900,1900,1890,1890,1890,1890,1888,1888,1888,1890,1890,1890,1890,1890,1910,1910,1885,1885,1904,1904,1895,1900,1890,1904,1904,1888,1888,1888,1888,1887,1886,1888,1888,1906,2010,1892,1896,1896,1998,1882,1882,1901,1896,1896,1886,1886,1886,1894,1894,1894,1885,1886,1886,1887,1889,1897,1886,1886,1886,1880,1890,1888,1888,1890,1886,1886,1886,1900,1888,1886,1886,1969,1886,1890,1886,1886,1886,1886,1886,1909,1909,1909,1909,1909,1888,2002,2002,2002,2002,2002,2002,1894,2006,1884,1901,1893,1887,1890,1885,1895,1886,1886,1905,1886,1890,1885,2003,1898,1895,1890,1903,1911,1900,1895,1890,1890,1890,1890,1895,1890,1873,1896,1896,1896,1896,1890,1883,1900,1900,1900,1900,1926,1926,1971,1890,1971,1890,1910,1955,1886,1907,1909,1896,1884,1884,1906,2003,1896,1896,1888,1907,1908,1923,1908,1907,1907,1907,1910,1923,1923,1923,1910,1910,1890,1890,1908,1946,1910,1910,1981,1981,1908,1908,1906,1954,1954,1907,1904,1905,1907,1904,1906,1904,1910,1906,1908,1905,1905,1890,1890,1906,1906,1910,1906,1926,1911,1910,2012,1908,2008,2012,1910,1908,1908,1906,1911,1911,1911,1906,1912,1912,1909,1909,1886,1886,1913,2005,1915,1905,1906,1888,1909,1909,1909,1909,2002,1885,1885,1885,2002,2002,2002,2002,2002,2002,2005,2005,2005,2005,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,1910,1901,1880,1884,1884,1885,1885,1886,1900,1904,1904,1904,1904,1904,1904,1904,1904,1888,1892,1903,1898,1898,1898,1898,1898,1898,2012,2012,1896,2003,2006,2006,2006,2006,1888,1888,1888,1888,1888,1888,1884,1886,2003,1886,1884,1889,1886,1882,1886,1886,1888,1890,1894,1885,1885,1961,1961,1880,1999,1894,1910,1886,1932,1888,2005,1895,1895,1897,1897,1897,1897,1880,1890,1888,1895,1880,1885,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,1958,1958,1958,2004,2004,2005,2005,1933,1933,1933,1933,2008,1903,1910,1910,1910,2006,2006,2006,2006,2005,2005,2005,2005,2005,2005,2005,1896,1896,1896,1896,1896,1896,1896,1896,1896,1896,1896,1896,1896,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2001,2001,2001,2001,2001,1920,1920,2000,2000,2000,2000,2000,2000,1886,2005,2005,2005,2005,2005,2005,1916,1916,1916,1916,1916,2000,2000,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,1896,1896,1895,1895,1997,1997,1997,1997,1891,1886,1890,1891,1886,1886,1886,2012,2012,1901,2011,1927,2007,2007,2007,2007,2009,2009,1886,1886,2010,1924,2006,1891,1891,1891,1906,1906,1896,1891,1886,1891,1886,2010,2010,1901,1901,1901,1901,1906,2010,2010,2007,1891,1886,1886,2010,2010,1891,1891,1891,1891,2011,1901,1891,1903,1890,1901,1963,2005,2005,1901,1901,1926,1920,1891,1901,1905,1913,1900,1900,1906,1906,1941,1946,1937,1936,1952,1938,1923,1921,1915,1910,1894,1890,1964,2003,1910,2007,1964,1905,1955,1904,1904,1896,1908,2011,2011,1909,2012,2012,1961,1885,2006,1900,1900,2008,2008,1959,1959,2008,2008,1887,1890,1964,1964,2011,2011,1924,1951,1955,2011,2011,2012,1900,1886,1890,1890,1890,1887,2009,2009,2009,2009,2011,2011,2011,2011,1893,1896,2011,2011,1896,1896,2010,2011,2011,1893,1911,1911,1910,2012,2012,2011,2011,2011,2012,2011,2011,2011,2012,2012,1896,1898,2005,2011,2012,1911,1880,2003,2005,2007,1889,2005,1912,1891,1948,2008,1986,1958,1886,2007,1898,1898,1898,1899,1899,1886,1906,1906,1894,1893,1900,2009,2009,2009,2009,1954,1954,2002,2002,2002,2002,2002,2002,2001,2001,2001,2007,2007,2007,2007,1890,1906,1906,1903,1899,2008,2008,2008,2008,2008,2008,2003,1880,1880,1891,2008,2008,2008,2008,2010,2011,2011,2011,1910,1910,1910,1910,2012,2012,2012,2006,2007,2007,2007,2007,2010,2010,2010,2010,2010,2010,2010,2010,2010,2012,1891,2009,2009,1907,1907,2009,2009,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2002,2002,2002,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,1984,1984,1999,1999,1999,1999,1999,1999,2000,2000,2000,2000,1886,2006,2003,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,1908,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,1996,1998,1998,1998,2007,2007,1908,1886,1886,1900,1885,1885,1884,2011,2011,2011,2011,2003,2007,2007,2007,1896,2000,2000,2000,1900,2007,2007,2007,2007,2007,2007,2007,2007,2007,2004,2004,2004,2004,2004,2004,2004,1890,1908,1911,1911,1922,1908,1908,1908,2012,2012,1890,1909,1890,1905,1890,1910,1910,1910,1885,1885,1885,1895,1903,1930,1930,1885,1885,1890,1895,2012,1899,1900,1885,1885,1905,1905,1905,1905,1905,1895,1895,1905,1910,1901,1902,1955,1906,1925,1911,1911,1955,1900,1928,1905,1905,1895,1895,1893,1890,1954,1954,1954,1913,1915,1954,1954,1954,1954,1954,1908,1908,1915,1908,1923,1893,1900,1900,1890,1900,1902,1909,1913,1900,1923,1932,1911,1909,1909,1954,1890,1910,1910,1910,1890,1909,1909,1895,1900,1909,1903,1902,1902,2005,2005,1931,1907,2002,2002,2002,1925,1904,1890,1928,1927,1927,2010,2010,1927,1925,1924,1922,1923,1915,1910,1923,1935,1928,1925,1925,1925,1890,1925,1890,1927,1923,1908,1912,1953,1930,1956,1929,1927,1922,1937,1929,1929,1923,2012,1922,1911,1930,1910,1907,1906,1926,1926,1910,1901,1908,1927,1912,1891,1891,1891,1891,1891,2011,2011,1928,1908,1885,1927,1915,1900,1996,1996,1996,1886,1915,1927,2010,1890,1906,1920,1925,1912,1912,1891,1891,1885,2003,1905,2010,2010,1885,1885,1908,1905,1905,1905,1890,1905,1905,1890,1890,1907,1910,1925,1925,1925,1908,1887,1903,1910,1910,1929,1929,1929,1929,1929,1894,1894,1894,2008,2008,2008,2008,1900,1893,1890,1916,1916,1916,1939,1939,1904,1909,1897,1922,1900,1900,1890,1890,1886,1885,1900,1900,1902,1887,1891,1896,1896,2006,2006,2006,2008,2008,1912,1905,1894,2007,2007,1900,1900,1902,1888,2010,2010,1911,1931,1931,1911,1904,1905,1881,1881,1908,1912,1912,1912,1912,1912,1916,2008,1940,1940,1940,1940,1941,1941,1973,1973,1973,1973,1925,1925,1925,1941,1941,1916,1925,1932,1941,1930,1940,1909,1908,1908,1929,1906,1906,2012,1951,1948,1955,2011,2011,1952,1885,1900,1922,2009,2009,2009,2009,2009,2011,1893,1890,1900,1900,1890,1890,1895,1892,2007,2007,2007,2011,1910,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1913,1886,2002,2002,1911,1911,1912,1906,1891,1906,1891,1891,1896,1896,1890,1890,1909,1904,1929,1899,1926,1940,1940,1930,1930,1932,1932,1932,1926,1931,1931,1931,1949,1910,1891,1891,1891,1951,1896,1896,1937,1901,2000,1906,2010,2010,1953,1927,1906,1906,1931,1937,1934,2012,1937,1930,1911,1931,1930,1931,1930,1931,1885,1928,1928,1930,1929,1929,1947,2008,1922,1911,1928,1921,1925,1925,1910,1906,2007,2010,2010,2010,2012,1910,1936,1889,1889,2008,1897,1906,1913,1910,2007,1926,1906,1953,1953,1925,1924,1922,1913,1913,2007,1941,1938,1907,1924,1924,2010,1924,2010,2010,1891,1908,2006,1892,1928,1929,1890,1900,1900,1906,1916,2003,2003,2003,2003,1912,1926,1926,1927,1914,1955,1924,1956,2008,2008,2008,1910,1925,1953,1959,1899,1899,1954,1954,1912,1929,1952,1957,1952,1925,1953,1953,1953,1952,1952,1946,1946,1924,1996,1952,1952,2011,2011,2011,1906,1906,1954,1901,1953,1891,1910,1906,1906,1952,1952,1949,1930,2010,1968,1968,1968,1924,1924,1947,1952,1952,1952,1929,1910,1925,1896,1897,1922,1952,1889,1957,1906,1954,1953,1941,1896,1926,1926,1949,1891,1891,2009,2009,1927,1952,1952,1952,1941,2006,2006,2012,1948,1937,2005,2005,1949,1896,1924,1949,1949,1949,1921,1921,1929,1999,1999,2001,1999,1999,2001,2001,2000,2001,1999,1999,2003,1940,1940,1950,1942,1936,1937,1937,1955,1937,1938,1952,1949,1951,1959,1932,1932,1927,1924,1890,1890,1947,1947,1919,1949,1948,1940,1909,1951,1951,1951,1940,1925,1907,1937,1893,1999,1949,1925,1922,1924,1938,2011,2011,1951,1949,1952,1911,1957,1923,1921,1931,1927,1983,1952,1890,1951,1953,1890,1952,1953,1951,1951,1951,1921,1952,1955,1949,1943,1952,1952,1952,1951,1992,1950,1946,1961,1943,1943,1943,1943,1949,1947,1942,1949,1921,1952,1952,1913,1900,2006,2007,1895,1905,1888,1926,1908,1904,1954,1954,1954,1900,2005,2005,1953,2008,1940,1940,1935,2006,2006,1933,1938,1935,1912,1905,1910,1910,1910,1947,1949,1949,1890,1893,1910,2006,1952,1951,1951,1944,1944,1951,1890,1906,1900,1961,1953,1953,1939,1939,1900,1940,1940,1940,1939,1939,1940,1939,1939,1954,1949,1923,1949,1949,1949,1951,1927,1927,1928,1942,1918,1952,1951,1951,1986,1986,1986,1986,1986,1986,1986,1986,1986,1986,1953,1892,1952,1946,1940,1939,1941,1941,1941,1941,1946,1941,1941,1929,1954,1952,1948,1948,1948,1954,1941,1893,1914,1913,1914,1908,1885,1885,1895,1951,1885,1941,1941,1942,1941,1941,1941,1941,1947,1999,1925,1934,1981,1956,1951,1909,1946,1928,1928,1927,1910,1906,1885,1894,1898,1964,1951,2003,1951,1951,1931,2011,2011,1931,1931,1947,1947,1947,1947,1947,1969,1980,1940,1914,1952,1907,2005,2008,1954,2011,2011,2011,2011,1900,2012,2009,2009,2011,2011,1952,2006,2006,1895,1949,2009,1951,1951,2006,2007,2011,2006,2009,1952,1953,1910,2005,1965,1907,1905,1952,1954,1894,1908,2012,2012,1954,1947,1949,1963,1900,1942,1949,1946,1951,1951,1907,1907,1907,1907,1910,1948,1948,1974,1974,1948,1998,1958,2008,2008,2008,2008,1957,1928,1942,1925,1928,1928,1928,1928,1929,1929,1929,1924,1924,1924,1924,1926,1926,1926,1926,1926,1926,1953,1920,1924,1920,1919,1919,1920,1921,1926,2000,2007,2007,1896,1896,1893,1890,1896,1913,1913,1913,1891,1891,1896,1896,1886,1923,2006,1906,2006,2006,1978,1978,1890,1890,2004,2005,1887,1900,1998,2007,2007,2007,2007,2007,2007,2007,2007,2008,2008,2008,2008,2008,2008,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,1907,1910,1908,2007,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1891,1891,1890,1890,2004,1958,1958,1958,1958,1958,1886,1898,1905,1953,1886,1886,1900,1900,1896,1896,1895,1895,2010,2010,2010,1959,1952,1948,1951,1951,1895,1938,1938,1938,1939,2008,2008,1957,1902,1885,1901,1904,1904,1904,1904,1890,1909,1947,1947,1953,1910,1907,1891,1886,1896,1896,1910,1929,2008,1952,1891,1925,1900,1900,1900,1896,1896,1886,1890,1900,1891,1901,1896,1911,1896,1911,1956,1949,1942,1942,1952,1952,1953,2012,2012,1954,1996,1996,1948,1996,1938,1979,1980,1980,1995,1995,1995,1995,1995,1952,1952,1952,1952,1952,1996,1996,1997,1997,1997,1997,1997,1952,1952,1952,1952,2011,2011,1951,1885,1880,1880,1947,1948,1930,1999,1927,1957,2011,1951,1952,1952,1939,1940,1954,1954,1989,1999,1926,1910,1910,1910,1910,1906,1906,1906,1984,2002,2002,1906,1906,1907,1924,1930,1930,2001,2001,2001,1905,1890,1890,1890,1890,1890,1890,1886,1886,1886,2002,2002,2002,2002,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1908,2011,2011,2000,2000,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1886,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1909,1909,1997,1997,1997,1997,1928,1928,1928,1928,1928,1928,1928,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,1895,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2006,2006,2006,2006,1898,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,2002,1919,1919,1919,1919,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2004,2000,2000,2000,2000,2000,2000,2000,2000,2000,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2007,2007,2007,2007,2007,2007,1896,1896,1907,1907,1907,1981,1981,1981,1885,1885,1880,1884,1985,1985,1985,1881,1902,1888,1948,1896,2007,2007,2007,2007,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1888,1984,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,1890,1885,1901,2008,2008,2008,2008,2008,2008,2008,2004,2004,2007,2007,1886,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2007,2007,2007,2007,2007,2007,2007,1888,1884,1884,1891,1891,1951,1891,1913,1913,1983,1983,1983,1983,1983,1983,1983,1983,1908,1908,1908,2008,2008,2008,2009,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1896,1896,1905,1905,1905,1905,1905,1905,1905,1903,1903,1903,1903,1903,1903,1903,1903,1903,1980,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,1938,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2006,2006,2006,2006,2006,2003,2003,2003,2003,2003,2003,1910,1910,1892,2001,2001,2001,2001,2001,1886,1999,1999,1999,1967,1998,1998,1998,1998,1897,1999,1999,1999,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2006,1941,1997,1997,1997,1997,1997,1905,1905,1905,1906,1896,1892,1890,1890,1905,1905,1905,1980,1893,1906,1910,1904,1910,1908,1888,1888,1893,1897,1890,1890,1890,1893,1893,1927,1927,1918,1906,1904,1923,1906,1906,1906,1902,1900,1900,1896,1910,1922,1917,1923,1923,1923,1890,1902,1896,1892,1900,1900,1900,1890,1972,1890,1904,1904,1904,1893,1909,1910,1898,1896,1898,1937,1898,1961,1961,1896,1904,1904,1900,1903,1908,1908,1908,1890,1898,1905,1954,1910,1904,1904,1901,1910,1908,1908,2000,1906,1910,1912,1890,1890,1908,1954,1925,1914,1908,1894,1893,1902,1902,1898,1951,1951,1951,1906,2007,1888,2011,1971,1971,1896,1896,1964,1900,1900,2011,1888,1900,1900,1898,2000,1904,1904,1890,1948,2002,2008,2008,2008,1895,1890,2001,1910,1910,1893,1890,1906,1908,1925,1889,1902,1901,1942,1890,1887,1892,1892,1891,1901,1900,1900,1892,1889,1889,1889,1890,1890,1896,1890,1928,1896,1891,1920,1895,1895,1893,1886,1905,1900,1900,2008,2008,2008,2008,2008,1906,1906,1906,1906,1887,1889,2011,1896,1896,2003,2003,2003,2003,1891,1891,1891,1894,1890,1890,1889,1897,1924,2010,1894,1890,1890,1889,1946,1946,1946,1946,1946,1946,1946,1946,1946,1892,1998,1999,1905,2002,2002,2002,2002,2002,2002,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,1890,1890,1890,1890,1930,1930,1930,1890,1890,1886,1894,1890,1890,2006,1999,1886,2003,2003,2003,1896,2005,2005,2005,2005,1901,1901,1901,1901,1901,1901,1901,2001,2001,2001,2001,2001,2003,2003,2003,2003,2003,2003,2003,2003,2003,1997,1886,1889,1999,1999,1900,1890,1890,1890,1902,1902,1909,2005,1908,1908,1909,2005,1912,1966,1966,1966,1930,1890,2005,2003,2003,2003,2003,2003,2011,2011,2011,2011,2011,2011,2011,2011,2011,1904,1904,1893,2005,2003,2003,1899,2003,2003,2003,1937,1893,1906,2005,2005,2005,2005,2005,1906,1904,1904,1922,1922,1916,1916,1916,1962,2006,2006,2006,2006,2006,2006,2006,2006,2006,1890,1889,1978,1978,1901,2002,1892,1900,1906,1890,1890,1936,1925,1908,1908,1930,1901,1896,1890,1890,1894,1893,1906,2000,2000,2000,2000,1909,1909,1912,1890,1909,1918,1918,1916,1937,1944,1944,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1937,1937,1909,1905,1910,1910,2006,2006,2006,2006,2006,1905,1890,1905,1910,1928,1925,1923,1910,1920,1906,1925,1925,1914,1922,1916,1934,1904,1907,1907,1904,1908,1908,1907,1906,1908,1908,1962,1962,1906,1895,1908,1909,1908,1911,1925,1927,1924,1927,1952,1955,1958,1950,1962,1951,1928,1955,1953,1953,1950,1950,1953,1954,1952,1954,1954,1953,1953,1953,1953,1953,1954,1966,1971,1978,1974,1976,2005,1965,1961,1969,1971,1962,1962,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1980,1980,1983,1970,1970,1968,1968,1966,1967,1969,1969,1970,1966,1969,1983,1984,1979,1979,1988,1964,1964,1962,1962,1962,1962,1970,1962,1964,1963,1968,1966,1963,1961,1963,1962,1967,1965,1962,1962,1962,1964,1968,1962,1963,1963,1963,1964,1963,1963,1962,1963,1963,1963,1962,1962,1965,1970,1970,1970,1970,1970,1970,1968,1970,1969,1969,1968,1968,1968,1965,1963,1963,1963,1962,1962,1962,1962,1963,1963,1961,1961,1961,1962,1963,1963,1963,1962,1963,1962,1962,1962,1964,1968,1969,1969,1968,1963,1963,1962,1961,1986,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1979,1979,1979,1979,1979,1979,1979,1984,1984,1986,1979,1979,1979,1979,1980,1980,1980,1983,1982,1982,1982,1983,2003,2003,2003,1914,1910,1922,1910,1911,1912,1908,2008,2008,2008,2008,2008,2008,2008,2008,2008,1906,1906,1906,1905,1892,1908,1906,1906,1906,1981,1906,1908,2001,2001,2001,2001,2001,2001,2001,2001,2001,2005,2005,1902,1970,1970,1970,1914,2000,2003,1911,1911,1910,1909,1914,1914,1966,1966,1966,1966,1966,1985,1924,1924,1964,1964,1964,1964,1964,1964,1924,1924,1924,2012,1947,1927,1924,1946,1924,1930,1923,1923,1926,1891,1910,1910,1910,1923,1925,1908,1908,1908,1908,1915,1915,1906,1911,1927,1908,1910,1910,1908,1910,1914,1910,1910,1910,1910,1920,1922,1920,1910,1907,1993,1908,1959,1923,1920,1922,2007,2007,2007,1968,1968,1908,1927,1914,1908,1910,1900,1900,1900,1891,1901,1908,1899,1898,1968,1892,1901,1891,1911,1910,1975,1975,1975,1906,1882,1891,1920,1966,1966,1966,1968,1968,1968,1968,1900,1906,1916,1892,1884,1892,1892,1901,1915,1915,1915,1914,1908,1908,1910,1908,1908,1928,1928,1928,1928,1938,1908,1923,1898,1908,1908,1904,1963,1963,1911,1902,1962,1962,1962,1962,1962,1906,1965,1965,1930,1898,1905,1890,1901,1901,1901,1901,1901,1901,1901,1931,1931,1931,1919,1919,1918,1918,1896,1896,1906,1961,1906,1903,1953,1922,1909,1905,1902,1910,2005,1906,1906,1924,1925,1925,1903,1922,1927,1925,1922,1919,1919,1908,1904,1900,1974,1974,1974,1974,1974,1974,1974,1939,1915,1915,1910,1919,1910,1925,1923,1948,1922,1903,1903,1905,1900,1923,1922,1923,1909,1909,1911,1923,1915,1916,1923,1925,1922,1918,1920,1920,1928,1922,1922,2012,1924,1924,1923,1923,1923,1922,1930,1922,1922,1922,1924,1924,1925,1923,1923,1924,1922,1922,1908,1921,1924,1924,1922,1921,1920,1923,1889,1926,1922,1920,1920,1920,1923,1920,1919,1916,1914,1919,1920,1922,1941,1923,1922,1920,1920,1927,1920,1927,1924,1924,1926,1924,1923,1923,1923,1929,1926,1925,1925,1925,1937,1937,1924,1925,1949,1926,1924,1924,1937,1924,1932,1919,1922,1921,1917,1919,1919,1918,1917,1919,1919,1911,1994,1989,1910,1900,2007,2008,1988,1988,1988,1988,1998,2002,1924,2001,2000,1900,1943,1999,2001,1983,2000,2005,2007,2007,2007,2007,2007,1999,2007,2006,1942,1942,2000,2007,2007,1923,2003,1922,1920,1920,1914,1913,1913,1917,1912,1913,1913,1922,1923,1918,1911,1923,1905,1927,1922,1922,1926,1920,2007,2012,1981,2004,2012,2011,1928,1951,1951,1975,1962,1962,2005,1998,1998,1998,2000,1990,2005,2000,2000,2000,2000,1908,2007,1993,2010,2010,2010,2010,2010,2010,2010,2010,1894,1894,1894,1894,1896,1896,1896,1896,1930,1890,1900,1896,1935,1902,1929,1929,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1902,1904,1910,1892,1888,1886,1905,1902,1924,1887,1900,1893,1886,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1904,1904,1962,1962,1927,1927,1964,1905,1906,1965,1904,1906,1902,1902,1902,1902,1902,1902,1886,1904,1965,1965,1965,1968,1968,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1892,1892,1901,1969,1969,1969,1969,1969,1965,1960,1960,1960,1960,1960,1960,1993,1993,1969,1969,1969,1969,1969,1969,1969,1981,1981,1981,1981,1981,1980,1980,1980,1980,1980,1976,1976,1976,1976,1968,1968,1968,1901,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1930,1973,1967,1967,1967,1967,1967,1967,1967,1967,1902,1902,1902,1902,1890,1947,1947,1947,1901,1890,1890,1891,1889,1889,1888,1906,1903,1903,1966,1885,1900,1900,1930,1894,1929,1929,1929,1905,1905,1905,1928,1928,1928,1903,1905,1896,1901,1902,1901,1901,1888,1892,1892,1902,1902,1902,1902,1965,1965,1965,1965,1965,1965,1966,1966,1966,1959,1959,1900,1965,1965,1965,1965,1965,1965,1965,1916,1907,1964,1896,1900,1954,1903,1903,1962,2003,2003,1900,1899,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1960,1967,1967,1967,1967,1910,1910,1900,1892,1894,1954,1954,1954,1930,1896,1900,1908,1900,1960,1893,1906,1910,1966,1910,1902,1902,1905,1908,1964,1968,1968,1968,1906,1906,1904,1966,1966,1966,1966,1961,1961,1968,1958,1958,1958,1958,1958,1958,1898,1910,1961,1961,1961,1961,1961,1886,1886,1960,1960,1911,1911,1923,1923,1923,1914,1914,1914,1970,1970,2000,1910,1910,1904,1904,1904,1900,1968,1968,1968,1968,1929,1929,1929,1929,1929,1929,1929,1929,1929,1929,1929,1929,1929,1909,1910,1963,1963,1899,1908,1929,1929,1929,1900,1891,1896,1891,1958,1958,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1900,1902,1902,1902,1898,1906,1910,1923,1923,1923,1928,1910,1910,2006,2006,1911,1900,1927,1941,1908,1908,1908,1906,1904,1905,1940,1940,1940,1908,1908,1996,1996,1996,1973,1973,1973,1905,1893,1893,1905,1922,1923,1923,1905,1900,1907,1923,1905,1912,1906,1923,1908,1921,1926,1912,1912,1921,1910,1925,1925,1984,1908,1908,1908,1895,1922,1924,1920,1908,1908,1906,1911,1918,1925,1921,1921,1918,1999,1999,1999,1923,1923,1958,1958,1958,1958,1913,1913,1929,1959,1924,1910,1910,1910,1926,1961,1961,1961,1905,1908,2005,1886,1904,1904,1879,1884,1892,1941,1956,1956,1956,1956,1956,1956,1956,1956,1956,1915,1915,1915,1915,2006,2006,1893,1910,1896,1896,1903,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1953,1953,1967,1967,1907,1896,1970,1970,1970,1970,1970,1970,1970,1888,2007,2007,2007,1997,1997,2006,2006,2006,2006,2006,2006,2006,2006,1908,1908,1908,1908,1908,1902,1902,1902,1902,1908,1908,1908,1912,1997,1997,1997,1997,1997,1998,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1981,1904,1890,1925,1886,1884,1906,2010,1889,1884,1924,1900,1894,1894,1890,1908,1935,1891,1898,1899,1904,1890,1890,1890,1890,1920,1920,1920,1998,1998,1998,1998,1998,1998,1998,2001,2001,2001,2001,2001,2001,2001,2001,2001,1996,1996,1996,1996,1996,1996,1996,1902,1901,1901,1931,1931,1931,1961,1961,1961,1900,1885,1891,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1951,1951,1968,1981,1938,1890,1941,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,1920,1929,1929,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1974,1974,1977,1977,1977,1977,1977,1909,1910,1925,1925,1925,1925,1925,1974,1974,1974,1898,1966,1958,1958,1958,1958,1958,1958,1958,1958,1958,1958,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1973,1973,1973,1973,1959,1959,1959,1959,1959,1959,1959,1959,1908,1966,1966,1966,1966,1966,1896,1896,1926,1926,1926,1926,1904,1904,1968,1968,1968,1968,1968,1908,1961,1981,1981,1961,1961,1961,1961,1960,1953,1953,1953,1953,1953,1900,1900,1900,1900,1925,1925,2001,2001,2001,1953,1953,1904,1904,1904,1962,1962,1962,1962,1962,1905,1939,1974,1974,1974,1974,1974,1974,1967,1967,1967,1967,1985,1985,1985,1906,1893,1970,1970,1970,1970,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1961,1966,1966,1966,1966,1966,1966,1966,1961,1961,1890,1887,1895,1890,1886,1902,1890,1890,1907,1890,1890,1890,1915,1915,1915,1915,1915,1915,1890,1890,1900,1886,1895,1890,1900,2010,1890,1890,1886,1886,1890,2001,1890,1900,1888,1908,1884,1888,1889,1890,1890,1885,1890,1890,1920,1965,1965,1902,1999,1923,1923,1912,1923,1890,1896,1953,1934,1956,1894,1949,1936,1944,1947,1948,1930,1896,1949,1949,1949,1944,1948,1948,1948,1947,1947,1947,1948,1917,1953,1947,1947,1928,1924,1928,1902,1900,1900,1950,1892,1892,1948,1948,1948,1949,1949,1949,1949,1948,1948,2011,1946,1948,1949,1945,1945,1896,1894,1923,1923,1924,1925,1908,1908,1908,1910,1908,1925,1923,1929,1929,1936,1929,1948,1903,1922,1926,1933,1949,1906,1952,1952,1900,1953,1908,1905,1905,1905,1900,2005,1890,1985,2003,1905,1948,1955,1955,1930,1926,1941,1941,1939,1895,1948,1948,1927,1931,1970,1970,1970,1947,1901,1951,1941,1947,1947,1949,1946,1952,1952,1953,1941,1939,1939,1939,1895,1951,1942,2012,1947,1951,1963,1963,1951,1951,1954,1962,1885,1949,1949,1949,1949,1949,1973,1973,1973,1973,1942,1954,1953,2006,1917,1915,1953,1953,1949,1949,1953,1953,1955,1930,1910,1925,1955,1921,1921,1922,1949,1949,1949,1952,1952,1903,1923,2011,1900,1913,1922,1921,1900,1938,1921,1926,1900,1922,1948,1949,1900,1906,1949,1959,1966,1915,1948,1928,1925,1922,1949,1922,1906,1954,1954,1983,1983,1983,1967,1967,1921,1952,1953,2011,2011,1947,1947,1953,2000,1952,1952,1952,1951,1955,1960,1961,1961,1960,1960,1960,1960,1959,1971,1956,1956,1956,1956,1957,1957,1957,1957,1957,1942,1939,1924,1924,1951,1926,1951,1926,1926,1948,1926,1925,1949,1942,1944,1944,1941,1940,1942,1929,1922,1951,1945,1910,1941,1941,1941,1942,1996,1947,1966,1938,2005,1936,1927,1927,1951,1953,1896,1957,1941,1914,1921,1905,2005,1955,1900,1910,1921,1923,1946,1910,1942,1952,1955,1955,1955,1955,1955,1946,1946,1946,1952,1946,1946,1946,1956,1956,1956,1946,1948,1955,1960,1957,1957,1956,1954,1954,1954,1954,1954,1996,1954,1954,1956,1955,1956,1956,1959,1973,1973,1956,1952,1954,1955,1953,1954,1954,1954,1954,1953,1954,1954,1953,1953,1949,1949,1949,1953,1952,1948,1948,1954,1954,1953,1948,1953,1953,1954,1954,1949,1953,1953,1953,1956,1961,1907,1956,1959,1955,1955,1955,1948,1948,1952,1960,1947,1943,1943,1942,1942,1949,1940,1955,1955,1948,1954,1910,1910,1954,1955,1953,1953,1953,1953,1953,1955,1955,1954,1955,1955,1954,1953,1954,1954,1954,1954,1954,1954,1954,1954,1943,1943,1954,1902,1890,1915,1951,1951,1983,1954,1948,1924,1962,1951,1954,1951,1951,1951,1951,1951,1951,1906,1954,1952,1927,1902,1896,1910,1910,1948,1924,1954,1925,1942,1949,1923,1959,1952,1952,1957,1951,1925,1925,1921,1921,1970,2005,1922,1927,1919,1951,1926,1910,1910,1928,1951,1951,1947,1968,1949,1949,1949,1949,1922,1941,1947,1952,1926,1926,1954,2008,2008,2008,1921,1956,1947,1949,1949,1951,1951,1941,1931,1921,1921,1928,1915,1910,1905,1905,1954,1954,1954,1954,1948,1919,1919,1958,1909,1907,1907,1985,1922,2010,2010,1923,1922,1922,1922,1954,1947,1947,1922,1955,1953,1952,1962,1962,1921,1949,1949,1910,1949,1921,1924,1931,1947,1947,1947,1949,1955,1955,1948,1948,1947,1947,1947,1947,1911,1926,1924,1953,1908,1952,1914,1914,1947,1949,1948,1948,1949,1949,1906,1947,1947,1950,1948,1946,1946,1942,1948,1920,1961,1961,1941,1942,1934,1955,1940,1939,1948,1947,1935,1923,1925,1948,1948,1930,1931,1931,1929,1930,1925,1925,1947,1947,1929,1929,1941,1920,1953,1953,1959,1959,1943,1943,1931,1929,1916,1921,1921,1921,1932,1927,1929,1929,1940,1908,1948,1922,1924,1924,1922,2000,1922,1922,1954,1906,1888,1890,1890,1880,1880,1918,1905,1905,1951,1951,1886,1954,1954,1998,1942,1942,1914,1888,1954,1954,1954,1954,2004,1900,1905,1888,1924,1924,1888,1905,1905,1969,1969,1969,1969,1969,1969,1960,1960,1961,1961,1961,1961,1971,1971,1971,1971,1971,1906,1997,1997,1997,1997,1997,1997,1911,1898,1898,1888,1895,1901,1958,1958,1958,1958,1958,1890,1895,1900,1900,1900,1905,1908,1908,1908,1910,1890,1895,1901,1913,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1898,1898,1952,1952,1964,1964,1964,1900,1896,1886,1886,1890,1936,1890,1886,1886,1886,1890,1896,1883,1890,1894,1886,1886,1890,1896,1890,1890,1887,1886,1886,1890,1886,1890,1888,1888,1900,1889,1893,1890,1886,1896,1900,1906,1999,1916,2006,1890,1886,1884,1890,1904,1890,1890,1982,1982,1890,1890,1890,1986,1986,2007,1885,1885,1885,1885,1890,1887,1905,1905,1905,2012,1888,1888,1894,1923,1890,1888,1888,1888,1896,1910,1910,1914,1903,1890,1889,1889,1890,1895,1900,1900,1926,1880,2000,2000,2000,1890,1890,1890,1906,1906,1900,1894,1906,1910,1910,1926,2005,1890,1895,1900,1900,1888,1890,1896,1890,1888,1890,1890,1888,1890,1895,1890,1974,1890,1896,1896,1903,1903,1911,1888,1905,1891,1984,1984,1984,1890,1890,1890,1890,1953,1900,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1895,1895,1929,1929,1890,1890,1890,1907,1890,2007,1899,1900,1906,1889,1889,1890,1910,1900,1901,1915,1889,1890,1905,1964,1964,1890,1890,1896,1896,1890,1904,1904,1896,1891,1892,1892,1885,1891,1890,1895,1886,1890,1906,1906,1906,1906,1985,1900,1893,1890,1890,1922,1971,1971,1971,1971,1901,1900,1900,1900,1900,1890,1961,1961,1905,1901,1905,1906,1999,1900,1965,1895,1905,1890,1906,1998,1998,1950,1950,1950,1902,1902,1928,1901,1896,1890,1890,1896,1896,1890,1885,1890,1895,1890,1890,1901,1901,1901,1900,1900,1890,1890,1910,1890,1890,1900,1892,1900,2006,1961,1961,1961,1965,1890,1900,1900,1890,1906,1932,1890,1905,1905,1922,1895,1895,1968,1968,1968,1962,1968,1968,1968,1900,1900,1890,1890,1890,1895,1924,1924,1901,1890,1923,1900,1886,1900,1900,1898,1895,1895,1895,1890,1890,1956,1895,1903,1905,1909,1890,2010,2010,2010,2011,2011,2011,1902,1902,1902,1924,2008,2008,1890,1890,1927,1927,1929,1932,1928,1912,1928,2012,2007,1907,1916,1911,1917,1919,1919,1940,1924,1910,1910,2007,1922,1922,1925,1905,1999,2005,1915,1925,1923,1923,1911,1923,1920,1952,1924,1997,1929,1942,1928,1986,1955,1926,1920,1926,1909,1925,1909,1911,1911,1956,1926,1931,1936,1927,1927,1925,1938,1928,1931,1937,1916,1910,1907,1924,2002,1906,1912,1910,1910,1912,1911,1911,1904,1917,1906,1890,1925,1909,1927,1890,1909,1933,1908,1922,1923,1928,1924,1925,1925,1925,1905,1905,1948,1917,1922,1919,1907,1912,1951,1907,1989,1906,1896,2004,1911,1969,1969,1906,1923,1906,1921,1968,1968,1968,1923,1932,1906,1906,1901,1901,1913,1906,1924,1915,2005,1906,1904,1898,1904,1906,1906,1994,1994,1995,1926,1906,1901,2007,2007,1906,1906,1926,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1910,1907,1986,1986,1962,1962,1962,1960,1960,1960,1960,1926,1926,1947,1947,1947,1947,1947,2000,1967,1967,1970,1961,1961,1961,1961,1961,1908,2008,2008,2008,1924,1924,1924,1924,1924,2005,1922,1922,1905,1910,1910,1909,1900,1894,1894,1905,1969,1969,1922,1900,1962,1962,1962,1895,1907,1907,1905,1905,1909,1908,1910,1928,1910,1910,1915,1916,1915,1895,1895,1907,1890,1954,1900,2007,2011,2011,1983,1910,1922,2001,2001,1922,2008,2008,1912,1908,1914,1919,1919,2004,1905,1972,1981,2005,1994,1994,2002,2002,2008,2008,1991,1991,1999,1992,1994,1987,2003,2006,2004,2012,1979,2005,2008,1987,1999,2002,2012,2001,2004,2004,2005,2004,2000,2007,1983,1994,1994,2005,1984,1984,1993,1981,1982,1981,1981,1981,1981,1988,1999,1999,1985,1985,1951,1951,1993,1999,1999,1999,2005,1996,2001,2000,1998,2007,2007,2007,1932,1906,1948,2001,2003,1946,1984,1984,1984,1985,1985,1984,1984,1985,1991,1996,1991,1984,1994,1988,1993,2007,2008,2008,2011,2011,2011,2011,2001,2007,1984,1991,2007,2007,2007,1978,1979,1971,1971,1971,1971,1971,1971,1971,2000,2006,1993,1994,2003,2005,1955,1955,2005,1991,1983,2001,1935,1935,1991,2005,1993,2000,1916,1896,1983,1997,1951,2005,1985,1985,2006,2006,2006,2006,2007,1985,1999,1997,2006,1994,2008,2008,1985,1985,1990,1990,1974,1974,1974,1974,2001,2006,1987,1988,1988,1989,1997,1997,1994,1994,1991,1997,1997,1997,1997,1997,1997,1998,1978,1940,1983,1983,1983,1985,1985,1985,1985,1999,1999,1999,1991,2007,2005,2000,2004,2004,2004,2007,2008,2008,2008,2008,2009,1918,2002,1999,2002,1999,2000,2002,1999,2005,1999,2012,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,1996,1996,1996,1996,1996,1996,1996,1996,1996,1947,1999,1999,2004,2004,1996,1996,1996,1996,1996,1997,1997,1998,1998,1998,2000,2000,1998,1998,1998,1998,1949,2000,2003,2005,2006,2006,2006,2001,2001,2003,2003,2003,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,2000,2001,2002,2002,2002,2003,1999,2004,2004,2006,2007,2007,2007,2007,2007,1924,1986,1998,1998,1995,1985,1985,1994,1994,1997,1999,1999,1999,1999,1996,1996,1998,1998,1999,2000,1998,1998,2000,2000,2000,2000,2000,2000,2006,2006,2006,2000,1948,1996,2001,1985,1985,1985,1994,1994,1994,1994,2000,2000,2000,2000,2000,2001,2001,2001,2001,2001,2001,2006,2006,2006,1955,1954,1955,1955,1956,1967,1999,1954,1955,1955,1962,1961,1962,1957,1985,1990,1990,1993,1994,1994,1991,1982,1994,2008,2012,1943,1969,1968,2011,2011,2006,2008,1961,2000,1988,1978,1983,1978,1978,1978,1979,1978,1978,1978,1987,1987,1982,1978,1978,1981,1978,1978,1978,1984,1994,1995,1995,1949,2012,2012,1949,2002,1952,1948,2005,1947,1942,1952,1952,1955,1931,1924,1937,1937,1940,1923,1942,2004,1999,1946,2004,1949,1949,1949,1949,1940,1938,1940,2005,2007,2006,1937,1929,2012,2012,1946,1928,1942,1947,1941,1940,1940,2005,1942,2002,1967,1939,1938,1948,1937,1937,1940,1956,1929,1938,1955,1930,1930,1924,1940,1926,1940,1939,1936,1933,1938,1938,1939,1942,1950,1940,1938,1938,1939,1946,1942,2009,1941,1942,2010,1942,1951,1951,1946,1956,1954,1956,1952,1952,1953,1953,1952,2012,2012,1951,1948,2012,1952,2012,2012,1950,1952,2011,2011,1933,1954,1954,1953,1955,1953,1954,1951,2007,1942,1942,1942,1950,1947,1942,1911,1951,1952,1951,1951,1951,1952,1951,1952,2011,1993,1992,1928,1928,2008,1912,1933,1949,1928,1892,2004,1922,1905,1927,1913,1919,1926,1917,1917,1926,1926,2012,2005,1916,1916,1922,1919,1920,1919,2011,2012,1928,1928,1925,1928,1928,1938,1946,1932,2012,1930,1928,1937,1929,1929,1929,1928,1928,1929,1932,1929,1911,1929,2007,1927,1927,1915,1885,1927,1926,1926,1922,1925,1925,2012,2012,1925,1929,1919,1919,2012,1928,1925,1929,1930,1930,1930,2007,1926,1927,1927,1929,1928,1928,1936,1932,1932,1970,1970,1970,1970,1911,1923,1922,1926,1896,1926,1917,1927,2004,2012,2012,1925,1910,1964,1910,2009,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1925,1925,1925,1925,1925,1910,1910,1911,1911,1880,1888,1910,2007,2007,1903,1901,1920,1916,2012,1925,1925,1915,1914,1915,1909,1942,1921,1895,1900,1925,1927,2005,1927,1974,1974,1974,1974,1974,1974,1974,1974,1974,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1925,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1997,1997,1910,1923,1930,1910,2004,1922,1946,1950,1950,1925,1924,1922,2004,1925,1924,1922,1922,1925,1924,1900,1928,1924,1905,1908,1920,1924,1926,2008,1924,1922,1920,1920,1923,2005,2006,2007,2007,1923,1923,1906,2006,1920,2002,1920,1926,1921,1911,1913,1917,1906,1924,1923,1922,1920,1920,1924,1924,1924,2010,1890,1925,1922,1896,2004,2011,2012,1918,2008,2011,2011,2012,1913,1906,1955,1924,2011,1911,1911,2005,2010,2010,1911,1911,1911,1911,1911,1906,1922,1911,1922,1906,1906,1906,1906,1909,1909,2011,1949,1925,1911,1924,1911,1929,1910,1939,2006,2007,2007,2012,1921,1926,1927,2011,1931,1928,1928,1929,1926,1926,1926,2011,1925,1926,1929,1926,2004,1931,1931,1924,2012,1925,1893,1924,1922,1922,1903,1924,2012,1924,1921,1921,1922,1922,2005,1925,1926,2010,2007,2011,2008,1924,1924,1923,1928,2012,1925,1929,1925,2008,2006,2005,1926,1925,1925,1927,1927,1921,1921,1924,1936,2012,1921,1921,1921,2007,1912,2011,2010,1912,1911,2012,1912,1910,2007,2007,1915,1920,1909,1937,1960,1940,2011,2012,2012,2011,1914,1882,1997,1915,2010,2010,1900,1925,1940,1940,1922,1925,1908,1908,1895,1895,1895,1922,1925,1922,1922,1923,1908,1891,1899,1906,1900,1904,1903,1891,1904,1895,1925,1885,1893,1907,1902,1888,1905,1917,1900,1951,1901,1901,1900,1894,1900,1903,1896,1896,1890,1936,1936,1900,1905,1904,1904,1895,1895,1895,1924,1904,1893,1909,1909,1890,1890,1909,1930,1904,1901,1918,1905,1905,1900,2007,1906,1908,1900,1890,1904,1904,1906,1927,1900,1902,1890,1897,1905,1927,1898,1898,1896,1900,1910,1901,1905,1907,1902,1890,1910,1906,1908,1901,1905,1904,1904,1921,1921,2006,1923,1885,1905,1906,1907,1907,1923,2005,1905,1890,1912,1900,1893,1905,1926,1907,1901,1907,1919,2006,2008,1925,1925,1893,1906,1890,1905,1903,1927,1927,1902,1905,1901,1900,1929,1929,1925,1922,1905,1926,2008,1885,1927,1890,1890,1898,1908,1908,1911,1909,1909,1909,1906,1908,1904,1905,2007,1905,2010,1910,1890,1906,2008,2008,2008,2010,2010,2010,1909,1923,1903,1903,1907,1909,1900,1903,1905,1905,1910,1909,1910,1910,1905,1929,1905,1907,1908,1933,1905,1911,1911,1910,1908,1997,1951,1949,1949,1952,1910,1910,1910,1953,1953,1953,1953,1952,1954,1949,1908,1921,1911,1905,2012,1888,1927,1925,1925,2012,2004,2004,1951,1900,1951,1910,1954,1954,1954,1949,1950,1950,1949,1949,1951,1951,1951,1951,1951,1951,1951,1951,1957,1957,1950,1951,1950,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1963,1951,1951,1951,1952,1951,1951,1951,1952,1951,1951,1951,1951,1951,1952,1952,1951,1952,1954,1952,1952,1954,1952,1952,1952,1952,1952,1953,1963,1963,1952,1952,1953,1953,1956,1952,1953,1952,1952,1952,1952,1952,1952,1953,1952,1952,1952,1952,1952,1952,1952,1954,1952,1952,1953,1953,1953,1950,1942,1956,1956,1956,1949,1949,1949,1949,1937,1938,1952,1952,1929,1955,1966,1947,1952,1953,1948,1950,1932,1946,1946,1946,1948,1965,1936,1951,1942,1946,1946,1946,1946,1946,1939,1939,1948,1940,1939,1939,1939,1939,1951,1951,1951,1935,1935,1948,1937,1927,1929,1944,1949,1953,1927,1940,1957,1930,1955,1955,1955,1936,1936,1934,1936,1933,2003,2005,2006,1922,1937,1935,1939,1934,1949,1933,1934,1938,1980,1945,1938,1938,1925,1939,1943,1955,1942,1943,1931,1936,1935,1935,2000,2000,2000,1940,1939,2011,2011,1938,1940,1955,1955,1941,1952,1952,1955,1947,1951,2010,2010,1943,1943,1940,1937,1930,1936,1942,1940,1952,1946,1946,1947,1984,1956,1956,1959,1963,1964,1952,1985,1960,1954,1936,1930,1950,1953,1947,1948,1947,1947,1947,1947,1947,1947,1947,1947,1947,1950,1951,1951,1947,1948,1955,1948,1948,1948,1951,1951,1951,1952,1952,1952,1954,1954,1954,1953,1953,1953,1953,1954,1953,1954,1954,1955,1938,1934,1924,1924,1929,1929,1939,1929,1934,1929,1955,1955,1955,1929,1929,1929,1949,1929,1936,1945,1925,1936,1929,1934,1929,1934,1929,1929,2010,1929,1929,1959,1940,1930,1935,1948,1957,1957,1934,1931,1931,1973,1929,1929,2004,1940,1978,1938,1940,1940,2001,1932,1932,1936,1936,1934,1940,1951,1972,1937,1953,2010,1937,1943,1954,1940,1938,1936,2005,1940,1940,1940,2000,1941,2000,1956,1956,1958,1959,1962,1962,1955,1955,1955,2001,2010,2005,2005,2005,2005,1948,2000,1955,1955,1955,1938,1955,1948,1954,1938,1959,2003,1953,1955,1955,1949,1949,1952,1955,1955,1948,1954,1946,1955,1954,1954,1954,1954,1954,1954,1954,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1926,1950,1953,1953,1954,1953,1953,1947,1956,1956,1948,1948,1943,1940,1950,1940,1940,1940,1954,1998,2002,1929,1941,1942,1934,1934,1946,1956,1935,1951,1955,1938,2011,1960,1930,1952,1955,1955,1961,1955,1935,1955,1955,1955,1955,1957,1954,1955,1948,1947,1947,1953,1988,1988,1983,1983,1983,1983,1983,1983,1983,1930,1935,1932,1934,1948,2011,2011,2011,2011,1980,1980,1973,2002,1959,1959,1941,1946,1942,2000,1947,1948,1954,1940,1940,1940,1940,1940,1940,1949,1949,1948,1952,1940,1958,1888,1960,1965,1948,1954,1954,1940,1948,1940,1946,1940,1940,1947,1938,2009,2009,1940,1959,1959,1948,1943,1942,1942,1942,1948,1949,1949,1948,1948,1948,1948,1948,1945,1945,1948,1948,1952,1949,1957,1957,1951,1955,1955,1952,2001,1953,1953,1953,1955,1953,1953,1953,1953,1955,1955,1953,1953,1953,1954,1955,1953,1955,1956,1955,1955,1955,1955,1954,1954,1955,1955,1954,1955,1955,1954,1987,1954,1954,1954,1954,1956,1951,1954,1954,1953,1953,1951,1953,1953,1953,1953,1966,1951,1951,1951,1951,1952,1952,1952,1955,1952,1952,1952,1951,1952,1952,1953,1952,1952,1953,1953,1955,1955,1955,1954,1954,1955,1954,1954,1954,1954,1954,1955,1955,1955,1955,1955,1954,1954,1956,1955,1956,1955,1955,1955,1955,1954,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1954,1955,1955,1955,1955,1955,1954,1957,1956,1955,1957,1957,1960,1959,1952,1952,1952,1952,1955,1952,1952,1952,1953,1952,1954,1953,1953,1953,1953,1953,1953,1952,1953,1955,1955,1955,1955,1957,1955,1954,1954,1954,1955,1954,1954,1956,1954,1954,1954,1954,1954,1954,1952,1952,1952,1952,1952,1952,1954,1955,1955,1955,1956,1955,1957,1957,1958,1957,1956,1957,1955,1950,1955,1955,1956,1958,1984,1942,1937,1959,1978,1956,1956,1954,1954,1954,1954,1954,1954,1954,1956,1954,1954,1955,1955,1955,1954,1955,1954,1954,1955,1955,1955,1954,1954,1954,1954,1954,1954,1954,1954,1954,1956,1955,1956,1999,1937,1954,1959,1959,1961,1955,1955,1955,1955,1959,1959,1959,1952,1962,1929,1953,1955,1954,1955,1955,1954,1958,1955,1948,1955,1941,1941,1939,1953,1954,1954,1960,1960,1957,1984,1984,1984,1984,1956,1974,1974,1929,1962,1961,1961,1956,1955,1940,1947,1964,1948,1948,1950,1953,1953,1953,1953,1953,1953,1955,1954,1954,1955,1955,1955,1954,1954,1954,1984,1984,1984,1984,1986,1986,1994,1995,1996,1995,1996,1995,1959,1999,1959,1963,1964,2004,1954,1954,1954,1955,1955,1955,1956,1956,1956,1956,1954,1959,1957,1957,1957,1956,2005,1955,1955,1956,1956,1955,1955,1943,1943,1958,1957,1957,1958,1958,1958,1958,1958,1958,1958,1958,1959,1959,1950,2006,2006,2006,2006,2006,2006,1955,1952,1950,2002,2002,1940,1957,1957,1957,1960,1961,1977,1953,1953,1953,1954,1954,1953,1954,1954,1954,1954,1954,1953,1954,1954,1954,1953,1954,1954,1954,1954,1954,1954,1954,1953,1953,1955,1955,1955,1956,1953,1954,1954,1954,1954,1954,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1962,1962,1953,1953,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1958,1954,1954,1954,1954,1954,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1955,1953,1953,1954,1954,1954,1953,1953,1954,1954,1954,1954,1954,1906,1922,2006,1929,2012,2012,2012,2012,2008,2008,1908,1908,1910,1908,1910,2009,2009,1927,1926,1926,1900,1908,1893,1910,1902,2006,2006,2006,1910,1905,1927,1909,1926,1890,1904,1927,1927,1927,1955,1955,1955,1955,1902,1907,1912,1924,1910,1910,1900,1905,1922,1914,1914,1914,1914,1905,1910,1910,1910,1910,1910,1900,1930,1890,2006,1925,2008,1910,1905,2004,2005,1892,1900,1900,1904,1905,1910,1895,1888,1936,1885,2007,2007,2009,1926,1885,1885,1988,2000,1926,1993,1897,1890,1890,2003,1910,1910,1929,1890,1890,1890,1999,1925,1929,1910,1928,1939,1933,1910,1921,1929,2011,2011,2011,2011,2007,1896,1907,1924,1891,2012,2001,2009,1896,1925,1907,1926,1908,1910,1911,1896,1904,1904,1889,1896,1891,2008,1896,1906,1900,1903,1890,1919,1919,1914,1921,2001,1908,1923,1941,1913,1926,2000,1922,1922,1906,1954,2007,1891,2012,2012,1911,1912,1928,1925,2009,2011,2011,1955,1911,1911,1890,2009,2009,1909,2007,2010,2010,2011,1900,1922,2001,2001,1990,1927,1921,1999,1912,2010,1904,1911,1926,1926,1946,1923,1913,2012,2011,2011,1928,1928,2010,2010,2010,1922,1922,1922,1921,1924,1920,1920,2011,1922,1919,1920,1917,1920,1917,2010,1907,1921,1925,2012,1911,1925,1922,1911,1939,1920,1921,1929,1928,1927,1927,1903,1917,1910,1926,1925,1930,2011,1912,1912,1910,2009,2006,2006,1923,1907,1926,1928,1926,1926,1926,1896,2012,1916,1976,1923,1932,2012,2011,1927,1928,1926,1925,1925,2007,1922,1922,2011,1925,1924,1953,1922,1931,1925,1925,1952,1928,1922,1922,1923,1951,1928,1926,1896,1906,1904,1926,2005,1960,1956,1956,1924,1935,1935,1927,1928,1929,1956,1956,1956,2007,1994,1928,1938,1950,1921,1921,1932,1969,1896,1922,1968,1925,2002,1928,1909,1938,1942,1945,1928,2006,2000,1937,1928,1928,1938,1924,1928,1947,1947,1926,1942,1924,1926,1935,1910,1910,1934,1934,1938,1937,1941,1912,1908,1908,1962,1908,1922,1891,1930,1908,1928,1926,1925,1925,1925,1931,1941,1924,1929,1929,1925,1925,2008,1926,1946,1923,1923,2006,1929,2007,1954,1952,1976,1975,1976,1976,1955,1957,1968,1967,1967,1962,1937,1927,1924,1948,1938,1930,1928,1926,1925,1930,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1951,1951,1948,1951,1947,1941,1941,1942,1942,1939,2007,2005,1963,1941,1948,1951,2005,2002,1939,1932,2011,2001,1947,1947,1947,1947,1948,1948,1951,1955,1948,1947,1947,1948,1986,1983,1982,1982,1982,1983,1983,1983,1942,1951,1941,1942,2007,1948,2005,1942,1942,2005,2005,1924,1914,1939,1940,1925,2012,1997,1928,1909,1928,1925,1924,1911,1911,1940,1930,1930,1949,1940,1936,1928,1941,1930,1949,2002,2003,1942,1951,2001,2010,2006,2006,2011,2011,2011,1946,1946,1997,1946,1949,2011,1994,1994,1948,1948,1943,2007,1948,1949,1994,1946,2012,1960,1960,2008,2008,2008,1908,2008,2010,1928,1929,1940,1925,1925,1928,2005,1915,1949,1927,2004,2007,2005,1941,2005,1944,2006,1941,2012,2004,2005,2012,1940,1997,2006,2008,2005,1943,2011,2012,1945,2012,2011,2011,2012,1941,1941,2012,1941,1949,2009,1938,1948,1930,2004,2006,2006,2007,2007,2007,1941,1942,1941,1939,1942,1942,1941,1926,1951,1948,1922,1952,1952,1955,1942,1946,1946,1942,1942,1942,2002,1922,2005,2005,1946,1944,2004,1941,1949,1946,2000,1982,1997,1956,2012,1965,1960,1959,1959,1959,2011,2011,2011,1948,1928,1951,1951,2006,1949,1953,2005,1949,2006,1949,1951,1950,1951,1951,1949,1955,1948,1945,1943,1942,1931,1949,1948,1952,1951,1956,1956,1957,1957,1968,1968,1968,1968,1968,1968,1968,1951,2012,2005,2005,2005,1951,2006,1950,1948,2007,1949,1971,2002,1961,1961,1961,1961,1961,1961,2001,2012,2012,2006,2007,2000,1948,1952,2003,1950,1942,1942,1942,1942,1942,1942,1951,2008,1960,1960,1994,1994,2001,2007,2007,2007,2007,2007,1906,2006,2006,1927,1936,1909,1905,1942,1994,1893,1942,1929,1955,1896,1992,1921,1936,2006,2007,1951,1957,2006,2006,2006,2006,2006,2006,1942,1942,1926,1927,2010,2007,1948,2001,2011,1992,2005,1961,1922,2012,2007,2011,2005,2012,2012,2012,2000,1928,2012,2003,2008,2008,1994,2007,1980,1958,1958,2008,2008,2008,2008,2008,2008,2008,2006,2007,1940,2007,2012,2008,2011,1964,2001,1962,1991,1991,2000,1984,2002,1943,1940,1999,1991,1999,1948,1991,1925,2004,1945,2000,2007,1954,2012,2012,2007,2011,1927,1955,1959,1997,1997,1997,1997,1957,1956,1956,1957,1985,1958,1957,1910,1973,1910,1998,2012,1947,2003,2002,1956,1960,1942,1947,1947,1947,2006,2000,1942,1949,1950,1952,1935,2011,2011,2001,2003,1993,2005,2005,1999,1999,1998,1943,1943,1943,2012,2001,2001,2004,2005,1942,1951,2001,2005,1948,1952,2008,2008,2010,2012,2006,1955,2011,2011,2012,2005,2007,1955,2006,1993,2001,2001,2009,1946,2011,2000,2009,1958,2007,1953,2007,1951,2004,1954,2010,1951,2012,2005,2006,1972,1987,1951,1951,2007,1954,1955,1997,1949,2006,1949,1959,1959,1959,1959,1959,1959,1925,1923,1940,1923,1923,1929,1922,1923,1923,2006,2011,1923,1925,1927,1925,1923,1930,2012,2012,1926,1921,1920,1948,1925,1929,1922,1952,1925,1925,1926,1922,1927,2007,2002,1924,1906,1922,1914,1925,1926,1922,1937,1978,1924,1926,1929,1942,1942,2007,2005,2004,1924,1931,1931,1931,1924,1934,1923,1927,1925,2007,1928,1926,1926,1927,1941,1925,1931,1963,1924,1920,1928,1930,1942,1922,1926,1923,1920,1928,1994,1996,1891,1891,1942,1925,1925,1920,1943,1927,1936,1941,1940,1944,1944,1944,1941,2009,1953,1941,1941,1955,1955,1954,1955,1955,1941,1941,1940,1941,1941,1941,1941,1941,1940,1940,1950,1956,1942,1942,1941,1941,1927,1927,1939,2012,1940,1928,1949,1928,1942,1952,2006,2006,2008,2008,1955,1941,1948,1948,1947,1955,2006,1927,1926,2010,2010,2010,1947,2007,1940,1940,1950,1942,1946,1946,1954,1938,1939,1939,1940,2007,1938,1940,1940,2012,2012,2012,1931,1941,2007,1959,1957,1923,1929,1946,2001,2006,1954,1960,1963,1963,1963,1963,1963,1963,1963,1963,1954,1941,1942,1948,1948,1928,2004,2004,1910,1942,1942,1938,1942,1942,1946,1946,1948,1948,1949,1947,1947,1947,1952,1980,1924,1924,2007,2002,2003,2011,2011,2010,1928,2010,2007,2010,2010,1903,1903,2006,2007,2010,2010,2010,2010,1925,1971,1893,1893,2007,2006,2006,2007,1926,1895,2009,2009,2009,2009,1922,1954,1929,2006,2011,1927,1931,1931,1927,1927,1926,1926,1947,1910,2007,1926,1929,1919,1962,1929,1952,1900,1949,1957,1888,1888,2006,1937,1915,1928,1922,1906,2005,2003,1947,1929,1930,1930,1949,2011,2011,1918,2003,1942,1942,2012,1924,1924,1954,1931,1939,1963,1963,1908,1908,1912,1908,1949,1948,2000,2006,2008,2008,1954,1999,1998,1924,1921,1953,1950,1911,1911,1909,1927,1952,1908,1895,1944,1925,1922,1905,1931,1910,1940,1925,1915,1900,1946,1925,1925,1932,1923,1995,1946,1946,1938,1922,1953,1935,1935,1956,1895,1905,1924,1924,1930,1947,1911,1929,1909,1953,1950,1950,1925,1925,1955,1920,1947,1912,1952,1907,1952,1952,1907,1925,1954,1952,2001,1925,1900,1948,1921,1922,1948,1939,1949,1895,1926,1926,1995,1921,1921,2011,1897,1895,1951,1949,1941,1970,2012,2012,2012,2012,1972,1973,1973,1973,1946,1995,1998,1999,1998,1998,1998,1999,1950,1950,1953,1939,1994,2004,1950,1946,2000,2000,1954,1954,1998,1998,1977,2001,1974,2001,1982,1982,1984,1984,1984,1946,1999,1945,2003,1950,1933,1951,1948,1948,1948,1948,1948,1948,1948,1948,1948,1947,1947,1947,1947,1949,1949,1948,1948,1948,1948,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1949,1951,1949,1949,1949,1949,1949,1951,1951,1951,1951,1951,1951,1951,1949,1949,1949,1949,1949,1951,1951,1952,1951,1951,1951,1953,1957,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1951,1952,1952,1952,1952,1952,1952,1952,1953,1952,1953,1952,1952,1953,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1942,1977,1950,1998,1950,1971,1997,1997,1963,1944,1941,1970,2009,1958,1972,1949,1972,1975,1977,1948,1948,1939,2002,1949,1939,1998,1984,1948,1945,1941,2004,1949,1947,1939,1954,1955,1954,1954,1954,1954,1954,1954,1954,1954,1955,1956,1955,1955,1956,1956,1956,1956,1956,1956,1956,1956,1957,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1955,1956,1955,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1954,1955,1961,1954,1954,1954,1957,1958,1958,1958,1957,1957,1958,1955,1956,1956,1955,1955,1955,1955,1965,1956,1955,1958,1957,1959,1956,1956,1955,1955,1957,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1962,1961,1961,1961,1961,2012,1973,1959,1960,1961,1961,1959,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1956,1956,1956,1956,1956,1956,1956,1956,1957,1957,1957,1956,1957,1957,1957,1957,1956,1957,1957,1957,1958,1958,1956,1956,1956,1956,1955,1955,1955,1955,1956,1956,1956,1955,1958,1955,1955,1955,1955,1954,1955,1955,1955,1955,1955,1955,1955,1956,1955,1955,1955,1955,1955,1955,1956,1956,1956,1956,1956,1956,1956,1957,1957,1957,1957,1957,1957,1955,1955,1955,1955,1955,1956,1962,1960,1960,1957,1956,1956,1956,1955,1956,1956,1956,1956,1956,1956,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1958,1958,1958,1958,1958,1958,1959,1959,1959,1958,1958,1958,1958,1958,1958,1958,1957,1957,1957,1958,1958,1957,1957,1957,1957,1957,1957,1957,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1957,1957,1957,1957,1957,1957,1957,1957,1957,1956,1956,1956,1957,1996,1998,1996,1998,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1956,1957,1957,1954,2010,2010,2010,1937,1979,1940,1952,1940,1947,2001,2006,1947,1928,1963,1955,1954,1931,1931,1960,1951,1987,1946,2002,2002,1926,1965,1965,1947,1955,1946,1974,1974,1931,1959,1954,1959,1953,1953,1953,1953,1954,1954,1954,1954,1954,1954,1953,1953,1953,1953,1953,1953,1953,1954,1956,1954,1954,1954,1983,1983,1997,1997,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,1982,1982,1982,1982,1982,1982,1982,1983,1983,1983,1983,1941,1952,1953,1953,1953,1953,1956,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1958,1958,1960,1960,1955,1955,1955,1961,1957,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1959,1957,1956,1958,1958,1957,1956,1956,1961,1962,1963,1966,1963,1963,1941,1941,1949,1941,1953,2010,1953,1953,1958,1944,2012,1942,1941,1940,1939,1938,1952,1952,1951,1951,1951,1951,1951,1957,1957,1951,1951,1952,1953,1951,1953,1952,1951,1953,1954,1953,1938,1938,1952,1953,1952,1954,1953,1953,1952,1951,1953,1952,1952,1954,2009,1952,1952,2004,1952,1952,1951,1955,1953,1953,2004,2008,1953,1954,1955,2006,1955,1955,1954,1954,2006,1957,1956,1956,1956,1955,1956,1956,1956,1957,1956,1956,1959,1959,1960,1960,1960,1961,1958,1978,1974,1974,1978,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1978,1978,1978,1977,1978,1977,1977,1978,1958,1960,1958,1958,1959,1960,1956,1956,1956,1957,1959,1959,1958,1958,1958,1957,1959,1968,1959,1958,1954,1954,1957,1957,1956,1956,1956,1958,1957,1958,1956,1957,1956,1957,1957,1957,1957,1953,1957,1957,1956,1957,1955,1956,1955,1956,1956,1956,1956,1957,1957,1964,1954,1955,1954,1958,1955,1956,1941,1941,1942,1936,1923,1942,1942,1926,1935,1948,1948,1948,1923,1923,1923,1952,1941,1941,1941,1930,1925,1925,1949,1949,1942,1948,1948,1948,2000,1958,1947,1942,1926,1947,1942,1938,1925,1952,1925,1925,1927,1927,1949,1927,1948,1948,1948,1952,1925,1948,1948,1952,1933,1927,1927,1941,1953,1951,1951,1957,2003,2003,2003,1915,1915,1929,1947,1948,1948,1952,1925,1948,1948,1930,1930,1950,1950,1922,2003,1947,1947,1942,1943,1943,1941,1942,1942,1946,1946,1928,1928,1927,1925,1949,1925,1943,1943,1942,1942,1943,1943,1943,1942,1943,1943,1944,1944,1942,1942,1942,1953,1944,1948,1947,1953,1953,1949,1954,1954,1953,1953,1963,1975,1975,1953,2007,2006,2006,2006,2006,2006,2007,2007,2007,2009,2009,2002,2001,2002,2001,2004,2002,2001,2001,2002,2003,2003,2004,2005,2003,2004,2003,2002,2002,2002,2002,2002,2002,2003,2002,2002,2001,2001,2001,2002,2002,2003,2002,2002,2002,2002,2002,2001,2002,2002,2004,2004,2004,2004,2004,2004,2004,2004,2004,2004,2006,2006,2006,2006,2005,2005,2006,2007,2007,2007,2007,2007,2007,2007,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2005,2004,2004,2004,2004,2005,2008,2008,1948,1905,1948,1940,1956,1956,1956,1956,1956,1956,1942,1942,1930,1941,1941,1941,1958,1916,1942,1949,1952,1948,1909,1952,1930,1930,1928,1941,1941,1955,1941,1927,1919,1941,1941,1932,1928,1940,2004,1920,1948,1952,1887,1949,1949,1954,2001,1952,1948,1949,1948,1951,1952,1951,2004,1952,2001,1946,1940,1932,1929,1929,1929,1929,1947,1940,1948,1948,1948,1946,1940,1940,1940,1941,1940,1906,1998,1949,1951,1946,1946,1941,1942,1942,1948,1942,1985,1951,1951,1940,1940,1951,1939,1949,2007,2006,1945,1945,1945,1945,1945,1945,1945,1942,1942,1942,1942,1942,1942,1942,1950,1942,1951,1942,1951,1951,1952,1951,1951,1951,1946,1946,1942,1939,1947,1950,1948,1948,1941,1942,1948,2011,2011,1951,1948,1950,1950,1951,2007,1942,1942,1944,1944,1944,1956,1956,1947,1940,1938,2006,1941,1948,1949,1948,1995,1996,1996,1996,1997,1997,1997,1997,1997,1954,1941,1939,1947,1948,2012,2012,1949,1940,1954,1946,1946,1948,1949,1963,1951,2011,2012,1947,1949,1947,1947,1947,1942,1942,1948,1946,1948,1938,1938,2005,1949,1941,1925,1949,1951,2007,1942,1947,1948,1943,1948,1947,1941,1941,1941,1941,2006,1949,1949,1949,2012,2012,1951,1938,2005,2007,2009,2009,1946,1946,2008,1938,2011,2011,1946,1951,1940,1941,1939,1949,1951,1994,1984,1984,1985,1985,1984,1984,1946,1946,1945,1947,1947,1947,1942,1930,1938,1940,1940,1916,1910,1952,1952,1945,1945,1945,1952,1948,1923,1947,1932,1939,1948,1948,1947,1947,1972,1949,1949,1950,1950,1950,1950,1949,2006,2006,1914,1891,1958,1952,1948,1940,2005,1947,1952,1952,1952,1951,1896,1948,1952,1955,1954,1931,1931,1931,1931,1955,1936,1937,1925,1928,1931,1933,1937,1927,1937,1924,1905,1931,1926,1952,1927,1927,1928,1927,1924,1924,1927,1949,1925,1931,1932,1932,1929,1928,1938,1938,1938,1937,1937,1938,1932,1932,1937,1952,1940,1940,1947,1947,1947,1954,1954,1938,1938,1951,1942,1938,1941,1941,1948,1940,1942,1930,1939,1948,2002,1952,1947,1951,1947,1954,1954,1949,1949,2005,1942,1941,1945,1939,1940,1926,1915,1915,1923,1941,1938,1938,1938,1940,1939,1916,1914,1924,1924,1924,1949,1949,1949,1980,1942,1942,1926,1925,1918,1910,1926,2011,2011,1937,2004,1906,1926,1930,1938,1938,1927,1929,1929,1927,1929,1929,1927,1933,1932,1932,1955,1931,1938,1932,1948,1948,1948,1948,1939,1928,1940,1953,1959,1959,1959,1959,1959,1959,1959,1939,1939,1939,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1972,1972,1972,1972,1951,1949,1949,1956,1947,1938,1965,1965,1940,1946,1955,1955,1940,1942,1924,1924,1936,1937,1929,1999,2004,2004,1926,1926,1926,1936,1929,1935,1936,1937,1936,1936,1936,1936,2006,1936,1936,1940,1946,1941,1973,1933,1927,1938,1939,1942,2008,1947,1955,1947,1947,1956,1953,1963,1963,1963,1963,1963,1963,1963,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1962,1962,1962,1962,1962,1962,1962,1962,1948,1958,1954,1958,1948,1946,1946,1947,1949,1940,2011,1946,1944,1944,1943,1944,1938,1951,1938,1941,1941,1941,1948,1948,1937,1941,1942,2002,2006,1939,1941,1939,1940,1942,1944,1942,1942,1946,1941,1941,1942,1940,1940,1941,1990,1990,1949,1949,1940,1940,1949,1937,1936,1991,1938,1937,1940,1940,1940,1936,1936,1937,1937,1937,2006,2000,2006,2007,2011,2001,1966,2006,2000,1996,2005,2005,1993,1951,2012,2007,2007,1951,1954,2011,1957,1957,1957,1952,2000,1998,1998,1998,1941,2004,2001,1941,2005,1941,2010,2007,1999,2004,2004,1950,2007,1953,2004,1959,1954,1954,2004,2000,2007,2007,1959,2012,2007,1955,2006,1996,1944,1944,2000,1949,1939,2006,1929,1938,1937,1934,1928,1954,1937,1938,1937,1948,1940,1978,1934,1944,1925,1925,1925,1928,1928,1931,1934,1953,2007,1940,1946,1927,1928,1929,1929,2001,2000,2000,1996,2007,1953,1938,1937,1935,1952,1924,1938,2005,1931,1949,1951,1929,1941,1949,1949,1955,1999,2004,1942,1951,1952,2010,2006,2007,1952,1947,1981,1957,2003,1952,1953,1949,2005,1948,1948,2005,2005,1955,1955,1955,2010,2011,1953,1953,1958,1956,1941,1955,1952,1958,1942,1943,2012,2008,1952,1952,2002,1956,1954,1952,1985,1953,1953,1961,2005,1954,1955,1942,2006,2006,1956,1956,1943,1943,1954,1954,1954,1954,1954,1954,1954,1950,1947,1946,1946,1943,1946,1946,1943,1943,1943,1943,1943,1947,1947,1947,1952,1948,1948,1951,1952,1948,1954,1949,1955,1952,1955,1952,1948,1953,1952,1953,2012,2008,1952,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2003,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,1950,2004,2004,2004,1954,1954,1954,1963,1960,1953,1949,1948,1951,1940,1948,1941,2005,1943,1938,1949,1939,1955,1952,1952,1966,2007,1962,1961,1963,1952,1955,1954,1953,1954,1954,1953,1953,2006,1954,2000,2012,2012,1952,2005,1954,1952,1951,1951,1953,2006,2012,2012,2006,1960,1952,1952,1951,1950,1948,1951,1951,2007,1955,2004,1956,1955,1955,2006,1955,1955,2006,1955,1955,1954,1954,1996,1962,1961,1957,1957,2012,1956,1956,1954,1957,1958,1958,1955,1956,1955,1956,1961,1962,1961,1962,1965,1973,2002,2000,1999,2000,2008,1999,2001,1999,2000,2000,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2007,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2005,2004,2004,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2000,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,2008,1940,2004,2005,2005,2005,2006,2006,2004,2002,2002,2002,2002,2002,2003,2003,2004,2005,2006,1998,1998,1998,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1998,1998,1998,2000,1998,1999,1999,2000,1999,1998,1998,1998,1998,1998,1998,1998,1999,2000,2000,2000,1999,2000,1999,1999,2000,2000,1999,1999,2003,2005,2005,2002,2002,2002,2005,2005,2005,2005,2005,2005,2006,2006,2006,2006,2006,2006,2006,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2006,2008,2008,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2010,2011,2010,2011,2010,2011,2011,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2008,2009,2009,2011,2011,2011,2012,2012,2012,2012,2010,2010,2010,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2012,2012,2011,2011,2008,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2010,2010,2011,2010,2010,2011,2010,2011,2011,2009,2010,2010,2009,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1962,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1968,1968,1968,1966,1966,1966,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1967,1968,1968,1968,1968,1967,1967,1967,1967,1967,1967,1967,1967,1967,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1973,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1967,1967,1967,1967,1967,1967,1967,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1979,1963,1991,1967,1991,1994,1958,1969,1968,1968,1968,1968,1972,1973,1968,1955,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1979,1980,1980,1980,1980,1980,1980,1980,1980,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1982,1983,1983,1983,1983,1983,1983,1983,1983,1998,1998,1998,1998,1998,1999,1998,1999,2000,2000,2000,2000,2000,2000,2000,2000,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1975,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1995,1995,1995,1996,1998,1998,1997,1997,1996,1996,1995,1994,1998,1998,1998,1998,1998,1998,1998,1957,1993,1959,1958,1958,1957,1958,1959,1963,1964,1964,1963,1961,1960,1958,1958,1970,1959,1958,1961,1962,1960,1966,1966,1929,1959,1959,1953,1953,1953,1953,1955,2009,2009,1973,1959,1955,1927,1961,1947,1969,1945,1973,1951,1934,1968,1951,1945,1945,1951,2005,1956,1957,1953,1953,1953,1958,1958,2000,2000,2000,2000,2006,2006,2006,1956,1917,1945,1900,1973,1952,1961,2001,2006,1947,1946,1945,1945,1945,1978,1947,1947,1947,2011,2011,1958,1958,1958,1958,1956,1957,1957,1958,1959,1957,1957,1957,1957,1957,1957,1957,1957,1958,1958,1963,1963,1965,1973,1974,1974,1973,1974,1973,1974,1973,1973,1973,1973,1973,1973,1973,1973,1973,1974,1974,1974,1977,1993,1993,1993,1963,1963,1981,1981,1981,1981,1982,1983,1983,1982,1964,1960,1984,1984,1990,1997,1984,1984,1948,1948,1960,1956,1956,1957,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1959,1959,1959,1959,1960,1960,1960,1960,1960,1961,1961,1959,1960,1960,1959,1959,1959,1959,1998,1998,1998,1998,1998,1998,1952,1952,1953,1952,1952,1952,1952,1952,1952,1952,1952,1951,1951,1953,1952,1953,1947,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1955,1954,1954,1954,1954,1954,1951,1951,1951,1951,1951,1955,1955,1952,1952,1953,1953,1953,1953,1952,1952,1952,1952,1952,1950,1953,1953,1956,1983,1983,1976,1977,1998,1998,1947,1947,1939,1939,1956,1956,1956,1985,1956,1956,1956,1952,1957,1959,1948,1985,1986,1986,1953,1953,1954,1953,1953,1953,1953,1953,1953,2004,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,2009,1954,1955,1955,1955,1953,1955,1954,1954,1954,1954,1953,1953,1954,1954,1961,1961,1963,1981,1973,1969,1969,1969,1965,1949,1960,1960,1955,1955,1955,1956,1920,1956,1954,1955,1956,1955,1955,1921,1955,1955,1955,1954,1954,1954,1956,1956,1956,1956,1956,1956,1956,1957,1957,1959,1958,1958,1958,1958,1954,1954,1954,1954,1954,1954,1953,1953,1953,1953,1953,1953,1954,1954,1954,1960,1964,1963,1964,1965,1966,1966,1965,1966,1965,1966,1966,1966,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1976,1978,1977,1977,1977,1978,1978,1967,1967,1967,1978,1978,1978,1978,1978,1978,1978,1979,1979,1979,1979,1979,1979,1979,1979,1980,1984,1984,1984,1984,1985,1997,1997,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1953,1953,1954,1954,1953,1953,1953,1954,1954,1954,1954,1954,1955,1955,1955,1955,1955,1955,1955,1955,1955,1954,1955,1955,1955,1955,1953,1954,1954,1955,1955,1950,1954,1961,1958,1958,1957,1978,1978,1977,1957,1957,1957,1958,1958,1958,1958,1957,1960,1960,1961,1958,1960,1956,1956,1956,1956,1956,1956,1956,1958,1956,1956,1957,1958,1958,1957,1957,1957,1957,1958,1958,1957,1957,1958,1958,1959,1959,1960,1966,1968,1967,1967,1967,1968,1967,1967,1967,1961,1963,1962,1963,1963,1961,1962,1961,1968,1964,1956,1959,1960,1953,1980,1980,1980,1980,1980,1982,1982,1982,1982,1982,1983,1983,1983,1992,1983,1983,1985,1984,1984,1984,1984,1983,1983,1986,1986,1986,1986,1985,1985,1986,1997,1997,1997,1997,1997,1997,1997,1997,1997,1982,1982,1982,1982,1982,1983,1983,1982,1982,1983,1983,1983,1983,1983,1992,1993,1993,1980,1980,1980,1980,1982,1982,1982,1982,1982,1984,1984,1984,1984,1984,1983,1987,1987,1987,1984,1983,1983,1984,1983,1983,1983,1983,1983,1983,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1984,1986,1983,1983,1984,1988,1985,1986,1996,1996,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1984,1984,1984,1984,1985,1985,1985,1985,1985,1995,1995,1995,1995,1995,1995,1995,1986,1985,1985,1985,1984,1985,1984,1986,1986,1986,1985,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1966,1966,1964,1972,1965,1928,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1976,1976,1976,1976,1977,1977,1977,1977,1974,1974,1974,1974,1974,1977,1977,1960,1970,1962,1962,1960,1960,1972,1972,1972,1972,1966,1966,1966,1967,1966,2003,1970,1970,1970,1970,1970,1970,1970,1971,1963,1966,1963,1964,1963,1963,1963,1974,1992,1970,1964,1968,1964,1964,1964,1964,1964,1965,1965,1965,1965,1965,1965,1965,1968,1968,1967,1967,1968,1968,1968,1968,1967,1978,1978,1972,1972,1972,1972,1972,1973,1973,1972,1972,1973,1973,1956,1957,1955,1955,1956,1955,1955,1956,1960,1955,1956,1970,1970,1970,1970,1970,1970,1970,1970,1963,1963,1963,1962,1963,1963,1963,1963,1960,1956,1957,1955,1953,1961,1961,1927,1927,1956,1984,1984,1985,1962,1962,1962,1962,1962,1959,1959,1955,1955,1955,1956,1956,1953,1953,1955,1953,1953,1953,1953,1954,1953,1953,1953,1953,1953,1953,1954,1953,1953,1955,1955,1954,1956,1955,1955,1982,1952,1951,1952,1952,1952,1952,1952,1953,1952,1952,1952,1952,1951,1951,1952,1951,1951,1951,1951,1952,1952,1952,1952,1952,1952,1967,1952,1952,1952,1951,1952,1951,1951,1951,1951,1951,1952,1951,1951,1951,1951,1951,1951,1952,1951,1952,1951,1952,1952,1952,1953,1952,1952,1955,1955,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1964,1953,1953,1953,1951,1951,1951,1951,1951,1951,1951,1951,1951,1950,1951,1951,2006,1949,1949,1949,1949,1949,1951,1949,2005,1949,2012,1949,2007,2006,2010,2012,2012,2003,2012,2012,1951,1952,1951,1951,2005,1951,2005,1951,1951,1956,1956,1951,1954,2011,1951,1951,2011,2012,2012,1952,1954,1952,2007,1951,1951,2004,1950,1952,2007,1953,1957,1957,1953,1952,1951,2006,2006,1953,2005,1951,1951,1954,1957,1973,1953,1955,1955,2004,2011,2011,1956,2006,1952,2012,2012,1952,1953,1953,1953,1953,1953,1953,1953,1953,1952,1952,1955,1953,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,1952,2007,1953,1953,1952,1952,1952,1951,1953,1952,1952,1953,1953,1953,1953,1953,1953,1954,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1953,1957,1953,1957,1957,1956,1954,1954,1955,1954,1954,1954,1966,1967,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1967,1967,1966,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1973,1973,1973,1973,1964,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1970,1952,1969,1965,1966,1966,1966,1966,1969,1974,1967,1967,1967,1967,1967,1967,1963,1963,1963,1964,1970,1964,1972,1972,1966,1972,1971,1964,1965,1971,1968,1968,1968,1968,1968,1972,1969,1969,1969,1969,1969,1969,1971,1971,1971,1972,1972,1972,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1974,1975,1975,1975,1975,1975,1975,1975,1974,1974,1974,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1976,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1965,1964,1964,1964,1965,1973,1965,1965,1966,1966,1966,1968,1967,1966,1967,1967,1966,1967,1967,1967,1968,1969,1970,1968,1968,1968,1974,1974,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1974,1974,1974,1974,1974,1974,1974,1974,1977,1976,1977,1977,1977,1975,1974,1974,1977,1977,1985,1979,1981,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1983,1984,1991,1991,1991,1986,1985,1993,1987,1986,1986,1987,1988,1989,1987,1987,1986,1990,1990,1968,1962,1963,1963,1964,1964,1968,1968,1969,1969,1968,1967,1968,1967,1968,1976,1976,1975,1975,1975,1975,1976,1976,1976,1974,1976,1974,1976,1974,1974,1974,1974,1974,1974,1976,1976,1979,1981,1981,1981,1982,1983,1982,1982,1982,1981,1983,1983,1983,1983,1983,1982,1983,1987,1988,1985,1984,1984,1984,1985,1985,1972,1972,1972,1973,1973,1972,1972,1971,1971,1969,1972,1971,1972,1968,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1962,1962,1962,1967,1963,1963,1962,1962,1962,1967,1966,1966,1964,1962,1964,1964,1971,1969,1972,1972,1972,1972,1969,1970,1969,1971,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1963,1980,1980,1980,1980,1980,1979,1979,1981,1981,1981,1981,1981,1981,1981,1981,1981,1979,1979,1979,1981,1980,1980,1980,2010,2010,2010,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2011,2006,2006,2006,2006,2006,1964,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1973,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1965,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1966,1984,1984,1984,1985,1986,1997,1997,1997,1997,1997,1997,1997,1997,1974,1973,2012,2011,2011,2012,2012,2012,2011,2011,2011,2010,2011,2011,2011,2011,2011,1963,1963,1965,1963,1963,1963,1963,1970,1970,1968,1963,1963,1963,1969,1970,1970,1970,1970,1970,1969,1969,1970,1969,1968,1968,1968,1968,1968,1968,1969,1964,1969,1969,1967,1967,1967,1969,1969,1968,1968,1968,1968,1968,1968,1970,1970,1970,1970,1969,1973,1972,1972,1972,1973,1973,1973,1973,1973,1973,1973,1972,1972,1972,1972,1972,1972,1969,1969,1969,1969,1969,1969,1970,1970,1970,1970,1970,1971,1971,1970,1971,1971,1971,1971,1971,1972,1971,1971,1971,1971,1971,1971,1970,1970,1971,1969,1969,1963,1963,1963,1963,1968,1968,1973,1973,1968,1974,1968,1969,1964,1964,1964,1964,1964,1964,1964,1964,1972,1972,1972,1972,1972,1973,1973,1973,1973,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1972,1973,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1970,1970,1971,1971,1971,1970,1971,1971,1971,1971,1970,1971,1968,1967,1966,1967,1967,1966,1967,1969,1971,1971,1971,1973,1972,1969,1969,1971,1970,1974,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1968,1969,1965,1965,1966,1966,1966,1964,1965,1963,1971,1971,2002,2004,2004,2004,2004,1962,1964,1964,1963,1964,1965,1965,1972,1963,1963,1963,1963,1962,1964,1962,1963,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1969,1973,1973,1973,1973,1973,1972,1973,1972,1976,1974,1974,1974,1974,1974,1976,1974,1974,1975,1974,1975,1976,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1960,1959,1959,1957,1957,1958,1959,1960,1959,1961,1961,1962,1958,1958,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1957,1956,1957,1957,1956,1956,1956,1956,1956,1956,1956,1956,1956,1979,1979,1979,1979,1998,1998,1998,1998,1998,1998,1998,1998,2006,2003,2012,2012,2003,2003,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2012,2011,2011,2011,2011,2011,2011,2011,2012,2012,2012,2012,2012,2012,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1983,1976,1976,1976,1976,1976,1978,1972,1969,1969,1969,1975,1975,1976,1976,1976,1978,1978,1978,1978,1978,1980,1980,1978,1978,1978,1980,1980,1980,1980,1981,1981,1983,1984,1984,1984,1982,1982,1982,1982,1982,1986,1986,1986,1986,1986,1987,1986,1988,1987,1990,1990,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1978,1984,1984,1984,1984,1984,1984,1970,1970,1970,1970,1971,1972,1972,1972,1972,1972,1972,1972,1970,1970,1970,1970,1971,1972,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1999,1998,1998,1998,1998,1998,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1999,1963,1994,1969,1967,1968,1964,1969,1968,1999,1999,1999,1999,1999,1999,1999,1963,1971,1971,1963,1963,1971,1963,1964,1964,1963,1964,1970,1970,1963,1963,1963,1971,1969,1963,1963,1963,1963,1964,1971,1971,1971,1970,1970,1970,1970,1970,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1971,1972,1973,1972,1972,1973,1973,1989,1988,1988,1989,1979,1985,1989,1985,1982,1976,1976,1976,1974,1974,1973,1973,1990,1976,1971,1973,1973,1974,1977,1977,1978,1979,1970,1979,1977,1989,1979,1977,1978,1964,1965,1964,1964,1965,1963,1964,1964,1974,1962,1963,1959,1959,1959,1959,1960,1959,1973,1961,1961,1961,1961,1961,1961,1960,1960,1959,1959,1959,1959,1962,1962,1962,1959,1959,1959,1957,1960,1960,1958,1958,1958,1958,1958,1958,1957,1958,1957,1957,1957,1957,1957,1957,1957,1957,1971,1971,1971,1971,1971,1972,1972,1972,1972,1972,1972,1972,1972,1973,1973,1973,1973,1973,1973,1966,1969,1966,1966,1966,1966,1966,1969,1968,1997,1971,1971,1970,1971,1966,1973,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1974,1976,1976,1976,1976,1977,1976,1976,1976,1977,1988,1994,1972,2004,1973,1973,1973,1973,1973,1975,1975,1972,1973,1973,1973,1973,1978,1978,1978,1979,1983,1995,1996,1994,2000,1993,1993,1994,1997,1978,1979,1979,1979,1979,1979,1979,1980,1980,1978,1995,1995,1995,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2003,2003,2003,2003,2003,1977,2004,2004,1977,1977,1977,1978,1978,1978,1977,1977,1977,1978,1977,1977,1977,1977,1977,1977,1978,1978,1978,1978,1978,1984,1984,1981,1981,1981,1983,1983,1983,1983,1983,1982,1981,1983,1983,1983,1981,1983,1982,1982,1981,1982,1982,1982,1982,1982,1982,1983,1983,1983,1983,1981,1982,1983,1983,1983,1983,1981,1981,1980,1981,1981,1981,1981,1981,1981,1981,1982,1982,1981,1981,1981,1982,1983,1981,1981,1981,1980,1980,1980,1980,1982,1982,1982,1982,1982,1982,1982,1980,1982,1982,1982,1982,1982,1982,1982,1980,1980,1980,1980,1980,1980,1980,1980,1980,1980,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1983,1984,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,1975,1975,1975,1977,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1987,1983,1983,1985,1985,1985,1985,1985,2003,2003,2004,2004,2004,2005,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,2001,1974,1976,1974,1974,1974,1974,1974,1974,1974,1986,1978,1978,1978,1978,1978,1974,1979,1974,1974,1974,1979,1996,1996,1996,1996,1996,1996,1997,1997,1997,1997,1998,1997,1997,1997,1997,1997,1998,1998,1998,1998,1998,1999,1998,1998,1998,1998,1998,1998,1998,1999,1998,1998,1998,1998,1998,1998,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1997,1996,1997,1997,1997,1997,1997,1996,1997,1996,1997,1997,1997,1998,2000,1999,1998,2000,1999,1999,1999,1999,1999,1999,1998,1998,1998,1997,1996,1996,1997,1997,1996,1997,1997,1997,1997,1997,1997,2000,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998,1998],"yaxis":"y","type":"scattergl"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Before 1980 (1: Yes, 0: No)"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Year Built"}},"legend":{"tracegroupgap":0},"title":{"text":"Year built vs. before1980"}},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('0b6d41ef-2f1c-4e74-b6aa-cb27b93d9e98');
+var gd = document.getElementById('aa07b9f5-1121-4ebe-b48a-27144f144782');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -4938,9 +4938,9 @@ <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
                         })                };                });            </script>        </div>
 </div>
 <div class="cell-output cell-output-display">
-<div>                            <div id="f2dde298-4930-4351-bc72-ee7b23189ed9" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("f2dde298-4930-4351-bc72-ee7b23189ed9")) {                    Plotly.newPlot(                        "f2dde298-4930-4351-bc72-ee7b23189ed9",                        [{"hovertemplate":"before1980=%{x}\u003cbr\u003elivearea=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"","showlegend":false,"x":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,0,0,0,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,0,0,1,1,0,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,0,0,0,1,0,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,1,1,0,1,1,0,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,1,0,1,1,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,1,0,0,0,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,1,0,0,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,0,0,1,1,0,1,1,0,0,1,1,1,1,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,0,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,0,1,0,0,1,1,1,1,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,0,1,1,0,0,0,1,0,0,1,1,1,1,1,1,0,1,1,1,0,0,0,1,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,1,1,0,1,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,0,1,0,1,1,1,1,1,0,0,0,1,1,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,0,0,0,1,1,0,0,0,1,0,1,0,1,0,0,1,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,1,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,0,0,1,1,0,0,1,0,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,1,0,1,1,1,1,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,1,0,1,1,1,0,0,0,0,1,0,0,1,0,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,0,1,0,1,1,1,0,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,0,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,1,0,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,0,0,0,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"xaxis":"x","y":[1346,1249,1346,1146,1249,1249,1098,1346,1249,1346,1098,3902,2732,2927,2811,3106,2732,2564,1731,1508,1508,1508,1754,1754,1508,1243,1754,1754,1508,1508,1508,1731,1508,1508,1731,1731,1754,1754,1754,1509,1509,1509,1509,1509,1509,1509,2854,2855,3126,1834,3305,3305,3305,2927,1960,2042,1960,2042,2042,2079,1960,2042,1982,2588,2588,2855,1279,1574,2042,1743,1574,1574,2580,2079,1279,2079,1804,1432,1731,1420,1731,1743,1731,1456,1743,1470,1731,1743,1743,1420,1743,1743,1504,1463,1743,1432,1749,1749,1731,1731,1420,1420,1237,1237,1731,1731,1731,1731,947,947,1743,1743,1420,1420,1743,1743,1420,1420,1739,1739,1432,1432,1731,1731,1731,1731,1491,1731,1432,1743,1743,1420,1420,1743,1743,1743,1743,1743,1731,1731,1731,1731,1420,1420,1743,1743,1731,1731,1731,1731,1371,1432,1731,1504,1420,1731,1420,1743,1420,1432,1432,1743,1743,1456,1432,1743,1420,1731,1743,1432,1731,1420,1731,1432,1731,1432,1743,1420,1743,1743,1743,1743,1420,1731,1504,1504,1743,1731,1731,1743,1743,1731,1731,1731,1731,1731,1743,1743,1743,1743,1743,1731,1731,1731,1432,1731,1731,1743,1743,1420,1420,1731,1743,1743,1432,1432,1743,1420,1504,1743,1743,1420,1420,1743,1743,1743,1432,1432,1743,1743,1743,1492,1731,1731,1731,1420,1743,1731,1731,1432,1432,1420,1731,1731,1420,1432,1432,1420,1524,1524,1420,1731,1731,1731,1731,1432,1432,1432,1432,1743,1743,1731,1731,1420,1420,1731,1731,1432,1432,1731,1731,1731,1731,1420,1731,1731,1731,1731,1731,1731,1731,1731,1743,1743,1420,1420,1743,1743,1432,1432,1432,1432,1432,1731,1731,1731,1731,1237,1237,1731,1731,1731,1731,1731,1731,1743,1743,1420,1420,1420,1420,1420,1420,1743,1743,1420,1420,1463,1463,1492,1492,1420,1420,1731,1731,1743,1743,1420,1420,1267,1267,1503,1503,1420,1420,1731,1731,1743,1743,1432,1432,1731,1731,1731,1731,1731,1731,1420,1731,1731,1731,1731,1731,1731,1743,1743,1420,1420,1420,1420,1731,1731,1743,1743,1731,1731,1731,1731,1432,1432,1420,1420,1731,1731,1743,1743,1420,1420,1743,1743,1504,1504,1751,1751,1743,1743,947,947,1743,1743,1743,1743,1731,1731,1420,1420,1743,1743,1743,1743,1420,1420,1543,1543,1743,1731,1731,1743,1743,1743,1743,1743,1743,1743,1739,1743,947,1743,1743,1420,1743,1743,1173,2466,2001,2494,1173,2466,2016,1830,2466,1686,2466,2466,3668,3437,1905,1570,1905,1905,1905,3666,3666,3051,3687,3033,3872,3692,3449,2466,1887,1887,2466,1899,1899,1613,1601,1887,1570,1887,1173,1593,1899,2001,3656,3656,3428,3881,3539,1905,3883,3883,3697,3261,3688,4119,3037,2685,3001,3001,3883,3883,2699,3902,4129,2693,2693,3674,3355,3656,2139,2802,2139,2138,2599,2139,2599,2139,2802,2802,2139,2802,2599,2139,2531,2180,2630,2139,2138,2599,2599,2599,2139,2599,2599,2943,3176,3192,3192,3388,3769,2278,2278,3644,3644,2519,4009,2927,3428,3912,3554,3934,3769,3616,3540,3540,3934,3783,3708,2718,2732,3192,1924,2548,1960,1924,3192,3192,3176,1509,1509,1509,1853,1416,1508,1853,1853,1853,1508,1450,2115,2466,1581,1243,1243,1509,1731,1226,1152,1152,1271,1271,829,1265,1265,876,1342,1233,1180,1342,1614,1233,1180,1180,1233,1342,1180,1180,1342,1411,1766,1610,1411,1731,1394,1394,1526,1226,1226,1153,1277,1590,1302,1614,1342,876,876,1233,876,1342,1233,1180,1342,1342,1614,1148,1227,1227,868,868,1267,1257,1716,1401,1401,1401,1523,1610,1610,1540,1766,1779,1430,1274,1227,1152,1224,1152,1152,1152,1145,1145,1275,1279,1279,1146,1098,1098,1146,1098,1098,1146,1249,1098,1109,1243,1243,1509,1731,1509,1509,1731,1509,1836,1402,1494,1402,1494,1252,1506,1836,1426,1520,1450,1494,1853,1836,1836,1506,1506,1973,1494,2577,2566,1836,2835,2835,2169,2835,2835,2835,1396,2566,2001,2001,2016,2115,1887,2259,2115,2525,1803,1810,1992,2566,2191,1751,1524,1524,1524,1524,1751,1845,1677,1805,1874,1581,1600,1524,1489,1845,1845,1845,1803,1524,1803,3305,2927,1982,2079,2079,1960,1594,2015,2215,1594,1489,2487,2487,1834,3321,1858,1845,1524,1524,1524,1858,1524,1845,1845,1845,1858,1858,1516,1516,1858,1751,1858,1751,1803,1845,1858,1905,3883,2816,2001,2979,1570,3427,1905,1574,2079,1960,1574,2070,1960,1960,2070,1574,1960,1982,1574,1574,2070,2070,2079,1574,1960,2070,1960,2070,2041,1960,2079,1960,1279,1960,2042,1279,2202,2202,1812,2130,1808,1808,1808,1808,2525,1413,2513,1413,2387,2040,1818,1808,2513,1812,1733,2495,1287,2180,1287,1557,2374,2513,1413,2513,2374,2130,1725,2081,2130,2374,1557,1287,1733,2525,2525,1557,1557,2525,2525,1557,1557,2525,2525,1557,1557,2495,1557,2495,2495,2525,2525,1733,1733,2100,2100,2495,2524,2180,1733,1557,2180,2495,2180,2180,1733,1557,1733,1557,1330,1557,1557,2180,1349,1557,2525,1733,1733,1557,1557,1733,1733,2100,2100,1853,2180,1547,1733,1287,1557,2180,2495,1733,1733,2525,2525,1557,1557,1733,1733,1557,1557,2525,2525,2180,2180,2179,2179,1557,2180,2180,2180,1557,1557,2180,1557,1557,1733,1733,1547,1547,2180,1733,2525,1673,2070,1299,1893,1893,2076,1689,1579,1970,1579,1970,1970,1288,1579,2070,2076,1579,1893,1893,1304,1412,1558,1412,2081,1779,1779,1412,1779,1412,1412,2081,1412,1412,2081,2081,1164,960,1248,1248,1248,1056,1056,1164,1248,1164,1164,1164,1164,1386,912,912,1248,1204,1445,960,960,912,1204,960,1164,1056,1056,1386,960,1248,1248,1164,1248,1454,960,960,960,1164,1164,1164,1386,1386,1056,1056,1248,1248,1386,1445,1248,1164,1400,1056,1248,1249,1248,960,925,1121,1026,925,925,925,1121,1148,931,1144,1121,1144,1148,1148,1148,925,1148,931,1121,925,1026,1048,1144,931,1144,1144,1144,1048,1048,1048,1148,1148,1144,1026,1121,1121,931,931,1148,857,857,968,857,2244,857,857,1840,1205,968,1404,1404,968,1840,1840,968,857,857,857,857,1404,1840,968,857,1147,1134,857,857,1404,1044,1060,1324,1044,1060,1444,1300,840,1039,1039,840,840,840,840,840,987,987,987,1549,987,1183,1183,840,840,987,840,987,987,840,840,840,1095,857,1205,857,1404,1404,857,1404,968,968,857,857,857,1404,1404,1641,1629,1524,1074,1074,1260,1553,1754,2035,1346,1856,1147,2227,1841,1855,1914,1914,1686,1056,1481,1754,1726,1876,2302,1666,1540,1540,2061,2061,1524,1633,1633,1826,1600,1600,1600,1409,1728,1714,1855,1386,1829,1936,1456,1936,1666,1456,1936,1060,1060,2647,1589,1439,1044,1947,1044,848,1364,1060,1060,1060,1060,1060,1044,1947,1060,1060,1044,848,848,848,1947,1044,1044,1060,1178,1178,1576,1395,1178,1226,1431,1524,845,1497,992,1524,1524,1524,1340,1180,1072,1072,1044,1060,1044,1126,1126,1963,1571,1571,1871,1226,1380,1380,1044,1044,1431,1431,863,1593,1388,1483,1545,1284,2286,1936,1524,1600,1545,1545,1687,1431,1732,1468,1431,1858,2430,1389,1389,1687,1665,1208,1665,1476,1665,1280,808,808,1656,1656,808,1202,1211,1703,808,808,921,921,1202,921,1703,1703,808,1605,1380,1605,1307,1308,1605,1605,1297,1297,1322,1621,1428,1584,1584,1212,1018,1621,1646,1801,1884,1884,1636,1950,1950,1950,1268,1676,1676,1540,1565,1855,1855,1394,842,1394,1394,1394,1394,1119,1394,1405,1159,1159,1159,842,1405,1203,2030,1496,842,1496,842,952,952,842,1496,1236,1496,1280,2061,1388,1388,1389,1545,1545,1280,1676,1524,1524,1600,1600,998,1694,1694,1804,1280,2322,1666,2321,1826,1826,921,921,1211,921,1703,1202,1703,1202,1703,808,1703,1703,1703,1202,921,808,808,1680,1680,1680,1285,1680,2134,2134,1500,1057,2134,1519,1519,1030,1397,1312,1312,1010,1010,1406,1344,1406,1312,1295,1406,1406,1037,1037,1904,2280,2280,1882,2280,1904,2280,1904,1778,1512,2280,1719,1719,1719,1036,1320,1602,1923,1923,1923,1923,1248,1719,1320,1320,1923,1602,1719,1923,1719,1656,1320,1248,1584,1320,970,1350,1248,1320,970,1520,1212,1409,1584,1211,1703,808,1202,921,1703,808,921,921,921,1703,1703,921,1211,1211,1300,1300,1300,1388,1300,1300,1534,1300,1360,1300,976,1085,1131,793,978,1214,721,1085,1085,1534,1300,1534,4129,1992,2365,1571,1804,2100,1888,1620,1751,1626,1995,1801,1987,1801,1855,1855,1855,1316,1723,1619,1453,1391,1649,1391,1723,1453,1313,1391,1649,1391,1313,2916,2519,2851,2818,3230,2360,1509,1754,1243,1731,1754,1754,1508,1508,1508,1508,1754,1508,1570,1570,1804,1731,1458,1714,1803,2001,2001,1432,1743,1743,1743,1731,1731,1902,1975,1388,2024,1823,1339,1339,2008,1636,1496,1490,1490,1490,1490,1486,1490,2024,1823,1823,1823,1211,1490,1615,1615,936,1650,1650,1650,1650,1444,1444,1615,1731,1463,1743,1615,1615,1444,1615,1224,1444,1615,1615,1650,1731,947,947,1444,1444,1224,947,947,1731,1731,1972,1496,2365,1804,1888,2027,1804,1888,1888,2833,2851,1972,2519,2674,1972,2851,2851,2938,2851,2938,2851,1972,1519,1413,1413,1626,1296,1413,1413,1626,1413,1413,1413,1413,1413,1296,1413,1413,3192,1626,1626,1296,1116,1413,1413,1519,1626,1626,1413,1626,1413,1296,2272,2272,1521,1521,1521,1406,1521,1521,1704,1704,1406,1521,1819,1406,1704,1704,1406,1406,1874,2270,1681,1681,1681,2293,2144,2033,1863,2331,1671,2293,2331,1863,2144,2144,2144,2144,1691,2144,1863,2332,2144,1691,2331,2293,2293,2331,2144,2047,2144,1858,1758,1758,1522,1522,1522,1522,1723,1522,1758,2109,1805,2170,2170,1784,2814,2170,1816,1127,1816,1349,1816,1465,1155,1832,1004,1004,1284,1284,1284,1284,1465,1832,1832,1832,1539,1539,1539,1521,1616,1539,2190,2190,1220,1220,894,1332,1332,1332,1088,1088,1328,1332,1328,1328,1332,800,1138,1088,1252,800,1540,1444,1558,1426,1012,1300,1300,1300,1300,1709,1709,1300,1300,1134,1300,1300,1300,1300,1626,1626,1626,1012,1012,1893,1709,796,1134,1134,1474,1012,1012,1893,1893,3769,3708,3769,3596,3596,3769,3616,3360,3783,3783,3360,3360,3616,2292,1140,1376,1915,1456,1887,1052,1281,1281,1281,1140,1334,2936,1776,3230,3228,1012,1012,1012,1134,796,1012,1012,1134,2818,3783,3230,2379,2379,1934,2503,2774,2774,1713,2683,2503,1934,2503,2154,1988,1988,1713,2774,2774,1934,3192,3192,2851,1646,1646,2293,2144,2293,2054,2144,1691,1691,2293,2144,2144,1863,1691,2144,2144,2047,2144,1874,2054,1516,2331,2144,2851,1625,1889,1889,1625,1625,2160,2647,1625,2184,1625,2347,2347,2347,1988,1889,1889,1889,1625,1625,1625,1988,1625,1646,1708,1294,1708,1614,2491,1281,1951,1629,1951,2303,1789,1629,1629,1026,800,1402,800,1150,1548,1548,1708,1646,1417,1417,1417,1417,1646,1646,1143,1708,1400,1143,1143,1400,1646,1400,1538,1708,1143,1400,1646,1400,1400,1708,1646,1708,1646,1646,1646,1417,1646,1294,1294,1708,1294,1417,1646,1143,1538,1646,1400,1417,1143,1143,1143,1400,1646,1646,1708,1646,1400,1708,1708,1646,1708,1646,1417,1143,1417,1708,1294,1646,1646,1646,1789,2430,1951,1281,1281,1951,1509,1509,1509,1509,1509,1509,1754,1509,1509,1731,1509,1546,1754,1243,1797,2024,1550,1485,1794,1794,1480,1087,1273,1138,1485,1138,1166,1194,801,1797,1755,1138,1138,1478,1302,1302,1341,1341,1238,1408,1790,1755,1290,1358,1370,1698,1698,1766,1766,1794,1755,1794,1790,840,840,979,979,840,840,1095,1173,840,840,840,1039,1039,864,987,1173,1173,840,840,840,840,1095,840,840,1039,840,1265,1039,987,840,987,840,840,1039,1161,1161,840,1039,987,1072,1419,1723,1723,2310,1069,1655,1833,1631,1012,1012,853,853,1012,1012,1707,1570,1041,1041,838,1464,1404,1008,1770,1072,2212,1072,1079,897,897,1723,1723,1072,2730,1780,1773,2017,1813,1771,1072,1072,1780,1780,915,2002,1072,2002,1500,1888,1826,1839,1349,1524,1072,1580,2082,1413,2082,1693,1419,2082,1700,1700,2296,2261,1700,1881,1881,1881,2309,1723,1723,1714,1981,1487,1056,1846,1002,1002,1210,863,1002,863,863,863,863,863,853,863,1002,1002,1002,1059,1059,1059,1059,866,1069,1002,1002,866,866,1064,1314,1002,1215,1215,1215,2016,863,853,1333,1608,1762,1345,1753,1345,2157,1674,2285,1333,1333,1674,1674,1761,1695,1700,1290,1632,1486,1632,1632,1133,1001,1133,1146,1124,1146,1042,870,870,1001,870,2040,2040,1331,1487,1542,1992,2085,1811,1811,2099,1725,1158,2034,1372,1372,1159,1644,1445,1080,1080,1644,1644,1080,1447,1240,1393,1240,1240,824,824,1393,1308,1308,1216,1216,2134,2134,2134,1451,1451,1451,1522,1256,1133,1522,1451,1456,1456,1451,1522,1456,1456,1451,1256,1133,1354,1456,1354,1354,1522,1133,1451,1451,1456,1456,1456,1402,1354,1354,1354,1522,1522,1522,1522,1402,1345,1398,1398,1345,1207,1398,1345,1345,1345,1345,1398,1272,2302,2165,1957,2302,2179,2000,2302,1554,1712,1554,1712,1273,1556,1712,1555,1370,1555,2287,2484,2301,2484,2180,2301,1319,1568,1305,1697,1288,1568,1325,1756,1313,1278,1421,1743,1518,1421,1743,1709,2799,2799,2799,2132,2132,1950,1950,2146,2146,2152,2152,2558,2558,2181,2181,2342,2342,2442,2442,2152,2152,2417,2417,2462,2462,2828,2828,2451,2451,1845,1845,2442,2442,2152,2152,2451,2451,2828,2828,1950,1950,1845,1845,1950,1950,2462,2462,2055,2055,1950,1950,2536,2536,2536,2536,2536,2529,2536,2536,2536,2536,2529,2529,2536,2536,2252,2529,2529,2536,2529,2536,2536,3566,2946,2946,3680,3680,3196,3196,2984,2984,3123,3123,1325,1325,1278,1278,1568,1568,1305,1305,1704,1704,1288,1288,1568,1568,1322,1322,1319,1319,1781,1781,3146,3146,3080,3080,3133,3133,2529,2529,2536,2536,2529,2529,2536,2536,2536,2536,2484,2484,2301,2301,2554,2554,2484,2484,2535,2535,2535,2535,2529,2529,2536,2536,2536,2536,2535,2535,2535,2535,2529,2529,2535,2535,3109,3109,2909,2909,3105,3105,3317,2839,2922,3317,2910,3103,3031,3031,2339,2339,3122,3228,3228,2610,2610,2169,2301,2301,2502,1326,1305,1832,1844,2557,2055,1845,2145,2181,2141,2132,1845,2417,2999,1670,2994,3190,2911,2165,2498,2165,1841,2498,2511,2168,2168,2436,2436,2498,2466,2165,2498,2144,2165,2165,2934,2934,2055,1942,1670,1942,3122,2922,2910,3103,3317,3103,3317,1957,2167,2282,1762,3031,1334,1746,3060,3192,3598,4134,1185,1997,2856,2978,2978,1509,2541,2412,1531,1586,1509,1341,1586,2660,1517,3563,2275,2124,2275,1438,1648,1438,3950,2124,3054,1514,1622,1449,1622,1674,1514,1327,1350,1570,1866,1760,1350,1795,2603,1185,1185,1357,1575,1530,4504,2968,3546,4051,4111,2784,1730,2233,3802,1564,1541,1167,2575,2386,885,2029,1167,2030,2571,2231,1167,1795,1631,2623,2262,2120,2567,2512,2231,1786,2196,1762,2784,1451,1795,3673,2304,2972,2208,2938,2608,2702,2049,2075,1645,1786,3288,2907,2919,3004,2834,2848,1185,1726,1545,1862,1784,919,1771,1178,2104,2104,1976,1976,2598,1059,1327,2868,3322,3110,2820,2502,2828,3008,807,1137,1137,807,1463,1463,1137,1137,1137,1463,1137,1137,3011,3266,2919,1531,1175,1383,1383,1496,1178,1178,1516,1516,1181,1181,1181,1181,1181,1181,1370,1370,2575,2657,2030,1516,1516,1181,1181,1370,1370,1370,1370,1181,1181,1496,1496,1496,1181,1181,1181,1181,1516,1516,1181,1181,1370,1370,1370,1370,1181,1181,1516,1516,1792,1451,1792,1122,1132,1120,1182,1132,2578,2413,2412,2945,1652,1451,1451,1784,2343,2343,2237,2146,2049,2608,2851,2439,802,802,948,1063,948,919,2040,1582,2932,2301,2287,2360,2484,2180,2180,2484,2301,2287,2287,2069,2069,2484,2287,2287,2172,2287,2301,2301,2005,2301,2180,2360,2360,1185,1518,1541,1764,1680,876,720,720,1489,2146,1438,1404,2333,2958,1824,3292,1438,1642,1647,1647,2531,2224,2531,2834,2224,2009,2244,791,817,1148,2541,2480,2164,2541,1788,648,901,903,801,1694,948,1904,1148,817,1148,817,781,781,791,1451,1459,1762,1451,1451,1676,1459,1762,1695,2200,2200,2165,2144,1841,1968,2058,2245,2343,2245,1903,1976,1933,1612,2176,2060,1839,1953,2197,1967,1341,1517,1356,1967,1462,1438,1438,1647,1647,1438,1438,2038,2012,2541,1786,1618,1618,1618,1623,1531,1509,1746,1760,1509,2541,2691,1639,1795,2197,1997,1618,2196,2009,2224,948,1441,2173,1412,1792,1724,1724,1428,1837,2660,1185,2512,2856,2009,1639,1795,2480,2702,2072,2080,1554,2029,2029,2395,1671,1712,1722,1639,1421,1743,1709,1743,1743,1518,1421,1502,2124,2124,1648,2197,1451,1438,1648,1746,1609,1438,1733,1350,1585,1567,1835,2165,1841,1768,1539,1539,2179,1670,2055,2557,1541,1812,1712,1571,1666,1437,1645,1500,1712,1712,1712,2165,2436,2436,2511,2436,2436,2436,2436,2436,2436,2436,2511,2436,2511,2436,2436,2484,2484,2202,2202,2301,2301,2554,2484,2360,2154,2287,2301,1784,1776,1185,2410,1792,1731,2403,2674,2674,2604,2604,2396,2396,2790,2790,2791,2791,2586,2586,2791,2791,2396,2396,2637,2637,2396,2396,2674,2674,2557,2642,2791,2791,2586,2586,2396,2396,2907,2642,2674,2674,2619,2736,2736,2791,2791,2880,2880,2551,2551,1664,1539,1660,1764,1660,990,1033,914,1280,2027,1860,1664,1860,2027,1979,1783,1589,1783,1979,1860,1664,1860,2146,1776,1185,1792,1451,2343,2343,3313,2436,2436,2529,2529,3317,2965,2536,2536,2536,2529,2221,2632,2945,2751,3318,2674,3123,2892,2892,2586,2586,2880,2473,2518,2403,2403,2674,2674,2396,2396,2820,2132,2055,2158,3103,3603,3317,2628,2642,2638,2286,2619,2634,3227,2580,2328,1712,1712,1452,1452,1452,1452,1671,1671,1671,1671,1513,1513,1513,1513,1452,1452,1712,1671,1452,1671,1712,1712,1671,1712,1712,1712,1671,1671,1452,1452,1712,1712,1712,1712,1712,1712,1712,1712,1712,1712,1712,1712,1671,1671,1452,1452,1513,1513,1444,1444,1712,1712,1712,1712,1712,1712,1712,1647,1452,1452,1513,1513,1712,1712,1452,1452,1712,1712,1712,1712,1712,1712,1671,1671,1671,1671,1712,1712,1712,1712,1494,1494,1555,1571,1712,1712,1571,1571,1712,1712,1712,1712,1671,1671,1452,1452,1712,1712,1516,1370,1181,1516,1516,1496,1496,1181,1181,1370,1370,1516,1516,1181,1181,1181,1181,1516,1516,2566,2701,2365,2365,2566,2566,2701,2566,2566,2365,2365,2566,2566,2670,2365,2514,2514,2365,2514,2365,2701,2701,2365,2566,2701,2701,2514,2514,2365,2287,2287,2301,2301,2554,2554,2484,2484,2428,2428,2287,2287,2053,2053,2053,2053,2484,2484,2287,2301,2484,3172,3199,2311,2946,3146,2757,2757,2757,2757,2302,2302,1884,1884,2179,2179,2000,2000,1884,1884,2179,2179,2302,2302,2428,2428,2301,2301,2180,2180,2428,2428,2301,2301,2180,2180,2287,2302,2302,1957,1957,2217,2217,2302,2302,2165,2165,2000,2000,2249,2249,2179,2179,2302,2302,1957,1957,2302,2302,2179,2000,2302,2297,2297,1884,1884,2217,2217,2302,2302,2179,2179,2249,2249,2179,2179,3146,3146,3146,3146,3260,3260,3565,3103,3144,3144,3210,3566,3566,3259,3123,2390,3103,3260,2000,2000,2302,2302,2217,2217,2302,2302,1957,1957,2040,2040,2302,2302,2179,2179,2621,3115,3115,3689,3710,3674,3381,2984,2984,3150,3150,3262,3262,2583,3221,3123,3121,3121,2946,2946,3669,3669,3566,3566,3103,3103,2302,2302,2217,2217,2000,2302,2302,2179,2179,2302,2302,3063,2426,3271,2673,2554,2301,2180,2428,2301,2484,2368,3271,3267,2179,2484,2554,2301,2053,2428,3184,3144,3103,3221,3655,2946,3244,3623,3244,2407,2946,3680,3623,3103,3623,2202,2301,2484,2301,2428,2180,1704,1704,1319,1319,1697,1697,1571,1571,1280,1280,1756,1756,1697,1697,1305,1305,2801,3154,3260,3054,2627,1743,1743,1502,1502,1421,1421,1577,1577,1503,1503,1743,1743,1421,1421,1758,1758,1970,1838,1650,1838,1970,1421,1421,1502,1502,1421,1421,1743,1743,1502,1502,1580,1580,1743,1743,1577,1421,1421,1743,1743,3095,2302,2000,2000,2302,2000,2302,2179,2302,1697,1697,1278,1278,1704,1704,1319,1319,1781,1781,1568,1568,1703,1703,1781,1781,2744,2566,2566,2365,2566,2566,3623,3146,3203,3680,3623,3680,2566,2566,2584,2566,2584,2566,2701,2566,2738,2738,2365,2566,2738,2584,2566,2584,2566,806,1456,1456,805,805,860,753,753,784,830,830,936,859,750,1216,1168,1168,1168,1259,1276,761,747,805,826,1422,1000,807,775,775,772,864,1295,1513,1513,1513,1513,1513,1513,1026,1023,969,1024,762,766,766,766,775,770,769,769,769,2610,1195,1195,1352,767,946,946,772,772,903,903,771,816,816,825,825,969,969,874,874,1152,1152,799,799,805,1108,1108,1430,1052,1110,936,1296,949,1069,1698,1698,1205,1205,915,1170,1140,986,986,532,532,820,840,814,835,998,1327,1369,1008,1008,1008,993,1240,1244,1066,1066,918,1120,995,995,995,965,1208,1208,1187,960,960,960,1004,871,1004,1004,1222,1028,1151,1259,1008,1008,860,831,843,1004,850,989,989,1575,1447,1267,726,1008,1293,836,836,1074,833,833,855,1260,868,1688,1266,1081,1120,1120,987,854,921,1172,1172,1172,930,930,1514,989,1131,1712,966,931,978,1146,919,1203,1203,1203,852,874,906,950,1409,1409,943,943,727,949,1092,1240,1046,1987,947,1047,1015,1141,1262,1080,1080,1442,3031,910,1529,1400,1400,1147,988,1238,768,2149,1762,1762,817,895,749,749,912,763,1027,1027,920,917,1215,1918,1054,1053,1040,1460,1460,1460,1085,763,763,746,1538,1538,777,896,896,819,896,816,1200,750,954,954,1000,741,741,735,737,1410,836,957,1527,1450,1450,2550,2550,1434,1434,1130,1130,1130,1230,1186,852,852,3131,952,1644,2047,1473,1053,1939,1939,1120,1120,1120,926,925,925,1074,1001,1054,1333,1299,899,899,1092,1092,1449,1182,1191,1000,1206,912,2074,2074,1661,1257,1125,1237,1187,1210,1074,997,1074,898,1557,1557,1470,1081,1160,1160,1643,1336,1336,1722,1333,1333,1361,867,867,1101,1101,1969,697,697,697,1434,697,694,694,694,1287,1367,1417,1417,776,694,819,1209,1669,1703,1574,1574,1458,1234,1203,824,1720,1720,923,1421,1421,1127,1040,1040,1092,575,1089,1089,1525,1228,929,929,1694,1694,897,1440,728,728,1397,1397,1414,2903,1348,1170,2067,989,1211,1662,918,1356,1133,1193,1398,1160,843,1282,1300,1076,1076,1076,1815,1389,1649,1148,974,1111,1068,1132,1008,1008,1283,1146,1146,1354,2291,1604,1730,1126,1126,950,1305,1305,1401,1140,1073,1073,1200,1200,1200,1042,1042,1309,1115,1245,1270,1334,1164,1373,1237,909,1120,966,962,1010,1054,1032,1032,976,976,998,1000,1000,1080,1094,1094,1440,1440,863,863,1161,1161,1019,1019,827,1000,967,889,860,1624,1435,1750,889,1228,1228,1064,1064,778,778,1864,1864,1487,1008,1008,869,1144,1144,840,840,1144,1052,1197,911,1659,1659,941,941,1299,1299,1026,1026,993,994,868,868,1238,1338,1338,914,954,1180,984,1068,916,1608,1608,1184,1090,1331,1375,1373,1368,1368,1120,1401,1369,1231,1374,1424,1323,1006,1145,2223,1010,1098,1098,1014,1050,1007,1554,979,1305,992,1119,1100,1103,1102,954,1195,977,1145,1079,994,911,1839,902,2982,1223,1338,1393,1393,1368,2002,1525,2031,884,960,987,1854,936,2238,1352,2844,923,923,1004,969,1967,1000,1100,1126,912,1699,1699,2746,2031,3370,3191,2995,1327,1744,1806,3188,2837,1641,2454,1372,2110,2543,1403,2785,2488,2389,2389,2344,1140,1965,1965,1736,1853,1368,1219,1116,3526,1356,1465,1305,2229,1786,2378,1902,1800,1534,2018,1483,1767,2512,1414,1414,938,818,1161,1421,1175,1784,1316,974,1410,1485,1834,1634,3244,2231,2902,1680,2428,1240,2735,1188,2107,2158,1380,1198,1728,1352,1397,1197,949,1352,1320,1400,1450,1813,1391,1391,1967,1665,2958,1370,2231,1791,1330,1700,2092,4031,978,2096,2659,1403,1690,2522,1863,1863,2367,5480,2766,2843,2229,3244,2159,1264,1193,2998,2757,992,955,1234,1445,1445,2799,2917,2141,1193,2383,1193,1193,1410,1194,1335,1664,1664,2141,1159,1657,1594,1594,1528,1130,940,958,1446,1228,925,1077,1720,1734,1314,1467,922,1132,1484,1484,1039,1193,1174,990,2707,1000,1000,874,1225,1212,870,997,907,1352,865,930,1678,729,1109,1282,4420,820,820,812,973,1934,1023,1023,1000,874,1382,1382,2471,1663,1663,2137,1173,2531,3712,1920,3864,3864,3536,5398,1677,836,3963,1461,3898,1507,2854,2854,2728,980,885,1996,1262,1423,2506,1722,1359,996,1671,1474,1363,1365,1720,1978,1061,1167,1167,6561,1013,1275,831,722,722,547,547,835,835,752,838,1277,1002,956,992,956,1052,616,1424,1007,845,750,1055,1005,853,1556,802,3575,1076,915,915,747,747,747,1182,821,769,1009,1009,1031,804,809,809,801,1100,973,1241,1241,1263,1263,1011,996,1286,1039,1121,1033,1033,2304,2304,1132,1026,1026,993,993,767,767,860,763,749,749,746,746,745,969,1029,759,1147,973,1321,1005,1014,814,1087,719,1037,1069,1143,1669,1209,1515,1093,1485,1207,1207,1215,971,971,907,924,914,1102,1136,953,1485,3004,973,1151,1058,1554,1380,1131,3303,2850,1782,2066,1732,1732,1205,1147,1081,1582,990,1084,1486,1114,1118,1118,785,816,801,785,785,1001,960,2391,3246,3246,1172,1327,4207,1387,1746,1746,1092,1138,1074,1016,1095,1268,1046,1273,1273,1657,1800,2974,1211,1211,1203,1278,2708,2708,1894,1754,1925,942,1610,912,1152,1152,3089,1761,1761,1115,1530,1816,3006,1450,2303,1044,2468,2931,2282,1557,1234,1377,1247,1664,2975,2917,1321,1061,1587,1645,1243,1499,3357,1145,1790,1801,2696,2868,2103,1366,2863,1575,3646,2252,1055,1479,2202,2912,1585,1666,2111,1870,1082,1059,1059,976,1517,1517,1003,719,707,719,566,787,783,753,730,753,575,783,803,794,1162,2852,2795,2181,2618,2037,1833,1833,980,1003,972,765,2070,2114,1091,1149,1735,1781,1086,1386,1772,1310,1069,1729,1729,1351,1351,1617,1617,1344,1344,1523,1120,981,936,917,783,1106,2063,1613,1613,1541,4125,4423,725,1532,3783,1200,1760,1142,1442,1167,1746,1327,1517,1598,1631,1786,2848,2029,2651,2104,1933,1648,1438,1438,1438,2104,1639,1618,1013,2888,1747,1509,1929,1724,1357,3666,3666,3678,3678,3198,4326,3297,3940,1059,1516,1370,1181,1496,1181,1181,1516,1370,1181,1516,1506,1367,1367,1506,1370,1181,1516,1181,1181,1509,1516,1181,1181,1516,2911,3675,3372,2788,2049,2244,1957,1957,1570,1745,1854,1185,1726,1412,1467,1467,1745,1564,1334,1566,1156,1278,1156,1133,1133,1156,1162,950,1712,1712,1712,1712,1712,1712,1448,1448,1712,1712,1674,1674,1514,1514,1712,1712,1448,1448,1712,1712,1512,1437,1712,1448,1671,1712,1712,1512,1288,1288,1697,1697,1756,1756,1305,1305,1278,1278,1704,1704,1305,1305,1280,1280,1697,1288,1288,1697,1697,1768,1768,1704,1704,2338,2338,2180,2180,2484,2484,2301,2301,2287,2287,1833,1833,3097,3097,2390,2390,2813,2813,759,1579,1018,1018,1223,733,984,984,832,832,832,832,832,982,2196,2196,1451,1185,1461,1185,1451,1554,1788,3192,3947,4471,2341,3554,3852,1778,1695,1451,1600,948,1575,970,1340,1347,1273,1303,1575,1704,1568,1557,1704,1697,1808,1347,1347,1437,1500,1715,2462,2055,1950,2146,1613,1313,1756,1239,1697,1697,1278,1768,1704,1228,1228,1288,2152,2417,1950,1613,2557,1697,1712,1512,1712,1671,1712,1712,1712,1437,1712,1756,1703,1703,1756,1756,1305,1305,1697,1697,1704,1704,1674,1514,1377,1571,1712,1448,1377,1448,857,738,989,792,1066,745,1045,1055,1694,1425,951,1011,1011,1034,1506,921,1931,1065,673,1358,1003,954,947,777,730,786,786,834,820,820,1016,816,990,1229,1229,915,926,926,770,822,868,868,1059,817,770,1038,2515,861,1039,1039,1145,794,695,1050,768,720,875,952,856,926,800,800,798,812,921,774,882,888,819,542,1124,847,945,945,945,2254,818,1485,782,909,909,1234,1234,1234,916,916,962,880,1877,876,682,874,1031,1031,1081,1081,949,949,762,750,796,796,781,850,967,815,953,1031,1390,1791,1049,990,863,863,1027,888,888,523,515,513,738,512,550,674,643,639,2184,562,562,795,898,725,725,955,725,721,721,721,721,3004,1322,1357,1013,1762,3660,1800,1784,1676,1979,3060,1786,1639,1786,2780,1357,1013,2164,2541,1013,1357,1176,864,1103,1072,1732,1732,681,976,945,521,731,1243,1410,1730,728,883,755,972,972,674,1788,964,1345,884,892,817,1286,842,1374,1374,1374,1374,1374,2307,966,462,647,715,720,1028,876,1530,866,648,851,594,832,808,808,761,760,1290,933,996,999,837,1079,1242,808,1018,1566,759,759,722,759,962,962,723,759,1297,1297,1215,972,891,891,723,1555,1555,886,972,972,720,882,720,882,882,720,1033,1057,720,972,719,1368,755,973,892,944,944,944,847,757,1090,874,1020,1248,939,960,960,700,773,937,951,845,952,1079,1854,762,972,904,1872,759,1150,757,1513,1488,1120,1026,1042,889,522,828,804,804,1448,1448,771,1085,673,673,1004,805,920,794,818,554,1329,1329,1329,1349,1306,997,997,997,1481,1481,1032,948,1800,734,880,888,1219,1077,1551,1551,874,856,982,904,904,899,1190,961,928,1956,1956,1038,701,701,902,902,880,1168,1090,1090,679,679,733,903,903,1119,1119,1385,1853,916,675,727,727,1679,1089,676,621,1439,775,880,1324,884,1106,1106,707,707,1457,1095,872,641,937,916,776,766,568,663,1487,1212,898,898,951,951,705,1150,1150,2387,2387,2367,1794,1224,936,950,866,1114,1132,2244,876,984,984,1569,2393,2413,1603,2720,1565,1565,910,1387,576,1620,1620,1620,1620,1350,1069,1310,853,1218,1074,889,1217,1123,1120,1104,1105,1105,2105,2105,877,820,1248,706,792,1209,761,914,808,775,1277,1277,1487,750,1104,1104,884,723,1938,606,1692,999,999,1239,1336,1336,1952,4479,2401,1641,869,878,712,1497,673,673,847,980,2357,1126,1006,1006,988,720,676,838,838,976,896,921,921,927,769,869,869,1228,1084,1221,793,793,1400,821,1194,653,1172,943,1214,731,1377,1167,1167,1173,1989,1989,1258,1258,803,938,1672,1311,1311,886,1900,1900,1098,1142,1342,765,1888,1418,1381,1954,905,731,1848,2256,824,1894,1894,816,1331,1937,1876,1561,1308,1308,931,2370,2368,1972,1930,1126,840,953,1542,1542,932,1126,1229,927,1328,1756,1196,875,1702,1040,912,1188,1188,1077,1321,2048,1262,1874,962,1547,959,964,870,1017,852,832,1484,1484,850,1678,921,1732,1300,1300,1300,1300,1300,2477,2477,1826,1821,1473,1486,1486,1486,1486,1486,1493,864,590,1482,899,826,1481,1190,1888,1888,1450,1485,854,771,2361,2361,812,1050,837,1020,1058,1481,1481,1132,2340,2340,1047,1020,2189,2189,749,2360,1728,1728,2030,2030,952,840,1869,1445,1058,787,1154,1156,804,1726,842,1056,1519,3547,1682,1394,3694,791,791,843,1125,852,1324,1324,873,2271,2271,852,2152,2152,945,952,844,828,2215,1005,2096,2012,963,856,987,1467,780,1004,1004,1840,1888,1776,1776,1268,996,1449,748,1048,1147,1246,1080,1306,2363,2363,491,1451,1451,2036,1373,2489,2385,2137,2137,912,1957,1917,1917,948,877,1470,912,1235,991,681,880,818,2173,1652,1652,1977,1986,1970,909,1052,1052,1690,773,956,1144,1832,912,946,2452,2004,996,825,827,1221,1737,1529,1117,894,1502,1440,2036,2008,883,3610,3610,1620,957,1183,1378,900,752,1511,992,872,821,821,798,863,2028,2084,2726,1235,612,884,918,1264,1075,1173,849,1528,2191,2191,1262,766,766,1916,1900,1533,1889,952,928,2562,2562,1988,1988,1109,1025,875,864,864,1047,1151,1761,839,1854,800,781,1110,909,1055,2088,844,834,976,937,1510,1344,1028,869,1530,846,1398,874,950,917,969,1242,852,844,844,973,846,1145,798,993,993,1264,1272,961,1215,1215,1068,905,1014,1130,1313,1313,926,981,981,938,1063,987,975,897,780,960,960,1347,1179,1295,1094,1396,1365,1179,1108,1046,1055,846,1136,1121,1334,1316,1059,1297,906,906,1454,1454,1928,1928,872,1048,1309,1351,1351,1034,1029,669,1435,970,966,966,1364,975,866,900,885,954,784,784,848,848,848,910,967,756,1062,748,755,772,1183,960,1870,839,835,828,1056,1092,828,1400,1036,733,1439,903,903,934,934,664,619,1025,1025,886,924,576,816,829,832,1115,1115,1286,1267,1484,1251,1251,1383,1085,1931,2044,1775,1775,974,1455,1570,1644,3914,2303,1140,1152,1487,4092,4092,2543,2706,797,1116,1233,1007,638,1219,1935,3257,815,855,880,1107,2713,882,621,873,621,1298,1004,1839,996,1203,1570,2302,1330,1047,1268,1268,1632,1564,929,2611,1173,783,985,985,1776,1776,1776,2624,1351,1838,1104,1648,1423,1410,1972,1175,1291,2275,1230,1680,1184,1796,1523,1322,1337,1598,1318,1318,1203,1814,1264,991,990,1069,1142,726,1815,916,907,962,1700,1700,1117,1225,925,925,1147,1147,1257,903,1115,1174,1797,1038,1010,653,653,2032,1046,932,932,720,2061,2061,1053,1512,1493,1272,901,1967,940,1028,928,1178,1065,577,1403,1403,936,935,935,842,1346,869,1294,1092,999,1985,1600,801,808,808,905,1848,1848,1660,740,1360,1627,1534,619,619,771,1490,1144,964,964,1304,1415,1059,1008,1513,1220,853,1436,1426,779,770,1100,920,1055,981,1022,1022,948,1448,1031,937,923,923,919,838,992,1678,1003,1011,1088,1331,931,1011,1708,1792,1160,1266,1266,1179,1306,1306,1473,522,805,1020,1020,845,1878,1787,1787,951,951,2050,2145,2145,858,1098,1046,1070,1881,1054,1069,1676,1283,1092,914,914,884,884,961,984,984,934,1009,820,1494,1494,763,727,1083,725,725,730,730,725,758,1964,727,725,750,1088,727,727,1088,734,1068,1114,1027,1027,813,720,784,784,864,866,836,836,995,995,883,870,870,869,874,874,1367,1440,842,1310,1310,1076,1506,1612,1131,675,675,1236,1080,1163,1561,1229,1229,1229,730,761,747,1493,1529,1342,1208,949,1179,904,908,925,921,921,674,674,1418,1557,895,895,1632,1289,957,957,1105,1216,416,416,1429,2052,1044,873,873,1739,1430,847,1154,1460,1076,861,962,1214,1807,1807,1344,865,1529,1625,1464,1838,2365,1100,675,1057,793,793,999,881,881,2125,2125,737,857,962,859,859,1200,1093,960,1476,1085,1360,1089,1089,1063,1101,1400,505,505,1212,951,1965,1965,1097,1013,1189,1750,1750,842,936,546,900,830,2071,922,922,734,734,934,934,794,794,2001,1012,600,1745,1745,1745,949,658,658,657,828,720,720,788,471,471,755,954,861,1080,1128,744,802,802,702,824,362,800,552,552,1369,726,707,940,904,955,736,726,987,1544,890,696,696,602,1015,904,791,486,859,783,472,892,892,684,1048,702,785,880,966,966,783,783,1011,951,601,601,880,710,1527,901,1179,797,1218,878,1044,546,546,2040,787,960,973,754,1988,750,1286,612,931,1324,1270,565,1063,1063,1278,956,735,739,779,984,1044,1348,1348,687,687,612,1597,1043,829,829,829,950,792,813,882,882,1083,657,694,921,924,1058,918,910,742,1230,893,1115,1172,991,1342,1189,780,677,1154,731,731,1304,850,1308,809,593,593,927,1527,732,728,705,1179,895,847,1142,543,705,800,1000,887,817,1313,1313,922,840,840,978,1036,737,1083,915,1219,552,754,720,721,730,658,1072,1300,1471,770,718,898,898,840,1167,622,1056,744,744,984,1033,1156,636,967,936,1037,700,1149,1149,700,521,1058,731,731,1413,822,822,980,1002,1002,755,863,1520,840,840,819,770,849,849,1288,1725,1052,624,624,1462,954,1073,1073,1020,1092,1005,1005,1800,1022,822,827,827,968,996,996,1433,1937,1006,1499,960,936,1500,1500,855,855,855,666,1009,1784,1950,1080,1080,548,1578,707,862,862,823,1271,1363,1115,1013,1036,1066,1066,1398,1128,1451,828,589,1149,1067,750,750,662,928,825,788,892,892,846,846,873,1023,1102,912,912,882,882,1050,1066,982,723,656,916,872,720,977,1124,861,908,1247,978,1007,959,1294,1294,1183,1183,988,799,799,940,940,940,801,884,884,884,884,1000,776,1042,921,921,1088,1088,983,983,1044,751,1191,1000,1000,1079,1079,950,950,440,1426,1102,669,860,853,858,558,832,919,605,768,931,931,1018,1100,1548,1213,1213,892,1153,748,1588,864,1044,870,992,745,838,838,916,916,965,1126,1126,761,1437,1437,1253,890,890,994,994,1108,1108,1185,1593,2194,2094,872,1339,1046,1062,1274,1274,1274,1058,1058,1058,1231,1231,1231,1160,1321,1950,1355,1070,1049,922,838,1171,747,751,751,805,1205,1504,1442,1178,1178,1006,1449,1477,972,1154,894,1077,1077,816,1062,860,1363,720,720,1015,1002,1002,911,911,684,724,724,635,635,659,683,1210,1210,1411,2623,1074,1074,1027,1086,1167,1584,1153,926,926,799,1209,1045,1045,1357,2283,1048,1048,1036,1044,1052,1056,1424,799,1139,1446,879,943,966,868,1379,1379,1112,1397,1009,720,795,1040,1358,1325,880,880,956,956,960,1273,971,1251,1032,2679,2679,2117,1218,1218,884,1930,958,993,2411,1927,1927,1139,870,870,870,870,870,870,870,870,870,870,870,870,870,870,870,870,870,870,1181,1125,994,994,902,1104,753,524,524,524,909,925,925,991,764,1037,847,1578,548,959,1728,840,1064,1064,1267,1189,901,901,863,863,1339,1488,1488,792,792,919,919,783,1180,1180,1330,1116,1878,1878,780,1532,1532,1532,879,945,945,748,2308,829,1184,1184,1205,434,434,434,901,2001,1802,899,1392,1360,1288,1288,957,957,735,735,1321,1321,1388,1173,920,1590,1858,1496,1496,1479,1769,2112,1969,1147,880,1448,1942,1076,1017,1017,1152,1478,1478,886,714,714,861,811,811,700,700,700,660,955,1892,2036,2980,1415,928,928,729,1425,1418,1520,1334,643,1369,1369,1862,818,1888,2094,572,1236,2374,1836,1246,856,856,1211,1211,700,704,759,753,936,1944,704,678,1151,1151,1197,1197,883,1520,1135,1182,928,1327,1550,1340,722,1176,870,3189,755,1469,1580,1418,931,1808,1152,1247,762,880,948,1569,1569,1196,1196,1533,2200,1789,1829,1617,1680,1680,772,2246,520,520,480,560,965,965,1433,1712,1961,1510,878,1600,2190,1420,768,972,1848,2998,1188,1823,1683,1683,920,1318,1598,1100,1583,1570,1432,1320,1234,976,976,976,1077,1077,678,1528,985,1011,987,986,1362,1362,641,641,1624,1310,1310,1484,1637,1203,1184,1198,2300,1574,1664,1034,1523,1462,1462,1140,1140,1467,1472,1460,1934,1637,1092,1133,2425,1548,1946,2404,1444,1620,1620,1536,1925,1925,1299,1462,1621,1621,1013,1177,1349,1349,1824,1664,1612,924,1498,1162,835,931,1283,1620,850,808,756,1467,935,1376,987,862,862,634,850,886,701,852,1235,1296,1301,1296,831,869,869,869,1222,1225,1225,1225,1225,1225,1225,1502,912,868,873,1528,1528,966,966,1472,1268,972,942,924,936,932,936,918,960,1231,1620,545,770,724,724,724,724,770,2102,2098,950,1910,1010,1010,1025,1360,1088,1088,1088,1088,1088,1088,2468,1063,1576,1868,5034,1565,1591,1424,1646,1169,614,1248,1290,2356,2356,1874,1874,2400,2409,993,1248,1680,1654,1932,2000,962,962,475,533,533,533,1648,1369,1875,730,2426,2054,1915,1915,1915,1915,1915,1915,1915,1915,1332,1332,1332,1332,1180,1180,1332,1332,1332,1332,1088,1748,840,1830,1219,1507,1255,1027,859,1382,1297,1674,1372,844,836,1414,2340,1577,1850,1425,1246,868,1326,1269,1044,1169,1746,832,941,936,1174,727,662,1119,936,1057,846,936,1278,2025,3097,1925,1925,1925,1925,1925,1925,1925,1925,1925,1925,1925,1925,1925,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1363,1706,1440,1119,1061,3444,3031,1093,1497,1376,1544,1248,1544,753,1365,876,1085,1830,1849,1611,864,981,871,815,981,901,1383,1433,1207,1439,1202,1045,842,906,2769,1974,1778,3072,2940,2182,2795,1412,1320,2040,1947,2052,827,2516,2516,1050,944,2335,1252,916,916,902,2503,2503,1303,1719,3134,1522,1493,1522,1522,2006,2006,1216,920,1792,798,2836,621,453,947,782,782,1215,1206,1902,604,891,1376,1391,802,2193,1278,1506,1234,1830,1830,2358,981,960,960,2018,1987,768,525,971,971,2054,1018,574,780,563,537,843,940,960,514,514,636,1668,1026,1018,1073,1092,1365,1365,916,1202,1032,795,1828,1122,954,1130,2867,1020,1922,1184,1586,2190,1104,1334,1649,2155,869,1161,1010,694,694,1567,1118,2215,2456,997,1807,1728,1188,2515,1770,1556,1556,2185,2185,871,847,2125,2125,1348,1008,776,709,2224,2224,1414,938,1162,2188,2216,4598,1725,2850,1003,1003,1003,802,3120,2927,2924,2998,2602,2467,2602,2467,1854,619,2308,2277,1269,1491,3784,2031,2031,1424,671,671,1780,2793,2793,1877,1877,1877,2658,2045,2045,2045,1993,1993,1357,1074,2385,1791,17942,1254,1655,1744,1177,2155,1326,1903,984,2138,858,1944,1020,727,3607,2424,865,865,865,1023,1023,865,812,812,675,1555,1173,1188,1102,1102,1256,1897,1222,1379,1417,1356,1167,1268,1655,958,1225,1371,1982,1982,1982,1982,2234,1774,1774,1320,2218,1753,1219,1219,1528,1528,1528,1890,988,767,1342,1504,2523,1461,2072,2624,1552,1880,2098,948,553,602,1496,8870,8870,8870,1412,2477,2665,2665,2477,1242,980,1239,1239,1679,1208,998,1190,1704,11435,844,5365,5365,2359,2359,2707,2707,2070,2070,2039,2039,2039,2039,2070,2070,2039,2039,2039,2039,2070,2070,2005,1476,2005,1722,1722,1722,1722,1722,1722,1722,1722,1722,1722,1722,1722,912,1252,1160,936,1057,1029,1029,1029,857,808,1038,812,913,1428,1426,1892,1892,1845,774,770,770,759,1033,1033,1033,1033,1021,1868,1426,1438,1438,1456,2105,664,835,1310,1263,628,835,696,628,1421,1340,1071,1123,794,970,584,1125,2178,1044,1044,1490,718,718,840,1572,1666,1572,1666,1940,1552,1869,1535,794,1058,1455,926,836,1140,1140,1050,1191,1191,1191,1140,1191,1191,3169,1270,1314,1170,950,950,1234,1920,969,938,938,803,1953,1953,997,2456,2410,2156,2033,1973,1000,2247,1208,1139,858,1361,1359,1359,1180,2084,1102,1102,2630,840,1583,968,1882,793,961,1268,1268,855,1781,1548,1548,847,1124,1600,1555,1684,2082,1670,912,2200,916,684,684,560,1207,714,1457,1457,1263,1263,2874,922,548,548,548,1050,1586,530,530,530,530,530,1114,1114,1242,1595,878,1878,1797,1797,1912,1145,1925,1821,836,672,1079,1014,1007,2119,2119,998,1381,831,831,909,2146,930,930,2342,1491,1280,1078,1029,679,1528,1528,1086,977,1469,1469,1469,1144,1506,1596,929,1306,1306,1814,1814,1155,1931,1177,1053,933,1175,1221,1118,1820,942,1241,985,1114,1360,874,1476,748,775,845,894,1126,931,1093,1047,1120,1050,1190,864,864,1430,2560,1162,1054,1890,1563,1611,1915,830,830,1343,1071,1192,988,1114,1440,1800,1800,1064,1278,2161,2161,723,862,1519,970,1207,755,1558,1155,994,1124,2282,1252,2658,2442,1168,1230,796,2178,2178,1238,1238,869,1711,2192,1903,1903,1471,1471,1057,2277,2277,1052,1310,1173,1143,1099,1099,1250,1094,1098,1098,1098,823,2407,1682,1170,1170,1096,994,1073,580,577,1059,1300,1452,1307,1946,2252,1926,1962,1500,1633,954,954,1034,616,616,1522,1314,1303,883,1022,1022,1541,1342,1754,1462,1069,1069,4794,1662,2097,2281,2281,1996,1954,1954,1905,1905,1511,1860,839,1878,1878,1521,1739,1790,1706,2022,1924,1148,1422,1422,986,1981,1583,1079,1079,847,1044,1044,1305,1305,1057,1091,2512,887,885,1000,931,904,945,1084,851,851,1084,997,1287,1287,889,530,973,1242,959,921,822,869,1550,1084,1084,1048,1639,1639,4252,827,778,1072,2266,2266,831,1785,1131,1567,1652,2097,2263,2097,2760,2041,1194,939,821,821,1380,1593,1388,1614,2420,2181,2181,2463,787,781,608,592,599,592,608,707,781,621,602,609,602,609,872,669,1123,1565,1894,1143,1904,1904,1189,977,1350,1067,1243,1243,1510,1753,1869,799,1176,739,803,1717,960,999,993,954,1106,1000,1009,1125,1697,800,800,800,736,1100,818,1064,1064,797,1952,881,2804,708,1055,1287,2516,2516,1630,906,1494,2791,894,1004,1599,2512,954,856,2020,839,829,825,825,825,2874,822,822,996,899,992,938,1951,1426,795,1197,981,1182,1182,795,1115,2454,2170,2160,2160,2792,849,807,1838,1838,2284,1846,1392,1199,904,2146,1188,771,517,517,823,1750,2000,1092,1092,1986,1020,936,1230,880,880,2058,1096,2588,2533,1124,1027,1810,1370,1180,1177,1387,1640,1549,1568,1046,920,892,1225,1159,927,819,819,815,1465,718,1274,1052,2190,2351,2190,2250,1193,1360,1050,481,764,1786,1786,844,2291,859,908,784,1318,579,345,345,1159,1159,976,976,977,1300,1292,1392,2514,2514,2514,1687,1687,1240,1598,1109,1387,1326,1474,1474,1205,1205,1160,1078,2492,794,929,764,798,794,1408,677,677,677,887,1364,822,902,1446,1386,918,1458,1147,740,632,2460,1189,1794,860,860,713,2259,1876,2277,2262,1040,816,816,1062,1000,1804,2566,2759,2136,1070,2432,2245,863,1375,1023,1637,954,954,1101,1101,723,1305,1305,1872,1305,1213,1023,1305,947,1213,1197,1197,1421,1260,1260,1024,891,1565,1820,1820,1561,1038,1114,931,1117,962,939,983,983,950,768,1829,1259,483,1301,936,913,1104,911,1548,810,1315,1315,937,768,2029,1073,1300,1313,865,1134,988,2192,652,1820,1820,689,1691,1138,919,1179,1010,596,993,702,2522,831,1243,1053,1638,2145,1026,965,1239,1239,1311,1250,1029,1550,1262,992,1429,1289,1289,1063,1950,1192,1995,1284,611,401,606,606,895,800,3003,1069,1660,1266,838,920,1512,2116,1828,1676,1420,1138,669,1035,1552,1086,1089,1119,1013,2014,2112,787,954,980,980,840,1466,1825,1224,1648,1115,1303,5631,2166,1174,1816,1008,2775,2775,1597,770,690,1716,1065,1134,1134,2624,2624,1126,1169,1687,1326,1020,1020,941,960,1183,914,1012,1012,1239,1328,1875,1979,980,980,1167,1946,926,1015,1015,1015,986,2103,1790,1100,1159,1274,1139,782,782,1296,1296,1296,1296,1296,1296,1296,1296,1600,1296,1014,2103,2463,771,864,871,900,1488,955,1768,2369,958,977,1112,1159,927,1398,1301,894,1181,900,1194,838,979,841,942,2503,2503,1289,2821,1433,1063,874,1609,2068,1637,2126,2126,2322,2282,1547,1502,1764,888,2739,1284,982,1482,1482,674,1151,906,1504,1694,1805,1260,775,1998,2185,2185,850,3219,2782,809,809,537,572,572,572,537,891,1484,2160,1306,1358,1494,1800,2292,954,2642,2527,2535,2535,988,2679,2159,2149,2255,2259,759,1824,1792,1146,1029,2385,1946,1946,2605,2434,3094,3230,2397,1337,647,1911,2696,1718,1698,756,1894,2707,1120,1953,2616,2616,1933,1547,1347,2673,1442,1316,1822,756,652,824,490,651,626,626,1457,1403,1090,851,1131,994,1536,1962,2039,1656,2039,1673,2133,1154,2393,1169,1392,1390,1390,1349,1449,1449,1449,910,910,911,911,1097,1097,1215,1215,1215,1215,1179,1445,1454,1463,1392,1392,1646,1386,1087,1881,2189,2189,1051,1051,2181,1019,724,854,850,843,2037,2037,1581,1702,1039,738,1378,1782,1920,1920,784,611,880,880,1384,1384,1544,1408,1092,1062,1065,770,1068,1068,1056,1894,1893,1335,1335,1424,924,1335,1721,1069,912,912,912,1069,1130,912,1069,912,912,1472,966,1364,2098,714,714,1091,1091,1148,1434,1148,1153,1217,1148,1153,1217,1153,1217,1434,1153,1565,1668,1520,1520,1479,1150,1479,1479,1803,1803,1803,1622,1594,1708,1131,770,798,768,795,768,804,1701,2934,1600,942,1663,1663,941,941,2601,2601,1872,1872,1852,1852,1790,844,1408,2346,877,877,1576,1059,1222,834,740,1672,1626,1428,1050,2188,1850,1300,780,1239,1417,1789,953,866,866,1222,1082,1609,1476,1382,1012,1012,1787,786,2156,805,1973,1040,1047,2342,1119,1826,1826,1188,1528,1592,2219,1626,2002,895,1744,1018,767,1176,1296,1296,828,828,1176,5363,5363,1043,1836,1666,630,1836,839,1228,1728,1728,1836,1666,1666,1539,1836,1106,1106,1106,560,560,1666,1836,1836,1661,1666,1661,1836,1209,700,2038,2038,1921,1868,1506,2181,1702,1702,738,699,1025,1036,2226,599,1268,1118,815,815,1338,933,1173,1173,1000,1798,804,1021,1021,1013,1013,936,869,925,1374,1126,1126,968,968,1064,1004,2048,1145,1289,1493,1371,3754,1482,2456,1679,1482,1647,1890,1391,1832,1857,2183,2935,3024,1753,848,987,1080,1732,1035,1909,1851,1035,1909,987,987,987,2767,816,1283,816,1283,731,816,816,731,731,1283,816,1283,1283,1283,1283,816,1283,816,1028,3844,2882,2409,1752,1782,2313,2313,1594,1315,2313,1728,1594,1782,1782,1315,1594,1351,2313,1594,1315,2313,1351,2472,1230,1520,1399,1142,1142,1093,992,1715,987,1095,2101,874,1884,1311,1632,1481,1472,3019,1511,2062,1020,1020,914,1328,1415,1742,885,875,1624,1281,885,913,979,1408,1077,1300,1281,999,970,2084,1062,1393,1062,1062,937,2384,2382,3155,849,1306,2449,2567,827,1271,827,2876,1693,4929,4323,5019,732,1153,864,844,1153,1027,1027,1122,867,1122,1027,1027,1027,1153,1027,1869,1893,1893,1893,1162,1162,1770,1744,2170,1744,1099,1234,1162,1744,1235,3174,1079,1074,821,821,726,2575,1720,1726,1736,1400,1461,1297,1256,1199,1716,1604,1180,1180,1604,1180,1605,1373,591,941,584,591,1121,1121,584,584,1458,1230,2086,1590,1460,1460,1553,1718,1652,1780,1708,2031,1653,1782,1730,1730,2018,4020,2176,806,1124,886,886,812,1431,3659,787,1345,709,976,744,1068,736,648,1146,1438,1316,1341,1077,1255,1659,803,753,735,1233,1195,792,792,654,1210,1208,1175,833,834,1188,1135,691,1308,699,699,651,1237,838,1220,1146,1175,1216,787,1156,1152,1255,1169,847,785,658,712,1160,1371,2073,2278,1494,1494,1286,1506,1729,1758,1749,1697,1911,1329,1046,1775,1775,2980,2120,901,2238,1458,1292,871,1635,784,823,1442,919,1147,2496,600,825,1933,1926,1926,1926,664,665,706,706,706,780,779,760,821,821,840,1412,1412,2595,1465,1752,818,1749,1848,818,818,1749,936,1410,1848,1467,1331,1467,1410,1410,818,1749,1848,1848,818,1848,1848,1749,1410,1848,1749,1467,1410,3392,3392,1752,1752,1471,1620,779,1471,1752,2253,1752,3043,4144,1532,2065,1300,1823,1887,2008,1887,1764,1764,1764,1619,1619,2811,2667,1820,1842,1842,1795,1795,1846,1846,1846,1840,1840,1881,1881,1605,1605,1605,1448,1448,2485,2485,2080,2080,1927,1927,1927,1927,2293,2293,2293,1797,1054,1054,1508,1470,2146,802,1169,1466,1084,1041,1006,1084,1007,1041,1084,1041,933,1008,971,1960,1960,2295,2213,1143,3115,3115,2430,1143,2430,2295,1960,1960,2295,2430,1850,3490,3115,2430,3199,2430,1960,4495,3199,5561,778,1148,711,506,686,717,1365,632,632,1766,1149,1149,1195,1182,857,1695,939,896,1763,964,964,2481,2886,964,2343,964,964,2481,964,2343,964,2481,2886,964,2740,964,964,2343,964,2886,964,2343,964,3228,1767,1939,3228,1767,1939,3228,1767,3067,1939,3228,1767,3067,1939,3228,1767,3067,1939,1767,1939,3228,1767,1939,3228,1767,1939,3228,1767,1939,3228,1767,1939,3228,1767,3067,1939,3228,1767,1939,5171,4799,4723,6095,5636,854,854,635,989,797,991,632,993,498,772,498,991,635,791,783,497,514,635,992,816,988,992,989,639,503,998,995,822,780,484,1001,484,505,796,992,998,640,647,827,509,485,782,640,798,1026,1800,1438,1621,806,1261,974,1041,900,809,1259,1663,893,1639,900,1258,1312,793,1639,758,1258,1664,1001,1639,816,1258,1664,816,1639,1258,1664,1001,1639,1258,1664,1639,809,1258,1664,1312,926,900,1258,1664,1001,900,1258,1664,816,793,1001,900,816,1258,1664,1312,816,893,793,1639,758,900,809,1258,1664,816,893,793,1001,1639,1041,900,816,758,900,816,893,793,1639,1041,900,758,900,1258,1664,1312,816,816,893,793,1001,1001,1041,900,816,758,900,1258,1664,1312,816,816,793,1001,1001,1639,1041,900,816,900,809,1258,1664,816,816,893,926,1001,1639,900,816,758,809,1258,1664,816,816,926,1001,1041,900,816,758,900,809,1258,816,816,893,926,793,1001,1639,1041,900,816,758,900,1258,816,816,926,1001,1639,1041,816,900,1258,926,1639,1041,816,758,1258,1664,816,926,1001,1670,1052,816,757,900,831,1277,816,926,1020,1670,900,816,757,900,831,1277,1697,816,926,1020,1670,1052,900,816,900,831,1277,816,1099,1671,1670,1052,816,757,900,831,1277,1697,1099,1670,1052,900,831,1670,1052,831,1697,816,1670,831,577,930,577,577,450,1065,987,688,449,987,449,690,688,632,987,678,844,908,672,1199,637,829,844,844,637,1454,595,1077,1230,918,886,886,883,883,2091,1413,1413,1621,1622,1231,636,636,1794,1083,1254,1764,1254,1254,895,1155,1701,1086,712,1231,1184,1184,1027,1086,963,1197,1197,1038,963,1038,1197,963,1197,1197,963,1197,1197,3374,1263,1165,1182,1165,1039,725,346,397,390,416,1004,2732,2016,2016,722,1472,1707,1032,1768,962,981,1288,1403,720,1767,1767,2146,1039,1415,1415,1415,1690,1690,1963,1798,1146,1716,1595,2222,1296,1347,1347,1593,1460,693,3326,2100,950,2478,1250,1250,1054,4102,2529,1951,1780,1378,1322,1326,1922,1196,864,1252,1252,1252,1289,777,784,2562,2034,1724,1309,1432,791,796,961,1740,1740,1426,1402,404,404,505,2703,1782,2422,1050,1549,1655,1488,2088,1864,1386,1386,2058,1626,1792,1861,3017,3010,1408,1606,1302,2052,1436,2342,2100,1548,1548,2716,650,750,750,1086,1947,1076,1908,1036,1036,1920,1536,1794,1784,1328,1928,1553,2139,2139,1759,1397,671,700,882,2200,671,2364,2364,2456,963,1483,1806,982,982,1666,1750,1030,1452,1735,1563,1662,1105,905,2020,2044,2137,2137,1322,1266,937,918,1766,1388,1388,1793,1443,1621,2366,2068,624,1299,2624,1329,1171,1171,1680,1440,2176,2287,2725,2610,2450,2450,2590,2590,4097,4969,5928,4540,2083,2178,1001,3628,3628,1253,1367,1368,1246,657,2759,2250,1708,1743,2358,2054,1294,1601,2680,1827,1488,895,1258,768,768,768,768,768,768,768,768,882,2936,1475,1388,652,1352,1115,1352,1254,1115,1115,1103,1022,805,993,1249,708,788,703,1015,992,1070,1591,711,1474,1317,711,1607,1178,1460,800,1348,972,1466,786,544,1677,1179,1583,1120,1141,995,2782,2053,2053,2058,2657,2051,2051,1272,1605,1721,1721,1697,1271,1283,1064,1047,1635,1158,1036,1219,1232,1057,1219,1219,1219,2318,1305,906,2121,1196,1206,1564,1084,980,974,1920,1920,1839,1932,1264,1592,1636,1722,945,428,476,476,1044,1716,1643,1595,1595,1595,1643,1643,1519,1513,1513,1513,1299,1299,1531,1529,1602,2862,2862,1930,1438,2094,2094,1175,967,1170,967,1022,2522,1484,1150,1201,1340,1340,1340,3119,2313,2313,2618,2618,1850,1850,1850,598,1020,1567,1043,1451,966,787,853,1376,1114,3382,856,2072,2072,1604,2548,2372,1328,2702,2394,2895,940,2174,1420,797,980,2173,2094,3756,3756,4708,3524,3947,1247,1064,1247,1140,1446,1296,627,1790,3791,1370,1113,2481,742,550,552,844,906,631,867,844,868,1058,1175,1405,1405,994,1175,1175,967,967,1694,850,1415,1694,994,2005,1435,1176,1415,1435,1415,1415,994,1415,1415,850,970,1272,970,2123,2123,1438,1438,1583,1817,1488,2127,1933,1964,1443,1443,1429,1429,1429,1886,1886,1445,1355,1460,1009,1123,1032,1032,1356,1460,1009,1123,1123,1355,1355,1460,1460,1009,1009,1122,1122,1032,1032,1356,1356,1356,1465,1009,1180,864,1450,1450,1685,1014,1151,1151,2168,1450,1014,1151,1450,751,751,1685,1685,1014,1151,1151,751,751,1685,1014,1014,1151,1151,751,751,1685,1014,751,751,1685,1014,1151,1151,1685,2168,1450,751,751,1685,1685,1151,1151,751,751,1685,1685,1014,1014,2168,1685,1685,1014,1151,2219,1685,1685,1014,1014,2168,2168,2201,2201,1689,2201,2201,1689,1689,3359,2201,1689,1689,1017,1017,1157,2169,2201,2201,1689,1017,1017,1157,1157,2169,2169,720,720,5528,2306,1076,1076,1173,1173,822,771,948,1841,2759,1536,913,1255,906,1137,1228,1251,1476,957,1044,1298,1147,1029,965,842,952,1576,728,1470,920,1431,1806,2071,1683,571,571,1745,2516,1854,1792,1226,1684,1163,999,1160,1367,921,1632,1627,1471,909,906,462,1073,1351,1351,1103,1397,1057,1245,820,1262,1063,1001,858,1108,1067,1067,1055,1700,1120,1988,1798,1741,1807,1940,1614,1676,1879,1523,1305,1298,1299,1299,1364,1284,1364,1364,1284,1364,1284,1364,1364,1364,1298,1284,1364,1940,1940,2391,1535,1179,1847,1484,1823,2469,1962,1853,1660,1622,1950,1016,1202,1046,1535,1288,1371,1371,1860,1853,1643,1929,1727,2032,2132,1603,1980,2803,1548,1248,1556,1525,1955,1418,1371,1371,1371,1976,1610,1689,1434,1689,1024,2290,1399,1553,2069,1995,1995,1316,1019,2048,1512,1281,2148,1881,1932,1653,1653,2102,1712,1906,1937,1854,1854,992,1687,1195,1830,1936,1777,1013,1304,2332,1075,2116,2048,1642,1815,2048,1364,1034,2048,1102,1408,1450,1450,1450,1229,2122,2073,2073,2196,1792,1460,1792,1472,1359,617,617,617,833,617,617,833,850,833,617,850,833,833,617,617,617,617,3038,3038,1334,617,617,617,617,603,833,833,1587,1486,1450,1551,1760,2195,1725,1265,1883,1199,2000,1462,1114,1717,1182,1145,998,658,646,1140,1140,2651,1140,998,1716,1999,2841,2185,2044,1922,1528,1528,1513,900,1836,1552,1267,1068,1132,1114,1230,1303,1095,1095,1095,1613,1613,1212,1068,718,1068,2029,2082,2137,1701,1768,1427,1935,1056,1056,773,439,439,900,849,1161,924,924,770,389,389,770,389,389,1036,944,944,2122,887,1441,922,901,887,1364,806,1094,1069,2324,1500,1448,1448,1087,966,1614,1549,1512,1730,1872,1662,1420,953,798,2212,2187,2186,1518,1386,1129,1510,2132,1020,1468,1059,1416,943,1710,1666,1825,1418,799,912,2064,780,1880,1806,1807,1024,1024,1138,973,1478,1753,976,3066,1939,1620,1661,1646,1496,1808,1622,448,1932,1916,3709,1700,2973,570,558,558,1420,1980,2937,1048,580,666,432,881,702,979,979,1734,2257,1035,778,1946,2155,1522,1479,899,899,1164,1976,1890,1614,2090,2265,1905,1242,719,746,733,915,2203,1045,1775,1580,1580,1436,613,670,814,2069,910,874,874,910,910,1694,858,858,732,1554,2809,1884,925,924,941,1289,2054,1594,1807,645,631,890,1234,1234,1298,1396,1712,1848,1735,1065,1027,2033,942,1100,1476,1340,3329,1142,2886,934,1519,2836,984,984,3291,1188,2691,1609,1133,1796,1796,1620,1830,1803,1354,1332,1354,767,567,554,554,972,1093,1093,1346,1107,1391,1037,1105,839,1664,1107,1107,913,829,1109,1338,1007,922,1019,1246,1190,1413,1483,2082,1300,1365,1602,1178,1027,1017,1220,1220,3200,931,952,944,1234,966,1008,1127,968,968,1128,1015,1015,1227,1192,1087,1280,1629,1449,3003,1170,946,993,1268,1271,1100,1100,1733,1074,1225,1133,1095,1293,1471,2022,2290,1466,2697,1827,1869,2040,1038,1703,2961,1654,2300,1169,1300,2075,1152,1663,2547,1154,1271,1063,1063,1031,1231,1098,894,1094,2332,2332,1165,1248,1177,986,2292,1504,2154,1742,1227,1261,1626,1686,1431,2734,2734,1396,1400,1436,1472,955,1524,1177,922,2212,4029,3935,2426,2426,2514,1918,2035,2306,1512,2660,2330,1208,1428,2437,4018,2389,2550,2367,3376,3376,3666,3666,3376,2876,4354,2270,1178,1007,4090,4260,4260,1093,2363,2061,2885,2885,2300,3479,2215,2786,1960,3283,3283,1520,1320,1470,1943,1421,1538,2969,1474,1268,1714,3342,3222,4310,1711,2370,2596,2630,887,832,832,1864,1223,1223,4760,2471,2471,2471,2840,3021,3293,2484,2484,2484,2496,3041,2988,1963,1417,1417,1417,1417,1417,1417,1417,1417,5485,3483,3483,3483,2196,932,932,1948,1173,5026,6085,908,568,3623,1017,749,706,706,919,706,706,706,706,919,706,919,706,919,919,706,706,706,706,3164,1884,756,482,927,2973,2852,2714,1529,1225,3040,3691,2657,1144,992,992,992,992,992,1394,1144,1144,1364,1409,3262,1392,613,613,1107,1107,563,1728,2883,754,1634,2832,668,845,660,856,1055,892,1056,2074,800,800,558,896,700,918,720,720,906,906,906,918,690,720,906,906,3198,3198,818,878,705,752,719,894,795,1056,1056,650,648,1167,961,3021,2995,1440,1440,1420,1484,851,1440,1739,2034,2094,2094,2094,3899,1838,1838,1838,1838,1838,2113,2096,2981,1409,765,987,911,2437,877,949,979,1076,710,877,877,949,1076,1076,877,949,634,710,877,949,1071,1440,929,929,626,626,929,929,929,626,658,643,756,650,2302,1494,1069,1678,1920,1924,2440,2369,1920,1920,1065,1370,1228,1228,795,1224,2253,2253,451,1564,781,605,602,1518,1518,584,871,1016,831,1064,2265,992,576,1568,1321,1321,2032,1950,1950,927,954,908,881,1339,1181,1181,1164,1368,2148,1100,1269,1489,553,946,1664,740,1184,440,440,708,440,440,919,454,666,1334,2280,605,1717,1410,574,1345,928,2396,1642,873,715,715,715,873,715,715,873,873,447,715,778,938,938,938,720,1389,1389,1807,2185,3514,937,917,678,575,2758,3724,1460,1484,584,1100,1256,882,438,2503,2649,841,3977,3074,1050,440,440,918,1312,1411,2486,1050,800,800,1050,422,613,294,704,711,704,711,760,704,1707,889,532,532,540,538,540,629,411,568,863,1548,1548,1286,1194,1079,1338,1338,1741,2425,4850,7143,2309,2309,2428,2428,1712,3983,714,781,781,781,821,783,780,820,821,780,784,820,821,783,782,820,361,2202,1102,567,567,3746,1340,950,722,699,2736,2896,2817,950,753,545,802,952,739,947,692,952,958,739,739,947,692,952,947,1455,1802,692,1862,2315,2132,2132,1716,1966,1767,1394,1920,1445,1587,1134,986,2746,2689,4797,4425,763,900,2331,1680,881,4255,3500,5506,877,610,729,1579,3009,1419,1419,1474,1638,1276,1638,3341,1517,6026,1502,2718,819,824,1309,1376,1542,4326,2512,1679,1840,1746,2591,6701,4186,4514,2546,5077,2911,2547,2533,2939,1280,1280,2409,3013,988,887,2262,1470,1470,2508,2588,2750,2427,2124,1344,1615,1209,1161,1209,871,871,570,570,1220,1244,716,705,890,512,852,1169,821,401,565,718,955,955,733,876,2553,1302,3529,3343,2466,2137,1574,1580,664,622,664,622,459,454,464,2106,451,788,788,788,757,1265,1265,3030,2508,452,470,1202,874,1373,874,1373,797,1373,874,1373,1373,1373,1373,1373,874,797,815,483,419,2247,2247,4032,1481,563,529,563,529,501,563,501,1830,2633,2139,2152,1564,2107,1121,2202,1620,2202,1380,1190,915,1370,320,615,568,411,723,926,942,926,926,711,711,711,709,1291,1322,1523,1291,1584,1670,1657,924,2037,2047,1107,1037,1041,2409,970,1101,2990,919,637,637,637,919,637,637,637,919,919,919,1051,860,972,977,860,860,1051,1051,1051,1051,1051,1051,873,771,873,873,771,873,771,873,873,771,873,873,771,873,873,771,659,873,771,873,771,873,659,761,805,980,858,1538,1180,1985,904,1263,706,630,1226,1226,1036,826,1100,1472,898,552,1095,1626,1626,1554,2626,1115,917,1078,1213,1163,1021,778,1213,1163,1213,1320,1047,1027,956,1296,1296,792,792,1025,1376,1489,1401,1376,1376,1376,1541,2387,1469,1519,702,714,739,550,560,685,1177,1702,1152,932,695,694,694,695,694,694,930,980,695,980,1220,615,612,1525,1062,1747,1032,1502,1171,1121,1119,1173,1325,2272,813,1835,807,1757,807,807,1024,1074,1503,1286,2170,813,807,807,769,807,1757,769,1239,769,807,1239,807,918,777,985,1089,900,1021,1007,555,1007,587,555,1034,1021,587,1034,1007,1592,1821,1866,1432,1500,1552,1552,1026,4062,1358,645,638,742,638,1578,1578,1578,2168,1082,713,817,1116,1116,728,632,632,713,1116,1116,952,1478,1478,952,952,1382,1623,1382,937,1382,1382,1450,1430,1270,1337,973,663,1065,1421,1421,1041,1369,1369,4528,577,293,722,590,722,1396,1396,497,557,497,557,1376,1376,689,424,424,851,851,1398,351,783,1018,529,529,731,567,1035,786,644,672,539,815,1688,1688,1559,1559,1006,853,2414,2414,2374,873,902,938,938,1000,454,642,649,454,900,7427,1997,1067,1067,1067,765,1067,853,1135,1135,1135,1135,700,1610,1535,3873,5603,705,681,667,1087,457,717,1282,1213,753,1213,1213,457,1213,1213,2181,938,341,938,793,341,793,341,378,642,818,966,1590,951,2232,939,2716,1397,1420,774,1405,1450,844,856,783,721,711,692,1116,1116,1006,1889,1035,1354,1230,1789,1420,2100,1478,1424,1166,3419,848,1800,1032,766,823,846,861,1624,1826,951,777,777,1071,820,820,783,1023,1060,1060,1097,837,1608,1630,839,716,828,876,1181,436,673,883,1661,974,1105,714,714,1500,668,957,957,895,909,909,1169,1215,796,956,1294,1294,821,839,939,714,1222,1222,677,952,952,861,1087,943,923,923,711,711,955,906,1186,657,1083,1340,1116,1116,619,823,1737,1737,1177,906,1011,1011,1011,1090,1358,1235,1341,964,1155,1292,1212,1047,1129,1040,780,1297,1527,966,864,864,1064,1222,727,938,938,938,813,1118,1068,1211,833,1502,933,836,836,1100,1582,1055,1055,756,2750,842,842,750,970,1044,1044,1044,1081,1302,1061,744,963,1136,1997,1082,1174,972,918,1032,1268,1172,1291,916,1111,1001,2560,725,1046,646,676,999,999,1338,962,1132,672,672,682,852,852,742,756,756,752,921,1010,757,1476,1038,1089,976,976,1071,1071,743,1104,704,644,1502,704,836,1078,1078,931,922,902,682,1025,1025,965,1792,1795,944,772,749,1302,1156,700,1052,765,1358,646,705,600,1017,1040,700,1162,1064,790,644,1273,1012,826,600,1244,635,836,836,936,936,936,683,647,1154,921,979,1268,1268,1009,1009,771,1008,790,1062,1069,738,1382,988,853,853,988,988,1116,988,1072,1248,1454,1454,1001,692,912,912,912,912,912,731,626,1250,1250,829,789,763,1081,1364,1382,1420,590,1180,992,736,736,995,832,786,556,1073,1283,980,608,872,872,835,824,850,902,909,721,1303,350,1027,728,768,839,923,609,720,1038,1210,1058,911,973,584,1486,548,664,750,859,1684,704,836,836,1136,794,794,999,1098,1098,1248,1081,1081,981,1675,1675,1675,655,636,922,950,1590,1590,790,1123,964,964,912,836,1352,961,1352,840,852,1012,1012,1227,1144,1144,1216,1038,1071,1521,1118,1059,1143,1150,1150,838,1000,1000,940,940,949,738,738,834,837,1260,1260,1266,1266,1055,1148,928,1361,1140,1140,824,732,732,838,756,906,913,1089,1012,803,803,959,1118,1118,986,1116,746,882,948,661,850,962,1007,998,1682,1113,1129,883,883,1319,854,682,1459,1459,682,993,896,896,1062,801,801,1029,921,1237,779,779,733,733,738,728,728,1251,1251,909,930,724,924,1017,1017,960,907,991,823,1078,1044,1284,770,770,770,771,774,1092,1822,945,1724,1119,759,1270,902,902,720,961,836,832,728,680,1267,932,788,788,1120,820,1053,1053,919,919,1353,1122,783,762,836,768,720,1489,1489,927,1442,1442,1144,2021,712,909,909,1049,847,694,720,1217,696,696,858,1454,1454,1454,557,1545,861,822,822,800,800,455,784,1354,1354,841,872,1912,743,743,418,418,418,418,871,1049,1049,1059,1038,1278,1278,1008,718,913,913,795,1075,902,639,1064,929,924,912,759,784,825,717,717,587,742,742,718,966,665,874,1021,936,936,1181,1147,930,930,722,722,899,714,711,971,1299,1190,730,811,660,1116,767,767,731,976,775,781,920,920,972,2523,788,932,821,848,976,890,993,1075,975,975,864,1006,750,768,869,559,937,988,1037,956,688,864,864,765,921,921,799,720,950,950,1181,1181,608,807,774,576,868,868,1239,1239,891,891,810,1040,887,634,687,687,628,851,788,788,806,643,1075,804,1040,1040,944,1046,1023,1023,2157,976,1436,954,954,1340,1340,1065,803,929,874,1490,913,708,708,799,793,793,817,715,672,672,960,960,1470,828,1136,3663,956,956,2200,1374,645,464,464,588,468,1041,1041,409,559,374,485,485,689,638,898,651,646,653,1637,1160,823,823,1081,2542,1975,1086,1586,1574,1722,1924,1618,561,561,563,1142,587,1758,1840,1494,1494,1500,1816,804,914,604,1887,1391,1906,1916,1147,1146,1104,1104,742,1461,1104,922,1410,774,1900,1258,1273,783,651,1273,1344,994,1809,687,968,1285,1458,1089,2937,1434,1854,1854,1197,913,1426,1595,1056,647,1147,1166,1743,1450,1535,1271,1578,1258,1106,970,830,1340,1340,1478,649,667,1276,1128,1728,1147,1357,1336,1704,1062,1891,2208,1353,1922,1473,1366,742,1427,1427,1151,1149,1217,960,960,1730,2036,2036,1341,827,1261,1144,1216,509,509,1296,1341,740,527,987,1386,1593,1593,1828,1499,880,880,2247,782,1350,2116,2385,1916,1473,1742,1608,850,1156,922,890,1368,2088,1956,1928,1286,1286,653,1500,1652,811,811,1360,1791,2780,1836,848,848,608,1158,1354,1052,998,788,904,1211,591,959,1465,826,1337,2634,1770,2617,2617,900,2058,1738,1786,682,847,847,1446,2448,1372,1372,2856,717,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,944,944,746,746,1008,1714,1061,1449,1655,2082,764,975,975,1087,1087,1348,2056,480,1178,1842,1528,2134,690,689,689,1903,1472,2250,2250,1539,1324,1324,905,1377,1343,1343,3317,1757,1616,667,1552,1650,1202,957,1023,760,1889,1826,2301,883,883,1099,616,872,444,872,2206,1264,1049,947,1370,1161,583,606,1067,1988,704,996,1897,1284,671,1080,1067,1603,769,1091,1091,662,662,662,1032,1033,644,1637,1287,3137,3207,1081,962,1849,1706,1501,1505,799,965,950,950,950,976,1060,2243,1493,1722,1284,1548,1554,1298,1415,1197,496,496,509,726,3373,960,960,1496,629,1080,1106,1441,1886,1024,1710,1438,442,447,562,538,490,700,500,1536,1844,1635,1923,1923,1592,791,858,801,2370,1319,2056,1508,1898,724,1536,1531,1531,1767,1992,2824,510,1572,1968,2128,663,1582,2093,1143,1143,2064,2093,1143,1168,1168,1168,765,1944,1944,2104,807,916,916,3520,4725,4131,2852,6344,3330,3907,1837,2482,2225,1705,3402,3402,1263,1424,2092,2092,2917,938,1583,1328,2291,2150,3495,1521,3036,1216,2806,1510,2381,1910,2602,1473,3549,4390,5202,3016,3332,1824,4610,4633,5061,6476,4237,5501,4689,4689,6577,3544,4540,4424,3822,3822,2782,3894,4619,4649,4712,1004,1590,2430,1173,2407,937,2156,819,2146,702,1057,1057,1575,1108,1806,2076,1144,2084,1884,5767,2106,2484,2450,4460,3349,1714,1358,1432,1833,1372,1009,1009,2451,1267,3091,2658,5042,2040,1880,3451,3367,1917,1278,1725,1854,468,467,1045,381,579,1137,1023,917,1012,1019,956,1314,939,1051,1051,1456,975,1075,1270,1990,1148,1397,2107,2797,1004,880,2668,2415,2668,1524,700,1288,2328,2328,1470,781,1152,750,925,875,1336,1303,1297,1336,1336,1303,2653,1336,1336,1614,2342,1032,848,570,570,739,532,825,598,775,1319,1133,741,741,751,554,766,1305,488,494,875,747,608,1091,791,1091,2321,2451,2458,2298,1062,988,1228,988,1839,3193,807,807,1858,2634,2634,1417,1558,1435,1435,1072,453,505,891,1895,644,400,400,1982,1065,1513,1213,1528,1069,1092,1288,1037,1075,1075,2462,1075,920,1782,1704,1726,1070,1024,935,2510,2648,2648,1972,1017,914,2117,2490,1171,2924,2444,1075,1442,1171,2080,2080,3269,1836,3881,4294,2040,1920,1920,2317,2337,3063,3063,2645,3653,3304,2967,2114,1866,2959,3676,4298,3497,3354,4593,3790,2433,3345,6002,4570,4092,2856,2856,2936,4870,2627,3010,2362,2215,2920,2096,2690,2690,2203,2901,2901,2901,2901,2959,2959,3833,2368,2368,2025,1786,2453,2453,3076,4293,2138,2138,4024,2172,2343,2505,2312,3387,3753,3753,1249,2521,1410,3188,2108,744,2713,2713,2713,2713,2713,2008,2008,2153,1857,2220,3395,1987,3414,2709,3309,2994,2833,2833,3384,3384,3384,3384,3841,4580,2557,2766,2938,3256,3256,2024,1975,1025,1229,1301,1196,1108,725,2596,2318,2908,2259,2457,3187,2747,761,772,2670,2508,902,2374,1561,1561,2527,4808,2624,2145,1133,623,1813,2269,1284,4884,2305,2305,3139,3139,3139,3140,2898,1872,3603,3415,4345,2793,3184,3184,2521,2591,3431,3431,1408,1408,1584,1584,2484,2231,2079,1944,2079,1944,2249,2249,3929,4166,3220,1112,765,1077,1083,1303,744,2668,2310,932,941,766,701,1085,1085,996,1205,2972,2972,2970,2793,4507,4673,3515,1009,1549,1854,2885,1351,2131,2639,3192,2364,5981,3841,3455,3502,3254,3455,4192,3729,6684,3757,3612,1488,1488,1248,1644,1846,1404,1248,1846,1404,1846,1846,1846,2976,1404,1846,1846,1248,1404,1404,4420,3353,3353,1846,1107,782,638,1227,814,1227,782,1002,638,782,814,1107,752,752,2041,1522,1185,963,1144,1827,887,1144,887,1273,887,887,887,1335,3376,2870,1313,743,743,789,1176,1313,872,1131,743,1096,902,1096,1096,1176,1237,1272,1775,1953,2031,2101,2434,3735,2101,3254,1279,2257,2490,2100,2100,1454,1130,1396,1690,1690,765,1556,1089,1094,1094,769,1607,1392,1735,1452,1560,1750,2465,2430,2714,1889,1889,1889,1326,1312,1191,1156,1798,1230,685,631,1080,1080,1080,802,1080,847,1932,2500,2665,1303,1281,1373,2995,2528,2762,1449,2904,1190,1190,1190,1190,1190,895,1022,1161,1161,2248,865,1057,1330,1499,2682,1891,1891,1891,2476,1891,1891,2535,1774,2307,1905,1317,1545,1210,1317,1258,1276,1317,1276,1255,1276,1276,2965,939,2212,2541,952,952,1580,1798,1749,1368,1368,2430,2430,2540,2636,3201,1537,1173,876,1226,851,1229,1178,1202,3147,1800,1622,2603,1696,1983,2590,3180,2224,3887,1975,1828,2278,2325,1800,3339,3372,3650,3296,3544,3004,3394,4159,3734,4220,4400,3490,5209,3527,5704,5704,8590,5861,5662,9694,4267,4331,4324,3449,3449,3116,3970,2435,2756,2756,2230,2230,2756,2435,2808,2435,2435,2756,2808,5700,2815,3257,3257,1817,2761,2761,1222,3885,1663,1170,3682,2202,2384,2202,2202,1391,1127,2510,1322,2358,1106,2599,2232,4997,4081,3160,2910,2351,2351,1645,2715,2182,2799,3137,3294,3418,4079,2994,1350,3567,3567,1042,4717,1216,1068,1056,1146,1087,3846,1215,3542,1481,2095,2801,1740,2774,2978,1217,3176,1147,2938,1360,1200,1178,1331,1001,1177,996,2210,1916,1292,1603,1239,2182,1917,3150,1395,1520,1520,2385,1825,1145,2551,932,1459,3376,1202,1738,1738,1258,2039,2026,1736,2336,2450,2398,1674,2441,3156,3156,5735,2261,3932,2028,5909,5909,3697,3149,5498,5498,21503,2357,3114,2710,2888,3251,5335,3578,4813,1166,1166,1169,1529,961,2155,1254,1568,3851,1163,1084,1587,1105,1129,1059,3827,2720,3230,1352,1370,2750,4387,1505,1700,2551,2042,2778,1508,2309,1242,1045,2615,1128,1072,1072,1141,1141,2792,2314,1081,2053,1894,1097,1102,2707,3331,4260,2662,1633,920,1590,912,2080,1221,2248,2697,1830,1012,1208,1323,1323,1323,2660,1280,1323,975,2146,1366,3109,3246,1152,1152,1160,988,1047,1500,936,1509,1296,2332,3169,3169,2941,1038,1180,1247,3298,2780,2440,1016,1411,1411,997,2972,2574,1300,1403,1609,1186,2266,1711,1322,1322,1220,980,1212,1220,958,1251,1294,2410,1892,1227,1287,955,2014,1926,1910,860,886,633,1032,1151,1089,1515,1146,1150,767,843,930,1095,1508,1251,922,1555,1386,1159,954,954,961,964,964,973,1189,1742,1742,1867,1630,2010,1910,1894,1418,4054,1029,1392,2082,1297,823,1038,1564,2447,2080,1930,912,1442,2538,1336,1224,1934,1044,2120,1911,1323,1323,2120,1323,1323,2120,1911,1272,768,768,1272,1272,1272,1272,1272,1272,1272,1272,1272,768,1272,768,1272,1272,1272,1272,768,768,768,1272,2528,1272,768,768,1272,1272,1272,1272,1272,1272,768,1272,937,943,639,943,639,943,943,639,639,943,943,1815,1626,1346,2702,1251,1099,2080,2556,1232,713,730,1498,1222,1228,1847,2263,2162,1801,1454,997,1053,1319,1000,1809,1012,1000,1210,1116,1173,2046,1013,960,1037,1037,848,2000,1980,1990,1911,1095,1083,1084,2000,2811,2480,2580,1182,1208,1475,1301,1382,1270,1239,1010,1417,1198,1198,1220,944,1317,1727,1535,890,782,622,1978,2700,2356,1466,3285,2699,2699,3584,2902,2176,2423,1559,3208,2706,1812,1933,1890,1862,855,984,907,1080,2082,1573,2317,974,1389,862,1341,916,1468,1867,1030,2173,2464,1095,2084,1833,1055,976,1239,2077,2812,2388,2388,4780,1300,2636,1318,3143,2100,981,981,1955,1276,2102,1606,3111,1203,910,1195,862,2964,2383,1401,1185,2879,2183,1991,1133,1128,1128,2368,1128,2598,2432,2148,1457,1540,1424,2584,1060,2772,2614,2937,2611,3235,1485,2231,1149,1168,2587,1152,1922,2336,3195,2472,2634,1767,3546,3546,1280,1280,1137,1126,2810,1078,2903,2166,1135,2676,3653,2400,3529,3346,1760,3773,2479,2455,1969,3727,3727,1150,3244,2048,2404,1408,1798,3338,3719,3476,2918,1128,1288,2793,1264,2204,2590,1470,944,2440,2440,1045,946,1429,2538,1288,1288,1580,1188,955,957,957,877,1010,957,1536,1355,2090,1400,1864,1650,1696,855,678,1187,1530,1734,1927,2512,1518,1043,1059,1491,1094,1639,1094,1280,792,1662,1353,1353,766,567,434,1931,985,1472,1472,1103,962,1628,877,1312,1540,1050,1050,1480,1480,1536,939,525,743,1079,953,953,1596,1892,1499,1274,1417,1161,1610,1610,672,1908,1169,1046,2152,1405,2128,1105,1536,1536,1159,2532,1339,1816,560,1690,1712,1911,1691,761,499,1013,1801,1518,1518,1540,1540,1926,1224,1608,1623,2128,1485,1496,744,1997,930,1099,1306,1182,2093,720,1847,1057,881,1096,1144,1997,1904,1032,1032,1211,2032,1792,1860,1083,1000,1000,1394,1557,715,1664,935,935,1120,1027,1554,876,2359,1140,814,1354,1117,1180,1006,1809,2678,1247,1798,2437,1396,1750,1738,1946,1984,758,1858,1834,1364,958,1863,1614,1614,1469,1336,1619,1906,1352,1541,1541,975,1440,1416,1763,1677,1392,958,1032,745,1054,1244,1023,1658,903,890,820,1314,805,805,1102,1815,1232,1119,579,579,845,1404,1404,1404,987,1130,1130,1130,1339,1027,607,1085,952,831,1481,2113,1504,836,616,616,3722,1536,1536,903,863,1075,1072,1125,764,764,738,734,734,937,937,1211,767,787,863,863,761,753,1086,1156,1156,1250,2187,787,1006,1312,1234,1234,1053,856,856,739,746,751,1141,1472,822,822,1105,1373,1336,991,1164,1015,987,987,1531,1381,1381,758,1034,865,999,1159,972,1427,1616,1618,1463,1151,1151,1456,1098,1663,1663,1322,914,1033,940,1058,1530,929,1072,1163,1432,784,784,1185,835,933,1351,1351,2952,751,992,992,1051,910,910,919,1185,1185,940,1379,768,748,748,798,804,804,793,1054,1042,1587,1587,1268,999,965,1092,1083,1456,798,1278,1099,958,743,999,1205,1132,915,1035,1323,715,1028,815,1126,1307,927,927,1125,978,967,937,937,1114,916,916,823,1087,1018,781,895,836,652,887,1369,1061,637,570,723,855,1028,836,836,731,731,1105,794,640,1056,1094,1020,747,1067,1042,955,733,1042,694,929,895,886,1002,685,967,694,1030,791,876,922,968,1200,1228,403,403,1029,1029,1029,878,360,913,913,1229,750,864,707,966,668,668,868,663,707,1268,1268,738,738,806,1057,979,895,676,536,962,1043,693,800,1126,1020,1020,870,1072,906,1073,2096,1120,1160,1635,1050,748,1328,777,1314,808,808,800,800,1007,1003,731,1003,1003,1036,781,824,1008,1362,1471,737,1049,793,1345,1345,942,1008,1008,1008,2748,875,876,878,878,886,875,878,884,1225,878,851,674,998,1037,705,1136,1435,1373,711,558,720,486,486,486,1060,1060,1060,1038,574,429,800,996,902,622,943,1681,649,947,661,1313,639,844,555,912,932,1008,719,925,925,540,816,816,865,1441,1441,1444,876,1065,679,866,866,1335,1245,1245,707,707,773,832,690,860,756,672,1313,939,847,826,674,735,703,1202,1372,973,973,1029,818,1027,709,709,762,796,960,960,1022,1022,1022,1272,1610,763,788,788,764,732,1125,1041,1041,1041,780,936,828,939,876,849,1065,1078,734,734,953,953,1062,1319,1319,620,973,574,857,1383,1306,828,973,973,973,973,1214,1215,939,1523,1652,1652,1652,1314,878,779,1081,1081,959,1165,1165,1223,828,2091,817,890,788,1165,612,612,822,1001,1001,767,857,1000,1426,1405,812,706,706,1117,1273,1184,921,565,1129,2242,2242,784,956,712,822,1080,1066,2704,1040,804,1360,1082,1078,1118,1108,2228,728,854,854,1774,903,990,1289,906,968,968,607,2776,2776,1023,1023,1023,1023,1023,1023,1023,1071,1074,650,1008,789,1268,1268,1268,1268,1075,1075,882,1228,799,799,951,808,818,1027,826,915,1350,1226,1002,1002,675,675,2067,922,922,601,1098,802,922,1248,1084,906,798,725,725,1055,681,1893,723,1828,1343,1049,784,889,889,1018,1091,1091,867,1022,613,762,762,527,1268,1268,1222,1222,1214,1113,882,784,784,987,1141,1512,1250,808,808,654,771,771,1299,1404,1970,672,672,1047,997,997,1140,746,652,652,1297,1537,682,771,1136,682,1061,1023,910,796,913,902,768,821,808,808,1111,832,832,1016,1064,932,988,1744,1087,1040,910,1869,862,752,752,1157,755,755,1046,821,1466,921,1025,1024,891,832,832,929,1420,1079,1441,1441,1088,1062,1144,831,1034,717,1459,1459,937,1451,1317,990,990,990,990,990,1095,1236,1236,1095,1095,1095,1092,986,1095,1281,1369,824,1114,743,743,745,895,1087,880,911,1427,739,1623,862,693,739,945,945,945,1356,990,862,1356,1121,1121,736,1580,2221,1016,1014,1016,1017,1040,1390,825,1015,1526,926,923,1288,952,950,950,1780,947,947,1315,947,1211,947,1187,1381,947,1211,1211,947,1429,947,1918,1114,1865,1116,1123,869,1559,763,1611,991,1215,1215,1240,934,1704,1070,829,1454,1070,874,777,1139,874,1224,1672,837,1192,1192,926,1252,1401,1732,1232,1176,1176,1096,1096,922,1290,1235,1396,1556,1599,1120,1019,1774,3170,1589,988,988,786,786,996,1027,841,1203,827,988,940,827,1023,840,840,847,844,1033,766,840,1021,840,804,804,804,804,1257,804,1026,1026,804,1227,1733,1663,1038,1410,1081,1109,1120,1068,768,768,768,1232,1000,926,926,728,900,835,753,888,888,1125,1125,918,798,771,735,761,1132,1132,632,686,1272,1272,1068,924,841,771,771,771,771,1764,1091,1189,971,1151,961,792,1908,910,871,920,1040,1940,1940,677,1166,755,777,776,750,1314,1495,997,997,1001,1003,1481,1001,994,980,1082,1082,982,982,1082,1117,1092,1211,1211,1211,1213,1211,975,1407,995,1144,1144,1195,807,807,807,1072,825,825,1066,1066,955,955,768,999,1093,1067,1508,949,1690,768,768,949,848,768,1280,887,887,1092,972,972,1092,857,930,972,1261,887,972,972,1420,972,1434,1600,1600,1600,1600,1600,1600,1048,1242,709,1388,1388,652,1050,1062,1062,1180,924,988,894,1108,840,986,830,992,996,994,1038,1038,1261,1003,1419,1003,1003,704,1333,1333,1606,1291,1218,1025,1032,1010,1003,1011,1570,1012,1111,923,923,923,1103,923,923,924,880,774,874,874,774,812,812,944,1119,836,836,945,1361,811,1057,1057,1036,827,827,830,1004,1040,1159,1049,925,925,715,1245,946,742,742,742,859,1017,1154,998,715,1073,1073,1156,1095,818,713,715,885,851,742,858,742,742,742,1495,1343,713,1234,965,707,715,715,1006,742,742,715,715,742,742,845,1626,924,2034,1082,2064,2095,1876,1862,2065,1746,874,1378,971,1336,1013,1912,1924,800,1098,1098,1496,701,743,1729,1664,712,930,930,722,1035,988,1813,864,976,817,1289,774,774,699,975,699,701,1842,1225,974,1116,775,775,874,1114,1104,1104,1104,1104,1104,1167,972,972,1482,1529,1520,1853,984,2471,1922,1199,1760,2088,1593,2671,2549,568,2205,2205,1921,2294,2669,1593,1977,954,1153,1922,1922,2948,833,2278,2235,2310,2382,999,1123,2553,2216,2216,1736,1257,933,917,1956,1956,1956,2104,889,984,1651,800,908,1001,1052,1229,844,1919,1919,2523,2495,2134,1311,2345,733,941,1948,2451,3070,1628,664,855,1642,1487,823,1573,1847,1554,1554,1321,1379,1469,1885,1032,1434,800,2117,2128,1163,612,1881,591,2445,771,1057,715,1037,797,2083,870,870,879,1189,2341,4450,2787,2787,1858,1882,1222,984,2563,1887,1982,1579,1315,852,2634,1819,1819,2878,1892,1957,1957,2665,1510,1371,2178,2169,2495,3224,1382,3117,2406,3270,3016,3138,610,610,2940,1064,958,3610,3493,3479,1394,2378,2894,3120,2894,1056,2410,2410,1136,1190,1293,1598,4978,1492,1765,2862,1515,1260,1222,2674,2506,2249,1055,2998,1935,1279,1255,897,1598,1246,1210,2578,2205,1344,1344,998,929,1161,947,1411,1203,1898,1401,1766,2134,2681,2249,2200,718,940,1012,1036,890,1280,1224,1117,2278,1250,971,1934,1390,3472,4024,1245,1204,1884,2181,1057,2653,1054,1054,2822,1839,2395,1422,1276,1345,1011,1286,2282,2348,1005,1005,1358,1024,957,1220,1381,1110,2946,768,2701,828,1471,1471,1432,1976,1976,1554,1168,2045,2815,1211,1392,2661,1236,1503,1184,1011,871,918,1126,1380,1849,822,894,1125,2325,2516,740,686,1346,1132,1697,4058,3170,873,1019,1525,827,974,912,965,754,997,1815,1308,952,1066,1210,1210,833,833,837,826,924,2763,889,889,1032,1373,1307,2025,650,852,1323,1274,930,930,930,1310,944,686,833,833,774,774,2962,721,988,947,768,3254,742,3511,1375,2118,1733,1625,2108,1625,1080,1259,1148,1504,1504,2022,745,749,2105,1006,1099,1313,1051,684,1115,809,637,1162,1162,885,670,670,936,885,885,936,1162,936,1070,1070,1020,1279,1278,706,706,870,1000,684,3325,3432,1120,980,1307,1263,3251,2559,1307,586,3254,3214,1061,2043,1734,1734,1735,1589,1045,1364,1101,912,1015,1263,1536,1450,1450,1450,1450,1542,1895,1542,1033,3398,1960,1326,3451,1310,3369,1572,1024,3557,3307,1403,1000,1063,974,1029,3136,3040,712,898,962,823,962,1015,846,1069,950,1258,1020,1348,1025,958,2994,2331,1054,2823,3509,1692,1120,3830,2829,3395,3395,2116,2116,2116,982,772,2867,1854,2684,3252,1868,1868,824,824,1134,3192,1038,1293,2296,818,2863,1407,1407,1536,1439,1520,1418,2948,2216,1165,2626,1932,927,927,933,3238,1262,1149,1040,3660,3022,3264,1439,3192,1713,3670,1716,3379,3094,3063,3338,2915,2921,2805,3400,3525,1722,3510,3265,2734,3404,2082,2082,3106,822,795,3539,977,852,3471,896,1167,2307,3225,3075,3217,3261,3261,3452,1122,1056,1818,985,988,964,1443,825,1144,1131,1828,1124,1063,1105,1096,790,915,1753,1753,1116,2148,1035,2952,3049,1200,811,2658,870,886,1556,2601,1497,1435,1196,2396,1045,1443,1680,1680,1579,3114,3114,2768,1067,2634,1250,2976,3161,955,1119,3200,622,2829,626,838,810,827,816,819,1346,689,906,989,1304,880,793,1225,1391,1198,1602,1602,1832,1832,1265,1165,1165,1165,840,1156,840,1195,3932,2880,3263,2422,974,2776,2251,1197,3213,1660,1666,6089,2160,2477,1824,1824,1824,1564,3682,4226,4303,3240,4859,4435,1458,2905,4646,1079,1427,1136,1231,1097,1434,1067,875,2158,585,604,1518,1518,2116,2215,2241,2240,2240,2039,1547,2551,2552,1152,1991,1415,2442,4953,3834,3610,1003,1206,1355,2014,3727,3162,1890,3815,3784,440,447,983,1880,1398,1559,1644,932,2148,2148,1935,2007,2684,3423,1389,4651,3951,3450,3768,3846,4538,4102,4579,2933,5075,3546,4084,4084,4159,905,3892,2734,3791,4326,3580,4293,1250,588,594,2074,2074,2142,2525,1891,2074,2074,3441,1680,2893,4299,3510,4191,3807,1111,4378,1109,2914,2914,4447,1781,2223,3706,1028,3834,3092,4424,1044,2536,2096,3917,2330,3913,4125,2493,3811,3811,3755,3045,1599,1117,1047,1600,1920,1920,1600,1440,1092,1289,1022,2050,4250,1726,3616,2112,1936,3709,4018,808,2961,4578,2492,4083,3863,1474,2937,2937,3892,3883,774,1076,1541,2180,1379,3532,3532,4116,4321,2870,3146,3575,4304,4092,3253,1969,806,968,3516,4207,3591,2779,4484,3513,802,3394,3647,3114,3731,3938,3938,2982,3088,3432,2208,3236,3236,3277,3880,2702,1486,4163,3205,3449,3791,3528,1044,3979,4071,3150,1449,3379,1864,4578,754,3475,1294,3150,798,2471,2978,3929,1207,2255,1151,884,3243,1381,1290,3700,991,3029,818,686,676,676,664,854,853,890,892,1009,856,856,1019,757,650,650,2868,2168,909,697,773,739,878,840,3270,3034,858,773,1208,1167,737,815,672,1343,775,940,996,1469,672,2555,2855,669,722,1035,1297,700,758,913,893,1872,836,800,1560,924,1004,2912,2501,1672,1406,672,672,672,957,1642,1448,1316,823,3079,675,822,888,576,1067,1005,1147,1102,678,643,1090,904,1102,1264,908,999,975,937,1991,2072,2033,1695,957,960,922,946,1285,925,850,994,627,859,725,846,717,2269,662,871,1155,939,939,1031,825,813,1139,821,1078,911,885,885,728,744,870,870,1440,1354,672,774,939,939,772,1266,786,2804,819,542,2068,1205,777,939,1756,1756,2289,2305,837,720,939,939,1291,1346,1994,1636,647,1853,2337,1856,944,2936,705,1104,1248,871,870,1006,1581,1337,757,941,870,2833,1105,884,1296,2653,2653,2653,860,732,3176,940,526,685,720,1059,1404,1806,1386,766,757,440,698,422,440,435,698,698,1167,783,971,937,852,763,2487,2487,980,802,802,1125,1629,714,709,1068,1297,778,1087,758,1543,1171,893,2049,847,1098,2160,2176,2178,1962,1964,2540,908,2532,1906,1866,1888,851,851,1876,1856,1960,1971,1921,1921,2006,2432,1387,1387,1892,1877,1877,1834,910,1349,2024,2024,2024,2482,1472,934,1050,1992,2429,1226,1046,1046,768,768,737,1076,744,1224,1850,2211,1844,996,845,940,1633,1450,1022,1738,1628,1628,1907,1029,2044,672,1210,1428,2876,2362,866,1119,1008,1001,864,1980,1980,1648,2135,851,823,2158,1031,936,1139,5274,1579,1058,1842,528,748,1695,960,694,1031,2006,2408,1904,1904,1067,1917,1002,683,664,732,838,833,833,1185,947,1000,998,792,1296,1153,879,758,722,1616,436,485,1118,1304,889,975,975,624,1400,865,989,989,759,755,710,1169,1169,876,1358,798,969,969,826,934,895,1837,1008,1040,747,747,936,775,813,853,1018,1203,1133,964,839,839,1146,988,886,1348,1460,1095,1502,880,1140,669,1993,865,1253,988,1020,1010,1373,975,873,1880,724,2202,826,2612,1635,1028,3317,3317,2800,2800,936,864,1752,1752,645,1405,1045,1045,1090,1090,1090,1240,1104,1104,1013,2090,936,1496,885,688,1024,1024,746,746,1261,1261,1600,1452,768,1292,1104,1104,1024,1024,1024,1653,1068,607,1057,968,1683,1252,1311,1311,1106,1139,688,690,690,707,707,688,1151,1282,1282,711,917,705,1301,1113,1160,1361,1361,1177,950,938,899,710,704,704,704,704,729,881,733,733,1156,707,1355,1223,710,1184,712,1236,710,917,736,1190,1190,707,1066,1066,987,870,1321,1321,1365,732,1162,735,1097,1475,915,1231,1270,1110,1121,1402,1028,1028,1099,1327,835,739,715,1121,1337,1229,1229,710,1185,1083,1474,744,744,1035,935,1280,1104,1127,838,838,1013,1100,1107,1235,1389,704,1057,1364,1030,984,928,928,704,734,774,1014,1014,734,704,886,704,704,704,2127,1242,1094,1308,1057,1057,577,1568,1371,1848,1578,1053,1885,1296,886,1641,558,994,2894,876,1032,720,1032,950,1064,922,922,939,1750,1137,816,1059,640,1153,803,1460,1716,1085,1205,770,1335,1096,1583,1096,1096,1096,1096,1096,1096,1096,1082,1309,1077,1041,1077,1587,1041,1041,1077,1077,1041,1041,1193,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1894,1607,1595,1096,1096,1096,1096,1096,1096,1096,1114,1114,1154,904,907,907,903,903,1149,988,2199,1158,900,903,863,1512,1351,1390,988,988,947,1147,1484,1353,1353,1357,1619,1100,1107,1107,1363,1134,1130,1061,864,1116,1013,1353,1017,863,3270,3407,1082,1411,1777,1388,1248,1248,1170,1019,1276,868,940,1346,1019,1082,940,1082,1377,1377,1081,942,1015,942,1080,945,1353,1435,1513,1080,1208,2842,2702,1492,1950,1937,3474,2036,1451,1907,1572,1598,1294,1031,1031,1031,1031,1031,1035,1243,853,853,1035,1031,1031,1031,851,853,1037,1034,1285,1031,1034,860,1099,1099,1426,1099,1075,1071,1346,1162,1111,1111,1014,1007,1614,1384,1119,1014,1114,1099,1456,1099,1099,1099,1397,1397,1397,1348,1243,1031,1167,1689,1037,1037,1037,1362,1099,1031,1031,1160,1342,1160,794,894,894,850,850,1663,1308,1106,995,1108,853,954,853,991,988,1603,1310,1310,1310,1382,1382,1372,1014,1181,1128,1073,1538,1444,1862,1060,1453,1452,1145,1440,1172,1005,1267,1141,1145,977,1145,1145,1145,1260,1145,1145,1785,1094,974,1202,1242,974,974,1261,1145,1145,1145,1488,1488,1145,1261,1145,1145,1261,1245,1145,1413,1413,1268,1268,1268,1154,1154,1154,983,1210,1154,1454,983,983,1154,1268,977,1145,1147,977,1145,1145,1147,469,1147,1415,1147,1147,1147,1147,1147,1147,1261,1147,1147,1147,977,1261,1133,1133,1133,1133,995,1133,1133,1133,1133,1133,1133,1688,1688,1133,1133,1273,1133,1133,1133,1277,1133,1133,1133,1133,1383,1133,1133,1133,1145,1145,1261,1413,2903,1405,1145,1261,977,977,1145,1147,1145,977,1261,1147,1147,1261,1147,1147,1261,1261,1145,977,1261,1541,1988,2323,1988,2323,1147,1147,1147,1147,977,1147,1261,1261,1147,1261,1261,1147,1261,1147,1147,1261,1147,1147,1343,1976,2934,2102,2096,773,1920,1317,700,1498,787,1069,2390,1362,1164,1007,939,817,1428,1428,1458,1326,1656,926,1747,1162,748,1217,1217,1313,1096,958,950,950,999,1095,880,1175,1005,837,875,875,844,1052,1029,1222,827,1063,1065,1008,1018,880,885,1065,818,1008,1557,2099,1764,1764,3292,3018,1677,1456,1535,2198,1535,2198,2198,2529,1535,1535,1870,1535,2608,2198,1535,2516,1734,1535,1535,1535,1535,585,920,776,776,920,776,920,589,589,589,417,2658,1403,2036,1545,1545,1671,1315,1353,1253,1253,1704,1464,1081,1779,1663,1350,1737,1374,1401,1567,1605,1456,1464,1642,1642,1681,1968,1683,1388,1416,1416,1642,1393,1405,1405,1478,2071,2071,2134,1486,1284,1356,1316,1535,1502,1347,1278,1722,1919,1920,2509,2315,2141,938,809,930,792,1533,1328,1223,1753,1509,808,1778,1148,1028,957,1045,2035,1726,1726,1298,762,1419,1191,1421,1860,1860,799,814,1400,1039,980,1374,2064,1041,1382,1391,1029,1234,1234,1242,1022,1620,2239,1258,980,1532,2436,1468,1554,1038,1172,3053,1133,1133,2854,1027,904,1469,1765,1330,1132,4054,3203,1151,2145,1699,3366,1560,1726,2150,2150,3760,1866,1802,1802,1964,1762,1983,1441,1775,2067,1602,1952,3285,2123,2284,1503,1965,1730,1892,2956,3099,1799,1799,1905,1905,2956,2552,1799,1905,1799,1799,1905,2956,1799,1905,1905,2552,1799,3099,1799,1799,2552,1799,2094,1907,1862,1818,1559,1641,2379,2354,1701,2756,2549,2549,2123,2123,2158,2698,1912,3368,2580,2256,1978,2073,1981,2162,2237,2237,2095,2600,1799,2305,1545,2795,2323,2203,2058,2004,2136,2208,3042,2050,2075,2023,1896,1989,2421,2345,2107,2350,3072,2204,1905,2991,2516,3595,2390,2440,1726,2752,834,1044,1203,442,696,1451,1451,778,592,1094,729,729,854,854,854,783,894,843,843,630,601,954,751,751,659,780,778,778,1039,832,649,1515,684,740,910,923,894,1340,1104,1104,1216,1216,670,871,746,746,747,928,844,675,675,779,685,604,604,916,710,752,827,997,1370,1315,1315,1559,1559,725,828,840,840,880,899,1160,1160,952,952,1809,1809,1232,2403,1115,1247,1668,1004,964,1017,1037,1068,950,982,710,710,810,756,678,581,726,726,911,911,714,989,989,860,863,863,806,806,672,672,921,1365,1078,779,1340,747,1233,753,806,806,1225,1412,870,1458,1340,958,5763,3790,1294,1285,1174,1412,1300,1272,1355,1412,1412,3588,3178,2577,2548,4107,2595,2507,1811,3784,1888,1764,4419,4591,2182,2230,1888,1761,2587,2238,2587,2587,2087,1635,3178,3178,1761,1761,2588,2595,2588,1635,2116,2815,2182,2507,2182,1759,2860,2182,2718,2269,2269,2718,2577,2577,2838,2245,2230,2745,2236,1948,1948,1767,2258,1845,1342,2236,1342,2236,1342,1442,2725,1426,2021,2311,2729,2693,2755,2755,2311,2311,2726,2755,2378,2378,2077,2077,2671,2671,2729,2729,2378,2378,2655,2655,2895,2895,2021,2021,2348,2348,2126,2126,2783,2783,2852,2121,2888,2783,2935,2935,2755,2661,2378,2755,2021,2348,2121,2121,2935,2935,2655,2655,2311,2311,2729,2729,2935,2348,2021,2737,3718,3188,1037,995,1063,1037,1041,1001,732,1231,1400,979,1319,1159,1203,875,914,1042,834,1322,1178,1680,831,1120,1417,1811,1097,1087,892,1697,1775,1340,1041,1037,891,1024,1024,2078,1687,1369,1167,913,1061,931,1226,1067,2257,1638,2381,1909,8964,758,758,909,1748,1742,1132,1123,935,1050,1360,1051,2961,978,2512,876,2840,971,1786,1786,1200,1200,2058,1118,614,614,751,503,810,504,660,849,614,2030,1395,1012,908,707,751,871,890,1078,766,987,1278,749,749,1140,1140,979,1332,1027,2954,3010,801,848,928,803,774,848,801,821,821,720,720,796,796,720,1232,1030,1065,770,1096,1457,1598,1412,1090,1089,943,943,1013,950,881,1273,752,1296,1051,1231,1545,3546,3546,1139,1421,2168,894,937,3139,941,826,1219,838,838,2770,2770,1282,1044,914,3251,855,3204,2761,1160,1386,1386,1386,576,1386,576,1970,576,1904,1489,775,950,1176,1103,2946,2946,1218,2373,1527,1365,1365,1364,1361,1699,1717,2555,2354,1690,1472,1084,2448,1369,1603,1603,1424,1060,1952,1712,1596,3360,2537,1584,899,1657,2195,2832,1055,1442,1156,935,1733,933,1726,1683,2826,1005,3251,1540,2209,2209,3096,3096,1476,2188,3128,3409,2796,2796,1167,1544,3336,1330,3126,3126,1148,1253,1076,1294,760,1787,1490,3015,1191,1185,1191,1191,959,687,1082,1053,817,1255,1408,1420,1818,2070,1797,2162,3064,1730,1688,845,845,796,796,800,790,1635,913,872,1122,1641,1109,1109,993,998,2046,2208,2208,2306,962,962,2306,1814,3205,3205,2661,3439,2092,1558,1206,2339,3527,1445,1852,1708,1708,1261,2012,938,1777,1252,1267,930,932,932,928,1075,1035,1089,882,1145,968,1181,1084,741,1406,594,1683,1213,960,1260,986,988,986,958,1204,1220,781,2548,831,926,1144,1261,1162,1438,1256,1325,1322,1242,1150,1352,993,975,942,778,999,999,864,1001,1107,980,980,1006,1235,1176,1172,1014,1264,1264,1225,757,875,933,1836,1220,3972,1023,897,3107,920,2091,2091,1059,864,1838,934,1166,1604,1116,1083,884,1225,1225,1154,1070,1119,1119,572,996,1045,1402,2168,1395,1395,1435,824,497,630,869,656,629,1074,946,6459,2805,1213,2801,2801,1644,2904,2278,1248,1438,1096,1096,1630,1055,976,1182,1370,2072,1068,1424,1284,1031,1804,997,1044,1007,1100,1100,1100,1100,1053,1164,522,672,604,641,928,928,604,680,928,653,646,648,1051,1051,687,475,1008,687,1008,687,1054,475,1100,1054,687,475,709,709,969,969,709,617,617,617,617,531,562,558,463,842,1145,782,1256,954,2410,1846,1846,990,1017,796,796,1521,1485,2208,2255,1842,1841,1915,1350,1214,2050,1012,2384,1020,1201,2336,1153,1153,2254,4928,1642,1642,1061,1254,2793,2438,1113,974,885,2155,1707,3224,1078,1936,905,902,1548,874,682,682,459,682,1009,1009,757,414,414,810,810,1140,1140,810,1140,810,1167,810,1167,1140,1167,1167,1940,691,691,940,940,475,940,940,940,1626,925,882,1900,1967,819,819,1062,1102,853,2687,745,645,578,558,630,1705,2161,2484,880,1252,1252,1504,1504,1993,1262,813,2687,3034,1176,1466,1564,1508,1396,1772,1491,2619,1173,1849,1626,1897,1191,2482,2359,3046,3642,2038,2038,2185,1088,1785,3894,1045,3012,2860,2596,2357,4277,2218,2686,2077,2135,1368,1662,3409,3177,3714,3967,3646,4548,1512,3540,4167,2641,5767,4550,3264,1619,4176,3869,3940,1555,2584,3250,2156,1617,1626,2226,3273,1941,1941,2215,2850,4831,6133,4177,5298,1511,2740,4623,3123,4581,4581,3307,3986,1148,3754,2195,1424,1412,4145,4468,3602,3857,1926,5309,4743,4712,4815,4234,3154,3154,4702,3113,3196,4417,3513,1999,1427,2421,2158,916,4214,2462,2562,1335,1424,2505,2367,3205,1391,1218,1374,2638,1889,2712,2579,1171,5244,3118,4615,2097,2892,2383,1756,3422,4242,4242,3417,6670,1329,3673,3150,1972,1851,2316,4355,4680,4024,1273,2007,2680,2706,2548,1990,2751,3677,4504,4005,2182,1758,4828,6458,4514,1735,2071,2733,2807,5011,3206,2987,2337,4792,1780,1780,3865,3319,2151,2442,2046,3987,3721,1833,1833,3537,2256,1832,4258,4084,3005,1676,2748,3478,5070,3609,3131,3714,3353,1712,2431,1837,2534,2534,2706,5243,2743,2570,3339,5625,6423,3447,2799,960,960,1327,1236,1129,1220,1220,1374,1219,2209,816,1287,1002,758,1116,1116,759,1418,1418,1147,762,1247,1024,1138,1271,989,853,1513,1492,1221,1808,1489,1442,1560,2045,1450,1223,1253,3036,4436,3401,3287,1160,1411,1203,1375,1203,1402,1411,1366,1494,1278,1203,1366,1375,1494,1411,1521,1494,1866,1702,1702,1698,1698,1698,1698,1698,1698,1702,1702,1702,1846,1912,2037,1684,1077,1077,1077,2171,3050,2866,3717,2607,3217,1106,1035,1240,2575,2660,6133,1793,3865,2881,1691,1691,2159,5521,3079,2818,2538,3086,1843,1931,1251,1893,2249,1730,3248,5062,1911,3296,4553,4553,1815,4232,2007,2371,4018,4018,1696,4799,5488,5488,5032,2472,1873,1873,2310,2253,3123,3113,1829,5154,2641,4265,4373,2433,2301,4312,2523,1502,5573,2992,2992,2239,2239,1597,1557,1260,2403,2403,3279,2321,2321,1652,3369,1523,1715,524,1509,1122,1746,2262,1939,1824,3163,1928,2346,3648,4503,2957,3264,3169,3144,4373,3777,2431,2431,1171,1615,1385,1586,1080,999,1090,1081,1415,1615,1592,1655,1150,1580,1312,1312,1277,1277,1312,912,912,1312,1411,1312,1411,5531,3955,994,1650,1284,1442,994,1650,1480,1480,1284,994,1650,994,1284,1480,1650,1617,1617,1159,2126,1796,1715,2100,2126,1796,1715,2100,2126,1796,1715,2100,2126,1796,1715,1681,2396,1832,1795,1742,2468,1795,1713,1742,1832,1795,1713,1681,2468,1832,1795,1713,1757,3104,1983,1983,1983,1983,3372,1862,4076,2758,2758,3370,2163,2758,2758,2819,2219,2798,1635,1714,1859,1714,1694,1859,1694,1694,1694,1694,1859,1859,1682,2191,1682,2099,2191,2626,2827,2410,2416,2416,2410,2542,2542,2425,2865,2760,2542,2865,2542,2584,2829,3215,2152,2513,1667,1667,2648,2918,2719,2719,2838,1320,1320,3579,3215,2982,1556,1320,1320,1320,1320,1556,1258,1310,1310,1252,1282,787,787,1258,1258,1262,1262,994,994,1258,885,885,1258,1262,1310,1262,994,994,1559,1321,1321,1559,1321,1321,1321,1321,1321,1559,1559,1247,1321,1559,1321,1321,1321,1321,1321,1658,1912,2130,2110,2110,1926,1926,1926,1659,1926,1926,1659,1594,1900,2221,3320,3042,3351,3262,3350,3040,3320,3320,3015,3015,3350,3040,3040,3320,3320,3320,3040,3040,3015,3015,3163,3163,3350,3350,2173,2221,2221,3078,3320,3320,3040,3040,3350,3350,2392,2755,2392,3350,2219,2219,2440,2440,2116,2116,2429,2429,1872,1872,2149,2149,2429,2429,2091,2091,2442,2442,2116,2116,1872,1872,2138,2138,2393,2393,2429,2429,2149,2149,2442,2442,1872,1872,1872,1872,2440,2440,1894,1894,2116,2116,2080,2092,1794,2092,1835,2092,2092,2092,2092,1794,2092,2092,1842,1842,2092,2092,2080,2080,1835,1835,1794,1794,2077,2077,1794,1794,2092,2092,2077,2077,1835,1835,2080,2080,2092,2092,2599,1844,2311,2651,2651,2496,2903,2903,2092,2092,2729,2729,3198,3198,2346,2477,2905,2729,2651,2477,3198,2755,2903,2903,2671,3320,3170,3015,3320,3163,3040,2651,2311,2651,2960,2378,2126,2311,2651,2651,2755,2311,2092,1901,2058,2310,2040,2058,2310,2021,2040,2040,2310,2310,1901,2058,2310,2310,2310,2310,1991,2310,2040,2310,2021,2021,2040,2040,2310,2310,2058,2058,1900,1900,2021,2021,969,969,943,943,654,943,969,654,943,969,654,969,654,654,969,654,943,969,654,969,654,943,654,969,654,943,943,943,943,969,654,654,969,969,943,969,855,945,870,1200,1200,855,1200,1200,855,1200,945,1200,1200,945,2070,1200,855,945,945,870,855,1200,870,945,1200,945,1200,855,1200,1200,1200,870,945,855,945,2070,945,870,1200,1200,712,870,870,870,712,712,712,712,1200,1200,1200,712,712,1200,870,870,870,870,1200,712,870,870,870,712,712,1200,1200,855,855,855,1200,1200,1200,1200,855,712,870,1200,1200,1200,1200,1200,1200,1650,1888,1888,1650,1650,1888,855,1200,1550,1200,855,855,855,855,855,1200,1200,1200,945,945,855,855,1200,1200,855,1200,1200,1200,870,1710,1200,1550,870,855,1550,1200,1200,870,855,1200,1710,945,945,945,1200,1200,945,1380,855,1550,1200,855,1200,1200,1200,945,1200,945,945,855,1200,1200,945,855,855,1200,1200,945,945,1200,945,855,1200,1550,1200,945,855,1550,1710,1200,855,1200,1380,855,945,1200,1200,1200,945,945,1200,945,945,945,855,945,1200,1200,2145,1200,1470,945,945,855,945,945,945,855,1380,1550,1200,945,1200,1200,855,1200,855,1200,945,945,1200,2145,945,1380,1200,1200,945,1200,1200,1200,945,1200,855,855,855,1200,1200,855,1200,945,945,1470,1200,1200,1200,855,945,945,1200,1200,1200,1200,945,1470,1200,1200,945,945,1200,1200,1200,1380,1200,2400,1200,855,1200,1200,855,855,1200,1200,855,1550,1550,945,945,1200,945,870,1200,1200,1200,1200,855,1200,855,1200,855,945,870,1200,945,855,1200,1200,855,1200,945,1200,1200,1200,1200,945,945,1200,1200,945,1200,1200,870,870,945,870,870,1200,855,1200,1200,945,945,945,1200,945,1380,855,1550,855,1550,1200,945,855,945,945,1200,1200,1200,1200,1200,945,855,855,855,945,855,1200,1200,1380,1200,945,1380,1200,1200,1200,945,945,1200,945,1200,1200,1200,855,855,945,1710,1200,1200,1200,945,1200,945,1200,945,945,945,855,855,1550,945,945,1200,1380,1200,945,1200,855,2048,1795,2140,2614,2020,3931,1539,2214,2651,1820,1820,2253,2422,3525,1874,1351,701,701,701,701,701,701,948,948,948,948,701,701,701,701,701,701,948,948,948,948,948,1019,1019,1019,701,948,701,701,1019,1019,701,1019,1019,1019,1019,1019,1019,701,1019,1019,1019,701,1019,1019,1019,1019,1019,701,701,1450,1796,1450,1185,1436,1752,1796,1752,1968,1968,1796,1796,1796,1450,1450,1450,1080,1178,1080,1080,1080,1080,1428,1428,1194,1194,1428,1428,1194,1194,1428,1373,1194,1194,1428,1194,1194,1428,1428,1428,1194,1194,1428,1428,1428,1428,1194,1428,1194,1194,1428,1194,1428,1142,1142,1142,1142,1142,1142,1142,1143,1143,1142,1142,1142,1143,2220,1608,1907,2220,2322,2322,1907,1608,2067,2405,1608,1548,2025,1907,2405,1907,1907,2405,2025,2314,1470,1423,1458,1458,1599,1531,1670,1591,2484,1719,1589,1690,2116,1608,1482,2104,2188,1712,1758,1765,1810,2197,2197,1920,1645,1913,1004,806,1072,1633,1530,2196,2196,1964,1119,1039,1572,1316,1935,1200,728,1964,996,917,1487,1300,1656,1656,1740,1813,1367,1507,830,830,999,1129,1690,1205,1211,1205,1211,1092,1103,1092,868,879,1303,1609,864,972,1096,1462,1755,746,1334,1813,1813,1813,2688,2157,2157,2157,3346,3106,1118,1118,1261,1198,1178,1137,1137,1414,1222,1179,1179,1128,1177,1153,1148,1176,1176,1119,1435,2044,2044,2107,1706,1616,1706,1706,1300,1706,1616,864,1040,1040,1040,864,672,672,864,864,1032,1053,1032,2079,1684,1921,1468,2756,2756,1303,1247,842,1303,1247,1303,1303,1942,1643,1136,1942,1942,2357,1413,2695,2695,1191,1191,2119,1218,1218,2141,697,697,634,634,634,537,634,1121,634,634,957,957,1006,537,634,1247,1142,1142,1142,1147,1142,1142,1732,1148,1142,1142,1142,1142,1142,1255,1227,1227,1128,1620,1620,1621,1607,1607,1620,1260,1105,1057,1702,907,900,900,903,975,976,976,940,1187,876,1074,1156,1715,1489,1619,1743,1730,2210,1972,1324,1641,2110,2238,2238,1214,1214,1747,1747,2481,2481,1226,2069,1497,1226,1429,1505,1565,1226,1533,1226,1209,908,1094,1149,854,1120,815,811,1348,1661,1444,900,900,1187,1123,1123,905,903,903,1054,1243,903,1248,1567,1435,1502,1352,1552,1583,1009,962,953,914,1159,1133,1133,1358,1266,1264,1262,1074,1145,2345,2109,2037,1390,1826,1063,1063,1120,1048,1048,1063,1063,868,872,1291,1468,1436,1436,1436,1468,1468,1436,1436,1436,1436,1468,1472,1184,1184,1472,1472,1440,1472,1468,1436,1436,1436,1436,1468,1459,1841,1841,1841,833,1306,987,1024,1043,1023,1056,1056,1307,1023,1482,1506,1537,1721,983,819,847,847,1366,692,1375,1049,1315,1298,1708,1153,2743,1908,1104,1116,1145,1444,1120,854,1173,1173,1271,1075,1331,1036,1523,1192,1559,1442,1205,1431,1299,1315,1357,1204,1136,1645,1645,1204,1048,899,995,995,1094,1089,872,1060,960,1362,874,874,1002,993,899,3313,1019,999,1027,1006,1357,1019,1019,1006,1647,1089,1007,1315,810,810,861,810,944,810,861,861,810,944,944,944,944,861,861,944,810,810,972,972,972,972,972,972,614,614,719,1129,788,1129,1082,1082,788,1064,1416,1184,855,835,855,1045,1203,1045,1045,835,1045,1045,1045,1045,1045,836,836,1264,1010,1010,1010,1010,1263,1343,953,1074,1074,1352,1397,1124,1124,1355,1074,1397,1074,1352,1358,898,878,1142,1142,813,1058,1058,815,1060,958,958,1612,1984,806,806,820,1002,961,806,963,953,1065,1618,1618,1618,1618,823,1277,961,895,1395,1476,1109,1342,1322,1525,1029,1662,1277,1682,1334,1212,1212,1834,1834,1742,1742,1092,1452,1452,2030,1232,1740,1591,1983,1254,1407,1432,1420,1273,2209,1299,1700,1073,1263,1263,1297,1263,1115,1247,1073,1332,1166,1520,1836,1769,1836,1836,1963,1330,1421,1664,1664,1196,2028,1687,2186,1049,1650,1261,1436,1920,1920,2107,2021,2238,1439,3242,2776,1889,1987,2210,1082,1082,1211,1211,1082,1293,1453,1453,1075,1293,1293,1444,1293,1222,1320,1444,821,1211,1444,1444,1211,1211,1453,821,821,833,833,1630,745,833,1673,1673,1801,1470,1673,1673,1801,1531,1470,1666,1666,1666,1266,1266,1362,1266,1667,1666,1362,1362,1362,1666,1667,2754,2511,2754,1238,836,1030,1030,836,836,1299,1238,1299,836,1238,836,836,836,1623,1723,1769,1640,1769,1640,1769,1666,1266,1362,1666,1667,1666,1362,1131,1131,1131,1102,1131,1102,1102,870,1131,1102,1102,1012,1178,1178,1217,1012,1012,1178,1217,1012,1178,1217,1855,1855,1508,1508,1999,1508,2200,2200,1102,1102,1102,1102,1073,1102,1102,1131,870,870,1102,1102,870,870,870,1102,1102,1073,870,1073,870,1073,1131,870,1120,1059,1059,596,796,796,602,1234,596,1059,596,1180,1133,1066,1122,1134,1122,1122,1066,1125,1048,1078,1069,954,1312,1048,1125,1397,1312,1397,1320,1320,1320,1320,1063,1320,1260,1063,1200,1200,1200,1200,1320,973,973,973,1138,1138,973,1138,1138,1138,1138,1138,1138,1138,1138,1138,1138,1138,721,1138,1138,973,973,973,973,1160,973,973,721,721,721,721,721,721,1138,721,1138,1138,721,1138,1138,721,1138,1138,1138,1138,1138,1138,721,721,721,721,1138,1138,1138,973,721,1138,721,973,1138,721,973,1138,721,721,1138,721,721,1138,721,973,973,721,973,1138,1138,1138,1138,1138,1713,1713,1890,1584,1649,573,732,732,553,732,553,553,732,732,732,553,732,732,732,553,732,906,732,732,966,906,732,906,732,836,836,836,732,732,732,1582,1809,1890,1572,1582,1582,839,860,793,860,1807,1807,2946,1658,2083,928,703,703,948,889,703,889,590,792,1777,2656,1692,2316,1853,1803,2295,1501,2195,2732,2798,2672,1497,1234,1350,1325,1202,1033,1033,2749,2295,1033,1205,1037,1357,2995,1452,1452,1425,1663,1663,1697,1302,2317,2317,2023,2023,1453,1470,2023,1961,1961,1480,1480,2123,2123,1008,1200,1157,1157,1169,1157,1157,1043,1040,1294,1274,797,856,797,880,880,880,880,797,1128,1128,1128,874,1534,1534,1665,1534,888,1000,1000,805,797,1113,1113,1312,1312,1142,1137,1103,1285,775,775,770,770,717,835,835,1423,1363,1363,1600,1354,1642,1366,1368,1155,1358,1369,1155,1636,1070,1367,1727,1440,1070,1070,1480,1119,1119,1377,1190,1102,1310,1115,1119,1279,1115,1366,892,1650,1088,1115,1115,1419,1115,1115,1103,1149,1043,1043,1579,1088,895,868,1536,892,1247,892,892,892,1088,1958,1212,1428,892,1261,892,1088,1316,1058,1058,892,1365,1115,1115,895,1275,849,844,1118,1488,1113,1367,1261,1118,1334,876,892,892,1416,1092,843,1154,1167,843,1154,1165,1215,1167,1154,1165,1154,1117,1215,1458,920,920,1387,1088,1218,1487,1296,1256,1256,892,892,1297,883,1337,2968,885,1716,883,883,922,1174,1289,3394,1716,2593,1118,3647,3596,2557,2990,2990,2244,2026,2026,987,1079,1082,712,4027,983,3746,1233,1313,2511,2511,1199,1299,3634,1343,1309,1811,2587,2587,1975,1562,3464,4349,1728,1728,4040,1047,1222,4362,1142,1224,1224,1031,1452,1215,4184,4024,1721,3535,1527,1527,2084,1427,2370,1611,1552,1674,3344,2731,2731,1329,2750,907,2058,2058,954,1180,926,1026,2336,930,1212,763,1687,930,930,1400,798,1534,1228,1227,1333,859,859,1431,1225,1193,956,1092,1867,2939,1082,1041,856,897,1044,1227,1529,950,950,1223,1082,950,1391,860,859,1001,1082,986,1047,1047,1082,1146,1144,1483,1287,849,1290,1466,1329,1058,842,1550,1281,1251,1704,1423,1320,1326,1963,1402,1402,1345,1904,1412,1776,1264,1264,2690,1362,1025,1720,1642,2400,1066,1644,1510,1585,1320,1134,1134,752,917,917,752,801,1175,1175,1175,917,917,752,752,1175,1175,1175,917,917,1309,700,700,945,1726,1428,1428,1509,1428,1428,1509,884,884,890,890,890,913,890,1029,784,1029,1029,1029,1061,784,1029,1061,784,784,1029,784,1029,1035,1029,1029,784,1029,1029,784,1061,2550,2090,1574,2704,1980,1980,1887,2801,1458,2192,1286,1396,1861,1861,1286,2105,2358,2105,2426,2123,2181,1760,1800,2935,1760,1760,2530,2530,1814,2212,2212,1861,2212,2114,1814,1286,1386,1286,2212,2114,1861,1825,1019,1720,1720,1825,1825,1895,1622,1720,1720,1895,1200,1200,1000,1200,1500,1012,1320,832,1568,1200,1000,1300,1200,1200,1500,1300,1200,1500,1500,1500,1500,1200,1320,1149,1500,1500,1100,1200,1200,1100,1100,1149,1149,1149,811,1173,1149,1270,1535,1535,1173,1535,1149,1149,1200,811,1173,1173,1300,1300,1300,1500,1300,1100,1200,1100,1100,800,1300,1173,1173,1100,1100,1173,1173,1270,967,1468,1422,1675,1674,1674,1412,1401,1830,1866,1274,1675,1738,1683,1852,1932,1944,1894,1675,1974,1836,1956,1718,1918,2142,2140,2140,2394,2436,2023,2023,1961,1961,1685,2023,1141,1480,1480,2023,1480,2389,3221,2023,1961,2023,2123,1480,1961,1961,2031,2036,2492,2380,2380,2264,1453,1453,2023,2023,2940,2575,2296,714,714,914,914,914,914,728,728,924,924,891,891,1247,728,714,888,888,888,728,914,914,1247,728,728,728,914,914,914,808,1050,1050,1050,1050,740,1050,735,1050,740,754,1050,1050,2389,2242,1374,1536,1536,1818,1707,1410,1716,2383,2383,2347,1536,1388,1374,1535,1531,1294,1410,2333,1694,2314,1448,2174,2312,1756,1972,1923,1908,1972,1758,1972,1908,1753,2204,1907,2085,1809,2204,2175,1764,1764,1681,2175,1776,2204,1660,1820,2477,2203,2267,2203,1820,1979,1979,2496,782,782,1217,782,1133,1133,1133,1238,1133,958,958,1238,1238,1217,958,1133,1556,1556,2100,1471,1655,2066,1655,1471,1908,1300,1300,1547,1547,1337,1904,2210,1868,1936,1972,1547,1265,2225,980,1247,1004,701,1004,1004,1223,1004,1004,1004,980,1994,1503,1503,2763,1506,1214,1517,1517,2113,2012,2226,2226,1966,1744,2248,1744,1262,2521,1547,1771,1780,1262,1908,1832,1972,1300,1368,1449,1449,1449,1449,1449,1449,1506,1534,2335,1489,1642,1170,1264,1500,1500,1489,1320,1298,1320,1284,1299,1298,1364,1299,1299,1299,1364,1299,1364,1299,1320,1364,1284,1364,1299,1284,1364,1284,1298,2357,2769,2489,2354,2357,2769,2489,2023,2769,2512,2354,2769,2356,2357,2231,1612,1612,1612,1631,1612,1572,1100,1408,1100,1536,1408,1584,1584,1584,1408,1408,1408,1100,1584,1100,1584,837,837,860,860,860,946,900,900,900,900,860,837,837,837,837,860,860,946,1408,1408,1408,1584,1584,1584,1584,1584,1408,1408,1408,1408,1584,1408,1408,1584,1408,1100,1100,1408,1408,1584,1584,1120,1584,1584,1440,1440,1632,1440,1584,1440,1584,1440,1440,1584,1584,1440,1584,1632,1584,760,760,886,886,886,993,1003,1150,1150,1003,1003,1150,1003,1750,2181,2407,2206,2815,2330,2248,2330,4111,2190,2206,2815,2206,2312,2815,2205,3241,1224,1261,2705,1264,1233,1193,1193,2201,2201,2756,1469,1532,1227,2264,1940,2703,2925,2201,1918,1931,1931,2201,1816,2111,2111,2906,2186,2844,2844,1666,1192,2066,2020,1562,1931,1931,1546,1541,1863,1931,2247,1988,1817,2198,1770,2201,2201,2224,2066,2216,2224,2288,2288,2284,2006,2006,2224,2201,2204,2204,2201,1918,1918,2204,2204,2201,1240,2709,2792,1379,1627,1627,1546,1546,1921,2125,2125,1609,1614,1753,1913,2224,2201,2201,2201,1918,2201,2201,2201,2764,2201,2201,1778,2201,1912,2027,3376,1227,2269,1227,1753,2647,2146,1932,2064,2310,2186,4189,3094,1316,1164,2719,1225,1316,1227,1234,2292,1442,1068,1449,1449,1442,1068,1449,1068,1068,959,763,967,769,763,763,763,959,769,959,763,952,960,960,975,952,952,967,952,952,952,952,952,967,967,952,952,952,952,769,763,763,952,763,952,952,763,952,1446,1446,1060,1446,1060,1060,3031,2871,2174,1852,2484,2125,2373,2721,1303,1303,1303,2771,2436,2755,2932,2738,3149,2598,2228,1297,1173,1360,1360,1360,1677,1316,1316,1326,1173,1562,1595,1595,1499,1845,1845,2421,2482,1502,2548,2548,1880,2072,2072,2362,2362,2953,1847,1847,1693,1877,2208,2208,2077,1944,2420,1724,1724,2659,2461,2506,2265,1584,1856,1024,1024,1224,1584,1024,1024,1024,1024,1024,1444,1444,1024,1224,1024,1444,3126,2834,1958,2894,2577,2326,2414,2557,2859,1539,3074,2719,2719,2112,3367,1981,2744,2369,2538,2010,1998,1660,1593,1593,1593,2018,1626,1626,1626,1626,2026,1626,2289,1976,1745,2672,2672,3176,2093,2410,2476,3010,1923,2618,2255,2250,1283,1450,1283,1280,1280,1438,1280,1280,1280,1438,1280,1847,1379,1960,1450,1450,1283,1283,1283,1283,1283,1553,1553,1930,1439,2001,1923,2795,1962,2122,2473,2102,2819,2311,2819,2473,2473,1933,1933,2700,2684,1933,1933,2795,2345,2795,2345,2345,2930,2289,2289,2289,2289,2783,2351,2930,2406,2391,2406,2569,2585,2585,3199,3199,2684,2406,2406,2899,3179,3179,2345,2345,3180,1061,1331,1722,1727,1722,1722,1064,1064,1727,1331,1064,2330,1828,2512,2512,2291,2291,2512,1665,2383,2821,2388,1828,2740,2291,2740,1828,1828,2512,2512,2512,1828,2393,1775,2064,2067,2166,1521,1481,1481,1521,2597,2166,1617,2306,1851,1851,1903,1788,1824,1788,1824,1864,1864,1931,2509,2509,1020,1509,1509,1020,1682,1682,904,692,904,904,904,904,904,904,692,904,904,904,904,692,692,692,692,692,692,692,692,904,1052,1403,1186,1186,1052,1403,1256,1334,1981,1264,2223,2090,2098,2098,1631,1631,2024,2368,2769,2274,2203,1878,2202,1925,1000,1731,1494,1607,1109,1000,1731,1000,1551,1109,1607,1537,1109,1551,1537,1768,532,1537,1607,1109,1537,1537,1607,532,1560,1109,1560,532,1537,1768,1551,532,1768,1109,1551,1768,1551,1551,1551,1560,1109,1109,1551,1768,1999,1551,1560,1551,2841,1990,2841,1990,2841,1990,2841,2231,1568,1568,2841,2558,2558,3103,2231,2231,1741,1529,1433,1528,1378,1429,1378,1378,1433,1324,1529,1529,1324,1324,1538,1123,2041,1171,1429,1385,2207,1528,1529,1265,1486,1458,1486,1160,1486,1450,1450,1450,1107,1849,1882,2037,3171,2866,2422,2348,2985,1548,1550,1591,1436,1796,1548,1590,1830,1172,1172,1804,1040,1744,1810,1778,1778,1828,1031,2090,2090,1036,1804,1036,2311,1483,1516,1040,1040,1040,1027,1494,1170,1170,1170,1494,1170,1170,1170,1170,1170,1170,1170,1494,1170,1170,906,906,1104,1108,1170,1170,927,1108,927,673,906,2202,1516,1516,1956,2772,2141,1600,1471,1988,2100,2554,2554,1492,2374,2230,2360,2190,1871,902,2070,2070,2325,2058,2119,2073,2073,1666,1874,1874,1516,2178,1702,2262,1185,1182,1185,1185,1179,1148,1171,1290,1160,1161,1163,1446,1208,1182,1182,1182,1184,2160,1174,1174,1174,1174,1174,1105,1322,1174,1174,1411,1411,1322,1175,1298,1297,1237,1237,1157,1112,1131,1341,1188,1188,1381,1247,1175,1175,1533,1215,1175,1631,1175,1463,1175,1175,1175,1216,831,599,831,599,831,599,831,599,831,831,599,831,831,831,831,831,599,599,831,2396,2224,2382,1935,1419,1419,2025,1744,2382,2246,2229,2229,1596,2166,2320,1925,1296,1013,676,676,1296,1296,736,648,901,1013,676,676,1290,1290,1290,1290,1290,871,1015,1013,983,648,648,680,1892,1033,1710,1925,1402,1019,1925,1925,2180,4930,4411,2877,3476,3287,3287,2929,3061,4313,3315,3315,1372,2286,1372,2063,1890,1343,1343,1343,1770,2562,2426,2255,2426,1676,3072,3730,3615,3726,1761,1710,1321,1761,1710,1761,1892,1892,1710,1761,1629,1617,1458,1297,1119,1119,1119,1119,1119,1119,1119,1119,1119,1297,1297,1119,812,1119,1019,1671,1671,1321,1710,1762,1849,1710,1892,1710,1558,1710,1710,1321,1715,1321,1321,1285,1710,1617,1710,975,975,1657,1154,1154,1520,2063,2063,822,1180,1225,822,1441,1524,1646,1205,1406,943,1567,1635,1544,1317,1883,1052,1544,1317,1317,1644,1402,884,925,1441,1441,1567,1172,1644,1402,1635,1402,1445,1172,1172,1567,1567,1172,1560,1172,1445,1118,2159,1721,2159,1625,1625,1973,1973,2159,1890,2159,1085,1140,1085,1085,1389,1389,914,914,914,1259,1259,914,914,1389,1259,1389,1389,1389,1438,804,804,1024,926,1146,804,804,1024,1024,804,706,903,903,803,706,897,706,618,618,706,618,897,867,867,903,903,1050,1050,1050,1050,1050,1050,1315,720,1050,1050,1050,1050,1050,1115,1115,1050,1050,1050,1050,868,1746,1746,1381,1238,1238,1238,1311,1238,1238,1311,974,993,974,678,787,787,678,678,1034,678,993,974,812,669,683,974,672,1036,1105,1105,815,815,815,815,1105,1240,972,975,975,1246,1245,1028,1070,1070,1036,1036,1028,1028,1036,1028,1070,1028,1070,1070,1345,1924,1632,1345,1632,1632,1632,1632,1345,1601,1345,1632,1310,1310,1310,1310,1909,1909,1345,1960,1909,1441,1441,1441,1441,1231,1231,1441,1747,1766,1886,2374,1746,2350,1766,1886,1886,2746,2855,3162,2381,2074,2349,2349,2349,2365,2056,2305,1987,1471,1453,1767,1821,1899,1984,1767,1767,1348,1504,1576,1529,1205,1205,2331,2719,2583,2269,2588,2173,2688,2594,2688,2688,2703,2365,2307,2376,2307,2307,1911,1926,1985,2365,2205,1985,3803,4462,1796,1984,3926,3646,2352,1658,1495,1714,1495,1713,1714,1714,1718,1603,1718,1603,1718,1638,1969,1873,1467,1202,1502,1633,1965,2013,955,955,1219,955,1219,1219,1041,1219,955,955,955,955,1219,1041],"yaxis":"y","type":"scattergl"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Built Before 1980 (1: Yes, 0: No)"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Square footage that is liveable"}},"legend":{"tracegroupgap":0},"title":{"text":"Square footage that is liveable v. before1980"}},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="deb7ec8c-0bb1-47f3-932b-b74a1aebae1e" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("deb7ec8c-0bb1-47f3-932b-b74a1aebae1e")) {                    Plotly.newPlot(                        "deb7ec8c-0bb1-47f3-932b-b74a1aebae1e",                        [{"hovertemplate":"before1980=%{x}\u003cbr\u003elivearea=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"","showlegend":false,"x":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,0,0,0,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,0,0,1,1,0,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,0,0,0,1,0,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,1,1,0,1,1,0,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,1,0,1,1,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,1,0,0,0,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,1,0,0,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,0,0,1,1,0,1,1,0,0,1,1,1,1,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,0,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,0,1,0,0,1,1,1,1,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,0,1,1,0,0,0,1,0,0,1,1,1,1,1,1,0,1,1,1,0,0,0,1,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,1,1,0,1,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,0,1,0,1,1,1,1,1,0,0,0,1,1,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,0,0,0,1,1,0,0,0,1,0,1,0,1,0,0,1,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,1,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,0,0,1,1,0,0,1,0,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,1,0,1,1,1,1,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,1,0,1,1,1,0,0,0,0,1,0,0,1,0,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,0,1,0,1,1,1,0,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,0,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,1,0,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,0,0,0,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"xaxis":"x","y":[1346,1249,1346,1146,1249,1249,1098,1346,1249,1346,1098,3902,2732,2927,2811,3106,2732,2564,1731,1508,1508,1508,1754,1754,1508,1243,1754,1754,1508,1508,1508,1731,1508,1508,1731,1731,1754,1754,1754,1509,1509,1509,1509,1509,1509,1509,2854,2855,3126,1834,3305,3305,3305,2927,1960,2042,1960,2042,2042,2079,1960,2042,1982,2588,2588,2855,1279,1574,2042,1743,1574,1574,2580,2079,1279,2079,1804,1432,1731,1420,1731,1743,1731,1456,1743,1470,1731,1743,1743,1420,1743,1743,1504,1463,1743,1432,1749,1749,1731,1731,1420,1420,1237,1237,1731,1731,1731,1731,947,947,1743,1743,1420,1420,1743,1743,1420,1420,1739,1739,1432,1432,1731,1731,1731,1731,1491,1731,1432,1743,1743,1420,1420,1743,1743,1743,1743,1743,1731,1731,1731,1731,1420,1420,1743,1743,1731,1731,1731,1731,1371,1432,1731,1504,1420,1731,1420,1743,1420,1432,1432,1743,1743,1456,1432,1743,1420,1731,1743,1432,1731,1420,1731,1432,1731,1432,1743,1420,1743,1743,1743,1743,1420,1731,1504,1504,1743,1731,1731,1743,1743,1731,1731,1731,1731,1731,1743,1743,1743,1743,1743,1731,1731,1731,1432,1731,1731,1743,1743,1420,1420,1731,1743,1743,1432,1432,1743,1420,1504,1743,1743,1420,1420,1743,1743,1743,1432,1432,1743,1743,1743,1492,1731,1731,1731,1420,1743,1731,1731,1432,1432,1420,1731,1731,1420,1432,1432,1420,1524,1524,1420,1731,1731,1731,1731,1432,1432,1432,1432,1743,1743,1731,1731,1420,1420,1731,1731,1432,1432,1731,1731,1731,1731,1420,1731,1731,1731,1731,1731,1731,1731,1731,1743,1743,1420,1420,1743,1743,1432,1432,1432,1432,1432,1731,1731,1731,1731,1237,1237,1731,1731,1731,1731,1731,1731,1743,1743,1420,1420,1420,1420,1420,1420,1743,1743,1420,1420,1463,1463,1492,1492,1420,1420,1731,1731,1743,1743,1420,1420,1267,1267,1503,1503,1420,1420,1731,1731,1743,1743,1432,1432,1731,1731,1731,1731,1731,1731,1420,1731,1731,1731,1731,1731,1731,1743,1743,1420,1420,1420,1420,1731,1731,1743,1743,1731,1731,1731,1731,1432,1432,1420,1420,1731,1731,1743,1743,1420,1420,1743,1743,1504,1504,1751,1751,1743,1743,947,947,1743,1743,1743,1743,1731,1731,1420,1420,1743,1743,1743,1743,1420,1420,1543,1543,1743,1731,1731,1743,1743,1743,1743,1743,1743,1743,1739,1743,947,1743,1743,1420,1743,1743,1173,2466,2001,2494,1173,2466,2016,1830,2466,1686,2466,2466,3668,3437,1905,1570,1905,1905,1905,3666,3666,3051,3687,3033,3872,3692,3449,2466,1887,1887,2466,1899,1899,1613,1601,1887,1570,1887,1173,1593,1899,2001,3656,3656,3428,3881,3539,1905,3883,3883,3697,3261,3688,4119,3037,2685,3001,3001,3883,3883,2699,3902,4129,2693,2693,3674,3355,3656,2139,2802,2139,2138,2599,2139,2599,2139,2802,2802,2139,2802,2599,2139,2531,2180,2630,2139,2138,2599,2599,2599,2139,2599,2599,2943,3176,3192,3192,3388,3769,2278,2278,3644,3644,2519,4009,2927,3428,3912,3554,3934,3769,3616,3540,3540,3934,3783,3708,2718,2732,3192,1924,2548,1960,1924,3192,3192,3176,1509,1509,1509,1853,1416,1508,1853,1853,1853,1508,1450,2115,2466,1581,1243,1243,1509,1731,1226,1152,1152,1271,1271,829,1265,1265,876,1342,1233,1180,1342,1614,1233,1180,1180,1233,1342,1180,1180,1342,1411,1766,1610,1411,1731,1394,1394,1526,1226,1226,1153,1277,1590,1302,1614,1342,876,876,1233,876,1342,1233,1180,1342,1342,1614,1148,1227,1227,868,868,1267,1257,1716,1401,1401,1401,1523,1610,1610,1540,1766,1779,1430,1274,1227,1152,1224,1152,1152,1152,1145,1145,1275,1279,1279,1146,1098,1098,1146,1098,1098,1146,1249,1098,1109,1243,1243,1509,1731,1509,1509,1731,1509,1836,1402,1494,1402,1494,1252,1506,1836,1426,1520,1450,1494,1853,1836,1836,1506,1506,1973,1494,2577,2566,1836,2835,2835,2169,2835,2835,2835,1396,2566,2001,2001,2016,2115,1887,2259,2115,2525,1803,1810,1992,2566,2191,1751,1524,1524,1524,1524,1751,1845,1677,1805,1874,1581,1600,1524,1489,1845,1845,1845,1803,1524,1803,3305,2927,1982,2079,2079,1960,1594,2015,2215,1594,1489,2487,2487,1834,3321,1858,1845,1524,1524,1524,1858,1524,1845,1845,1845,1858,1858,1516,1516,1858,1751,1858,1751,1803,1845,1858,1905,3883,2816,2001,2979,1570,3427,1905,1574,2079,1960,1574,2070,1960,1960,2070,1574,1960,1982,1574,1574,2070,2070,2079,1574,1960,2070,1960,2070,2041,1960,2079,1960,1279,1960,2042,1279,2202,2202,1812,2130,1808,1808,1808,1808,2525,1413,2513,1413,2387,2040,1818,1808,2513,1812,1733,2495,1287,2180,1287,1557,2374,2513,1413,2513,2374,2130,1725,2081,2130,2374,1557,1287,1733,2525,2525,1557,1557,2525,2525,1557,1557,2525,2525,1557,1557,2495,1557,2495,2495,2525,2525,1733,1733,2100,2100,2495,2524,2180,1733,1557,2180,2495,2180,2180,1733,1557,1733,1557,1330,1557,1557,2180,1349,1557,2525,1733,1733,1557,1557,1733,1733,2100,2100,1853,2180,1547,1733,1287,1557,2180,2495,1733,1733,2525,2525,1557,1557,1733,1733,1557,1557,2525,2525,2180,2180,2179,2179,1557,2180,2180,2180,1557,1557,2180,1557,1557,1733,1733,1547,1547,2180,1733,2525,1673,2070,1299,1893,1893,2076,1689,1579,1970,1579,1970,1970,1288,1579,2070,2076,1579,1893,1893,1304,1412,1558,1412,2081,1779,1779,1412,1779,1412,1412,2081,1412,1412,2081,2081,1164,960,1248,1248,1248,1056,1056,1164,1248,1164,1164,1164,1164,1386,912,912,1248,1204,1445,960,960,912,1204,960,1164,1056,1056,1386,960,1248,1248,1164,1248,1454,960,960,960,1164,1164,1164,1386,1386,1056,1056,1248,1248,1386,1445,1248,1164,1400,1056,1248,1249,1248,960,925,1121,1026,925,925,925,1121,1148,931,1144,1121,1144,1148,1148,1148,925,1148,931,1121,925,1026,1048,1144,931,1144,1144,1144,1048,1048,1048,1148,1148,1144,1026,1121,1121,931,931,1148,857,857,968,857,2244,857,857,1840,1205,968,1404,1404,968,1840,1840,968,857,857,857,857,1404,1840,968,857,1147,1134,857,857,1404,1044,1060,1324,1044,1060,1444,1300,840,1039,1039,840,840,840,840,840,987,987,987,1549,987,1183,1183,840,840,987,840,987,987,840,840,840,1095,857,1205,857,1404,1404,857,1404,968,968,857,857,857,1404,1404,1641,1629,1524,1074,1074,1260,1553,1754,2035,1346,1856,1147,2227,1841,1855,1914,1914,1686,1056,1481,1754,1726,1876,2302,1666,1540,1540,2061,2061,1524,1633,1633,1826,1600,1600,1600,1409,1728,1714,1855,1386,1829,1936,1456,1936,1666,1456,1936,1060,1060,2647,1589,1439,1044,1947,1044,848,1364,1060,1060,1060,1060,1060,1044,1947,1060,1060,1044,848,848,848,1947,1044,1044,1060,1178,1178,1576,1395,1178,1226,1431,1524,845,1497,992,1524,1524,1524,1340,1180,1072,1072,1044,1060,1044,1126,1126,1963,1571,1571,1871,1226,1380,1380,1044,1044,1431,1431,863,1593,1388,1483,1545,1284,2286,1936,1524,1600,1545,1545,1687,1431,1732,1468,1431,1858,2430,1389,1389,1687,1665,1208,1665,1476,1665,1280,808,808,1656,1656,808,1202,1211,1703,808,808,921,921,1202,921,1703,1703,808,1605,1380,1605,1307,1308,1605,1605,1297,1297,1322,1621,1428,1584,1584,1212,1018,1621,1646,1801,1884,1884,1636,1950,1950,1950,1268,1676,1676,1540,1565,1855,1855,1394,842,1394,1394,1394,1394,1119,1394,1405,1159,1159,1159,842,1405,1203,2030,1496,842,1496,842,952,952,842,1496,1236,1496,1280,2061,1388,1388,1389,1545,1545,1280,1676,1524,1524,1600,1600,998,1694,1694,1804,1280,2322,1666,2321,1826,1826,921,921,1211,921,1703,1202,1703,1202,1703,808,1703,1703,1703,1202,921,808,808,1680,1680,1680,1285,1680,2134,2134,1500,1057,2134,1519,1519,1030,1397,1312,1312,1010,1010,1406,1344,1406,1312,1295,1406,1406,1037,1037,1904,2280,2280,1882,2280,1904,2280,1904,1778,1512,2280,1719,1719,1719,1036,1320,1602,1923,1923,1923,1923,1248,1719,1320,1320,1923,1602,1719,1923,1719,1656,1320,1248,1584,1320,970,1350,1248,1320,970,1520,1212,1409,1584,1211,1703,808,1202,921,1703,808,921,921,921,1703,1703,921,1211,1211,1300,1300,1300,1388,1300,1300,1534,1300,1360,1300,976,1085,1131,793,978,1214,721,1085,1085,1534,1300,1534,4129,1992,2365,1571,1804,2100,1888,1620,1751,1626,1995,1801,1987,1801,1855,1855,1855,1316,1723,1619,1453,1391,1649,1391,1723,1453,1313,1391,1649,1391,1313,2916,2519,2851,2818,3230,2360,1509,1754,1243,1731,1754,1754,1508,1508,1508,1508,1754,1508,1570,1570,1804,1731,1458,1714,1803,2001,2001,1432,1743,1743,1743,1731,1731,1902,1975,1388,2024,1823,1339,1339,2008,1636,1496,1490,1490,1490,1490,1486,1490,2024,1823,1823,1823,1211,1490,1615,1615,936,1650,1650,1650,1650,1444,1444,1615,1731,1463,1743,1615,1615,1444,1615,1224,1444,1615,1615,1650,1731,947,947,1444,1444,1224,947,947,1731,1731,1972,1496,2365,1804,1888,2027,1804,1888,1888,2833,2851,1972,2519,2674,1972,2851,2851,2938,2851,2938,2851,1972,1519,1413,1413,1626,1296,1413,1413,1626,1413,1413,1413,1413,1413,1296,1413,1413,3192,1626,1626,1296,1116,1413,1413,1519,1626,1626,1413,1626,1413,1296,2272,2272,1521,1521,1521,1406,1521,1521,1704,1704,1406,1521,1819,1406,1704,1704,1406,1406,1874,2270,1681,1681,1681,2293,2144,2033,1863,2331,1671,2293,2331,1863,2144,2144,2144,2144,1691,2144,1863,2332,2144,1691,2331,2293,2293,2331,2144,2047,2144,1858,1758,1758,1522,1522,1522,1522,1723,1522,1758,2109,1805,2170,2170,1784,2814,2170,1816,1127,1816,1349,1816,1465,1155,1832,1004,1004,1284,1284,1284,1284,1465,1832,1832,1832,1539,1539,1539,1521,1616,1539,2190,2190,1220,1220,894,1332,1332,1332,1088,1088,1328,1332,1328,1328,1332,800,1138,1088,1252,800,1540,1444,1558,1426,1012,1300,1300,1300,1300,1709,1709,1300,1300,1134,1300,1300,1300,1300,1626,1626,1626,1012,1012,1893,1709,796,1134,1134,1474,1012,1012,1893,1893,3769,3708,3769,3596,3596,3769,3616,3360,3783,3783,3360,3360,3616,2292,1140,1376,1915,1456,1887,1052,1281,1281,1281,1140,1334,2936,1776,3230,3228,1012,1012,1012,1134,796,1012,1012,1134,2818,3783,3230,2379,2379,1934,2503,2774,2774,1713,2683,2503,1934,2503,2154,1988,1988,1713,2774,2774,1934,3192,3192,2851,1646,1646,2293,2144,2293,2054,2144,1691,1691,2293,2144,2144,1863,1691,2144,2144,2047,2144,1874,2054,1516,2331,2144,2851,1625,1889,1889,1625,1625,2160,2647,1625,2184,1625,2347,2347,2347,1988,1889,1889,1889,1625,1625,1625,1988,1625,1646,1708,1294,1708,1614,2491,1281,1951,1629,1951,2303,1789,1629,1629,1026,800,1402,800,1150,1548,1548,1708,1646,1417,1417,1417,1417,1646,1646,1143,1708,1400,1143,1143,1400,1646,1400,1538,1708,1143,1400,1646,1400,1400,1708,1646,1708,1646,1646,1646,1417,1646,1294,1294,1708,1294,1417,1646,1143,1538,1646,1400,1417,1143,1143,1143,1400,1646,1646,1708,1646,1400,1708,1708,1646,1708,1646,1417,1143,1417,1708,1294,1646,1646,1646,1789,2430,1951,1281,1281,1951,1509,1509,1509,1509,1509,1509,1754,1509,1509,1731,1509,1546,1754,1243,1797,2024,1550,1485,1794,1794,1480,1087,1273,1138,1485,1138,1166,1194,801,1797,1755,1138,1138,1478,1302,1302,1341,1341,1238,1408,1790,1755,1290,1358,1370,1698,1698,1766,1766,1794,1755,1794,1790,840,840,979,979,840,840,1095,1173,840,840,840,1039,1039,864,987,1173,1173,840,840,840,840,1095,840,840,1039,840,1265,1039,987,840,987,840,840,1039,1161,1161,840,1039,987,1072,1419,1723,1723,2310,1069,1655,1833,1631,1012,1012,853,853,1012,1012,1707,1570,1041,1041,838,1464,1404,1008,1770,1072,2212,1072,1079,897,897,1723,1723,1072,2730,1780,1773,2017,1813,1771,1072,1072,1780,1780,915,2002,1072,2002,1500,1888,1826,1839,1349,1524,1072,1580,2082,1413,2082,1693,1419,2082,1700,1700,2296,2261,1700,1881,1881,1881,2309,1723,1723,1714,1981,1487,1056,1846,1002,1002,1210,863,1002,863,863,863,863,863,853,863,1002,1002,1002,1059,1059,1059,1059,866,1069,1002,1002,866,866,1064,1314,1002,1215,1215,1215,2016,863,853,1333,1608,1762,1345,1753,1345,2157,1674,2285,1333,1333,1674,1674,1761,1695,1700,1290,1632,1486,1632,1632,1133,1001,1133,1146,1124,1146,1042,870,870,1001,870,2040,2040,1331,1487,1542,1992,2085,1811,1811,2099,1725,1158,2034,1372,1372,1159,1644,1445,1080,1080,1644,1644,1080,1447,1240,1393,1240,1240,824,824,1393,1308,1308,1216,1216,2134,2134,2134,1451,1451,1451,1522,1256,1133,1522,1451,1456,1456,1451,1522,1456,1456,1451,1256,1133,1354,1456,1354,1354,1522,1133,1451,1451,1456,1456,1456,1402,1354,1354,1354,1522,1522,1522,1522,1402,1345,1398,1398,1345,1207,1398,1345,1345,1345,1345,1398,1272,2302,2165,1957,2302,2179,2000,2302,1554,1712,1554,1712,1273,1556,1712,1555,1370,1555,2287,2484,2301,2484,2180,2301,1319,1568,1305,1697,1288,1568,1325,1756,1313,1278,1421,1743,1518,1421,1743,1709,2799,2799,2799,2132,2132,1950,1950,2146,2146,2152,2152,2558,2558,2181,2181,2342,2342,2442,2442,2152,2152,2417,2417,2462,2462,2828,2828,2451,2451,1845,1845,2442,2442,2152,2152,2451,2451,2828,2828,1950,1950,1845,1845,1950,1950,2462,2462,2055,2055,1950,1950,2536,2536,2536,2536,2536,2529,2536,2536,2536,2536,2529,2529,2536,2536,2252,2529,2529,2536,2529,2536,2536,3566,2946,2946,3680,3680,3196,3196,2984,2984,3123,3123,1325,1325,1278,1278,1568,1568,1305,1305,1704,1704,1288,1288,1568,1568,1322,1322,1319,1319,1781,1781,3146,3146,3080,3080,3133,3133,2529,2529,2536,2536,2529,2529,2536,2536,2536,2536,2484,2484,2301,2301,2554,2554,2484,2484,2535,2535,2535,2535,2529,2529,2536,2536,2536,2536,2535,2535,2535,2535,2529,2529,2535,2535,3109,3109,2909,2909,3105,3105,3317,2839,2922,3317,2910,3103,3031,3031,2339,2339,3122,3228,3228,2610,2610,2169,2301,2301,2502,1326,1305,1832,1844,2557,2055,1845,2145,2181,2141,2132,1845,2417,2999,1670,2994,3190,2911,2165,2498,2165,1841,2498,2511,2168,2168,2436,2436,2498,2466,2165,2498,2144,2165,2165,2934,2934,2055,1942,1670,1942,3122,2922,2910,3103,3317,3103,3317,1957,2167,2282,1762,3031,1334,1746,3060,3192,3598,4134,1185,1997,2856,2978,2978,1509,2541,2412,1531,1586,1509,1341,1586,2660,1517,3563,2275,2124,2275,1438,1648,1438,3950,2124,3054,1514,1622,1449,1622,1674,1514,1327,1350,1570,1866,1760,1350,1795,2603,1185,1185,1357,1575,1530,4504,2968,3546,4051,4111,2784,1730,2233,3802,1564,1541,1167,2575,2386,885,2029,1167,2030,2571,2231,1167,1795,1631,2623,2262,2120,2567,2512,2231,1786,2196,1762,2784,1451,1795,3673,2304,2972,2208,2938,2608,2702,2049,2075,1645,1786,3288,2907,2919,3004,2834,2848,1185,1726,1545,1862,1784,919,1771,1178,2104,2104,1976,1976,2598,1059,1327,2868,3322,3110,2820,2502,2828,3008,807,1137,1137,807,1463,1463,1137,1137,1137,1463,1137,1137,3011,3266,2919,1531,1175,1383,1383,1496,1178,1178,1516,1516,1181,1181,1181,1181,1181,1181,1370,1370,2575,2657,2030,1516,1516,1181,1181,1370,1370,1370,1370,1181,1181,1496,1496,1496,1181,1181,1181,1181,1516,1516,1181,1181,1370,1370,1370,1370,1181,1181,1516,1516,1792,1451,1792,1122,1132,1120,1182,1132,2578,2413,2412,2945,1652,1451,1451,1784,2343,2343,2237,2146,2049,2608,2851,2439,802,802,948,1063,948,919,2040,1582,2932,2301,2287,2360,2484,2180,2180,2484,2301,2287,2287,2069,2069,2484,2287,2287,2172,2287,2301,2301,2005,2301,2180,2360,2360,1185,1518,1541,1764,1680,876,720,720,1489,2146,1438,1404,2333,2958,1824,3292,1438,1642,1647,1647,2531,2224,2531,2834,2224,2009,2244,791,817,1148,2541,2480,2164,2541,1788,648,901,903,801,1694,948,1904,1148,817,1148,817,781,781,791,1451,1459,1762,1451,1451,1676,1459,1762,1695,2200,2200,2165,2144,1841,1968,2058,2245,2343,2245,1903,1976,1933,1612,2176,2060,1839,1953,2197,1967,1341,1517,1356,1967,1462,1438,1438,1647,1647,1438,1438,2038,2012,2541,1786,1618,1618,1618,1623,1531,1509,1746,1760,1509,2541,2691,1639,1795,2197,1997,1618,2196,2009,2224,948,1441,2173,1412,1792,1724,1724,1428,1837,2660,1185,2512,2856,2009,1639,1795,2480,2702,2072,2080,1554,2029,2029,2395,1671,1712,1722,1639,1421,1743,1709,1743,1743,1518,1421,1502,2124,2124,1648,2197,1451,1438,1648,1746,1609,1438,1733,1350,1585,1567,1835,2165,1841,1768,1539,1539,2179,1670,2055,2557,1541,1812,1712,1571,1666,1437,1645,1500,1712,1712,1712,2165,2436,2436,2511,2436,2436,2436,2436,2436,2436,2436,2511,2436,2511,2436,2436,2484,2484,2202,2202,2301,2301,2554,2484,2360,2154,2287,2301,1784,1776,1185,2410,1792,1731,2403,2674,2674,2604,2604,2396,2396,2790,2790,2791,2791,2586,2586,2791,2791,2396,2396,2637,2637,2396,2396,2674,2674,2557,2642,2791,2791,2586,2586,2396,2396,2907,2642,2674,2674,2619,2736,2736,2791,2791,2880,2880,2551,2551,1664,1539,1660,1764,1660,990,1033,914,1280,2027,1860,1664,1860,2027,1979,1783,1589,1783,1979,1860,1664,1860,2146,1776,1185,1792,1451,2343,2343,3313,2436,2436,2529,2529,3317,2965,2536,2536,2536,2529,2221,2632,2945,2751,3318,2674,3123,2892,2892,2586,2586,2880,2473,2518,2403,2403,2674,2674,2396,2396,2820,2132,2055,2158,3103,3603,3317,2628,2642,2638,2286,2619,2634,3227,2580,2328,1712,1712,1452,1452,1452,1452,1671,1671,1671,1671,1513,1513,1513,1513,1452,1452,1712,1671,1452,1671,1712,1712,1671,1712,1712,1712,1671,1671,1452,1452,1712,1712,1712,1712,1712,1712,1712,1712,1712,1712,1712,1712,1671,1671,1452,1452,1513,1513,1444,1444,1712,1712,1712,1712,1712,1712,1712,1647,1452,1452,1513,1513,1712,1712,1452,1452,1712,1712,1712,1712,1712,1712,1671,1671,1671,1671,1712,1712,1712,1712,1494,1494,1555,1571,1712,1712,1571,1571,1712,1712,1712,1712,1671,1671,1452,1452,1712,1712,1516,1370,1181,1516,1516,1496,1496,1181,1181,1370,1370,1516,1516,1181,1181,1181,1181,1516,1516,2566,2701,2365,2365,2566,2566,2701,2566,2566,2365,2365,2566,2566,2670,2365,2514,2514,2365,2514,2365,2701,2701,2365,2566,2701,2701,2514,2514,2365,2287,2287,2301,2301,2554,2554,2484,2484,2428,2428,2287,2287,2053,2053,2053,2053,2484,2484,2287,2301,2484,3172,3199,2311,2946,3146,2757,2757,2757,2757,2302,2302,1884,1884,2179,2179,2000,2000,1884,1884,2179,2179,2302,2302,2428,2428,2301,2301,2180,2180,2428,2428,2301,2301,2180,2180,2287,2302,2302,1957,1957,2217,2217,2302,2302,2165,2165,2000,2000,2249,2249,2179,2179,2302,2302,1957,1957,2302,2302,2179,2000,2302,2297,2297,1884,1884,2217,2217,2302,2302,2179,2179,2249,2249,2179,2179,3146,3146,3146,3146,3260,3260,3565,3103,3144,3144,3210,3566,3566,3259,3123,2390,3103,3260,2000,2000,2302,2302,2217,2217,2302,2302,1957,1957,2040,2040,2302,2302,2179,2179,2621,3115,3115,3689,3710,3674,3381,2984,2984,3150,3150,3262,3262,2583,3221,3123,3121,3121,2946,2946,3669,3669,3566,3566,3103,3103,2302,2302,2217,2217,2000,2302,2302,2179,2179,2302,2302,3063,2426,3271,2673,2554,2301,2180,2428,2301,2484,2368,3271,3267,2179,2484,2554,2301,2053,2428,3184,3144,3103,3221,3655,2946,3244,3623,3244,2407,2946,3680,3623,3103,3623,2202,2301,2484,2301,2428,2180,1704,1704,1319,1319,1697,1697,1571,1571,1280,1280,1756,1756,1697,1697,1305,1305,2801,3154,3260,3054,2627,1743,1743,1502,1502,1421,1421,1577,1577,1503,1503,1743,1743,1421,1421,1758,1758,1970,1838,1650,1838,1970,1421,1421,1502,1502,1421,1421,1743,1743,1502,1502,1580,1580,1743,1743,1577,1421,1421,1743,1743,3095,2302,2000,2000,2302,2000,2302,2179,2302,1697,1697,1278,1278,1704,1704,1319,1319,1781,1781,1568,1568,1703,1703,1781,1781,2744,2566,2566,2365,2566,2566,3623,3146,3203,3680,3623,3680,2566,2566,2584,2566,2584,2566,2701,2566,2738,2738,2365,2566,2738,2584,2566,2584,2566,806,1456,1456,805,805,860,753,753,784,830,830,936,859,750,1216,1168,1168,1168,1259,1276,761,747,805,826,1422,1000,807,775,775,772,864,1295,1513,1513,1513,1513,1513,1513,1026,1023,969,1024,762,766,766,766,775,770,769,769,769,2610,1195,1195,1352,767,946,946,772,772,903,903,771,816,816,825,825,969,969,874,874,1152,1152,799,799,805,1108,1108,1430,1052,1110,936,1296,949,1069,1698,1698,1205,1205,915,1170,1140,986,986,532,532,820,840,814,835,998,1327,1369,1008,1008,1008,993,1240,1244,1066,1066,918,1120,995,995,995,965,1208,1208,1187,960,960,960,1004,871,1004,1004,1222,1028,1151,1259,1008,1008,860,831,843,1004,850,989,989,1575,1447,1267,726,1008,1293,836,836,1074,833,833,855,1260,868,1688,1266,1081,1120,1120,987,854,921,1172,1172,1172,930,930,1514,989,1131,1712,966,931,978,1146,919,1203,1203,1203,852,874,906,950,1409,1409,943,943,727,949,1092,1240,1046,1987,947,1047,1015,1141,1262,1080,1080,1442,3031,910,1529,1400,1400,1147,988,1238,768,2149,1762,1762,817,895,749,749,912,763,1027,1027,920,917,1215,1918,1054,1053,1040,1460,1460,1460,1085,763,763,746,1538,1538,777,896,896,819,896,816,1200,750,954,954,1000,741,741,735,737,1410,836,957,1527,1450,1450,2550,2550,1434,1434,1130,1130,1130,1230,1186,852,852,3131,952,1644,2047,1473,1053,1939,1939,1120,1120,1120,926,925,925,1074,1001,1054,1333,1299,899,899,1092,1092,1449,1182,1191,1000,1206,912,2074,2074,1661,1257,1125,1237,1187,1210,1074,997,1074,898,1557,1557,1470,1081,1160,1160,1643,1336,1336,1722,1333,1333,1361,867,867,1101,1101,1969,697,697,697,1434,697,694,694,694,1287,1367,1417,1417,776,694,819,1209,1669,1703,1574,1574,1458,1234,1203,824,1720,1720,923,1421,1421,1127,1040,1040,1092,575,1089,1089,1525,1228,929,929,1694,1694,897,1440,728,728,1397,1397,1414,2903,1348,1170,2067,989,1211,1662,918,1356,1133,1193,1398,1160,843,1282,1300,1076,1076,1076,1815,1389,1649,1148,974,1111,1068,1132,1008,1008,1283,1146,1146,1354,2291,1604,1730,1126,1126,950,1305,1305,1401,1140,1073,1073,1200,1200,1200,1042,1042,1309,1115,1245,1270,1334,1164,1373,1237,909,1120,966,962,1010,1054,1032,1032,976,976,998,1000,1000,1080,1094,1094,1440,1440,863,863,1161,1161,1019,1019,827,1000,967,889,860,1624,1435,1750,889,1228,1228,1064,1064,778,778,1864,1864,1487,1008,1008,869,1144,1144,840,840,1144,1052,1197,911,1659,1659,941,941,1299,1299,1026,1026,993,994,868,868,1238,1338,1338,914,954,1180,984,1068,916,1608,1608,1184,1090,1331,1375,1373,1368,1368,1120,1401,1369,1231,1374,1424,1323,1006,1145,2223,1010,1098,1098,1014,1050,1007,1554,979,1305,992,1119,1100,1103,1102,954,1195,977,1145,1079,994,911,1839,902,2982,1223,1338,1393,1393,1368,2002,1525,2031,884,960,987,1854,936,2238,1352,2844,923,923,1004,969,1967,1000,1100,1126,912,1699,1699,2746,2031,3370,3191,2995,1327,1744,1806,3188,2837,1641,2454,1372,2110,2543,1403,2785,2488,2389,2389,2344,1140,1965,1965,1736,1853,1368,1219,1116,3526,1356,1465,1305,2229,1786,2378,1902,1800,1534,2018,1483,1767,2512,1414,1414,938,818,1161,1421,1175,1784,1316,974,1410,1485,1834,1634,3244,2231,2902,1680,2428,1240,2735,1188,2107,2158,1380,1198,1728,1352,1397,1197,949,1352,1320,1400,1450,1813,1391,1391,1967,1665,2958,1370,2231,1791,1330,1700,2092,4031,978,2096,2659,1403,1690,2522,1863,1863,2367,5480,2766,2843,2229,3244,2159,1264,1193,2998,2757,992,955,1234,1445,1445,2799,2917,2141,1193,2383,1193,1193,1410,1194,1335,1664,1664,2141,1159,1657,1594,1594,1528,1130,940,958,1446,1228,925,1077,1720,1734,1314,1467,922,1132,1484,1484,1039,1193,1174,990,2707,1000,1000,874,1225,1212,870,997,907,1352,865,930,1678,729,1109,1282,4420,820,820,812,973,1934,1023,1023,1000,874,1382,1382,2471,1663,1663,2137,1173,2531,3712,1920,3864,3864,3536,5398,1677,836,3963,1461,3898,1507,2854,2854,2728,980,885,1996,1262,1423,2506,1722,1359,996,1671,1474,1363,1365,1720,1978,1061,1167,1167,6561,1013,1275,831,722,722,547,547,835,835,752,838,1277,1002,956,992,956,1052,616,1424,1007,845,750,1055,1005,853,1556,802,3575,1076,915,915,747,747,747,1182,821,769,1009,1009,1031,804,809,809,801,1100,973,1241,1241,1263,1263,1011,996,1286,1039,1121,1033,1033,2304,2304,1132,1026,1026,993,993,767,767,860,763,749,749,746,746,745,969,1029,759,1147,973,1321,1005,1014,814,1087,719,1037,1069,1143,1669,1209,1515,1093,1485,1207,1207,1215,971,971,907,924,914,1102,1136,953,1485,3004,973,1151,1058,1554,1380,1131,3303,2850,1782,2066,1732,1732,1205,1147,1081,1582,990,1084,1486,1114,1118,1118,785,816,801,785,785,1001,960,2391,3246,3246,1172,1327,4207,1387,1746,1746,1092,1138,1074,1016,1095,1268,1046,1273,1273,1657,1800,2974,1211,1211,1203,1278,2708,2708,1894,1754,1925,942,1610,912,1152,1152,3089,1761,1761,1115,1530,1816,3006,1450,2303,1044,2468,2931,2282,1557,1234,1377,1247,1664,2975,2917,1321,1061,1587,1645,1243,1499,3357,1145,1790,1801,2696,2868,2103,1366,2863,1575,3646,2252,1055,1479,2202,2912,1585,1666,2111,1870,1082,1059,1059,976,1517,1517,1003,719,707,719,566,787,783,753,730,753,575,783,803,794,1162,2852,2795,2181,2618,2037,1833,1833,980,1003,972,765,2070,2114,1091,1149,1735,1781,1086,1386,1772,1310,1069,1729,1729,1351,1351,1617,1617,1344,1344,1523,1120,981,936,917,783,1106,2063,1613,1613,1541,4125,4423,725,1532,3783,1200,1760,1142,1442,1167,1746,1327,1517,1598,1631,1786,2848,2029,2651,2104,1933,1648,1438,1438,1438,2104,1639,1618,1013,2888,1747,1509,1929,1724,1357,3666,3666,3678,3678,3198,4326,3297,3940,1059,1516,1370,1181,1496,1181,1181,1516,1370,1181,1516,1506,1367,1367,1506,1370,1181,1516,1181,1181,1509,1516,1181,1181,1516,2911,3675,3372,2788,2049,2244,1957,1957,1570,1745,1854,1185,1726,1412,1467,1467,1745,1564,1334,1566,1156,1278,1156,1133,1133,1156,1162,950,1712,1712,1712,1712,1712,1712,1448,1448,1712,1712,1674,1674,1514,1514,1712,1712,1448,1448,1712,1712,1512,1437,1712,1448,1671,1712,1712,1512,1288,1288,1697,1697,1756,1756,1305,1305,1278,1278,1704,1704,1305,1305,1280,1280,1697,1288,1288,1697,1697,1768,1768,1704,1704,2338,2338,2180,2180,2484,2484,2301,2301,2287,2287,1833,1833,3097,3097,2390,2390,2813,2813,759,1579,1018,1018,1223,733,984,984,832,832,832,832,832,982,2196,2196,1451,1185,1461,1185,1451,1554,1788,3192,3947,4471,2341,3554,3852,1778,1695,1451,1600,948,1575,970,1340,1347,1273,1303,1575,1704,1568,1557,1704,1697,1808,1347,1347,1437,1500,1715,2462,2055,1950,2146,1613,1313,1756,1239,1697,1697,1278,1768,1704,1228,1228,1288,2152,2417,1950,1613,2557,1697,1712,1512,1712,1671,1712,1712,1712,1437,1712,1756,1703,1703,1756,1756,1305,1305,1697,1697,1704,1704,1674,1514,1377,1571,1712,1448,1377,1448,857,738,989,792,1066,745,1045,1055,1694,1425,951,1011,1011,1034,1506,921,1931,1065,673,1358,1003,954,947,777,730,786,786,834,820,820,1016,816,990,1229,1229,915,926,926,770,822,868,868,1059,817,770,1038,2515,861,1039,1039,1145,794,695,1050,768,720,875,952,856,926,800,800,798,812,921,774,882,888,819,542,1124,847,945,945,945,2254,818,1485,782,909,909,1234,1234,1234,916,916,962,880,1877,876,682,874,1031,1031,1081,1081,949,949,762,750,796,796,781,850,967,815,953,1031,1390,1791,1049,990,863,863,1027,888,888,523,515,513,738,512,550,674,643,639,2184,562,562,795,898,725,725,955,725,721,721,721,721,3004,1322,1357,1013,1762,3660,1800,1784,1676,1979,3060,1786,1639,1786,2780,1357,1013,2164,2541,1013,1357,1176,864,1103,1072,1732,1732,681,976,945,521,731,1243,1410,1730,728,883,755,972,972,674,1788,964,1345,884,892,817,1286,842,1374,1374,1374,1374,1374,2307,966,462,647,715,720,1028,876,1530,866,648,851,594,832,808,808,761,760,1290,933,996,999,837,1079,1242,808,1018,1566,759,759,722,759,962,962,723,759,1297,1297,1215,972,891,891,723,1555,1555,886,972,972,720,882,720,882,882,720,1033,1057,720,972,719,1368,755,973,892,944,944,944,847,757,1090,874,1020,1248,939,960,960,700,773,937,951,845,952,1079,1854,762,972,904,1872,759,1150,757,1513,1488,1120,1026,1042,889,522,828,804,804,1448,1448,771,1085,673,673,1004,805,920,794,818,554,1329,1329,1329,1349,1306,997,997,997,1481,1481,1032,948,1800,734,880,888,1219,1077,1551,1551,874,856,982,904,904,899,1190,961,928,1956,1956,1038,701,701,902,902,880,1168,1090,1090,679,679,733,903,903,1119,1119,1385,1853,916,675,727,727,1679,1089,676,621,1439,775,880,1324,884,1106,1106,707,707,1457,1095,872,641,937,916,776,766,568,663,1487,1212,898,898,951,951,705,1150,1150,2387,2387,2367,1794,1224,936,950,866,1114,1132,2244,876,984,984,1569,2393,2413,1603,2720,1565,1565,910,1387,576,1620,1620,1620,1620,1350,1069,1310,853,1218,1074,889,1217,1123,1120,1104,1105,1105,2105,2105,877,820,1248,706,792,1209,761,914,808,775,1277,1277,1487,750,1104,1104,884,723,1938,606,1692,999,999,1239,1336,1336,1952,4479,2401,1641,869,878,712,1497,673,673,847,980,2357,1126,1006,1006,988,720,676,838,838,976,896,921,921,927,769,869,869,1228,1084,1221,793,793,1400,821,1194,653,1172,943,1214,731,1377,1167,1167,1173,1989,1989,1258,1258,803,938,1672,1311,1311,886,1900,1900,1098,1142,1342,765,1888,1418,1381,1954,905,731,1848,2256,824,1894,1894,816,1331,1937,1876,1561,1308,1308,931,2370,2368,1972,1930,1126,840,953,1542,1542,932,1126,1229,927,1328,1756,1196,875,1702,1040,912,1188,1188,1077,1321,2048,1262,1874,962,1547,959,964,870,1017,852,832,1484,1484,850,1678,921,1732,1300,1300,1300,1300,1300,2477,2477,1826,1821,1473,1486,1486,1486,1486,1486,1493,864,590,1482,899,826,1481,1190,1888,1888,1450,1485,854,771,2361,2361,812,1050,837,1020,1058,1481,1481,1132,2340,2340,1047,1020,2189,2189,749,2360,1728,1728,2030,2030,952,840,1869,1445,1058,787,1154,1156,804,1726,842,1056,1519,3547,1682,1394,3694,791,791,843,1125,852,1324,1324,873,2271,2271,852,2152,2152,945,952,844,828,2215,1005,2096,2012,963,856,987,1467,780,1004,1004,1840,1888,1776,1776,1268,996,1449,748,1048,1147,1246,1080,1306,2363,2363,491,1451,1451,2036,1373,2489,2385,2137,2137,912,1957,1917,1917,948,877,1470,912,1235,991,681,880,818,2173,1652,1652,1977,1986,1970,909,1052,1052,1690,773,956,1144,1832,912,946,2452,2004,996,825,827,1221,1737,1529,1117,894,1502,1440,2036,2008,883,3610,3610,1620,957,1183,1378,900,752,1511,992,872,821,821,798,863,2028,2084,2726,1235,612,884,918,1264,1075,1173,849,1528,2191,2191,1262,766,766,1916,1900,1533,1889,952,928,2562,2562,1988,1988,1109,1025,875,864,864,1047,1151,1761,839,1854,800,781,1110,909,1055,2088,844,834,976,937,1510,1344,1028,869,1530,846,1398,874,950,917,969,1242,852,844,844,973,846,1145,798,993,993,1264,1272,961,1215,1215,1068,905,1014,1130,1313,1313,926,981,981,938,1063,987,975,897,780,960,960,1347,1179,1295,1094,1396,1365,1179,1108,1046,1055,846,1136,1121,1334,1316,1059,1297,906,906,1454,1454,1928,1928,872,1048,1309,1351,1351,1034,1029,669,1435,970,966,966,1364,975,866,900,885,954,784,784,848,848,848,910,967,756,1062,748,755,772,1183,960,1870,839,835,828,1056,1092,828,1400,1036,733,1439,903,903,934,934,664,619,1025,1025,886,924,576,816,829,832,1115,1115,1286,1267,1484,1251,1251,1383,1085,1931,2044,1775,1775,974,1455,1570,1644,3914,2303,1140,1152,1487,4092,4092,2543,2706,797,1116,1233,1007,638,1219,1935,3257,815,855,880,1107,2713,882,621,873,621,1298,1004,1839,996,1203,1570,2302,1330,1047,1268,1268,1632,1564,929,2611,1173,783,985,985,1776,1776,1776,2624,1351,1838,1104,1648,1423,1410,1972,1175,1291,2275,1230,1680,1184,1796,1523,1322,1337,1598,1318,1318,1203,1814,1264,991,990,1069,1142,726,1815,916,907,962,1700,1700,1117,1225,925,925,1147,1147,1257,903,1115,1174,1797,1038,1010,653,653,2032,1046,932,932,720,2061,2061,1053,1512,1493,1272,901,1967,940,1028,928,1178,1065,577,1403,1403,936,935,935,842,1346,869,1294,1092,999,1985,1600,801,808,808,905,1848,1848,1660,740,1360,1627,1534,619,619,771,1490,1144,964,964,1304,1415,1059,1008,1513,1220,853,1436,1426,779,770,1100,920,1055,981,1022,1022,948,1448,1031,937,923,923,919,838,992,1678,1003,1011,1088,1331,931,1011,1708,1792,1160,1266,1266,1179,1306,1306,1473,522,805,1020,1020,845,1878,1787,1787,951,951,2050,2145,2145,858,1098,1046,1070,1881,1054,1069,1676,1283,1092,914,914,884,884,961,984,984,934,1009,820,1494,1494,763,727,1083,725,725,730,730,725,758,1964,727,725,750,1088,727,727,1088,734,1068,1114,1027,1027,813,720,784,784,864,866,836,836,995,995,883,870,870,869,874,874,1367,1440,842,1310,1310,1076,1506,1612,1131,675,675,1236,1080,1163,1561,1229,1229,1229,730,761,747,1493,1529,1342,1208,949,1179,904,908,925,921,921,674,674,1418,1557,895,895,1632,1289,957,957,1105,1216,416,416,1429,2052,1044,873,873,1739,1430,847,1154,1460,1076,861,962,1214,1807,1807,1344,865,1529,1625,1464,1838,2365,1100,675,1057,793,793,999,881,881,2125,2125,737,857,962,859,859,1200,1093,960,1476,1085,1360,1089,1089,1063,1101,1400,505,505,1212,951,1965,1965,1097,1013,1189,1750,1750,842,936,546,900,830,2071,922,922,734,734,934,934,794,794,2001,1012,600,1745,1745,1745,949,658,658,657,828,720,720,788,471,471,755,954,861,1080,1128,744,802,802,702,824,362,800,552,552,1369,726,707,940,904,955,736,726,987,1544,890,696,696,602,1015,904,791,486,859,783,472,892,892,684,1048,702,785,880,966,966,783,783,1011,951,601,601,880,710,1527,901,1179,797,1218,878,1044,546,546,2040,787,960,973,754,1988,750,1286,612,931,1324,1270,565,1063,1063,1278,956,735,739,779,984,1044,1348,1348,687,687,612,1597,1043,829,829,829,950,792,813,882,882,1083,657,694,921,924,1058,918,910,742,1230,893,1115,1172,991,1342,1189,780,677,1154,731,731,1304,850,1308,809,593,593,927,1527,732,728,705,1179,895,847,1142,543,705,800,1000,887,817,1313,1313,922,840,840,978,1036,737,1083,915,1219,552,754,720,721,730,658,1072,1300,1471,770,718,898,898,840,1167,622,1056,744,744,984,1033,1156,636,967,936,1037,700,1149,1149,700,521,1058,731,731,1413,822,822,980,1002,1002,755,863,1520,840,840,819,770,849,849,1288,1725,1052,624,624,1462,954,1073,1073,1020,1092,1005,1005,1800,1022,822,827,827,968,996,996,1433,1937,1006,1499,960,936,1500,1500,855,855,855,666,1009,1784,1950,1080,1080,548,1578,707,862,862,823,1271,1363,1115,1013,1036,1066,1066,1398,1128,1451,828,589,1149,1067,750,750,662,928,825,788,892,892,846,846,873,1023,1102,912,912,882,882,1050,1066,982,723,656,916,872,720,977,1124,861,908,1247,978,1007,959,1294,1294,1183,1183,988,799,799,940,940,940,801,884,884,884,884,1000,776,1042,921,921,1088,1088,983,983,1044,751,1191,1000,1000,1079,1079,950,950,440,1426,1102,669,860,853,858,558,832,919,605,768,931,931,1018,1100,1548,1213,1213,892,1153,748,1588,864,1044,870,992,745,838,838,916,916,965,1126,1126,761,1437,1437,1253,890,890,994,994,1108,1108,1185,1593,2194,2094,872,1339,1046,1062,1274,1274,1274,1058,1058,1058,1231,1231,1231,1160,1321,1950,1355,1070,1049,922,838,1171,747,751,751,805,1205,1504,1442,1178,1178,1006,1449,1477,972,1154,894,1077,1077,816,1062,860,1363,720,720,1015,1002,1002,911,911,684,724,724,635,635,659,683,1210,1210,1411,2623,1074,1074,1027,1086,1167,1584,1153,926,926,799,1209,1045,1045,1357,2283,1048,1048,1036,1044,1052,1056,1424,799,1139,1446,879,943,966,868,1379,1379,1112,1397,1009,720,795,1040,1358,1325,880,880,956,956,960,1273,971,1251,1032,2679,2679,2117,1218,1218,884,1930,958,993,2411,1927,1927,1139,870,870,870,870,870,870,870,870,870,870,870,870,870,870,870,870,870,870,1181,1125,994,994,902,1104,753,524,524,524,909,925,925,991,764,1037,847,1578,548,959,1728,840,1064,1064,1267,1189,901,901,863,863,1339,1488,1488,792,792,919,919,783,1180,1180,1330,1116,1878,1878,780,1532,1532,1532,879,945,945,748,2308,829,1184,1184,1205,434,434,434,901,2001,1802,899,1392,1360,1288,1288,957,957,735,735,1321,1321,1388,1173,920,1590,1858,1496,1496,1479,1769,2112,1969,1147,880,1448,1942,1076,1017,1017,1152,1478,1478,886,714,714,861,811,811,700,700,700,660,955,1892,2036,2980,1415,928,928,729,1425,1418,1520,1334,643,1369,1369,1862,818,1888,2094,572,1236,2374,1836,1246,856,856,1211,1211,700,704,759,753,936,1944,704,678,1151,1151,1197,1197,883,1520,1135,1182,928,1327,1550,1340,722,1176,870,3189,755,1469,1580,1418,931,1808,1152,1247,762,880,948,1569,1569,1196,1196,1533,2200,1789,1829,1617,1680,1680,772,2246,520,520,480,560,965,965,1433,1712,1961,1510,878,1600,2190,1420,768,972,1848,2998,1188,1823,1683,1683,920,1318,1598,1100,1583,1570,1432,1320,1234,976,976,976,1077,1077,678,1528,985,1011,987,986,1362,1362,641,641,1624,1310,1310,1484,1637,1203,1184,1198,2300,1574,1664,1034,1523,1462,1462,1140,1140,1467,1472,1460,1934,1637,1092,1133,2425,1548,1946,2404,1444,1620,1620,1536,1925,1925,1299,1462,1621,1621,1013,1177,1349,1349,1824,1664,1612,924,1498,1162,835,931,1283,1620,850,808,756,1467,935,1376,987,862,862,634,850,886,701,852,1235,1296,1301,1296,831,869,869,869,1222,1225,1225,1225,1225,1225,1225,1502,912,868,873,1528,1528,966,966,1472,1268,972,942,924,936,932,936,918,960,1231,1620,545,770,724,724,724,724,770,2102,2098,950,1910,1010,1010,1025,1360,1088,1088,1088,1088,1088,1088,2468,1063,1576,1868,5034,1565,1591,1424,1646,1169,614,1248,1290,2356,2356,1874,1874,2400,2409,993,1248,1680,1654,1932,2000,962,962,475,533,533,533,1648,1369,1875,730,2426,2054,1915,1915,1915,1915,1915,1915,1915,1915,1332,1332,1332,1332,1180,1180,1332,1332,1332,1332,1088,1748,840,1830,1219,1507,1255,1027,859,1382,1297,1674,1372,844,836,1414,2340,1577,1850,1425,1246,868,1326,1269,1044,1169,1746,832,941,936,1174,727,662,1119,936,1057,846,936,1278,2025,3097,1925,1925,1925,1925,1925,1925,1925,1925,1925,1925,1925,1925,1925,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1423,1363,1706,1440,1119,1061,3444,3031,1093,1497,1376,1544,1248,1544,753,1365,876,1085,1830,1849,1611,864,981,871,815,981,901,1383,1433,1207,1439,1202,1045,842,906,2769,1974,1778,3072,2940,2182,2795,1412,1320,2040,1947,2052,827,2516,2516,1050,944,2335,1252,916,916,902,2503,2503,1303,1719,3134,1522,1493,1522,1522,2006,2006,1216,920,1792,798,2836,621,453,947,782,782,1215,1206,1902,604,891,1376,1391,802,2193,1278,1506,1234,1830,1830,2358,981,960,960,2018,1987,768,525,971,971,2054,1018,574,780,563,537,843,940,960,514,514,636,1668,1026,1018,1073,1092,1365,1365,916,1202,1032,795,1828,1122,954,1130,2867,1020,1922,1184,1586,2190,1104,1334,1649,2155,869,1161,1010,694,694,1567,1118,2215,2456,997,1807,1728,1188,2515,1770,1556,1556,2185,2185,871,847,2125,2125,1348,1008,776,709,2224,2224,1414,938,1162,2188,2216,4598,1725,2850,1003,1003,1003,802,3120,2927,2924,2998,2602,2467,2602,2467,1854,619,2308,2277,1269,1491,3784,2031,2031,1424,671,671,1780,2793,2793,1877,1877,1877,2658,2045,2045,2045,1993,1993,1357,1074,2385,1791,17942,1254,1655,1744,1177,2155,1326,1903,984,2138,858,1944,1020,727,3607,2424,865,865,865,1023,1023,865,812,812,675,1555,1173,1188,1102,1102,1256,1897,1222,1379,1417,1356,1167,1268,1655,958,1225,1371,1982,1982,1982,1982,2234,1774,1774,1320,2218,1753,1219,1219,1528,1528,1528,1890,988,767,1342,1504,2523,1461,2072,2624,1552,1880,2098,948,553,602,1496,8870,8870,8870,1412,2477,2665,2665,2477,1242,980,1239,1239,1679,1208,998,1190,1704,11435,844,5365,5365,2359,2359,2707,2707,2070,2070,2039,2039,2039,2039,2070,2070,2039,2039,2039,2039,2070,2070,2005,1476,2005,1722,1722,1722,1722,1722,1722,1722,1722,1722,1722,1722,1722,912,1252,1160,936,1057,1029,1029,1029,857,808,1038,812,913,1428,1426,1892,1892,1845,774,770,770,759,1033,1033,1033,1033,1021,1868,1426,1438,1438,1456,2105,664,835,1310,1263,628,835,696,628,1421,1340,1071,1123,794,970,584,1125,2178,1044,1044,1490,718,718,840,1572,1666,1572,1666,1940,1552,1869,1535,794,1058,1455,926,836,1140,1140,1050,1191,1191,1191,1140,1191,1191,3169,1270,1314,1170,950,950,1234,1920,969,938,938,803,1953,1953,997,2456,2410,2156,2033,1973,1000,2247,1208,1139,858,1361,1359,1359,1180,2084,1102,1102,2630,840,1583,968,1882,793,961,1268,1268,855,1781,1548,1548,847,1124,1600,1555,1684,2082,1670,912,2200,916,684,684,560,1207,714,1457,1457,1263,1263,2874,922,548,548,548,1050,1586,530,530,530,530,530,1114,1114,1242,1595,878,1878,1797,1797,1912,1145,1925,1821,836,672,1079,1014,1007,2119,2119,998,1381,831,831,909,2146,930,930,2342,1491,1280,1078,1029,679,1528,1528,1086,977,1469,1469,1469,1144,1506,1596,929,1306,1306,1814,1814,1155,1931,1177,1053,933,1175,1221,1118,1820,942,1241,985,1114,1360,874,1476,748,775,845,894,1126,931,1093,1047,1120,1050,1190,864,864,1430,2560,1162,1054,1890,1563,1611,1915,830,830,1343,1071,1192,988,1114,1440,1800,1800,1064,1278,2161,2161,723,862,1519,970,1207,755,1558,1155,994,1124,2282,1252,2658,2442,1168,1230,796,2178,2178,1238,1238,869,1711,2192,1903,1903,1471,1471,1057,2277,2277,1052,1310,1173,1143,1099,1099,1250,1094,1098,1098,1098,823,2407,1682,1170,1170,1096,994,1073,580,577,1059,1300,1452,1307,1946,2252,1926,1962,1500,1633,954,954,1034,616,616,1522,1314,1303,883,1022,1022,1541,1342,1754,1462,1069,1069,4794,1662,2097,2281,2281,1996,1954,1954,1905,1905,1511,1860,839,1878,1878,1521,1739,1790,1706,2022,1924,1148,1422,1422,986,1981,1583,1079,1079,847,1044,1044,1305,1305,1057,1091,2512,887,885,1000,931,904,945,1084,851,851,1084,997,1287,1287,889,530,973,1242,959,921,822,869,1550,1084,1084,1048,1639,1639,4252,827,778,1072,2266,2266,831,1785,1131,1567,1652,2097,2263,2097,2760,2041,1194,939,821,821,1380,1593,1388,1614,2420,2181,2181,2463,787,781,608,592,599,592,608,707,781,621,602,609,602,609,872,669,1123,1565,1894,1143,1904,1904,1189,977,1350,1067,1243,1243,1510,1753,1869,799,1176,739,803,1717,960,999,993,954,1106,1000,1009,1125,1697,800,800,800,736,1100,818,1064,1064,797,1952,881,2804,708,1055,1287,2516,2516,1630,906,1494,2791,894,1004,1599,2512,954,856,2020,839,829,825,825,825,2874,822,822,996,899,992,938,1951,1426,795,1197,981,1182,1182,795,1115,2454,2170,2160,2160,2792,849,807,1838,1838,2284,1846,1392,1199,904,2146,1188,771,517,517,823,1750,2000,1092,1092,1986,1020,936,1230,880,880,2058,1096,2588,2533,1124,1027,1810,1370,1180,1177,1387,1640,1549,1568,1046,920,892,1225,1159,927,819,819,815,1465,718,1274,1052,2190,2351,2190,2250,1193,1360,1050,481,764,1786,1786,844,2291,859,908,784,1318,579,345,345,1159,1159,976,976,977,1300,1292,1392,2514,2514,2514,1687,1687,1240,1598,1109,1387,1326,1474,1474,1205,1205,1160,1078,2492,794,929,764,798,794,1408,677,677,677,887,1364,822,902,1446,1386,918,1458,1147,740,632,2460,1189,1794,860,860,713,2259,1876,2277,2262,1040,816,816,1062,1000,1804,2566,2759,2136,1070,2432,2245,863,1375,1023,1637,954,954,1101,1101,723,1305,1305,1872,1305,1213,1023,1305,947,1213,1197,1197,1421,1260,1260,1024,891,1565,1820,1820,1561,1038,1114,931,1117,962,939,983,983,950,768,1829,1259,483,1301,936,913,1104,911,1548,810,1315,1315,937,768,2029,1073,1300,1313,865,1134,988,2192,652,1820,1820,689,1691,1138,919,1179,1010,596,993,702,2522,831,1243,1053,1638,2145,1026,965,1239,1239,1311,1250,1029,1550,1262,992,1429,1289,1289,1063,1950,1192,1995,1284,611,401,606,606,895,800,3003,1069,1660,1266,838,920,1512,2116,1828,1676,1420,1138,669,1035,1552,1086,1089,1119,1013,2014,2112,787,954,980,980,840,1466,1825,1224,1648,1115,1303,5631,2166,1174,1816,1008,2775,2775,1597,770,690,1716,1065,1134,1134,2624,2624,1126,1169,1687,1326,1020,1020,941,960,1183,914,1012,1012,1239,1328,1875,1979,980,980,1167,1946,926,1015,1015,1015,986,2103,1790,1100,1159,1274,1139,782,782,1296,1296,1296,1296,1296,1296,1296,1296,1600,1296,1014,2103,2463,771,864,871,900,1488,955,1768,2369,958,977,1112,1159,927,1398,1301,894,1181,900,1194,838,979,841,942,2503,2503,1289,2821,1433,1063,874,1609,2068,1637,2126,2126,2322,2282,1547,1502,1764,888,2739,1284,982,1482,1482,674,1151,906,1504,1694,1805,1260,775,1998,2185,2185,850,3219,2782,809,809,537,572,572,572,537,891,1484,2160,1306,1358,1494,1800,2292,954,2642,2527,2535,2535,988,2679,2159,2149,2255,2259,759,1824,1792,1146,1029,2385,1946,1946,2605,2434,3094,3230,2397,1337,647,1911,2696,1718,1698,756,1894,2707,1120,1953,2616,2616,1933,1547,1347,2673,1442,1316,1822,756,652,824,490,651,626,626,1457,1403,1090,851,1131,994,1536,1962,2039,1656,2039,1673,2133,1154,2393,1169,1392,1390,1390,1349,1449,1449,1449,910,910,911,911,1097,1097,1215,1215,1215,1215,1179,1445,1454,1463,1392,1392,1646,1386,1087,1881,2189,2189,1051,1051,2181,1019,724,854,850,843,2037,2037,1581,1702,1039,738,1378,1782,1920,1920,784,611,880,880,1384,1384,1544,1408,1092,1062,1065,770,1068,1068,1056,1894,1893,1335,1335,1424,924,1335,1721,1069,912,912,912,1069,1130,912,1069,912,912,1472,966,1364,2098,714,714,1091,1091,1148,1434,1148,1153,1217,1148,1153,1217,1153,1217,1434,1153,1565,1668,1520,1520,1479,1150,1479,1479,1803,1803,1803,1622,1594,1708,1131,770,798,768,795,768,804,1701,2934,1600,942,1663,1663,941,941,2601,2601,1872,1872,1852,1852,1790,844,1408,2346,877,877,1576,1059,1222,834,740,1672,1626,1428,1050,2188,1850,1300,780,1239,1417,1789,953,866,866,1222,1082,1609,1476,1382,1012,1012,1787,786,2156,805,1973,1040,1047,2342,1119,1826,1826,1188,1528,1592,2219,1626,2002,895,1744,1018,767,1176,1296,1296,828,828,1176,5363,5363,1043,1836,1666,630,1836,839,1228,1728,1728,1836,1666,1666,1539,1836,1106,1106,1106,560,560,1666,1836,1836,1661,1666,1661,1836,1209,700,2038,2038,1921,1868,1506,2181,1702,1702,738,699,1025,1036,2226,599,1268,1118,815,815,1338,933,1173,1173,1000,1798,804,1021,1021,1013,1013,936,869,925,1374,1126,1126,968,968,1064,1004,2048,1145,1289,1493,1371,3754,1482,2456,1679,1482,1647,1890,1391,1832,1857,2183,2935,3024,1753,848,987,1080,1732,1035,1909,1851,1035,1909,987,987,987,2767,816,1283,816,1283,731,816,816,731,731,1283,816,1283,1283,1283,1283,816,1283,816,1028,3844,2882,2409,1752,1782,2313,2313,1594,1315,2313,1728,1594,1782,1782,1315,1594,1351,2313,1594,1315,2313,1351,2472,1230,1520,1399,1142,1142,1093,992,1715,987,1095,2101,874,1884,1311,1632,1481,1472,3019,1511,2062,1020,1020,914,1328,1415,1742,885,875,1624,1281,885,913,979,1408,1077,1300,1281,999,970,2084,1062,1393,1062,1062,937,2384,2382,3155,849,1306,2449,2567,827,1271,827,2876,1693,4929,4323,5019,732,1153,864,844,1153,1027,1027,1122,867,1122,1027,1027,1027,1153,1027,1869,1893,1893,1893,1162,1162,1770,1744,2170,1744,1099,1234,1162,1744,1235,3174,1079,1074,821,821,726,2575,1720,1726,1736,1400,1461,1297,1256,1199,1716,1604,1180,1180,1604,1180,1605,1373,591,941,584,591,1121,1121,584,584,1458,1230,2086,1590,1460,1460,1553,1718,1652,1780,1708,2031,1653,1782,1730,1730,2018,4020,2176,806,1124,886,886,812,1431,3659,787,1345,709,976,744,1068,736,648,1146,1438,1316,1341,1077,1255,1659,803,753,735,1233,1195,792,792,654,1210,1208,1175,833,834,1188,1135,691,1308,699,699,651,1237,838,1220,1146,1175,1216,787,1156,1152,1255,1169,847,785,658,712,1160,1371,2073,2278,1494,1494,1286,1506,1729,1758,1749,1697,1911,1329,1046,1775,1775,2980,2120,901,2238,1458,1292,871,1635,784,823,1442,919,1147,2496,600,825,1933,1926,1926,1926,664,665,706,706,706,780,779,760,821,821,840,1412,1412,2595,1465,1752,818,1749,1848,818,818,1749,936,1410,1848,1467,1331,1467,1410,1410,818,1749,1848,1848,818,1848,1848,1749,1410,1848,1749,1467,1410,3392,3392,1752,1752,1471,1620,779,1471,1752,2253,1752,3043,4144,1532,2065,1300,1823,1887,2008,1887,1764,1764,1764,1619,1619,2811,2667,1820,1842,1842,1795,1795,1846,1846,1846,1840,1840,1881,1881,1605,1605,1605,1448,1448,2485,2485,2080,2080,1927,1927,1927,1927,2293,2293,2293,1797,1054,1054,1508,1470,2146,802,1169,1466,1084,1041,1006,1084,1007,1041,1084,1041,933,1008,971,1960,1960,2295,2213,1143,3115,3115,2430,1143,2430,2295,1960,1960,2295,2430,1850,3490,3115,2430,3199,2430,1960,4495,3199,5561,778,1148,711,506,686,717,1365,632,632,1766,1149,1149,1195,1182,857,1695,939,896,1763,964,964,2481,2886,964,2343,964,964,2481,964,2343,964,2481,2886,964,2740,964,964,2343,964,2886,964,2343,964,3228,1767,1939,3228,1767,1939,3228,1767,3067,1939,3228,1767,3067,1939,3228,1767,3067,1939,1767,1939,3228,1767,1939,3228,1767,1939,3228,1767,1939,3228,1767,1939,3228,1767,3067,1939,3228,1767,1939,5171,4799,4723,6095,5636,854,854,635,989,797,991,632,993,498,772,498,991,635,791,783,497,514,635,992,816,988,992,989,639,503,998,995,822,780,484,1001,484,505,796,992,998,640,647,827,509,485,782,640,798,1026,1800,1438,1621,806,1261,974,1041,900,809,1259,1663,893,1639,900,1258,1312,793,1639,758,1258,1664,1001,1639,816,1258,1664,816,1639,1258,1664,1001,1639,1258,1664,1639,809,1258,1664,1312,926,900,1258,1664,1001,900,1258,1664,816,793,1001,900,816,1258,1664,1312,816,893,793,1639,758,900,809,1258,1664,816,893,793,1001,1639,1041,900,816,758,900,816,893,793,1639,1041,900,758,900,1258,1664,1312,816,816,893,793,1001,1001,1041,900,816,758,900,1258,1664,1312,816,816,793,1001,1001,1639,1041,900,816,900,809,1258,1664,816,816,893,926,1001,1639,900,816,758,809,1258,1664,816,816,926,1001,1041,900,816,758,900,809,1258,816,816,893,926,793,1001,1639,1041,900,816,758,900,1258,816,816,926,1001,1639,1041,816,900,1258,926,1639,1041,816,758,1258,1664,816,926,1001,1670,1052,816,757,900,831,1277,816,926,1020,1670,900,816,757,900,831,1277,1697,816,926,1020,1670,1052,900,816,900,831,1277,816,1099,1671,1670,1052,816,757,900,831,1277,1697,1099,1670,1052,900,831,1670,1052,831,1697,816,1670,831,577,930,577,577,450,1065,987,688,449,987,449,690,688,632,987,678,844,908,672,1199,637,829,844,844,637,1454,595,1077,1230,918,886,886,883,883,2091,1413,1413,1621,1622,1231,636,636,1794,1083,1254,1764,1254,1254,895,1155,1701,1086,712,1231,1184,1184,1027,1086,963,1197,1197,1038,963,1038,1197,963,1197,1197,963,1197,1197,3374,1263,1165,1182,1165,1039,725,346,397,390,416,1004,2732,2016,2016,722,1472,1707,1032,1768,962,981,1288,1403,720,1767,1767,2146,1039,1415,1415,1415,1690,1690,1963,1798,1146,1716,1595,2222,1296,1347,1347,1593,1460,693,3326,2100,950,2478,1250,1250,1054,4102,2529,1951,1780,1378,1322,1326,1922,1196,864,1252,1252,1252,1289,777,784,2562,2034,1724,1309,1432,791,796,961,1740,1740,1426,1402,404,404,505,2703,1782,2422,1050,1549,1655,1488,2088,1864,1386,1386,2058,1626,1792,1861,3017,3010,1408,1606,1302,2052,1436,2342,2100,1548,1548,2716,650,750,750,1086,1947,1076,1908,1036,1036,1920,1536,1794,1784,1328,1928,1553,2139,2139,1759,1397,671,700,882,2200,671,2364,2364,2456,963,1483,1806,982,982,1666,1750,1030,1452,1735,1563,1662,1105,905,2020,2044,2137,2137,1322,1266,937,918,1766,1388,1388,1793,1443,1621,2366,2068,624,1299,2624,1329,1171,1171,1680,1440,2176,2287,2725,2610,2450,2450,2590,2590,4097,4969,5928,4540,2083,2178,1001,3628,3628,1253,1367,1368,1246,657,2759,2250,1708,1743,2358,2054,1294,1601,2680,1827,1488,895,1258,768,768,768,768,768,768,768,768,882,2936,1475,1388,652,1352,1115,1352,1254,1115,1115,1103,1022,805,993,1249,708,788,703,1015,992,1070,1591,711,1474,1317,711,1607,1178,1460,800,1348,972,1466,786,544,1677,1179,1583,1120,1141,995,2782,2053,2053,2058,2657,2051,2051,1272,1605,1721,1721,1697,1271,1283,1064,1047,1635,1158,1036,1219,1232,1057,1219,1219,1219,2318,1305,906,2121,1196,1206,1564,1084,980,974,1920,1920,1839,1932,1264,1592,1636,1722,945,428,476,476,1044,1716,1643,1595,1595,1595,1643,1643,1519,1513,1513,1513,1299,1299,1531,1529,1602,2862,2862,1930,1438,2094,2094,1175,967,1170,967,1022,2522,1484,1150,1201,1340,1340,1340,3119,2313,2313,2618,2618,1850,1850,1850,598,1020,1567,1043,1451,966,787,853,1376,1114,3382,856,2072,2072,1604,2548,2372,1328,2702,2394,2895,940,2174,1420,797,980,2173,2094,3756,3756,4708,3524,3947,1247,1064,1247,1140,1446,1296,627,1790,3791,1370,1113,2481,742,550,552,844,906,631,867,844,868,1058,1175,1405,1405,994,1175,1175,967,967,1694,850,1415,1694,994,2005,1435,1176,1415,1435,1415,1415,994,1415,1415,850,970,1272,970,2123,2123,1438,1438,1583,1817,1488,2127,1933,1964,1443,1443,1429,1429,1429,1886,1886,1445,1355,1460,1009,1123,1032,1032,1356,1460,1009,1123,1123,1355,1355,1460,1460,1009,1009,1122,1122,1032,1032,1356,1356,1356,1465,1009,1180,864,1450,1450,1685,1014,1151,1151,2168,1450,1014,1151,1450,751,751,1685,1685,1014,1151,1151,751,751,1685,1014,1014,1151,1151,751,751,1685,1014,751,751,1685,1014,1151,1151,1685,2168,1450,751,751,1685,1685,1151,1151,751,751,1685,1685,1014,1014,2168,1685,1685,1014,1151,2219,1685,1685,1014,1014,2168,2168,2201,2201,1689,2201,2201,1689,1689,3359,2201,1689,1689,1017,1017,1157,2169,2201,2201,1689,1017,1017,1157,1157,2169,2169,720,720,5528,2306,1076,1076,1173,1173,822,771,948,1841,2759,1536,913,1255,906,1137,1228,1251,1476,957,1044,1298,1147,1029,965,842,952,1576,728,1470,920,1431,1806,2071,1683,571,571,1745,2516,1854,1792,1226,1684,1163,999,1160,1367,921,1632,1627,1471,909,906,462,1073,1351,1351,1103,1397,1057,1245,820,1262,1063,1001,858,1108,1067,1067,1055,1700,1120,1988,1798,1741,1807,1940,1614,1676,1879,1523,1305,1298,1299,1299,1364,1284,1364,1364,1284,1364,1284,1364,1364,1364,1298,1284,1364,1940,1940,2391,1535,1179,1847,1484,1823,2469,1962,1853,1660,1622,1950,1016,1202,1046,1535,1288,1371,1371,1860,1853,1643,1929,1727,2032,2132,1603,1980,2803,1548,1248,1556,1525,1955,1418,1371,1371,1371,1976,1610,1689,1434,1689,1024,2290,1399,1553,2069,1995,1995,1316,1019,2048,1512,1281,2148,1881,1932,1653,1653,2102,1712,1906,1937,1854,1854,992,1687,1195,1830,1936,1777,1013,1304,2332,1075,2116,2048,1642,1815,2048,1364,1034,2048,1102,1408,1450,1450,1450,1229,2122,2073,2073,2196,1792,1460,1792,1472,1359,617,617,617,833,617,617,833,850,833,617,850,833,833,617,617,617,617,3038,3038,1334,617,617,617,617,603,833,833,1587,1486,1450,1551,1760,2195,1725,1265,1883,1199,2000,1462,1114,1717,1182,1145,998,658,646,1140,1140,2651,1140,998,1716,1999,2841,2185,2044,1922,1528,1528,1513,900,1836,1552,1267,1068,1132,1114,1230,1303,1095,1095,1095,1613,1613,1212,1068,718,1068,2029,2082,2137,1701,1768,1427,1935,1056,1056,773,439,439,900,849,1161,924,924,770,389,389,770,389,389,1036,944,944,2122,887,1441,922,901,887,1364,806,1094,1069,2324,1500,1448,1448,1087,966,1614,1549,1512,1730,1872,1662,1420,953,798,2212,2187,2186,1518,1386,1129,1510,2132,1020,1468,1059,1416,943,1710,1666,1825,1418,799,912,2064,780,1880,1806,1807,1024,1024,1138,973,1478,1753,976,3066,1939,1620,1661,1646,1496,1808,1622,448,1932,1916,3709,1700,2973,570,558,558,1420,1980,2937,1048,580,666,432,881,702,979,979,1734,2257,1035,778,1946,2155,1522,1479,899,899,1164,1976,1890,1614,2090,2265,1905,1242,719,746,733,915,2203,1045,1775,1580,1580,1436,613,670,814,2069,910,874,874,910,910,1694,858,858,732,1554,2809,1884,925,924,941,1289,2054,1594,1807,645,631,890,1234,1234,1298,1396,1712,1848,1735,1065,1027,2033,942,1100,1476,1340,3329,1142,2886,934,1519,2836,984,984,3291,1188,2691,1609,1133,1796,1796,1620,1830,1803,1354,1332,1354,767,567,554,554,972,1093,1093,1346,1107,1391,1037,1105,839,1664,1107,1107,913,829,1109,1338,1007,922,1019,1246,1190,1413,1483,2082,1300,1365,1602,1178,1027,1017,1220,1220,3200,931,952,944,1234,966,1008,1127,968,968,1128,1015,1015,1227,1192,1087,1280,1629,1449,3003,1170,946,993,1268,1271,1100,1100,1733,1074,1225,1133,1095,1293,1471,2022,2290,1466,2697,1827,1869,2040,1038,1703,2961,1654,2300,1169,1300,2075,1152,1663,2547,1154,1271,1063,1063,1031,1231,1098,894,1094,2332,2332,1165,1248,1177,986,2292,1504,2154,1742,1227,1261,1626,1686,1431,2734,2734,1396,1400,1436,1472,955,1524,1177,922,2212,4029,3935,2426,2426,2514,1918,2035,2306,1512,2660,2330,1208,1428,2437,4018,2389,2550,2367,3376,3376,3666,3666,3376,2876,4354,2270,1178,1007,4090,4260,4260,1093,2363,2061,2885,2885,2300,3479,2215,2786,1960,3283,3283,1520,1320,1470,1943,1421,1538,2969,1474,1268,1714,3342,3222,4310,1711,2370,2596,2630,887,832,832,1864,1223,1223,4760,2471,2471,2471,2840,3021,3293,2484,2484,2484,2496,3041,2988,1963,1417,1417,1417,1417,1417,1417,1417,1417,5485,3483,3483,3483,2196,932,932,1948,1173,5026,6085,908,568,3623,1017,749,706,706,919,706,706,706,706,919,706,919,706,919,919,706,706,706,706,3164,1884,756,482,927,2973,2852,2714,1529,1225,3040,3691,2657,1144,992,992,992,992,992,1394,1144,1144,1364,1409,3262,1392,613,613,1107,1107,563,1728,2883,754,1634,2832,668,845,660,856,1055,892,1056,2074,800,800,558,896,700,918,720,720,906,906,906,918,690,720,906,906,3198,3198,818,878,705,752,719,894,795,1056,1056,650,648,1167,961,3021,2995,1440,1440,1420,1484,851,1440,1739,2034,2094,2094,2094,3899,1838,1838,1838,1838,1838,2113,2096,2981,1409,765,987,911,2437,877,949,979,1076,710,877,877,949,1076,1076,877,949,634,710,877,949,1071,1440,929,929,626,626,929,929,929,626,658,643,756,650,2302,1494,1069,1678,1920,1924,2440,2369,1920,1920,1065,1370,1228,1228,795,1224,2253,2253,451,1564,781,605,602,1518,1518,584,871,1016,831,1064,2265,992,576,1568,1321,1321,2032,1950,1950,927,954,908,881,1339,1181,1181,1164,1368,2148,1100,1269,1489,553,946,1664,740,1184,440,440,708,440,440,919,454,666,1334,2280,605,1717,1410,574,1345,928,2396,1642,873,715,715,715,873,715,715,873,873,447,715,778,938,938,938,720,1389,1389,1807,2185,3514,937,917,678,575,2758,3724,1460,1484,584,1100,1256,882,438,2503,2649,841,3977,3074,1050,440,440,918,1312,1411,2486,1050,800,800,1050,422,613,294,704,711,704,711,760,704,1707,889,532,532,540,538,540,629,411,568,863,1548,1548,1286,1194,1079,1338,1338,1741,2425,4850,7143,2309,2309,2428,2428,1712,3983,714,781,781,781,821,783,780,820,821,780,784,820,821,783,782,820,361,2202,1102,567,567,3746,1340,950,722,699,2736,2896,2817,950,753,545,802,952,739,947,692,952,958,739,739,947,692,952,947,1455,1802,692,1862,2315,2132,2132,1716,1966,1767,1394,1920,1445,1587,1134,986,2746,2689,4797,4425,763,900,2331,1680,881,4255,3500,5506,877,610,729,1579,3009,1419,1419,1474,1638,1276,1638,3341,1517,6026,1502,2718,819,824,1309,1376,1542,4326,2512,1679,1840,1746,2591,6701,4186,4514,2546,5077,2911,2547,2533,2939,1280,1280,2409,3013,988,887,2262,1470,1470,2508,2588,2750,2427,2124,1344,1615,1209,1161,1209,871,871,570,570,1220,1244,716,705,890,512,852,1169,821,401,565,718,955,955,733,876,2553,1302,3529,3343,2466,2137,1574,1580,664,622,664,622,459,454,464,2106,451,788,788,788,757,1265,1265,3030,2508,452,470,1202,874,1373,874,1373,797,1373,874,1373,1373,1373,1373,1373,874,797,815,483,419,2247,2247,4032,1481,563,529,563,529,501,563,501,1830,2633,2139,2152,1564,2107,1121,2202,1620,2202,1380,1190,915,1370,320,615,568,411,723,926,942,926,926,711,711,711,709,1291,1322,1523,1291,1584,1670,1657,924,2037,2047,1107,1037,1041,2409,970,1101,2990,919,637,637,637,919,637,637,637,919,919,919,1051,860,972,977,860,860,1051,1051,1051,1051,1051,1051,873,771,873,873,771,873,771,873,873,771,873,873,771,873,873,771,659,873,771,873,771,873,659,761,805,980,858,1538,1180,1985,904,1263,706,630,1226,1226,1036,826,1100,1472,898,552,1095,1626,1626,1554,2626,1115,917,1078,1213,1163,1021,778,1213,1163,1213,1320,1047,1027,956,1296,1296,792,792,1025,1376,1489,1401,1376,1376,1376,1541,2387,1469,1519,702,714,739,550,560,685,1177,1702,1152,932,695,694,694,695,694,694,930,980,695,980,1220,615,612,1525,1062,1747,1032,1502,1171,1121,1119,1173,1325,2272,813,1835,807,1757,807,807,1024,1074,1503,1286,2170,813,807,807,769,807,1757,769,1239,769,807,1239,807,918,777,985,1089,900,1021,1007,555,1007,587,555,1034,1021,587,1034,1007,1592,1821,1866,1432,1500,1552,1552,1026,4062,1358,645,638,742,638,1578,1578,1578,2168,1082,713,817,1116,1116,728,632,632,713,1116,1116,952,1478,1478,952,952,1382,1623,1382,937,1382,1382,1450,1430,1270,1337,973,663,1065,1421,1421,1041,1369,1369,4528,577,293,722,590,722,1396,1396,497,557,497,557,1376,1376,689,424,424,851,851,1398,351,783,1018,529,529,731,567,1035,786,644,672,539,815,1688,1688,1559,1559,1006,853,2414,2414,2374,873,902,938,938,1000,454,642,649,454,900,7427,1997,1067,1067,1067,765,1067,853,1135,1135,1135,1135,700,1610,1535,3873,5603,705,681,667,1087,457,717,1282,1213,753,1213,1213,457,1213,1213,2181,938,341,938,793,341,793,341,378,642,818,966,1590,951,2232,939,2716,1397,1420,774,1405,1450,844,856,783,721,711,692,1116,1116,1006,1889,1035,1354,1230,1789,1420,2100,1478,1424,1166,3419,848,1800,1032,766,823,846,861,1624,1826,951,777,777,1071,820,820,783,1023,1060,1060,1097,837,1608,1630,839,716,828,876,1181,436,673,883,1661,974,1105,714,714,1500,668,957,957,895,909,909,1169,1215,796,956,1294,1294,821,839,939,714,1222,1222,677,952,952,861,1087,943,923,923,711,711,955,906,1186,657,1083,1340,1116,1116,619,823,1737,1737,1177,906,1011,1011,1011,1090,1358,1235,1341,964,1155,1292,1212,1047,1129,1040,780,1297,1527,966,864,864,1064,1222,727,938,938,938,813,1118,1068,1211,833,1502,933,836,836,1100,1582,1055,1055,756,2750,842,842,750,970,1044,1044,1044,1081,1302,1061,744,963,1136,1997,1082,1174,972,918,1032,1268,1172,1291,916,1111,1001,2560,725,1046,646,676,999,999,1338,962,1132,672,672,682,852,852,742,756,756,752,921,1010,757,1476,1038,1089,976,976,1071,1071,743,1104,704,644,1502,704,836,1078,1078,931,922,902,682,1025,1025,965,1792,1795,944,772,749,1302,1156,700,1052,765,1358,646,705,600,1017,1040,700,1162,1064,790,644,1273,1012,826,600,1244,635,836,836,936,936,936,683,647,1154,921,979,1268,1268,1009,1009,771,1008,790,1062,1069,738,1382,988,853,853,988,988,1116,988,1072,1248,1454,1454,1001,692,912,912,912,912,912,731,626,1250,1250,829,789,763,1081,1364,1382,1420,590,1180,992,736,736,995,832,786,556,1073,1283,980,608,872,872,835,824,850,902,909,721,1303,350,1027,728,768,839,923,609,720,1038,1210,1058,911,973,584,1486,548,664,750,859,1684,704,836,836,1136,794,794,999,1098,1098,1248,1081,1081,981,1675,1675,1675,655,636,922,950,1590,1590,790,1123,964,964,912,836,1352,961,1352,840,852,1012,1012,1227,1144,1144,1216,1038,1071,1521,1118,1059,1143,1150,1150,838,1000,1000,940,940,949,738,738,834,837,1260,1260,1266,1266,1055,1148,928,1361,1140,1140,824,732,732,838,756,906,913,1089,1012,803,803,959,1118,1118,986,1116,746,882,948,661,850,962,1007,998,1682,1113,1129,883,883,1319,854,682,1459,1459,682,993,896,896,1062,801,801,1029,921,1237,779,779,733,733,738,728,728,1251,1251,909,930,724,924,1017,1017,960,907,991,823,1078,1044,1284,770,770,770,771,774,1092,1822,945,1724,1119,759,1270,902,902,720,961,836,832,728,680,1267,932,788,788,1120,820,1053,1053,919,919,1353,1122,783,762,836,768,720,1489,1489,927,1442,1442,1144,2021,712,909,909,1049,847,694,720,1217,696,696,858,1454,1454,1454,557,1545,861,822,822,800,800,455,784,1354,1354,841,872,1912,743,743,418,418,418,418,871,1049,1049,1059,1038,1278,1278,1008,718,913,913,795,1075,902,639,1064,929,924,912,759,784,825,717,717,587,742,742,718,966,665,874,1021,936,936,1181,1147,930,930,722,722,899,714,711,971,1299,1190,730,811,660,1116,767,767,731,976,775,781,920,920,972,2523,788,932,821,848,976,890,993,1075,975,975,864,1006,750,768,869,559,937,988,1037,956,688,864,864,765,921,921,799,720,950,950,1181,1181,608,807,774,576,868,868,1239,1239,891,891,810,1040,887,634,687,687,628,851,788,788,806,643,1075,804,1040,1040,944,1046,1023,1023,2157,976,1436,954,954,1340,1340,1065,803,929,874,1490,913,708,708,799,793,793,817,715,672,672,960,960,1470,828,1136,3663,956,956,2200,1374,645,464,464,588,468,1041,1041,409,559,374,485,485,689,638,898,651,646,653,1637,1160,823,823,1081,2542,1975,1086,1586,1574,1722,1924,1618,561,561,563,1142,587,1758,1840,1494,1494,1500,1816,804,914,604,1887,1391,1906,1916,1147,1146,1104,1104,742,1461,1104,922,1410,774,1900,1258,1273,783,651,1273,1344,994,1809,687,968,1285,1458,1089,2937,1434,1854,1854,1197,913,1426,1595,1056,647,1147,1166,1743,1450,1535,1271,1578,1258,1106,970,830,1340,1340,1478,649,667,1276,1128,1728,1147,1357,1336,1704,1062,1891,2208,1353,1922,1473,1366,742,1427,1427,1151,1149,1217,960,960,1730,2036,2036,1341,827,1261,1144,1216,509,509,1296,1341,740,527,987,1386,1593,1593,1828,1499,880,880,2247,782,1350,2116,2385,1916,1473,1742,1608,850,1156,922,890,1368,2088,1956,1928,1286,1286,653,1500,1652,811,811,1360,1791,2780,1836,848,848,608,1158,1354,1052,998,788,904,1211,591,959,1465,826,1337,2634,1770,2617,2617,900,2058,1738,1786,682,847,847,1446,2448,1372,1372,2856,717,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,300,944,944,746,746,1008,1714,1061,1449,1655,2082,764,975,975,1087,1087,1348,2056,480,1178,1842,1528,2134,690,689,689,1903,1472,2250,2250,1539,1324,1324,905,1377,1343,1343,3317,1757,1616,667,1552,1650,1202,957,1023,760,1889,1826,2301,883,883,1099,616,872,444,872,2206,1264,1049,947,1370,1161,583,606,1067,1988,704,996,1897,1284,671,1080,1067,1603,769,1091,1091,662,662,662,1032,1033,644,1637,1287,3137,3207,1081,962,1849,1706,1501,1505,799,965,950,950,950,976,1060,2243,1493,1722,1284,1548,1554,1298,1415,1197,496,496,509,726,3373,960,960,1496,629,1080,1106,1441,1886,1024,1710,1438,442,447,562,538,490,700,500,1536,1844,1635,1923,1923,1592,791,858,801,2370,1319,2056,1508,1898,724,1536,1531,1531,1767,1992,2824,510,1572,1968,2128,663,1582,2093,1143,1143,2064,2093,1143,1168,1168,1168,765,1944,1944,2104,807,916,916,3520,4725,4131,2852,6344,3330,3907,1837,2482,2225,1705,3402,3402,1263,1424,2092,2092,2917,938,1583,1328,2291,2150,3495,1521,3036,1216,2806,1510,2381,1910,2602,1473,3549,4390,5202,3016,3332,1824,4610,4633,5061,6476,4237,5501,4689,4689,6577,3544,4540,4424,3822,3822,2782,3894,4619,4649,4712,1004,1590,2430,1173,2407,937,2156,819,2146,702,1057,1057,1575,1108,1806,2076,1144,2084,1884,5767,2106,2484,2450,4460,3349,1714,1358,1432,1833,1372,1009,1009,2451,1267,3091,2658,5042,2040,1880,3451,3367,1917,1278,1725,1854,468,467,1045,381,579,1137,1023,917,1012,1019,956,1314,939,1051,1051,1456,975,1075,1270,1990,1148,1397,2107,2797,1004,880,2668,2415,2668,1524,700,1288,2328,2328,1470,781,1152,750,925,875,1336,1303,1297,1336,1336,1303,2653,1336,1336,1614,2342,1032,848,570,570,739,532,825,598,775,1319,1133,741,741,751,554,766,1305,488,494,875,747,608,1091,791,1091,2321,2451,2458,2298,1062,988,1228,988,1839,3193,807,807,1858,2634,2634,1417,1558,1435,1435,1072,453,505,891,1895,644,400,400,1982,1065,1513,1213,1528,1069,1092,1288,1037,1075,1075,2462,1075,920,1782,1704,1726,1070,1024,935,2510,2648,2648,1972,1017,914,2117,2490,1171,2924,2444,1075,1442,1171,2080,2080,3269,1836,3881,4294,2040,1920,1920,2317,2337,3063,3063,2645,3653,3304,2967,2114,1866,2959,3676,4298,3497,3354,4593,3790,2433,3345,6002,4570,4092,2856,2856,2936,4870,2627,3010,2362,2215,2920,2096,2690,2690,2203,2901,2901,2901,2901,2959,2959,3833,2368,2368,2025,1786,2453,2453,3076,4293,2138,2138,4024,2172,2343,2505,2312,3387,3753,3753,1249,2521,1410,3188,2108,744,2713,2713,2713,2713,2713,2008,2008,2153,1857,2220,3395,1987,3414,2709,3309,2994,2833,2833,3384,3384,3384,3384,3841,4580,2557,2766,2938,3256,3256,2024,1975,1025,1229,1301,1196,1108,725,2596,2318,2908,2259,2457,3187,2747,761,772,2670,2508,902,2374,1561,1561,2527,4808,2624,2145,1133,623,1813,2269,1284,4884,2305,2305,3139,3139,3139,3140,2898,1872,3603,3415,4345,2793,3184,3184,2521,2591,3431,3431,1408,1408,1584,1584,2484,2231,2079,1944,2079,1944,2249,2249,3929,4166,3220,1112,765,1077,1083,1303,744,2668,2310,932,941,766,701,1085,1085,996,1205,2972,2972,2970,2793,4507,4673,3515,1009,1549,1854,2885,1351,2131,2639,3192,2364,5981,3841,3455,3502,3254,3455,4192,3729,6684,3757,3612,1488,1488,1248,1644,1846,1404,1248,1846,1404,1846,1846,1846,2976,1404,1846,1846,1248,1404,1404,4420,3353,3353,1846,1107,782,638,1227,814,1227,782,1002,638,782,814,1107,752,752,2041,1522,1185,963,1144,1827,887,1144,887,1273,887,887,887,1335,3376,2870,1313,743,743,789,1176,1313,872,1131,743,1096,902,1096,1096,1176,1237,1272,1775,1953,2031,2101,2434,3735,2101,3254,1279,2257,2490,2100,2100,1454,1130,1396,1690,1690,765,1556,1089,1094,1094,769,1607,1392,1735,1452,1560,1750,2465,2430,2714,1889,1889,1889,1326,1312,1191,1156,1798,1230,685,631,1080,1080,1080,802,1080,847,1932,2500,2665,1303,1281,1373,2995,2528,2762,1449,2904,1190,1190,1190,1190,1190,895,1022,1161,1161,2248,865,1057,1330,1499,2682,1891,1891,1891,2476,1891,1891,2535,1774,2307,1905,1317,1545,1210,1317,1258,1276,1317,1276,1255,1276,1276,2965,939,2212,2541,952,952,1580,1798,1749,1368,1368,2430,2430,2540,2636,3201,1537,1173,876,1226,851,1229,1178,1202,3147,1800,1622,2603,1696,1983,2590,3180,2224,3887,1975,1828,2278,2325,1800,3339,3372,3650,3296,3544,3004,3394,4159,3734,4220,4400,3490,5209,3527,5704,5704,8590,5861,5662,9694,4267,4331,4324,3449,3449,3116,3970,2435,2756,2756,2230,2230,2756,2435,2808,2435,2435,2756,2808,5700,2815,3257,3257,1817,2761,2761,1222,3885,1663,1170,3682,2202,2384,2202,2202,1391,1127,2510,1322,2358,1106,2599,2232,4997,4081,3160,2910,2351,2351,1645,2715,2182,2799,3137,3294,3418,4079,2994,1350,3567,3567,1042,4717,1216,1068,1056,1146,1087,3846,1215,3542,1481,2095,2801,1740,2774,2978,1217,3176,1147,2938,1360,1200,1178,1331,1001,1177,996,2210,1916,1292,1603,1239,2182,1917,3150,1395,1520,1520,2385,1825,1145,2551,932,1459,3376,1202,1738,1738,1258,2039,2026,1736,2336,2450,2398,1674,2441,3156,3156,5735,2261,3932,2028,5909,5909,3697,3149,5498,5498,21503,2357,3114,2710,2888,3251,5335,3578,4813,1166,1166,1169,1529,961,2155,1254,1568,3851,1163,1084,1587,1105,1129,1059,3827,2720,3230,1352,1370,2750,4387,1505,1700,2551,2042,2778,1508,2309,1242,1045,2615,1128,1072,1072,1141,1141,2792,2314,1081,2053,1894,1097,1102,2707,3331,4260,2662,1633,920,1590,912,2080,1221,2248,2697,1830,1012,1208,1323,1323,1323,2660,1280,1323,975,2146,1366,3109,3246,1152,1152,1160,988,1047,1500,936,1509,1296,2332,3169,3169,2941,1038,1180,1247,3298,2780,2440,1016,1411,1411,997,2972,2574,1300,1403,1609,1186,2266,1711,1322,1322,1220,980,1212,1220,958,1251,1294,2410,1892,1227,1287,955,2014,1926,1910,860,886,633,1032,1151,1089,1515,1146,1150,767,843,930,1095,1508,1251,922,1555,1386,1159,954,954,961,964,964,973,1189,1742,1742,1867,1630,2010,1910,1894,1418,4054,1029,1392,2082,1297,823,1038,1564,2447,2080,1930,912,1442,2538,1336,1224,1934,1044,2120,1911,1323,1323,2120,1323,1323,2120,1911,1272,768,768,1272,1272,1272,1272,1272,1272,1272,1272,1272,768,1272,768,1272,1272,1272,1272,768,768,768,1272,2528,1272,768,768,1272,1272,1272,1272,1272,1272,768,1272,937,943,639,943,639,943,943,639,639,943,943,1815,1626,1346,2702,1251,1099,2080,2556,1232,713,730,1498,1222,1228,1847,2263,2162,1801,1454,997,1053,1319,1000,1809,1012,1000,1210,1116,1173,2046,1013,960,1037,1037,848,2000,1980,1990,1911,1095,1083,1084,2000,2811,2480,2580,1182,1208,1475,1301,1382,1270,1239,1010,1417,1198,1198,1220,944,1317,1727,1535,890,782,622,1978,2700,2356,1466,3285,2699,2699,3584,2902,2176,2423,1559,3208,2706,1812,1933,1890,1862,855,984,907,1080,2082,1573,2317,974,1389,862,1341,916,1468,1867,1030,2173,2464,1095,2084,1833,1055,976,1239,2077,2812,2388,2388,4780,1300,2636,1318,3143,2100,981,981,1955,1276,2102,1606,3111,1203,910,1195,862,2964,2383,1401,1185,2879,2183,1991,1133,1128,1128,2368,1128,2598,2432,2148,1457,1540,1424,2584,1060,2772,2614,2937,2611,3235,1485,2231,1149,1168,2587,1152,1922,2336,3195,2472,2634,1767,3546,3546,1280,1280,1137,1126,2810,1078,2903,2166,1135,2676,3653,2400,3529,3346,1760,3773,2479,2455,1969,3727,3727,1150,3244,2048,2404,1408,1798,3338,3719,3476,2918,1128,1288,2793,1264,2204,2590,1470,944,2440,2440,1045,946,1429,2538,1288,1288,1580,1188,955,957,957,877,1010,957,1536,1355,2090,1400,1864,1650,1696,855,678,1187,1530,1734,1927,2512,1518,1043,1059,1491,1094,1639,1094,1280,792,1662,1353,1353,766,567,434,1931,985,1472,1472,1103,962,1628,877,1312,1540,1050,1050,1480,1480,1536,939,525,743,1079,953,953,1596,1892,1499,1274,1417,1161,1610,1610,672,1908,1169,1046,2152,1405,2128,1105,1536,1536,1159,2532,1339,1816,560,1690,1712,1911,1691,761,499,1013,1801,1518,1518,1540,1540,1926,1224,1608,1623,2128,1485,1496,744,1997,930,1099,1306,1182,2093,720,1847,1057,881,1096,1144,1997,1904,1032,1032,1211,2032,1792,1860,1083,1000,1000,1394,1557,715,1664,935,935,1120,1027,1554,876,2359,1140,814,1354,1117,1180,1006,1809,2678,1247,1798,2437,1396,1750,1738,1946,1984,758,1858,1834,1364,958,1863,1614,1614,1469,1336,1619,1906,1352,1541,1541,975,1440,1416,1763,1677,1392,958,1032,745,1054,1244,1023,1658,903,890,820,1314,805,805,1102,1815,1232,1119,579,579,845,1404,1404,1404,987,1130,1130,1130,1339,1027,607,1085,952,831,1481,2113,1504,836,616,616,3722,1536,1536,903,863,1075,1072,1125,764,764,738,734,734,937,937,1211,767,787,863,863,761,753,1086,1156,1156,1250,2187,787,1006,1312,1234,1234,1053,856,856,739,746,751,1141,1472,822,822,1105,1373,1336,991,1164,1015,987,987,1531,1381,1381,758,1034,865,999,1159,972,1427,1616,1618,1463,1151,1151,1456,1098,1663,1663,1322,914,1033,940,1058,1530,929,1072,1163,1432,784,784,1185,835,933,1351,1351,2952,751,992,992,1051,910,910,919,1185,1185,940,1379,768,748,748,798,804,804,793,1054,1042,1587,1587,1268,999,965,1092,1083,1456,798,1278,1099,958,743,999,1205,1132,915,1035,1323,715,1028,815,1126,1307,927,927,1125,978,967,937,937,1114,916,916,823,1087,1018,781,895,836,652,887,1369,1061,637,570,723,855,1028,836,836,731,731,1105,794,640,1056,1094,1020,747,1067,1042,955,733,1042,694,929,895,886,1002,685,967,694,1030,791,876,922,968,1200,1228,403,403,1029,1029,1029,878,360,913,913,1229,750,864,707,966,668,668,868,663,707,1268,1268,738,738,806,1057,979,895,676,536,962,1043,693,800,1126,1020,1020,870,1072,906,1073,2096,1120,1160,1635,1050,748,1328,777,1314,808,808,800,800,1007,1003,731,1003,1003,1036,781,824,1008,1362,1471,737,1049,793,1345,1345,942,1008,1008,1008,2748,875,876,878,878,886,875,878,884,1225,878,851,674,998,1037,705,1136,1435,1373,711,558,720,486,486,486,1060,1060,1060,1038,574,429,800,996,902,622,943,1681,649,947,661,1313,639,844,555,912,932,1008,719,925,925,540,816,816,865,1441,1441,1444,876,1065,679,866,866,1335,1245,1245,707,707,773,832,690,860,756,672,1313,939,847,826,674,735,703,1202,1372,973,973,1029,818,1027,709,709,762,796,960,960,1022,1022,1022,1272,1610,763,788,788,764,732,1125,1041,1041,1041,780,936,828,939,876,849,1065,1078,734,734,953,953,1062,1319,1319,620,973,574,857,1383,1306,828,973,973,973,973,1214,1215,939,1523,1652,1652,1652,1314,878,779,1081,1081,959,1165,1165,1223,828,2091,817,890,788,1165,612,612,822,1001,1001,767,857,1000,1426,1405,812,706,706,1117,1273,1184,921,565,1129,2242,2242,784,956,712,822,1080,1066,2704,1040,804,1360,1082,1078,1118,1108,2228,728,854,854,1774,903,990,1289,906,968,968,607,2776,2776,1023,1023,1023,1023,1023,1023,1023,1071,1074,650,1008,789,1268,1268,1268,1268,1075,1075,882,1228,799,799,951,808,818,1027,826,915,1350,1226,1002,1002,675,675,2067,922,922,601,1098,802,922,1248,1084,906,798,725,725,1055,681,1893,723,1828,1343,1049,784,889,889,1018,1091,1091,867,1022,613,762,762,527,1268,1268,1222,1222,1214,1113,882,784,784,987,1141,1512,1250,808,808,654,771,771,1299,1404,1970,672,672,1047,997,997,1140,746,652,652,1297,1537,682,771,1136,682,1061,1023,910,796,913,902,768,821,808,808,1111,832,832,1016,1064,932,988,1744,1087,1040,910,1869,862,752,752,1157,755,755,1046,821,1466,921,1025,1024,891,832,832,929,1420,1079,1441,1441,1088,1062,1144,831,1034,717,1459,1459,937,1451,1317,990,990,990,990,990,1095,1236,1236,1095,1095,1095,1092,986,1095,1281,1369,824,1114,743,743,745,895,1087,880,911,1427,739,1623,862,693,739,945,945,945,1356,990,862,1356,1121,1121,736,1580,2221,1016,1014,1016,1017,1040,1390,825,1015,1526,926,923,1288,952,950,950,1780,947,947,1315,947,1211,947,1187,1381,947,1211,1211,947,1429,947,1918,1114,1865,1116,1123,869,1559,763,1611,991,1215,1215,1240,934,1704,1070,829,1454,1070,874,777,1139,874,1224,1672,837,1192,1192,926,1252,1401,1732,1232,1176,1176,1096,1096,922,1290,1235,1396,1556,1599,1120,1019,1774,3170,1589,988,988,786,786,996,1027,841,1203,827,988,940,827,1023,840,840,847,844,1033,766,840,1021,840,804,804,804,804,1257,804,1026,1026,804,1227,1733,1663,1038,1410,1081,1109,1120,1068,768,768,768,1232,1000,926,926,728,900,835,753,888,888,1125,1125,918,798,771,735,761,1132,1132,632,686,1272,1272,1068,924,841,771,771,771,771,1764,1091,1189,971,1151,961,792,1908,910,871,920,1040,1940,1940,677,1166,755,777,776,750,1314,1495,997,997,1001,1003,1481,1001,994,980,1082,1082,982,982,1082,1117,1092,1211,1211,1211,1213,1211,975,1407,995,1144,1144,1195,807,807,807,1072,825,825,1066,1066,955,955,768,999,1093,1067,1508,949,1690,768,768,949,848,768,1280,887,887,1092,972,972,1092,857,930,972,1261,887,972,972,1420,972,1434,1600,1600,1600,1600,1600,1600,1048,1242,709,1388,1388,652,1050,1062,1062,1180,924,988,894,1108,840,986,830,992,996,994,1038,1038,1261,1003,1419,1003,1003,704,1333,1333,1606,1291,1218,1025,1032,1010,1003,1011,1570,1012,1111,923,923,923,1103,923,923,924,880,774,874,874,774,812,812,944,1119,836,836,945,1361,811,1057,1057,1036,827,827,830,1004,1040,1159,1049,925,925,715,1245,946,742,742,742,859,1017,1154,998,715,1073,1073,1156,1095,818,713,715,885,851,742,858,742,742,742,1495,1343,713,1234,965,707,715,715,1006,742,742,715,715,742,742,845,1626,924,2034,1082,2064,2095,1876,1862,2065,1746,874,1378,971,1336,1013,1912,1924,800,1098,1098,1496,701,743,1729,1664,712,930,930,722,1035,988,1813,864,976,817,1289,774,774,699,975,699,701,1842,1225,974,1116,775,775,874,1114,1104,1104,1104,1104,1104,1167,972,972,1482,1529,1520,1853,984,2471,1922,1199,1760,2088,1593,2671,2549,568,2205,2205,1921,2294,2669,1593,1977,954,1153,1922,1922,2948,833,2278,2235,2310,2382,999,1123,2553,2216,2216,1736,1257,933,917,1956,1956,1956,2104,889,984,1651,800,908,1001,1052,1229,844,1919,1919,2523,2495,2134,1311,2345,733,941,1948,2451,3070,1628,664,855,1642,1487,823,1573,1847,1554,1554,1321,1379,1469,1885,1032,1434,800,2117,2128,1163,612,1881,591,2445,771,1057,715,1037,797,2083,870,870,879,1189,2341,4450,2787,2787,1858,1882,1222,984,2563,1887,1982,1579,1315,852,2634,1819,1819,2878,1892,1957,1957,2665,1510,1371,2178,2169,2495,3224,1382,3117,2406,3270,3016,3138,610,610,2940,1064,958,3610,3493,3479,1394,2378,2894,3120,2894,1056,2410,2410,1136,1190,1293,1598,4978,1492,1765,2862,1515,1260,1222,2674,2506,2249,1055,2998,1935,1279,1255,897,1598,1246,1210,2578,2205,1344,1344,998,929,1161,947,1411,1203,1898,1401,1766,2134,2681,2249,2200,718,940,1012,1036,890,1280,1224,1117,2278,1250,971,1934,1390,3472,4024,1245,1204,1884,2181,1057,2653,1054,1054,2822,1839,2395,1422,1276,1345,1011,1286,2282,2348,1005,1005,1358,1024,957,1220,1381,1110,2946,768,2701,828,1471,1471,1432,1976,1976,1554,1168,2045,2815,1211,1392,2661,1236,1503,1184,1011,871,918,1126,1380,1849,822,894,1125,2325,2516,740,686,1346,1132,1697,4058,3170,873,1019,1525,827,974,912,965,754,997,1815,1308,952,1066,1210,1210,833,833,837,826,924,2763,889,889,1032,1373,1307,2025,650,852,1323,1274,930,930,930,1310,944,686,833,833,774,774,2962,721,988,947,768,3254,742,3511,1375,2118,1733,1625,2108,1625,1080,1259,1148,1504,1504,2022,745,749,2105,1006,1099,1313,1051,684,1115,809,637,1162,1162,885,670,670,936,885,885,936,1162,936,1070,1070,1020,1279,1278,706,706,870,1000,684,3325,3432,1120,980,1307,1263,3251,2559,1307,586,3254,3214,1061,2043,1734,1734,1735,1589,1045,1364,1101,912,1015,1263,1536,1450,1450,1450,1450,1542,1895,1542,1033,3398,1960,1326,3451,1310,3369,1572,1024,3557,3307,1403,1000,1063,974,1029,3136,3040,712,898,962,823,962,1015,846,1069,950,1258,1020,1348,1025,958,2994,2331,1054,2823,3509,1692,1120,3830,2829,3395,3395,2116,2116,2116,982,772,2867,1854,2684,3252,1868,1868,824,824,1134,3192,1038,1293,2296,818,2863,1407,1407,1536,1439,1520,1418,2948,2216,1165,2626,1932,927,927,933,3238,1262,1149,1040,3660,3022,3264,1439,3192,1713,3670,1716,3379,3094,3063,3338,2915,2921,2805,3400,3525,1722,3510,3265,2734,3404,2082,2082,3106,822,795,3539,977,852,3471,896,1167,2307,3225,3075,3217,3261,3261,3452,1122,1056,1818,985,988,964,1443,825,1144,1131,1828,1124,1063,1105,1096,790,915,1753,1753,1116,2148,1035,2952,3049,1200,811,2658,870,886,1556,2601,1497,1435,1196,2396,1045,1443,1680,1680,1579,3114,3114,2768,1067,2634,1250,2976,3161,955,1119,3200,622,2829,626,838,810,827,816,819,1346,689,906,989,1304,880,793,1225,1391,1198,1602,1602,1832,1832,1265,1165,1165,1165,840,1156,840,1195,3932,2880,3263,2422,974,2776,2251,1197,3213,1660,1666,6089,2160,2477,1824,1824,1824,1564,3682,4226,4303,3240,4859,4435,1458,2905,4646,1079,1427,1136,1231,1097,1434,1067,875,2158,585,604,1518,1518,2116,2215,2241,2240,2240,2039,1547,2551,2552,1152,1991,1415,2442,4953,3834,3610,1003,1206,1355,2014,3727,3162,1890,3815,3784,440,447,983,1880,1398,1559,1644,932,2148,2148,1935,2007,2684,3423,1389,4651,3951,3450,3768,3846,4538,4102,4579,2933,5075,3546,4084,4084,4159,905,3892,2734,3791,4326,3580,4293,1250,588,594,2074,2074,2142,2525,1891,2074,2074,3441,1680,2893,4299,3510,4191,3807,1111,4378,1109,2914,2914,4447,1781,2223,3706,1028,3834,3092,4424,1044,2536,2096,3917,2330,3913,4125,2493,3811,3811,3755,3045,1599,1117,1047,1600,1920,1920,1600,1440,1092,1289,1022,2050,4250,1726,3616,2112,1936,3709,4018,808,2961,4578,2492,4083,3863,1474,2937,2937,3892,3883,774,1076,1541,2180,1379,3532,3532,4116,4321,2870,3146,3575,4304,4092,3253,1969,806,968,3516,4207,3591,2779,4484,3513,802,3394,3647,3114,3731,3938,3938,2982,3088,3432,2208,3236,3236,3277,3880,2702,1486,4163,3205,3449,3791,3528,1044,3979,4071,3150,1449,3379,1864,4578,754,3475,1294,3150,798,2471,2978,3929,1207,2255,1151,884,3243,1381,1290,3700,991,3029,818,686,676,676,664,854,853,890,892,1009,856,856,1019,757,650,650,2868,2168,909,697,773,739,878,840,3270,3034,858,773,1208,1167,737,815,672,1343,775,940,996,1469,672,2555,2855,669,722,1035,1297,700,758,913,893,1872,836,800,1560,924,1004,2912,2501,1672,1406,672,672,672,957,1642,1448,1316,823,3079,675,822,888,576,1067,1005,1147,1102,678,643,1090,904,1102,1264,908,999,975,937,1991,2072,2033,1695,957,960,922,946,1285,925,850,994,627,859,725,846,717,2269,662,871,1155,939,939,1031,825,813,1139,821,1078,911,885,885,728,744,870,870,1440,1354,672,774,939,939,772,1266,786,2804,819,542,2068,1205,777,939,1756,1756,2289,2305,837,720,939,939,1291,1346,1994,1636,647,1853,2337,1856,944,2936,705,1104,1248,871,870,1006,1581,1337,757,941,870,2833,1105,884,1296,2653,2653,2653,860,732,3176,940,526,685,720,1059,1404,1806,1386,766,757,440,698,422,440,435,698,698,1167,783,971,937,852,763,2487,2487,980,802,802,1125,1629,714,709,1068,1297,778,1087,758,1543,1171,893,2049,847,1098,2160,2176,2178,1962,1964,2540,908,2532,1906,1866,1888,851,851,1876,1856,1960,1971,1921,1921,2006,2432,1387,1387,1892,1877,1877,1834,910,1349,2024,2024,2024,2482,1472,934,1050,1992,2429,1226,1046,1046,768,768,737,1076,744,1224,1850,2211,1844,996,845,940,1633,1450,1022,1738,1628,1628,1907,1029,2044,672,1210,1428,2876,2362,866,1119,1008,1001,864,1980,1980,1648,2135,851,823,2158,1031,936,1139,5274,1579,1058,1842,528,748,1695,960,694,1031,2006,2408,1904,1904,1067,1917,1002,683,664,732,838,833,833,1185,947,1000,998,792,1296,1153,879,758,722,1616,436,485,1118,1304,889,975,975,624,1400,865,989,989,759,755,710,1169,1169,876,1358,798,969,969,826,934,895,1837,1008,1040,747,747,936,775,813,853,1018,1203,1133,964,839,839,1146,988,886,1348,1460,1095,1502,880,1140,669,1993,865,1253,988,1020,1010,1373,975,873,1880,724,2202,826,2612,1635,1028,3317,3317,2800,2800,936,864,1752,1752,645,1405,1045,1045,1090,1090,1090,1240,1104,1104,1013,2090,936,1496,885,688,1024,1024,746,746,1261,1261,1600,1452,768,1292,1104,1104,1024,1024,1024,1653,1068,607,1057,968,1683,1252,1311,1311,1106,1139,688,690,690,707,707,688,1151,1282,1282,711,917,705,1301,1113,1160,1361,1361,1177,950,938,899,710,704,704,704,704,729,881,733,733,1156,707,1355,1223,710,1184,712,1236,710,917,736,1190,1190,707,1066,1066,987,870,1321,1321,1365,732,1162,735,1097,1475,915,1231,1270,1110,1121,1402,1028,1028,1099,1327,835,739,715,1121,1337,1229,1229,710,1185,1083,1474,744,744,1035,935,1280,1104,1127,838,838,1013,1100,1107,1235,1389,704,1057,1364,1030,984,928,928,704,734,774,1014,1014,734,704,886,704,704,704,2127,1242,1094,1308,1057,1057,577,1568,1371,1848,1578,1053,1885,1296,886,1641,558,994,2894,876,1032,720,1032,950,1064,922,922,939,1750,1137,816,1059,640,1153,803,1460,1716,1085,1205,770,1335,1096,1583,1096,1096,1096,1096,1096,1096,1096,1082,1309,1077,1041,1077,1587,1041,1041,1077,1077,1041,1041,1193,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1096,1894,1607,1595,1096,1096,1096,1096,1096,1096,1096,1114,1114,1154,904,907,907,903,903,1149,988,2199,1158,900,903,863,1512,1351,1390,988,988,947,1147,1484,1353,1353,1357,1619,1100,1107,1107,1363,1134,1130,1061,864,1116,1013,1353,1017,863,3270,3407,1082,1411,1777,1388,1248,1248,1170,1019,1276,868,940,1346,1019,1082,940,1082,1377,1377,1081,942,1015,942,1080,945,1353,1435,1513,1080,1208,2842,2702,1492,1950,1937,3474,2036,1451,1907,1572,1598,1294,1031,1031,1031,1031,1031,1035,1243,853,853,1035,1031,1031,1031,851,853,1037,1034,1285,1031,1034,860,1099,1099,1426,1099,1075,1071,1346,1162,1111,1111,1014,1007,1614,1384,1119,1014,1114,1099,1456,1099,1099,1099,1397,1397,1397,1348,1243,1031,1167,1689,1037,1037,1037,1362,1099,1031,1031,1160,1342,1160,794,894,894,850,850,1663,1308,1106,995,1108,853,954,853,991,988,1603,1310,1310,1310,1382,1382,1372,1014,1181,1128,1073,1538,1444,1862,1060,1453,1452,1145,1440,1172,1005,1267,1141,1145,977,1145,1145,1145,1260,1145,1145,1785,1094,974,1202,1242,974,974,1261,1145,1145,1145,1488,1488,1145,1261,1145,1145,1261,1245,1145,1413,1413,1268,1268,1268,1154,1154,1154,983,1210,1154,1454,983,983,1154,1268,977,1145,1147,977,1145,1145,1147,469,1147,1415,1147,1147,1147,1147,1147,1147,1261,1147,1147,1147,977,1261,1133,1133,1133,1133,995,1133,1133,1133,1133,1133,1133,1688,1688,1133,1133,1273,1133,1133,1133,1277,1133,1133,1133,1133,1383,1133,1133,1133,1145,1145,1261,1413,2903,1405,1145,1261,977,977,1145,1147,1145,977,1261,1147,1147,1261,1147,1147,1261,1261,1145,977,1261,1541,1988,2323,1988,2323,1147,1147,1147,1147,977,1147,1261,1261,1147,1261,1261,1147,1261,1147,1147,1261,1147,1147,1343,1976,2934,2102,2096,773,1920,1317,700,1498,787,1069,2390,1362,1164,1007,939,817,1428,1428,1458,1326,1656,926,1747,1162,748,1217,1217,1313,1096,958,950,950,999,1095,880,1175,1005,837,875,875,844,1052,1029,1222,827,1063,1065,1008,1018,880,885,1065,818,1008,1557,2099,1764,1764,3292,3018,1677,1456,1535,2198,1535,2198,2198,2529,1535,1535,1870,1535,2608,2198,1535,2516,1734,1535,1535,1535,1535,585,920,776,776,920,776,920,589,589,589,417,2658,1403,2036,1545,1545,1671,1315,1353,1253,1253,1704,1464,1081,1779,1663,1350,1737,1374,1401,1567,1605,1456,1464,1642,1642,1681,1968,1683,1388,1416,1416,1642,1393,1405,1405,1478,2071,2071,2134,1486,1284,1356,1316,1535,1502,1347,1278,1722,1919,1920,2509,2315,2141,938,809,930,792,1533,1328,1223,1753,1509,808,1778,1148,1028,957,1045,2035,1726,1726,1298,762,1419,1191,1421,1860,1860,799,814,1400,1039,980,1374,2064,1041,1382,1391,1029,1234,1234,1242,1022,1620,2239,1258,980,1532,2436,1468,1554,1038,1172,3053,1133,1133,2854,1027,904,1469,1765,1330,1132,4054,3203,1151,2145,1699,3366,1560,1726,2150,2150,3760,1866,1802,1802,1964,1762,1983,1441,1775,2067,1602,1952,3285,2123,2284,1503,1965,1730,1892,2956,3099,1799,1799,1905,1905,2956,2552,1799,1905,1799,1799,1905,2956,1799,1905,1905,2552,1799,3099,1799,1799,2552,1799,2094,1907,1862,1818,1559,1641,2379,2354,1701,2756,2549,2549,2123,2123,2158,2698,1912,3368,2580,2256,1978,2073,1981,2162,2237,2237,2095,2600,1799,2305,1545,2795,2323,2203,2058,2004,2136,2208,3042,2050,2075,2023,1896,1989,2421,2345,2107,2350,3072,2204,1905,2991,2516,3595,2390,2440,1726,2752,834,1044,1203,442,696,1451,1451,778,592,1094,729,729,854,854,854,783,894,843,843,630,601,954,751,751,659,780,778,778,1039,832,649,1515,684,740,910,923,894,1340,1104,1104,1216,1216,670,871,746,746,747,928,844,675,675,779,685,604,604,916,710,752,827,997,1370,1315,1315,1559,1559,725,828,840,840,880,899,1160,1160,952,952,1809,1809,1232,2403,1115,1247,1668,1004,964,1017,1037,1068,950,982,710,710,810,756,678,581,726,726,911,911,714,989,989,860,863,863,806,806,672,672,921,1365,1078,779,1340,747,1233,753,806,806,1225,1412,870,1458,1340,958,5763,3790,1294,1285,1174,1412,1300,1272,1355,1412,1412,3588,3178,2577,2548,4107,2595,2507,1811,3784,1888,1764,4419,4591,2182,2230,1888,1761,2587,2238,2587,2587,2087,1635,3178,3178,1761,1761,2588,2595,2588,1635,2116,2815,2182,2507,2182,1759,2860,2182,2718,2269,2269,2718,2577,2577,2838,2245,2230,2745,2236,1948,1948,1767,2258,1845,1342,2236,1342,2236,1342,1442,2725,1426,2021,2311,2729,2693,2755,2755,2311,2311,2726,2755,2378,2378,2077,2077,2671,2671,2729,2729,2378,2378,2655,2655,2895,2895,2021,2021,2348,2348,2126,2126,2783,2783,2852,2121,2888,2783,2935,2935,2755,2661,2378,2755,2021,2348,2121,2121,2935,2935,2655,2655,2311,2311,2729,2729,2935,2348,2021,2737,3718,3188,1037,995,1063,1037,1041,1001,732,1231,1400,979,1319,1159,1203,875,914,1042,834,1322,1178,1680,831,1120,1417,1811,1097,1087,892,1697,1775,1340,1041,1037,891,1024,1024,2078,1687,1369,1167,913,1061,931,1226,1067,2257,1638,2381,1909,8964,758,758,909,1748,1742,1132,1123,935,1050,1360,1051,2961,978,2512,876,2840,971,1786,1786,1200,1200,2058,1118,614,614,751,503,810,504,660,849,614,2030,1395,1012,908,707,751,871,890,1078,766,987,1278,749,749,1140,1140,979,1332,1027,2954,3010,801,848,928,803,774,848,801,821,821,720,720,796,796,720,1232,1030,1065,770,1096,1457,1598,1412,1090,1089,943,943,1013,950,881,1273,752,1296,1051,1231,1545,3546,3546,1139,1421,2168,894,937,3139,941,826,1219,838,838,2770,2770,1282,1044,914,3251,855,3204,2761,1160,1386,1386,1386,576,1386,576,1970,576,1904,1489,775,950,1176,1103,2946,2946,1218,2373,1527,1365,1365,1364,1361,1699,1717,2555,2354,1690,1472,1084,2448,1369,1603,1603,1424,1060,1952,1712,1596,3360,2537,1584,899,1657,2195,2832,1055,1442,1156,935,1733,933,1726,1683,2826,1005,3251,1540,2209,2209,3096,3096,1476,2188,3128,3409,2796,2796,1167,1544,3336,1330,3126,3126,1148,1253,1076,1294,760,1787,1490,3015,1191,1185,1191,1191,959,687,1082,1053,817,1255,1408,1420,1818,2070,1797,2162,3064,1730,1688,845,845,796,796,800,790,1635,913,872,1122,1641,1109,1109,993,998,2046,2208,2208,2306,962,962,2306,1814,3205,3205,2661,3439,2092,1558,1206,2339,3527,1445,1852,1708,1708,1261,2012,938,1777,1252,1267,930,932,932,928,1075,1035,1089,882,1145,968,1181,1084,741,1406,594,1683,1213,960,1260,986,988,986,958,1204,1220,781,2548,831,926,1144,1261,1162,1438,1256,1325,1322,1242,1150,1352,993,975,942,778,999,999,864,1001,1107,980,980,1006,1235,1176,1172,1014,1264,1264,1225,757,875,933,1836,1220,3972,1023,897,3107,920,2091,2091,1059,864,1838,934,1166,1604,1116,1083,884,1225,1225,1154,1070,1119,1119,572,996,1045,1402,2168,1395,1395,1435,824,497,630,869,656,629,1074,946,6459,2805,1213,2801,2801,1644,2904,2278,1248,1438,1096,1096,1630,1055,976,1182,1370,2072,1068,1424,1284,1031,1804,997,1044,1007,1100,1100,1100,1100,1053,1164,522,672,604,641,928,928,604,680,928,653,646,648,1051,1051,687,475,1008,687,1008,687,1054,475,1100,1054,687,475,709,709,969,969,709,617,617,617,617,531,562,558,463,842,1145,782,1256,954,2410,1846,1846,990,1017,796,796,1521,1485,2208,2255,1842,1841,1915,1350,1214,2050,1012,2384,1020,1201,2336,1153,1153,2254,4928,1642,1642,1061,1254,2793,2438,1113,974,885,2155,1707,3224,1078,1936,905,902,1548,874,682,682,459,682,1009,1009,757,414,414,810,810,1140,1140,810,1140,810,1167,810,1167,1140,1167,1167,1940,691,691,940,940,475,940,940,940,1626,925,882,1900,1967,819,819,1062,1102,853,2687,745,645,578,558,630,1705,2161,2484,880,1252,1252,1504,1504,1993,1262,813,2687,3034,1176,1466,1564,1508,1396,1772,1491,2619,1173,1849,1626,1897,1191,2482,2359,3046,3642,2038,2038,2185,1088,1785,3894,1045,3012,2860,2596,2357,4277,2218,2686,2077,2135,1368,1662,3409,3177,3714,3967,3646,4548,1512,3540,4167,2641,5767,4550,3264,1619,4176,3869,3940,1555,2584,3250,2156,1617,1626,2226,3273,1941,1941,2215,2850,4831,6133,4177,5298,1511,2740,4623,3123,4581,4581,3307,3986,1148,3754,2195,1424,1412,4145,4468,3602,3857,1926,5309,4743,4712,4815,4234,3154,3154,4702,3113,3196,4417,3513,1999,1427,2421,2158,916,4214,2462,2562,1335,1424,2505,2367,3205,1391,1218,1374,2638,1889,2712,2579,1171,5244,3118,4615,2097,2892,2383,1756,3422,4242,4242,3417,6670,1329,3673,3150,1972,1851,2316,4355,4680,4024,1273,2007,2680,2706,2548,1990,2751,3677,4504,4005,2182,1758,4828,6458,4514,1735,2071,2733,2807,5011,3206,2987,2337,4792,1780,1780,3865,3319,2151,2442,2046,3987,3721,1833,1833,3537,2256,1832,4258,4084,3005,1676,2748,3478,5070,3609,3131,3714,3353,1712,2431,1837,2534,2534,2706,5243,2743,2570,3339,5625,6423,3447,2799,960,960,1327,1236,1129,1220,1220,1374,1219,2209,816,1287,1002,758,1116,1116,759,1418,1418,1147,762,1247,1024,1138,1271,989,853,1513,1492,1221,1808,1489,1442,1560,2045,1450,1223,1253,3036,4436,3401,3287,1160,1411,1203,1375,1203,1402,1411,1366,1494,1278,1203,1366,1375,1494,1411,1521,1494,1866,1702,1702,1698,1698,1698,1698,1698,1698,1702,1702,1702,1846,1912,2037,1684,1077,1077,1077,2171,3050,2866,3717,2607,3217,1106,1035,1240,2575,2660,6133,1793,3865,2881,1691,1691,2159,5521,3079,2818,2538,3086,1843,1931,1251,1893,2249,1730,3248,5062,1911,3296,4553,4553,1815,4232,2007,2371,4018,4018,1696,4799,5488,5488,5032,2472,1873,1873,2310,2253,3123,3113,1829,5154,2641,4265,4373,2433,2301,4312,2523,1502,5573,2992,2992,2239,2239,1597,1557,1260,2403,2403,3279,2321,2321,1652,3369,1523,1715,524,1509,1122,1746,2262,1939,1824,3163,1928,2346,3648,4503,2957,3264,3169,3144,4373,3777,2431,2431,1171,1615,1385,1586,1080,999,1090,1081,1415,1615,1592,1655,1150,1580,1312,1312,1277,1277,1312,912,912,1312,1411,1312,1411,5531,3955,994,1650,1284,1442,994,1650,1480,1480,1284,994,1650,994,1284,1480,1650,1617,1617,1159,2126,1796,1715,2100,2126,1796,1715,2100,2126,1796,1715,2100,2126,1796,1715,1681,2396,1832,1795,1742,2468,1795,1713,1742,1832,1795,1713,1681,2468,1832,1795,1713,1757,3104,1983,1983,1983,1983,3372,1862,4076,2758,2758,3370,2163,2758,2758,2819,2219,2798,1635,1714,1859,1714,1694,1859,1694,1694,1694,1694,1859,1859,1682,2191,1682,2099,2191,2626,2827,2410,2416,2416,2410,2542,2542,2425,2865,2760,2542,2865,2542,2584,2829,3215,2152,2513,1667,1667,2648,2918,2719,2719,2838,1320,1320,3579,3215,2982,1556,1320,1320,1320,1320,1556,1258,1310,1310,1252,1282,787,787,1258,1258,1262,1262,994,994,1258,885,885,1258,1262,1310,1262,994,994,1559,1321,1321,1559,1321,1321,1321,1321,1321,1559,1559,1247,1321,1559,1321,1321,1321,1321,1321,1658,1912,2130,2110,2110,1926,1926,1926,1659,1926,1926,1659,1594,1900,2221,3320,3042,3351,3262,3350,3040,3320,3320,3015,3015,3350,3040,3040,3320,3320,3320,3040,3040,3015,3015,3163,3163,3350,3350,2173,2221,2221,3078,3320,3320,3040,3040,3350,3350,2392,2755,2392,3350,2219,2219,2440,2440,2116,2116,2429,2429,1872,1872,2149,2149,2429,2429,2091,2091,2442,2442,2116,2116,1872,1872,2138,2138,2393,2393,2429,2429,2149,2149,2442,2442,1872,1872,1872,1872,2440,2440,1894,1894,2116,2116,2080,2092,1794,2092,1835,2092,2092,2092,2092,1794,2092,2092,1842,1842,2092,2092,2080,2080,1835,1835,1794,1794,2077,2077,1794,1794,2092,2092,2077,2077,1835,1835,2080,2080,2092,2092,2599,1844,2311,2651,2651,2496,2903,2903,2092,2092,2729,2729,3198,3198,2346,2477,2905,2729,2651,2477,3198,2755,2903,2903,2671,3320,3170,3015,3320,3163,3040,2651,2311,2651,2960,2378,2126,2311,2651,2651,2755,2311,2092,1901,2058,2310,2040,2058,2310,2021,2040,2040,2310,2310,1901,2058,2310,2310,2310,2310,1991,2310,2040,2310,2021,2021,2040,2040,2310,2310,2058,2058,1900,1900,2021,2021,969,969,943,943,654,943,969,654,943,969,654,969,654,654,969,654,943,969,654,969,654,943,654,969,654,943,943,943,943,969,654,654,969,969,943,969,855,945,870,1200,1200,855,1200,1200,855,1200,945,1200,1200,945,2070,1200,855,945,945,870,855,1200,870,945,1200,945,1200,855,1200,1200,1200,870,945,855,945,2070,945,870,1200,1200,712,870,870,870,712,712,712,712,1200,1200,1200,712,712,1200,870,870,870,870,1200,712,870,870,870,712,712,1200,1200,855,855,855,1200,1200,1200,1200,855,712,870,1200,1200,1200,1200,1200,1200,1650,1888,1888,1650,1650,1888,855,1200,1550,1200,855,855,855,855,855,1200,1200,1200,945,945,855,855,1200,1200,855,1200,1200,1200,870,1710,1200,1550,870,855,1550,1200,1200,870,855,1200,1710,945,945,945,1200,1200,945,1380,855,1550,1200,855,1200,1200,1200,945,1200,945,945,855,1200,1200,945,855,855,1200,1200,945,945,1200,945,855,1200,1550,1200,945,855,1550,1710,1200,855,1200,1380,855,945,1200,1200,1200,945,945,1200,945,945,945,855,945,1200,1200,2145,1200,1470,945,945,855,945,945,945,855,1380,1550,1200,945,1200,1200,855,1200,855,1200,945,945,1200,2145,945,1380,1200,1200,945,1200,1200,1200,945,1200,855,855,855,1200,1200,855,1200,945,945,1470,1200,1200,1200,855,945,945,1200,1200,1200,1200,945,1470,1200,1200,945,945,1200,1200,1200,1380,1200,2400,1200,855,1200,1200,855,855,1200,1200,855,1550,1550,945,945,1200,945,870,1200,1200,1200,1200,855,1200,855,1200,855,945,870,1200,945,855,1200,1200,855,1200,945,1200,1200,1200,1200,945,945,1200,1200,945,1200,1200,870,870,945,870,870,1200,855,1200,1200,945,945,945,1200,945,1380,855,1550,855,1550,1200,945,855,945,945,1200,1200,1200,1200,1200,945,855,855,855,945,855,1200,1200,1380,1200,945,1380,1200,1200,1200,945,945,1200,945,1200,1200,1200,855,855,945,1710,1200,1200,1200,945,1200,945,1200,945,945,945,855,855,1550,945,945,1200,1380,1200,945,1200,855,2048,1795,2140,2614,2020,3931,1539,2214,2651,1820,1820,2253,2422,3525,1874,1351,701,701,701,701,701,701,948,948,948,948,701,701,701,701,701,701,948,948,948,948,948,1019,1019,1019,701,948,701,701,1019,1019,701,1019,1019,1019,1019,1019,1019,701,1019,1019,1019,701,1019,1019,1019,1019,1019,701,701,1450,1796,1450,1185,1436,1752,1796,1752,1968,1968,1796,1796,1796,1450,1450,1450,1080,1178,1080,1080,1080,1080,1428,1428,1194,1194,1428,1428,1194,1194,1428,1373,1194,1194,1428,1194,1194,1428,1428,1428,1194,1194,1428,1428,1428,1428,1194,1428,1194,1194,1428,1194,1428,1142,1142,1142,1142,1142,1142,1142,1143,1143,1142,1142,1142,1143,2220,1608,1907,2220,2322,2322,1907,1608,2067,2405,1608,1548,2025,1907,2405,1907,1907,2405,2025,2314,1470,1423,1458,1458,1599,1531,1670,1591,2484,1719,1589,1690,2116,1608,1482,2104,2188,1712,1758,1765,1810,2197,2197,1920,1645,1913,1004,806,1072,1633,1530,2196,2196,1964,1119,1039,1572,1316,1935,1200,728,1964,996,917,1487,1300,1656,1656,1740,1813,1367,1507,830,830,999,1129,1690,1205,1211,1205,1211,1092,1103,1092,868,879,1303,1609,864,972,1096,1462,1755,746,1334,1813,1813,1813,2688,2157,2157,2157,3346,3106,1118,1118,1261,1198,1178,1137,1137,1414,1222,1179,1179,1128,1177,1153,1148,1176,1176,1119,1435,2044,2044,2107,1706,1616,1706,1706,1300,1706,1616,864,1040,1040,1040,864,672,672,864,864,1032,1053,1032,2079,1684,1921,1468,2756,2756,1303,1247,842,1303,1247,1303,1303,1942,1643,1136,1942,1942,2357,1413,2695,2695,1191,1191,2119,1218,1218,2141,697,697,634,634,634,537,634,1121,634,634,957,957,1006,537,634,1247,1142,1142,1142,1147,1142,1142,1732,1148,1142,1142,1142,1142,1142,1255,1227,1227,1128,1620,1620,1621,1607,1607,1620,1260,1105,1057,1702,907,900,900,903,975,976,976,940,1187,876,1074,1156,1715,1489,1619,1743,1730,2210,1972,1324,1641,2110,2238,2238,1214,1214,1747,1747,2481,2481,1226,2069,1497,1226,1429,1505,1565,1226,1533,1226,1209,908,1094,1149,854,1120,815,811,1348,1661,1444,900,900,1187,1123,1123,905,903,903,1054,1243,903,1248,1567,1435,1502,1352,1552,1583,1009,962,953,914,1159,1133,1133,1358,1266,1264,1262,1074,1145,2345,2109,2037,1390,1826,1063,1063,1120,1048,1048,1063,1063,868,872,1291,1468,1436,1436,1436,1468,1468,1436,1436,1436,1436,1468,1472,1184,1184,1472,1472,1440,1472,1468,1436,1436,1436,1436,1468,1459,1841,1841,1841,833,1306,987,1024,1043,1023,1056,1056,1307,1023,1482,1506,1537,1721,983,819,847,847,1366,692,1375,1049,1315,1298,1708,1153,2743,1908,1104,1116,1145,1444,1120,854,1173,1173,1271,1075,1331,1036,1523,1192,1559,1442,1205,1431,1299,1315,1357,1204,1136,1645,1645,1204,1048,899,995,995,1094,1089,872,1060,960,1362,874,874,1002,993,899,3313,1019,999,1027,1006,1357,1019,1019,1006,1647,1089,1007,1315,810,810,861,810,944,810,861,861,810,944,944,944,944,861,861,944,810,810,972,972,972,972,972,972,614,614,719,1129,788,1129,1082,1082,788,1064,1416,1184,855,835,855,1045,1203,1045,1045,835,1045,1045,1045,1045,1045,836,836,1264,1010,1010,1010,1010,1263,1343,953,1074,1074,1352,1397,1124,1124,1355,1074,1397,1074,1352,1358,898,878,1142,1142,813,1058,1058,815,1060,958,958,1612,1984,806,806,820,1002,961,806,963,953,1065,1618,1618,1618,1618,823,1277,961,895,1395,1476,1109,1342,1322,1525,1029,1662,1277,1682,1334,1212,1212,1834,1834,1742,1742,1092,1452,1452,2030,1232,1740,1591,1983,1254,1407,1432,1420,1273,2209,1299,1700,1073,1263,1263,1297,1263,1115,1247,1073,1332,1166,1520,1836,1769,1836,1836,1963,1330,1421,1664,1664,1196,2028,1687,2186,1049,1650,1261,1436,1920,1920,2107,2021,2238,1439,3242,2776,1889,1987,2210,1082,1082,1211,1211,1082,1293,1453,1453,1075,1293,1293,1444,1293,1222,1320,1444,821,1211,1444,1444,1211,1211,1453,821,821,833,833,1630,745,833,1673,1673,1801,1470,1673,1673,1801,1531,1470,1666,1666,1666,1266,1266,1362,1266,1667,1666,1362,1362,1362,1666,1667,2754,2511,2754,1238,836,1030,1030,836,836,1299,1238,1299,836,1238,836,836,836,1623,1723,1769,1640,1769,1640,1769,1666,1266,1362,1666,1667,1666,1362,1131,1131,1131,1102,1131,1102,1102,870,1131,1102,1102,1012,1178,1178,1217,1012,1012,1178,1217,1012,1178,1217,1855,1855,1508,1508,1999,1508,2200,2200,1102,1102,1102,1102,1073,1102,1102,1131,870,870,1102,1102,870,870,870,1102,1102,1073,870,1073,870,1073,1131,870,1120,1059,1059,596,796,796,602,1234,596,1059,596,1180,1133,1066,1122,1134,1122,1122,1066,1125,1048,1078,1069,954,1312,1048,1125,1397,1312,1397,1320,1320,1320,1320,1063,1320,1260,1063,1200,1200,1200,1200,1320,973,973,973,1138,1138,973,1138,1138,1138,1138,1138,1138,1138,1138,1138,1138,1138,721,1138,1138,973,973,973,973,1160,973,973,721,721,721,721,721,721,1138,721,1138,1138,721,1138,1138,721,1138,1138,1138,1138,1138,1138,721,721,721,721,1138,1138,1138,973,721,1138,721,973,1138,721,973,1138,721,721,1138,721,721,1138,721,973,973,721,973,1138,1138,1138,1138,1138,1713,1713,1890,1584,1649,573,732,732,553,732,553,553,732,732,732,553,732,732,732,553,732,906,732,732,966,906,732,906,732,836,836,836,732,732,732,1582,1809,1890,1572,1582,1582,839,860,793,860,1807,1807,2946,1658,2083,928,703,703,948,889,703,889,590,792,1777,2656,1692,2316,1853,1803,2295,1501,2195,2732,2798,2672,1497,1234,1350,1325,1202,1033,1033,2749,2295,1033,1205,1037,1357,2995,1452,1452,1425,1663,1663,1697,1302,2317,2317,2023,2023,1453,1470,2023,1961,1961,1480,1480,2123,2123,1008,1200,1157,1157,1169,1157,1157,1043,1040,1294,1274,797,856,797,880,880,880,880,797,1128,1128,1128,874,1534,1534,1665,1534,888,1000,1000,805,797,1113,1113,1312,1312,1142,1137,1103,1285,775,775,770,770,717,835,835,1423,1363,1363,1600,1354,1642,1366,1368,1155,1358,1369,1155,1636,1070,1367,1727,1440,1070,1070,1480,1119,1119,1377,1190,1102,1310,1115,1119,1279,1115,1366,892,1650,1088,1115,1115,1419,1115,1115,1103,1149,1043,1043,1579,1088,895,868,1536,892,1247,892,892,892,1088,1958,1212,1428,892,1261,892,1088,1316,1058,1058,892,1365,1115,1115,895,1275,849,844,1118,1488,1113,1367,1261,1118,1334,876,892,892,1416,1092,843,1154,1167,843,1154,1165,1215,1167,1154,1165,1154,1117,1215,1458,920,920,1387,1088,1218,1487,1296,1256,1256,892,892,1297,883,1337,2968,885,1716,883,883,922,1174,1289,3394,1716,2593,1118,3647,3596,2557,2990,2990,2244,2026,2026,987,1079,1082,712,4027,983,3746,1233,1313,2511,2511,1199,1299,3634,1343,1309,1811,2587,2587,1975,1562,3464,4349,1728,1728,4040,1047,1222,4362,1142,1224,1224,1031,1452,1215,4184,4024,1721,3535,1527,1527,2084,1427,2370,1611,1552,1674,3344,2731,2731,1329,2750,907,2058,2058,954,1180,926,1026,2336,930,1212,763,1687,930,930,1400,798,1534,1228,1227,1333,859,859,1431,1225,1193,956,1092,1867,2939,1082,1041,856,897,1044,1227,1529,950,950,1223,1082,950,1391,860,859,1001,1082,986,1047,1047,1082,1146,1144,1483,1287,849,1290,1466,1329,1058,842,1550,1281,1251,1704,1423,1320,1326,1963,1402,1402,1345,1904,1412,1776,1264,1264,2690,1362,1025,1720,1642,2400,1066,1644,1510,1585,1320,1134,1134,752,917,917,752,801,1175,1175,1175,917,917,752,752,1175,1175,1175,917,917,1309,700,700,945,1726,1428,1428,1509,1428,1428,1509,884,884,890,890,890,913,890,1029,784,1029,1029,1029,1061,784,1029,1061,784,784,1029,784,1029,1035,1029,1029,784,1029,1029,784,1061,2550,2090,1574,2704,1980,1980,1887,2801,1458,2192,1286,1396,1861,1861,1286,2105,2358,2105,2426,2123,2181,1760,1800,2935,1760,1760,2530,2530,1814,2212,2212,1861,2212,2114,1814,1286,1386,1286,2212,2114,1861,1825,1019,1720,1720,1825,1825,1895,1622,1720,1720,1895,1200,1200,1000,1200,1500,1012,1320,832,1568,1200,1000,1300,1200,1200,1500,1300,1200,1500,1500,1500,1500,1200,1320,1149,1500,1500,1100,1200,1200,1100,1100,1149,1149,1149,811,1173,1149,1270,1535,1535,1173,1535,1149,1149,1200,811,1173,1173,1300,1300,1300,1500,1300,1100,1200,1100,1100,800,1300,1173,1173,1100,1100,1173,1173,1270,967,1468,1422,1675,1674,1674,1412,1401,1830,1866,1274,1675,1738,1683,1852,1932,1944,1894,1675,1974,1836,1956,1718,1918,2142,2140,2140,2394,2436,2023,2023,1961,1961,1685,2023,1141,1480,1480,2023,1480,2389,3221,2023,1961,2023,2123,1480,1961,1961,2031,2036,2492,2380,2380,2264,1453,1453,2023,2023,2940,2575,2296,714,714,914,914,914,914,728,728,924,924,891,891,1247,728,714,888,888,888,728,914,914,1247,728,728,728,914,914,914,808,1050,1050,1050,1050,740,1050,735,1050,740,754,1050,1050,2389,2242,1374,1536,1536,1818,1707,1410,1716,2383,2383,2347,1536,1388,1374,1535,1531,1294,1410,2333,1694,2314,1448,2174,2312,1756,1972,1923,1908,1972,1758,1972,1908,1753,2204,1907,2085,1809,2204,2175,1764,1764,1681,2175,1776,2204,1660,1820,2477,2203,2267,2203,1820,1979,1979,2496,782,782,1217,782,1133,1133,1133,1238,1133,958,958,1238,1238,1217,958,1133,1556,1556,2100,1471,1655,2066,1655,1471,1908,1300,1300,1547,1547,1337,1904,2210,1868,1936,1972,1547,1265,2225,980,1247,1004,701,1004,1004,1223,1004,1004,1004,980,1994,1503,1503,2763,1506,1214,1517,1517,2113,2012,2226,2226,1966,1744,2248,1744,1262,2521,1547,1771,1780,1262,1908,1832,1972,1300,1368,1449,1449,1449,1449,1449,1449,1506,1534,2335,1489,1642,1170,1264,1500,1500,1489,1320,1298,1320,1284,1299,1298,1364,1299,1299,1299,1364,1299,1364,1299,1320,1364,1284,1364,1299,1284,1364,1284,1298,2357,2769,2489,2354,2357,2769,2489,2023,2769,2512,2354,2769,2356,2357,2231,1612,1612,1612,1631,1612,1572,1100,1408,1100,1536,1408,1584,1584,1584,1408,1408,1408,1100,1584,1100,1584,837,837,860,860,860,946,900,900,900,900,860,837,837,837,837,860,860,946,1408,1408,1408,1584,1584,1584,1584,1584,1408,1408,1408,1408,1584,1408,1408,1584,1408,1100,1100,1408,1408,1584,1584,1120,1584,1584,1440,1440,1632,1440,1584,1440,1584,1440,1440,1584,1584,1440,1584,1632,1584,760,760,886,886,886,993,1003,1150,1150,1003,1003,1150,1003,1750,2181,2407,2206,2815,2330,2248,2330,4111,2190,2206,2815,2206,2312,2815,2205,3241,1224,1261,2705,1264,1233,1193,1193,2201,2201,2756,1469,1532,1227,2264,1940,2703,2925,2201,1918,1931,1931,2201,1816,2111,2111,2906,2186,2844,2844,1666,1192,2066,2020,1562,1931,1931,1546,1541,1863,1931,2247,1988,1817,2198,1770,2201,2201,2224,2066,2216,2224,2288,2288,2284,2006,2006,2224,2201,2204,2204,2201,1918,1918,2204,2204,2201,1240,2709,2792,1379,1627,1627,1546,1546,1921,2125,2125,1609,1614,1753,1913,2224,2201,2201,2201,1918,2201,2201,2201,2764,2201,2201,1778,2201,1912,2027,3376,1227,2269,1227,1753,2647,2146,1932,2064,2310,2186,4189,3094,1316,1164,2719,1225,1316,1227,1234,2292,1442,1068,1449,1449,1442,1068,1449,1068,1068,959,763,967,769,763,763,763,959,769,959,763,952,960,960,975,952,952,967,952,952,952,952,952,967,967,952,952,952,952,769,763,763,952,763,952,952,763,952,1446,1446,1060,1446,1060,1060,3031,2871,2174,1852,2484,2125,2373,2721,1303,1303,1303,2771,2436,2755,2932,2738,3149,2598,2228,1297,1173,1360,1360,1360,1677,1316,1316,1326,1173,1562,1595,1595,1499,1845,1845,2421,2482,1502,2548,2548,1880,2072,2072,2362,2362,2953,1847,1847,1693,1877,2208,2208,2077,1944,2420,1724,1724,2659,2461,2506,2265,1584,1856,1024,1024,1224,1584,1024,1024,1024,1024,1024,1444,1444,1024,1224,1024,1444,3126,2834,1958,2894,2577,2326,2414,2557,2859,1539,3074,2719,2719,2112,3367,1981,2744,2369,2538,2010,1998,1660,1593,1593,1593,2018,1626,1626,1626,1626,2026,1626,2289,1976,1745,2672,2672,3176,2093,2410,2476,3010,1923,2618,2255,2250,1283,1450,1283,1280,1280,1438,1280,1280,1280,1438,1280,1847,1379,1960,1450,1450,1283,1283,1283,1283,1283,1553,1553,1930,1439,2001,1923,2795,1962,2122,2473,2102,2819,2311,2819,2473,2473,1933,1933,2700,2684,1933,1933,2795,2345,2795,2345,2345,2930,2289,2289,2289,2289,2783,2351,2930,2406,2391,2406,2569,2585,2585,3199,3199,2684,2406,2406,2899,3179,3179,2345,2345,3180,1061,1331,1722,1727,1722,1722,1064,1064,1727,1331,1064,2330,1828,2512,2512,2291,2291,2512,1665,2383,2821,2388,1828,2740,2291,2740,1828,1828,2512,2512,2512,1828,2393,1775,2064,2067,2166,1521,1481,1481,1521,2597,2166,1617,2306,1851,1851,1903,1788,1824,1788,1824,1864,1864,1931,2509,2509,1020,1509,1509,1020,1682,1682,904,692,904,904,904,904,904,904,692,904,904,904,904,692,692,692,692,692,692,692,692,904,1052,1403,1186,1186,1052,1403,1256,1334,1981,1264,2223,2090,2098,2098,1631,1631,2024,2368,2769,2274,2203,1878,2202,1925,1000,1731,1494,1607,1109,1000,1731,1000,1551,1109,1607,1537,1109,1551,1537,1768,532,1537,1607,1109,1537,1537,1607,532,1560,1109,1560,532,1537,1768,1551,532,1768,1109,1551,1768,1551,1551,1551,1560,1109,1109,1551,1768,1999,1551,1560,1551,2841,1990,2841,1990,2841,1990,2841,2231,1568,1568,2841,2558,2558,3103,2231,2231,1741,1529,1433,1528,1378,1429,1378,1378,1433,1324,1529,1529,1324,1324,1538,1123,2041,1171,1429,1385,2207,1528,1529,1265,1486,1458,1486,1160,1486,1450,1450,1450,1107,1849,1882,2037,3171,2866,2422,2348,2985,1548,1550,1591,1436,1796,1548,1590,1830,1172,1172,1804,1040,1744,1810,1778,1778,1828,1031,2090,2090,1036,1804,1036,2311,1483,1516,1040,1040,1040,1027,1494,1170,1170,1170,1494,1170,1170,1170,1170,1170,1170,1170,1494,1170,1170,906,906,1104,1108,1170,1170,927,1108,927,673,906,2202,1516,1516,1956,2772,2141,1600,1471,1988,2100,2554,2554,1492,2374,2230,2360,2190,1871,902,2070,2070,2325,2058,2119,2073,2073,1666,1874,1874,1516,2178,1702,2262,1185,1182,1185,1185,1179,1148,1171,1290,1160,1161,1163,1446,1208,1182,1182,1182,1184,2160,1174,1174,1174,1174,1174,1105,1322,1174,1174,1411,1411,1322,1175,1298,1297,1237,1237,1157,1112,1131,1341,1188,1188,1381,1247,1175,1175,1533,1215,1175,1631,1175,1463,1175,1175,1175,1216,831,599,831,599,831,599,831,599,831,831,599,831,831,831,831,831,599,599,831,2396,2224,2382,1935,1419,1419,2025,1744,2382,2246,2229,2229,1596,2166,2320,1925,1296,1013,676,676,1296,1296,736,648,901,1013,676,676,1290,1290,1290,1290,1290,871,1015,1013,983,648,648,680,1892,1033,1710,1925,1402,1019,1925,1925,2180,4930,4411,2877,3476,3287,3287,2929,3061,4313,3315,3315,1372,2286,1372,2063,1890,1343,1343,1343,1770,2562,2426,2255,2426,1676,3072,3730,3615,3726,1761,1710,1321,1761,1710,1761,1892,1892,1710,1761,1629,1617,1458,1297,1119,1119,1119,1119,1119,1119,1119,1119,1119,1297,1297,1119,812,1119,1019,1671,1671,1321,1710,1762,1849,1710,1892,1710,1558,1710,1710,1321,1715,1321,1321,1285,1710,1617,1710,975,975,1657,1154,1154,1520,2063,2063,822,1180,1225,822,1441,1524,1646,1205,1406,943,1567,1635,1544,1317,1883,1052,1544,1317,1317,1644,1402,884,925,1441,1441,1567,1172,1644,1402,1635,1402,1445,1172,1172,1567,1567,1172,1560,1172,1445,1118,2159,1721,2159,1625,1625,1973,1973,2159,1890,2159,1085,1140,1085,1085,1389,1389,914,914,914,1259,1259,914,914,1389,1259,1389,1389,1389,1438,804,804,1024,926,1146,804,804,1024,1024,804,706,903,903,803,706,897,706,618,618,706,618,897,867,867,903,903,1050,1050,1050,1050,1050,1050,1315,720,1050,1050,1050,1050,1050,1115,1115,1050,1050,1050,1050,868,1746,1746,1381,1238,1238,1238,1311,1238,1238,1311,974,993,974,678,787,787,678,678,1034,678,993,974,812,669,683,974,672,1036,1105,1105,815,815,815,815,1105,1240,972,975,975,1246,1245,1028,1070,1070,1036,1036,1028,1028,1036,1028,1070,1028,1070,1070,1345,1924,1632,1345,1632,1632,1632,1632,1345,1601,1345,1632,1310,1310,1310,1310,1909,1909,1345,1960,1909,1441,1441,1441,1441,1231,1231,1441,1747,1766,1886,2374,1746,2350,1766,1886,1886,2746,2855,3162,2381,2074,2349,2349,2349,2365,2056,2305,1987,1471,1453,1767,1821,1899,1984,1767,1767,1348,1504,1576,1529,1205,1205,2331,2719,2583,2269,2588,2173,2688,2594,2688,2688,2703,2365,2307,2376,2307,2307,1911,1926,1985,2365,2205,1985,3803,4462,1796,1984,3926,3646,2352,1658,1495,1714,1495,1713,1714,1714,1718,1603,1718,1603,1718,1638,1969,1873,1467,1202,1502,1633,1965,2013,955,955,1219,955,1219,1219,1041,1219,955,955,955,955,1219,1041],"yaxis":"y","type":"scattergl"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Built Before 1980 (1: Yes, 0: No)"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Square footage that is liveable"}},"legend":{"tracegroupgap":0},"title":{"text":"Square footage that is liveable v. before1980"}},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('f2dde298-4930-4351-bc72-ee7b23189ed9');
+var gd = document.getElementById('deb7ec8c-0bb1-47f3-932b-b74a1aebae1e');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -4965,9 +4965,9 @@ <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
                         })                };                });            </script>        </div>
 </div>
 <div class="cell-output cell-output-display">
-<div>                            <div id="1a5c20ce-234e-4701-8288-91a60d6e4491" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("1a5c20ce-234e-4701-8288-91a60d6e4491")) {                    Plotly.newPlot(                        "1a5c20ce-234e-4701-8288-91a60d6e4491",                        [{"hovertemplate":"before1980=%{x}\u003cbr\u003ededuct=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"","showlegend":false,"x":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,0,0,0,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,0,0,1,1,0,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,0,0,0,1,0,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,1,1,0,1,1,0,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,1,0,1,1,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,1,0,0,0,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,1,0,0,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,0,0,1,1,0,1,1,0,0,1,1,1,1,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,0,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,0,1,0,0,1,1,1,1,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,0,1,1,0,0,0,1,0,0,1,1,1,1,1,1,0,1,1,1,0,0,0,1,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,1,1,0,1,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,0,1,0,1,1,1,1,1,0,0,0,1,1,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,0,0,0,1,1,0,0,0,1,0,1,0,1,0,0,1,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,1,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,0,0,1,1,0,0,1,0,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,1,0,1,1,1,1,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,1,0,1,1,1,0,0,0,0,1,0,0,1,0,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,0,1,0,1,1,1,0,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,0,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,1,0,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,0,0,0,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"xaxis":"x","y":[0,0,0,3220,0,1000,0,0,0,0,0,0,0,0,5300,4200,0,4600,0,3750,3200,0,4500,4350,4312,3270,0,2000,5000,0,4300,4095,4035,0,4860,3960,1490,4000,0,0,0,0,3000,0,4000,3317,2700,0,5500,0,4000,4396,4440,5800,0,2990,0,0,0,1630,4500,0,0,0,6000,0,3000,3500,0,0,0,5280,5252,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,0,0,0,8281,0,5000,3742,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6375,500,7550,3981,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,5440,5157,5000,0,0,0,0,500,0,0,7470,0,0,0,0,1688,6960,0,0,0,0,0,4980,1560,6535,2613,0,0,3400,0,0,4995,0,5000,0,4460,1294,13975,0,0,0,2755,3930,0,0,0,0,3580,3390,0,0,0,0,0,4200,0,0,1500,0,0,8000,4921,8000,3500,0,5198,5970,5285,5000,0,0,0,2362,3660,3476,0,0,0,0,1051,6000,0,2250,0,5921,3500,0,2000,4900,0,3500,5000,6500,5000,4899,0,2670,5720,2100,0,5000,0,0,0,2000,3356,2522,0,0,0,0,2940,0,0,0,0,0,3700,0,0,0,1000,0,0,1800,2500,0,3500,1780,1600,0,1900,0,1980,0,0,0,3260,5500,3815,0,4620,0,351,3013,4500,0,3750,0,3600,0,4723,0,4800,0,0,0,0,0,4500,4290,4000,4050,0,3900,6860,0,0,0,0,5418,4999,0,7000,3500,5056,0,0,0,0,5500,0,0,0,0,0,0,5295,0,0,3500,0,4050,5597,0,4000,0,1620,0,0,6220,0,4000,0,4400,5500,2289,6000,0,1000,0,3700,9537,5322,4000,0,5000,0,0,5000,0,5500,5910,2800,5530,0,3188,3600,3000,4290,0,4300,3897,0,0,4740,0,3630,0,0,0,4000,4655,5500,3000,0,6922,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4860,0,4000,5000,3212,5585,0,0,0,0,0,0,0,5250,1600,5000,0,5000,0,0,5100,0,4267,7634,6000,0,5000,6000,0,0,0,0,6500,0,0,1000,4758,0,5280,300,5280,5850,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3723,0,0,0,0,0,3578,0,5000,0,5000,0,3844,5846,6500,5000,5000,4116,0,0,0,0,0,6140,4500,5000,0,5000,0,0,7600,0,0,0,5000,0,4921,0,0,0,0,5000,0,5000,6500,0,3926,0,0,0,0,0,6500,0,3000,0,5000,0,4292,0,0,0,3247,5000,6000,0,5000,0,4971,5000,0,3292,0,0,0,0,4163,7390,0,0,6025,1320,3500,0,3559,0,0,0,4347,0,5250,3000,0,2000,3294,4950,0,5100,3678,0,1000,3750,10900,4200,3900,4616,4500,0,0,0,4500,4243,4000,4947,3815,3325,0,0,3783,0,3900,7879,0,0,0,0,3150,3540,0,4300,0,4122,0,1279,3635,805,3400,0,3585,0,0,0,0,0,0,0,0,4380,3600,4393,3000,0,0,0,0,0,0,0,0,4164,3903,5000,3450,3920,0,2547,2400,2500,4400,2000,1500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1984,0,0,0,0,0,0,0,0,0,0,4734,0,0,3030,0,0,0,0,1500,0,0,2000,0,0,0,3000,3593,0,4068,4800,0,3540,3600,0,2187,0,0,5000,4500,1565,0,0,3297,0,2090,5546,4200,0,0,0,4928,0,4000,3500,0,3750,0,4500,0,0,0,3000,0,4000,0,0,8000,0,1892,0,0,0,0,2700,3800,0,0,0,0,0,0,1000,0,0,3870,0,0,0,4200,0,3541,0,0,0,3900,0,0,4440,4000,2495,0,1675,4000,4950,2398,1500,2000,0,0,0,0,3000,0,4647,4000,8500,0,1500,4000,4800,0,1400,1100,5550,0,4894,5100,4050,3200,5000,2700,3000,0,2817,0,0,0,0,3863,985,0,3000,3685,0,0,5000,4300,0,0,0,2500,2640,0,3000,0,4000,0,0,3299,0,2850,0,4600,2600,0,4671,2800,3913,0,3800,0,0,3373,0,0,0,0,2150,0,3600,3900,0,0,6100,2940,0,0,0,0,0,0,4753,0,0,4197,3800,0,1530,5000,2000,0,0,0,0,3747,2956,1180,5000,3064,0,0,0,4515,2000,3630,0,752,4548,4454,0,0,0,0,0,2890,0,0,0,0,1515,0,1525,0,0,0,2973,0,4500,3100,0,0,0,0,3500,984,2727,4000,0,0,0,3096,0,3300,5000,3570,0,3520,4000,0,0,0,0,0,0,1436,0,0,0,0,0,0,0,0,0,0,3897,0,0,0,2000,0,0,4000,3500,3600,2250,4000,0,0,0,3897,4500,0,0,4500,4819,0,0,3900,0,2912,3900,0,0,0,0,4533,4000,3750,0,4700,4400,5423,2000,4500,0,3200,0,3750,0,0,0,3750,0,0,4360,1000,0,3000,3093,0,0,0,1677,5000,0,0,4000,0,4500,3382,0,0,0,0,0,0,0,0,8014,0,1500,2000,0,0,0,2500,2900,3060,0,0,3520,4500,0,4000,1025,0,3922,1000,1015,4200,3728,3000,0,4575,4000,2821,0,0,3000,0,0,0,1100,0,4025,4500,4437,0,3147,0,5000,0,2000,0,4017,0,0,0,4000,0,3800,2522,0,0,3450,3600,2670,4000,0,3349,3297,4200,0,0,3450,4600,0,0,3660,3555,1114,0,0,0,4500,0,0,0,3675,3894,1710,0,0,0,0,2000,0,0,0,2500,3645,0,0,0,3390,0,3507,2900,5452,0,0,4050,0,0,2000,3784,3923,0,0,0,4185,0,3000,3223,0,400,0,0,0,1720,4000,3813,3369,5940,5000,3000,6540,4000,0,1415,0,0,3840,4050,0,0,0,0,4050,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,4474,0,3150,3750,4000,2129,0,5425,0,0,4200,0,3900,5000,0,0,3000,0,0,0,3000,0,0,0,5852,0,0,4000,0,6000,0,0,0,4500,3000,3600,3000,0,0,0,0,0,2800,3000,4651,3240,0,4500,0,0,0,0,5000,0,5946,1370,4900,4385,1500,0,0,4500,4182,5926,0,0,0,0,6250,3800,0,1822,1500,0,0,0,3825,2383,3741,4400,3900,0,0,0,0,0,0,0,5000,1758,0,3600,3600,0,0,3161,9695,5000,0,4500,4000,0,0,0,0,4800,0,3300,3185,0,5160,0,0,5056,5100,0,0,2600,4000,1053,6000,0,3500,0,2580,5300,0,0,5900,0,0,6222,0,1953,6300,5000,0,0,0,2000,0,5100,5200,0,6800,0,500,4999,5500,0,0,0,0,4000,0,0,5760,3840,4855,0,5700,4128,1370,0,0,0,6274,2700,0,3000,5000,5320,3800,3900,5000,5500,0,0,0,0,1800,1000,5000,3308,0,0,0,0,0,3690,0,5400,0,4500,0,4600,0,2850,0,0,3500,0,2900,4000,4000,3484,0,0,0,0,3636,3000,0,3615,4890,0,970,0,0,2800,0,0,0,3240,0,2000,4200,0,0,1017,0,0,0,0,0,4500,1000,0,0,2000,2000,0,0,0,0,6000,0,5500,0,0,6000,5553,6000,3450,0,0,0,5446,7625,4859,0,0,0,4677,0,0,0,0,2500,5200,0,0,6366,0,3000,2391,3815,0,0,0,0,0,0,0,0,0,6000,0,6000,0,2600,0,5400,0,0,0,3283,6825,0,5280,5000,4000,3000,4980,0,0,2980,0,3500,6000,2500,0,5000,4283,5057,1880,0,5940,3000,3200,0,5500,4306,5640,4925,0,3900,5400,4150,5180,4890,0,0,0,0,2500,1567,0,4260,5000,5460,0,0,0,4500,0,0,0,4000,1510,4846,1440,0,4050,0,0,1370,1500,4350,0,4000,450,5643,3257,0,0,0,3687,4800,2437,0,0,0,4215,0,3750,0,3677,0,0,4200,4500,1380,4999,0,0,4422,3000,4350,2000,3800,3897,0,1637,0,3828,4800,0,4196,0,0,4983,5500,0,1280,0,0,3610,0,0,3700,4000,0,0,4500,0,3647,4400,0,4300,0,3500,2460,2615,0,3200,3000,4000,3660,0,2114,0,0,2913,0,2500,3458,0,0,0,3250,0,0,4500,0,2000,0,0,0,2663,4400,0,0,0,3200,5626,2200,0,0,5029,0,0,2266,5500,3592,5700,0,4350,3960,3297,0,5000,5775,0,4107,0,0,0,0,4537,0,0,0,5800,0,2469,0,3000,0,5690,0,5190,1750,4030,0,0,0,0,0,0,0,3600,0,0,0,0,4416,3467,2500,0,0,0,0,3897,0,4515,0,4050,0,3660,1350,0,0,3003,0,0,0,4680,0,0,0,3000,3552,0,0,0,0,0,3100,0,0,0,0,0,0,2790,0,4200,0,0,0,0,0,0,0,3493,0,0,4500,0,2972,4125,0,0,0,0,0,0,3676,360,2050,0,0,0,0,0,0,0,3051,4500,2608,3100,4110,0,0,0,4721,2904,4025,0,0,0,4000,0,0,0,3709,750,3500,4195,4400,0,0,2500,3750,0,2500,0,5000,3510,0,5438,0,0,0,0,0,5500,0,0,0,4500,0,3615,2365,2100,2675,0,1210,0,0,0,4400,0,0,0,3700,0,0,3342,0,4590,0,0,0,4550,0,4784,0,2387,9200,0,0,4260,0,0,4000,0,0,0,0,0,0,0,2188,0,1810,2999,5112,0,3000,0,3700,4375,0,4041,0,0,0,0,5023,0,0,0,0,5000,8450,0,0,1530,0,0,0,2700,0,5100,0,1200,0,5000,3267,0,3636,0,3570,2790,0,0,0,0,5400,0,4350,5250,0,4015,0,0,4375,0,0,2451,0,0,3500,2574,0,0,0,3500,4500,0,3200,1780,0,0,2000,0,3500,0,0,0,0,0,0,0,2000,3000,0,4375,0,5000,0,1582,2480,0,3030,1200,0,2600,2604,3100,3062,2670,2677,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5700,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3300,0,4750,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,500,0,0,0,6100,0,8332,0,0,0,3500,0,0,2720,0,0,0,6500,0,0,3000,5446,0,11500,5000,0,0,2000,0,0,0,0,0,2500,2350,0,2500,4800,10000,1500,0,0,9955,0,0,0,5000,6000,0,3000,0,8000,0,0,7500,0,0,0,0,0,0,0,0,0,0,7266,3747,0,4851,6000,0,0,0,0,0,0,0,0,0,0,700,0,0,0,0,5000,0,2000,5500,0,0,0,0,0,1000,0,0,1300,0,0,0,0,6050,0,0,0,3600,0,0,0,4180,0,0,1000,0,6500,0,0,0,7000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6800,0,5800,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3045,0,0,0,3670,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,5250,0,0,1000,0,4000,4000,0,0,0,0,0,0,0,0,0,0,0,4305,0,0,0,550,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,6154,0,0,3600,4500,4000,3500,0,750,0,0,0,0,0,0,5500,0,0,250,0,0,0,8000,0,0,0,3700,0,2500,0,3000,0,0,0,0,4400,0,0,0,0,0,0,0,1500,0,0,0,0,0,0,0,0,4500,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,1000,0,0,5000,0,6163,0,0,3000,5000,1373,2000,0,0,0,0,0,0,0,0,0,0,0,6500,5500,6350,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1400,0,0,0,0,0,3000,0,0,0,0,0,1500,3000,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3070,0,0,5000,0,0,0,4850,3863,5000,4000,0,0,1410,4000,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,6000,10000,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8000,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5300,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5940,0,0,0,0,8356,1600,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2820,0,4000,0,2500,0,0,0,0,0,0,0,0,0,0,0,6750,0,0,0,4300,0,2500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,2500,0,350,0,0,0,0,0,0,0,1003,0,2500,0,0,0,1500,0,0,0,0,0,3500,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,4322,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8998,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,5000,0,6000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4879,5000,0,2500,4500,0,5025,1246,5000,3386,0,0,0,0,6084,0,0,4000,0,0,0,2625,4571,0,0,0,0,0,0,4000,0,0,0,0,5340,0,0,0,0,0,0,0,0,5425,0,5600,3700,0,0,5900,5000,0,0,0,0,3000,0,5000,5000,0,2500,0,2820,0,3258,0,5886,0,2630,0,3750,6100,0,0,0,0,5000,0,0,1100,0,0,0,0,5700,3400,0,0,0,4000,0,4000,3655,0,3500,0,3500,4000,4000,0,0,5204,0,0,5000,0,0,0,0,0,0,0,0,0,2000,0,0,0,5050,0,3202,5000,0,0,5850,4000,5438,0,6900,0,4500,3000,5000,1750,0,0,0,4000,0,0,0,1750,0,4000,0,0,750,0,0,1554,0,0,0,0,6800,5000,0,4000,0,0,0,0,2500,0,938,700,5000,3800,0,1443,0,0,0,0,0,0,0,0,1500,0,4500,0,2000,0,0,4000,0,0,0,0,0,0,0,4000,0,1000,2000,0,7000,2410,0,1000,5000,1500,0,0,0,0,10432,6000,0,0,0,3348,5000,0,1800,6000,0,0,0,3200,0,0,0,0,0,0,0,4815,0,0,0,3000,0,0,4000,2745,0,0,0,0,0,0,0,4260,4500,3500,0,4500,5000,0,0,0,0,0,0,5500,0,0,0,0,5000,0,6500,0,0,0,0,0,5346,0,6437,0,5300,0,0,0,0,5337,0,4476,4000,0,0,4380,0,3525,0,0,0,5653,0,0,0,5284,5000,4500,0,0,1400,3000,0,0,0,0,0,6000,3330,0,0,4000,5100,0,4000,0,0,4000,0,0,0,0,5250,5000,0,0,0,0,0,0,0,0,0,0,0,4000,0,5834,0,4410,0,2700,0,0,5250,6081,0,0,0,0,0,0,3250,0,0,6000,7300,3450,0,0,4459,3000,0,0,0,0,0,0,0,0,0,7250,5835,0,4200,410,0,3000,0,0,5620,3800,3450,0,2925,5000,7500,2500,6500,0,0,0,2000,324,10000,7000,5000,0,6700,3400,0,0,0,0,2500,4000,0,4350,0,0,8000,0,0,0,4873,0,0,0,0,0,5000,0,0,800,900,5000,4800,3000,2000,0,0,5000,0,1028,5500,0,0,0,0,0,6000,0,0,3500,0,0,0,0,1457,0,3000,0,0,2000,2000,0,0,0,0,0,6000,3500,0,0,0,5000,0,0,0,0,0,0,0,5000,0,3543,0,1000,0,0,0,3482,1000,2500,0,0,0,0,0,4000,0,3000,0,0,0,0,7000,0,0,0,4125,5500,0,4600,5000,0,8000,0,0,0,8500,0,0,0,0,0,0,5000,0,0,0,7171,500,5000,0,0,9900,0,0,5000,0,4400,0,3000,3894,6000,0,0,2500,0,0,0,0,0,0,0,5650,7500,3000,0,0,0,4850,6500,3000,0,2125,6500,4254,1500,3900,0,0,0,0,1345,4416,0,0,4000,6000,0,0,0,0,0,0,0,0,0,6000,4500,0,6500,0,5500,6470,2700,0,0,7500,1200,0,0,0,9000,0,0,0,0,0,0,1500,0,3300,0,5000,7500,0,0,3000,0,0,0,0,0,5000,0,0,0,0,3916,0,6000,3000,0,4000,0,1250,0,0,0,0,8700,0,4000,0,850,3000,500,7000,0,0,4200,7000,2000,2100,0,0,3400,0,5000,5000,0,0,0,0,0,6000,0,5000,7000,2700,0,7750,0,9000,0,3000,7500,5000,0,0,5000,0,0,5000,6000,0,5000,0,4000,5550,0,500,641,4066,4600,0,2500,0,0,0,0,5500,0,6800,0,1500,0,0,0,0,4000,0,0,0,0,0,7000,5000,0,0,0,3000,500,0,3802,0,0,0,0,2850,5000,6600,1500,0,0,0,0,0,0,0,0,0,0,2500,5000,4400,0,5500,0,0,0,0,0,0,0,0,0,0,3200,0,0,4000,2500,0,0,3500,7500,0,0,0,0,0,0,0,1000,0,0,5000,0,4000,0,0,0,0,500,0,0,0,0,0,5000,5000,2500,2000,6800,10000,5000,0,7000,0,0,0,0,4000,0,3277,5000,0,0,0,0,0,5000,0,2550,0,0,4342,1700,0,1900,0,3300,5125,5000,5520,0,522,0,0,4500,0,4000,0,0,0,2200,0,0,0,0,4159,0,0,0,4500,0,2851,0,0,0,0,0,2700,3000,4000,1500,0,5000,0,0,0,0,0,0,0,5900,3217,3500,3589,0,4459,0,3000,0,4812,0,0,0,0,3000,5000,1000,0,0,5700,9000,0,800,0,1000,0,0,5000,0,10365,0,0,3600,0,0,0,2500,2700,2000,2500,0,0,0,4200,0,0,0,0,0,0,0,0,4000,0,5000,0,7500,7805,5000,3000,0,0,0,0,0,0,3750,0,5500,0,0,0,0,5400,0,0,0,0,0,0,6398,150,0,192,1000,0,0,1500,5000,0,0,0,0,0,9925,0,0,0,0,0,0,0,3000,0,5000,0,0,0,0,5000,0,0,0,8000,0,0,0,0,1195,0,2160,0,500,0,4350,1800,0,8355,750,0,0,0,4000,2495,5460,0,0,0,0,0,0,0,0,3000,0,3500,0,930,0,0,0,0,0,2000,5989,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3614,0,0,4665,0,0,0,6000,0,0,750,3350,5000,0,0,2000,0,4985,3000,0,8000,5000,7750,0,0,0,5000,0,3000,0,3645,5000,0,4000,6000,0,0,6000,4459,0,0,0,0,0,4330,0,0,0,0,7500,4686,0,0,5000,0,0,0,0,0,0,0,0,0,0,5000,5000,0,5000,5500,0,0,0,0,0,0,0,6750,0,0,0,0,0,0,0,0,4200,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1650,0,5000,4000,0,0,0,5000,6500,0,5000,5000,0,0,0,0,3000,0,0,0,5000,0,0,5000,0,0,0,0,0,5113,0,0,0,6500,0,0,0,0,0,6500,0,4500,0,2500,0,0,0,0,4900,7000,0,5000,0,5000,9900,3200,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3500,0,4600,0,4000,0,0,3950,0,4930,0,2000,3500,0,0,4900,0,5200,4000,0,0,0,0,0,0,0,0,0,2000,5000,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4700,0,0,0,0,0,0,0,0,0,4365,0,0,0,0,7500,0,0,0,0,0,0,3740,0,2500,0,2421,5000,7020,1014,3600,0,0,0,0,0,0,0,0,0,0,0,0,2500,5000,0,2500,0,0,0,2500,0,0,2550,4137,5300,4600,2000,5000,0,0,0,0,7220,0,3000,0,0,0,4826,4000,4200,3000,0,3200,3000,0,0,0,0,6200,2000,5000,0,0,3750,1000,0,0,4800,1200,0,450,0,2930,0,0,6600,0,0,4725,4900,0,0,5000,2000,0,2000,3000,0,0,0,1000,4546,0,3000,0,0,3542,4500,0,0,3000,0,0,4000,4120,0,0,0,0,0,0,0,4300,0,0,0,0,0,5000,0,0,0,0,0,5000,0,0,0,5000,0,1000,3483,0,0,0,4691,0,2913,4920,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,3375,0,0,0,3000,0,0,0,0,0,3270,0,3800,0,0,0,5000,1200,0,0,0,0,0,0,0,5000,6000,0,4000,0,700,10000,0,0,0,0,0,0,0,4400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3378,0,2385,0,1322,4000,0,0,0,0,0,0,0,0,0,0,3285,2380,3300,0,0,0,0,0,3000,0,0,0,0,3693,4625,5070,0,5500,0,2500,3500,0,0,0,5263,0,3200,0,1161,5000,0,0,6300,0,0,0,4500,4000,0,0,0,0,2532,2900,4000,4350,0,2900,0,5500,0,2000,0,0,0,4000,0,3500,0,0,5700,0,5300,0,0,3330,3500,0,0,3767,4828,0,0,0,4545,0,5100,5000,0,3000,0,3300,0,3868,0,0,0,0,3800,0,0,3207,0,0,3000,0,2000,0,5000,0,3066,3922,5658,0,0,4500,0,0,2375,0,5000,4000,0,0,4000,0,0,0,0,0,0,2902,2025,0,4000,0,5000,0,3200,0,0,550,0,0,3800,0,0,0,0,0,0,0,0,0,4800,0,4047,0,0,0,0,0,0,3772,3000,0,0,0,0,571,3500,0,3340,0,0,0,0,6000,4000,0,2600,0,0,1200,4000,0,0,0,4633,3800,0,1935,2500,0,5580,0,5000,0,4497,0,0,3375,0,0,0,0,5000,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,5771,0,0,0,0,0,0,0,0,0,0,3450,0,2484,2000,0,0,0,2500,0,0,4400,1917,0,0,0,5500,0,4906,6000,5000,0,0,2000,0,0,3000,5000,3000,0,2275,6000,0,4000,0,0,4000,7446,0,0,1000,5500,5000,0,7500,0,4000,5000,3500,0,5000,0,0,5000,0,0,0,4795,0,3900,0,0,0,0,0,0,0,0,7644,0,0,4000,0,3000,0,5000,0,4500,0,7147,0,4000,3000,0,5907,0,7500,0,0,0,0,3100,3000,0,0,4500,7484,3000,1000,2000,0,0,8000,3845,0,0,5000,0,5000,5000,0,6200,4322,0,1500,0,0,5000,0,0,4000,0,8364,0,0,0,1300,0,6580,0,750,4500,0,3000,0,0,0,1175,0,5364,0,4200,0,7500,0,1500,3500,2500,850,0,0,5000,3600,0,1650,5000,3800,7825,0,0,4050,0,3200,3200,0,0,9100,0,0,0,0,0,0,0,0,0,5000,0,0,4000,5000,2800,4157,0,0,2500,0,5000,0,5000,0,0,0,2391,0,0,4000,590,4625,0,0,3489,2500,0,0,9500,0,5000,0,4320,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3750,0,2038,0,0,3250,3262,0,0,1950,0,0,3900,0,3150,2593,0,3500,1000,0,6500,5000,3180,0,0,0,0,5000,5000,0,5314,3720,4632,0,0,0,0,0,0,2255,0,0,0,0,5000,0,4000,0,5000,1250,0,0,3469,0,0,7000,4000,0,4000,5000,0,1636,0,4500,0,0,4500,0,0,8500,4500,0,5000,9500,7500,0,0,0,0,0,8067,6000,0,0,0,6000,0,0,0,5800,4000,4936,0,0,5000,0,0,0,0,0,1115,0,5850,0,0,5000,0,5000,0,0,0,10000,0,6000,4000,0,850,0,4147,2000,2300,0,4000,0,6800,0,0,0,0,0,0,0,0,0,0,0,0,410,0,6000,0,3750,3383,2000,5000,6200,0,4058,0,0,0,2300,0,5719,5000,2000,0,0,0,6500,0,0,0,0,4000,0,0,0,0,0,0,6000,0,0,0,0,0,5000,0,0,3858,0,6409,0,3289,3299,0,0,1250,4000,0,3237,4000,0,0,0,0,3400,0,3505,0,0,0,0,0,0,5692,0,0,0,4799,2960,0,0,0,2000,0,0,0,0,0,0,0,2796,5100,0,0,0,3700,0,0,4000,0,6300,0,0,3000,4900,0,3000,5000,0,5000,0,0,0,0,0,0,3500,6800,0,0,0,0,0,0,1750,0,6000,1000,4000,0,7200,4940,3450,0,2731,5000,0,0,774,0,0,0,0,5500,7000,0,0,0,7500,0,0,0,0,0,4650,5000,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,6800,0,0,4700,4500,0,0,0,0,0,2600,3000,2000,0,2800,0,0,0,0,6330,4392,900,5000,0,0,0,0,0,0,0,6925,0,0,3000,5750,0,0,0,0,0,8550,0,8000,0,5000,0,2000,0,0,4000,7500,3000,0,0,5000,0,1000,0,5000,0,0,0,0,0,1847,0,5000,0,2000,0,4000,0,5000,0,0,4245,6500,0,0,0,0,878,3000,0,5000,0,7000,4150,2600,0,0,1616,0,0,1500,0,0,2000,0,0,0,875,0,0,420,0,0,0,2700,0,4000,3300,0,0,2500,3300,0,2500,3600,0,0,0,2500,0,0,4000,12139,0,5000,0,5000,0,9453,0,0,5000,0,6469,3618,0,0,0,0,0,3900,3500,0,5000,10261,3310,0,0,5000,0,6963,0,0,0,2500,0,4150,3500,0,850,0,3000,6000,0,0,1000,0,0,5663,0,0,5000,750,0,0,0,0,0,0,0,0,0,1000,0,0,0,5612,0,6651,4500,0,0,3000,0,5250,0,0,0,5000,0,100,4440,0,0,0,0,5000,0,0,0,0,0,0,2100,0,0,0,0,2000,0,1000,6605,6600,0,0,2000,5000,3400,0,0,2765,1800,3721,0,0,6000,0,4500,0,2500,4700,6000,0,3500,0,2500,0,5000,5000,0,0,1000,0,7000,0,0,0,5000,4540,0,1125,2397,5000,5000,0,4000,0,0,0,1768,6000,3000,5000,0,0,5000,0,2500,3883,2600,4095,4000,0,0,0,0,0,0,0,4350,5000,5000,0,2500,1000,0,0,0,6500,3500,0,0,0,0,0,0,3905,2650,0,7000,0,0,0,0,0,4000,5000,2913,0,4810,0,3200,0,0,0,0,0,0,5000,0,0,0,0,0,0,3534,6000,0,0,0,5300,3700,0,0,13000,4226,0,0,0,0,4500,0,2500,0,6000,5000,0,5000,0,0,11950,3000,0,0,0,1800,0,3500,0,2500,0,0,4767,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,3780,0,1710,0,0,0,0,0,2000,0,0,0,0,0,0,1800,665,0,0,0,0,4000,0,0,0,1000,0,0,0,0,0,4730,0,0,0,0,0,0,0,0,0,0,0,0,0,4500,0,0,0,2500,0,0,0,1500,0,0,0,3100,0,0,4500,0,3450,0,0,0,0,4500,0,0,0,0,0,2227,3298,0,0,4300,7000,4000,0,2000,0,0,3960,5905,0,0,0,750,0,0,5000,0,2700,0,0,0,0,0,0,0,1800,0,0,0,0,0,0,0,0,0,0,0,0,3000,2000,0,4000,0,0,0,6000,0,840,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3700,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,3900,3481,0,0,4000,2000,0,0,3125,4650,0,0,3900,0,0,0,4000,0,0,0,0,0,3600,0,0,5667,5250,8000,0,0,2000,4205,4000,0,0,5000,4850,0,0,0,0,5000,0,0,0,5000,0,4500,0,0,3210,0,0,3500,0,0,2719,5000,4000,4000,0,0,0,4430,0,0,0,4700,0,3500,0,5040,0,3750,0,0,0,0,0,0,5000,0,0,6912,0,0,0,100,5000,0,5000,0,4000,0,2723,0,4500,4470,4800,0,5239,0,4120,0,4000,2500,0,0,0,0,3435,0,0,0,0,0,4586,0,0,0,0,4000,3000,4000,4605,4000,0,0,0,5770,0,0,0,2400,0,0,0,0,0,0,4000,5000,0,0,0,5000,0,0,0,0,0,5524,0,0,0,0,3000,0,0,0,1250,5152,0,0,6755,0,4960,0,1000,2548,3000,0,0,0,0,2500,0,4000,0,4000,0,3359,3000,4000,6000,0,3904,0,4000,0,5000,0,0,0,0,4000,5000,0,0,0,0,0,0,4900,2000,1000,7000,5000,0,0,5732,0,0,0,4923,0,0,0,0,0,3390,5000,5000,0,5308,0,5000,0,5801,0,0,0,0,6300,5600,0,1900,0,6500,3750,0,4440,0,3000,0,0,4440,0,0,5316,2500,0,0,4000,0,4500,0,0,5000,0,0,0,0,0,2500,0,0,7000,0,0,4678,2776,0,4000,5000,7347,0,2500,0,5777,0,0,4000,0,0,4500,0,3743,1500,0,5700,4500,0,4000,0,5500,0,4500,0,0,5500,800,0,0,4000,4300,0,3000,0,2000,0,5500,0,4300,6200,0,0,0,0,2895,0,3720,0,0,5900,0,6000,0,6420,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3269,0,0,0,5000,0,0,0,0,0,0,0,0,2000,0,5000,0,0,0,2500,4100,5000,0,0,5000,0,3829,0,4260,0,1852,4480,0,3492,0,4000,0,0,0,0,5500,0,7620,0,3000,5000,0,0,0,0,3000,4500,0,3500,3500,0,3928,0,0,0,4450,0,0,3700,0,0,3940,0,0,4000,2400,0,3500,0,0,3500,4500,4608,9210,4405,0,0,6483,0,0,0,0,0,2200,5000,3500,0,0,3000,0,0,0,0,6500,0,0,0,0,0,0,0,0,0,6000,3000,3594,0,0,0,0,2300,0,4000,0,0,3960,0,5000,0,0,0,0,5000,0,0,0,0,0,0,4410,0,5190,5000,0,0,0,0,0,3795,0,0,5600,0,0,0,5000,0,4000,4080,0,4000,8670,0,5500,5000,0,0,3300,600,4000,0,4500,2000,4000,0,0,0,0,0,0,0,0,4500,0,3000,2500,0,0,0,0,0,0,0,0,0,2700,900,0,6800,4000,0,1000,10850,600,3650,0,0,0,0,0,7000,995,0,5000,0,4000,0,2997,0,0,7415,0,0,4908,2222,2571,2500,2500,0,0,0,3000,5000,1500,0,4000,0,0,1280,7650,0,0,0,0,0,0,0,6000,0,0,0,3200,10545,0,0,0,0,0,9600,0,4025,0,0,0,0,0,5299,6000,570,0,3445,0,0,0,0,3697,0,3500,0,0,0,5000,3041,8000,2979,4000,0,0,3000,0,4000,0,0,3500,6000,0,0,2600,4000,0,0,0,0,0,4000,0,0,0,0,0,0,0,5000,0,0,4546,0,4625,0,5000,0,4835,2200,6750,0,3149,0,6312,2602,5724,5397,0,1000,0,5800,0,5000,3500,4800,4560,1000,1000,0,5000,0,3230,0,0,0,0,4000,0,0,0,0,0,0,6000,0,0,0,5000,0,1137,0,0,6400,0,0,5000,0,7500,0,5500,5000,7000,0,0,0,0,0,4000,1770,1760,0,0,0,0,3000,0,4350,0,0,0,0,0,0,0,0,1200,0,0,0,0,0,0,0,0,0,5000,3000,0,0,0,10496,6000,0,4500,8020,0,4223,0,0,2000,0,0,0,8000,8000,7500,0,5000,0,2000,6000,0,1906,0,3500,0,3000,0,0,3000,7630,0,0,0,0,0,0,4475,0,0,0,0,5000,0,25000,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,10097,0,0,0,0,0,11250,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,5000,0,5000,0,0,7000,0,0,0,0,0,0,5000,0,0,0,0,4000,0,0,0,0,0,0,0,0,4000,3000,0,0,0,0,3386,3541,0,0,3901,0,0,5000,0,0,0,0,0,0,0,0,0,0,4931,2130,0,1070,3000,5650,0,3500,5000,0,3000,0,300,0,0,3000,0,0,0,0,0,0,0,2500,5000,5000,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,5000,0,6000,0,0,2500,0,1840,0,6000,5000,4500,5000,0,0,0,4000,6500,3575,5000,0,0,0,0,0,0,0,0,2600,5000,0,5000,5433,0,0,0,0,0,0,1754,5000,0,5000,10000,5000,0,0,0,0,0,3000,3500,0,6250,0,0,2000,6250,0,0,0,0,4000,0,0,0,4000,0,0,3500,4004,0,0,0,0,0,0,0,800,3500,6500,0,0,5100,5000,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7000,0,0,0,0,7000,0,6000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,10000,0,0,0,0,6908,0,0,7800,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,3000,0,4000,6000,5000,0,0,0,0,0,0,7000,0,0,3000,0,0,5400,5500,0,0,0,0,5725,0,0,0,0,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,10000,0,0,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,6000,0,5000,5000,0,0,0,0,0,0,5000,4000,0,3000,0,0,0,1000,0,2025,4000,0,2000,1000,6000,0,0,0,0,0,0,0,5000,0,3500,0,1695,0,0,0,0,3734,2000,4000,0,0,0,0,0,3000,0,6465,0,0,0,6550,0,0,5440,0,0,0,0,3500,0,0,0,0,0,2800,0,4000,0,0,0,1685,0,0,7200,0,0,0,3500,5000,0,0,0,5700,4000,0,0,0,0,0,0,0,0,0,0,5757,0,0,0,1200,0,5000,0,0,0,9850,7386,785,0,475,0,1500,0,0,0,1000,1900,2000,0,0,2500,6500,0,0,5500,0,4500,0,0,0,0,0,3400,0,0,5000,2800,0,0,0,0,6000,0,1000,4800,4000,1000,0,0,2000,0,200,1500,3297,3000,0,0,0,0,0,1500,0,0,8000,0,1000,0,0,3100,0,0,0,0,8200,6000,0,2000,4000,0,0,0,0,0,0,5000,1000,1000,0,2694,5000,0,2000,5000,2100,5000,0,1500,0,1000,0,0,0,0,0,0,5000,5750,0,0,5000,0,0,1000,0,0,0,0,0,0,5000,4000,3400,0,5000,5000,0,0,3500,6000,0,0,10104,2500,0,0,0,7000,1700,0,0,0,0,0,5500,0,10000,0,0,3500,0,0,3050,3000,8000,0,0,0,0,5324,0,3500,0,3377,0,3500,1000,0,0,0,0,1250,4000,0,4100,0,0,5000,5000,4000,0,0,0,0,2839,5000,6500,0,0,0,0,3000,0,0,0,0,7500,5000,5000,0,5000,4625,5000,0,0,0,4500,0,1000,0,0,0,0,0,0,0,4000,0,0,0,0,0,5000,0,7838,0,0,5070,0,4000,0,9000,0,5580,0,0,0,0,4000,4515,0,0,0,2300,0,0,0,1500,2500,0,0,0,4000,9000,3217,0,0,2000,0,8000,5000,4000,6000,0,0,0,0,4500,8000,6000,0,4748,0,0,0,0,0,5500,0,5000,4500,5000,3000,0,2500,2000,0,0,0,0,0,0,0,0,0,6935,0,0,1500,5000,0,0,0,0,0,0,0,4300,0,3257,0,0,0,7350,7000,6200,0,0,0,5350,0,0,4000,0,0,0,0,0,2700,2000,0,0,0,0,3000,4000,5000,4000,2000,0,2000,5355,5000,3305,5000,0,3640,0,5000,0,7293,0,4000,0,7450,0,0,0,5500,0,9800,0,4000,7170,4500,6000,2000,4000,2333,0,0,4000,4000,5000,0,2300,0,0,0,0,0,0,3000,0,3940,0,0,0,2500,0,0,0,0,1000,0,0,0,6000,2500,0,1000,0,0,0,3000,4500,0,0,4800,500,0,1622,5500,3500,0,0,0,0,0,0,0,0,2000,5000,3606,0,6700,5000,0,0,0,0,0,0,0,0,0,0,2100,0,0,4302,0,0,0,3200,2000,3000,2500,0,0,0,3057,0,3500,6600,3500,6000,0,250,10000,0,0,0,0,5000,500,0,3000,7000,4000,0,0,6100,0,0,0,1499,5930,0,0,0,0,4600,4000,0,0,9888,5600,2500,0,0,0,0,0,0,5527,2000,8455,3500,5830,1350,0,1380,0,707,0,4300,0,5000,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,3000,0,0,4000,2000,4000,0,2350,0,3000,0,0,4500,4000,0,0,6000,425,0,0,500,1411,0,0,5000,0,4000,0,0,0,0,0,0,7000,4000,0,5000,0,0,0,0,0,0,0,6200,0,0,3600,0,0,0,4500,0,0,2825,0,0,5000,0,2000,0,0,5000,2000,2775,4360,0,0,0,0,3000,0,0,0,1000,5000,0,0,7000,0,2500,0,1500,3000,0,2160,0,6000,9000,6400,1900,0,0,4110,0,0,3000,5259,0,1000,0,2000,0,4361,4600,0,4000,0,0,4912,0,750,0,5000,0,2879,0,5000,0,4000,7605,5000,0,900,2500,0,0,0,0,11970,3000,0,0,0,0,0,0,5500,0,0,10227,8183,0,0,2000,0,0,0,0,0,0,1600,6000,2500,0,0,0,1000,4000,0,0,0,4000,800,0,5000,0,0,1000,0,0,0,0,4000,0,0,0,0,5000,0,0,0,0,6394,0,0,0,2000,0,5000,5000,0,2000,0,0,0,5000,5917,0,3105,0,0,0,5500,4217,3000,0,0,0,6000,0,0,6000,0,0,11700,0,4000,0,0,4000,6500,0,0,3342,3375,6000,0,0,6250,1951,0,2500,1247,1000,0,5550,3000,8000,2000,0,0,0,0,6000,7653,0,3211,0,0,0,3829,0,0,350,600,1250,0,4000,0,0,0,6100,0,4500,0,0,5993,5000,0,0,0,9000,0,0,0,0,2675,0,3000,0,0,0,0,0,5000,0,0,0,0,3000,0,6000,5000,3500,0,0,0,0,4000,0,0,3000,0,0,0,2000,0,0,0,6500,9488,10048,0,3000,5000,0,0,0,0,0,0,2700,0,0,0,0,0,3500,0,0,7000,2400,3500,0,0,1500,0,0,0,0,3500,4500,0,0,4000,6000,0,5000,0,1500,6350,0,0,5000,4800,0,0,5000,5000,0,3990,0,0,0,2000,0,0,0,0,0,4500,5376,0,0,7000,0,5000,4000,0,0,1600,0,0,0,3500,0,2500,0,0,0,4000,0,0,0,3000,3500,0,0,0,0,0,0,0,6389,0,0,2000,6152,4500,5000,0,1700,0,0,0,2000,0,0,0,0,1500,0,7009,6000,3223,0,0,0,0,0,4690,0,4000,5000,1000,1100,0,5000,0,0,0,0,0,6250,1250,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,5000,0,0,0,0,1000,0,0,0,0,0,3200,5400,4500,0,4000,0,0,0,0,0,0,0,5000,3500,6000,0,0,0,0,6000,799,3000,0,0,0,0,5400,2750,0,2500,0,3750,5000,4957,4000,7000,0,0,0,3000,0,3000,2246,2419,4000,0,0,3500,0,1200,4000,6460,0,9000,0,0,0,0,3000,4394,0,5000,5000,3000,2753,3464,5000,0,4170,0,0,0,0,2500,5900,7900,3000,0,0,0,5000,5000,9000,0,2000,0,0,2000,0,0,0,0,2500,0,0,1500,530,7475,4928,0,0,0,0,0,0,0,8000,9600,0,0,2145,0,6320,0,0,0,0,0,0,0,3337,5300,0,0,0,1860,0,0,4800,0,3000,3600,2445,2999,0,0,4890,4800,4759,0,0,0,12000,0,0,0,9021,0,0,0,0,0,0,0,0,0,0,0,0,0,7200,0,0,5343,0,0,0,0,2900,0,0,0,0,0,3700,4000,0,5862,0,0,7000,0,0,0,0,0,8250,0,0,4000,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,3000,0,0,0,0,0,6930,0,0,10337,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,5700,0,0,6000,0,0,0,0,0,0,0,0,7200,10000,0,0,0,0,0,0,0,0,0,0,2500,0,0,10500,0,3000,0,0,0,0,0,0,0,8000,10000,0,0,0,0,0,0,0,0,0,0,0,0,5000,2700,0,0,0,2518,3400,0,4673,0,0,0,0,0,3500,0,0,0,0,0,8000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2028,5000,0,0,0,0,0,0,9300,0,3600,6600,0,0,0,0,0,0,0,0,0,0,9000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,2194,0,0,0,0,0,0,0,0,0,1500,0,0,0,6500,0,6000,0,0,9649,2500,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9600,4296,4032,0,7000,0,0,0,6000,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8000,0,6900,0,0,2000,3030,3000,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,3500,0,2570,0,4500,0,2750,0,6288,6000,0,1000,0,0,0,5000,0,0,0,0,48266,0,0,68195,0,0,64133,0,69480,9249,67500,83162,0,58500,14249,0,51425,9249,62840,0,0,9249,48309,41208,0,0,0,53950,57016,0,0,0,0,34421,0,17703,101809,14000,99749,44206,34421,18603,0,0,63900,32025,17211,42206,34309,39656,26603,35309,39421,0,31809,34421,15000,18603,95427,34421,0,0,0,0,0,0,0,0,0,0,0,0,0,3500,0,5000,0,0,0,0,1000,1600,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,6000,0,0,5647,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4500,0,0,0,0,0,0,5500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5100,0,0,0,0,3500,0,0,0,0,4000,0,0,0,0,2680,5000,0,0,0,0,6500,0,0,0,6000,5000,0,0,0,0,0,1800,2000,0,0,0,0,0,0,4000,5000,0,0,0,0,0,0,0,0,0,5800,0,3000,7729,0,2500,6500,0,0,2000,0,0,0,5000,0,4000,0,0,0,0,4979,1500,4500,0,5000,5000,0,0,0,0,3000,0,2500,0,0,9000,8000,5600,0,0,2500,4600,0,3000,5000,0,5000,0,0,0,0,0,0,0,5300,4000,0,0,0,2000,2500,4000,2000,600,4000,0,0,6269,3500,6000,0,3750,0,0,4771,10000,0,450,0,0,3720,0,9900,0,0,10000,1500,0,0,0,0,0,0,5000,0,0,0,0,3500,0,0,0,0,0,0,0,0,1276,0,0,4000,5460,0,0,7300,3000,0,6500,6000,0,4088,0,4000,0,0,4000,4000,0,0,0,0,0,0,0,10000,0,0,0,0,0,4910,0,3000,0,0,0,0,0,0,0,5370,5297,5000,4000,0,4000,16430,7000,4988,3561,0,4000,5700,0,900,0,5500,5000,0,0,0,1500,0,0,0,0,0,4000,5989,4410,0,5500,0,0,4000,5000,9000,2500,0,4900,0,4000,5000,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,9418,0,0,0,0,3000,0,0,4000,0,0,0,0,0,0,0,3000,0,0,0,0,6795,4200,0,0,0,0,0,3000,0,0,0,0,0,0,4300,0,0,0,4472,3473,7000,3500,4000,2500,0,3500,1500,0,5500,8000,6500,0,3000,3850,0,0,3900,0,0,0,0,0,0,0,3000,1800,11535,4500,0,0,7630,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,2000,5000,0,0,3500,4000,5000,0,0,6500,0,0,0,0,0,0,0,0,3000,0,3000,0,0,2500,1250,0,4500,0,0,4540,0,0,0,6000,7417,0,5000,6000,0,0,0,5000,6500,0,2000,0,0,3000,1500,0,0,0,0,7425,500,2000,0,0,2039,5000,0,0,5200,0,0,0,3550,3792,0,0,0,6800,0,250,0,0,0,5104,0,0,0,6897,3550,3876,5000,4056,0,500,0,0,0,0,0,0,0,0,0,0,0,2500,2600,1825,4000,0,0,0,0,0,0,6000,0,0,0,5000,0,0,0,0,5000,4170,0,2938,0,0,3000,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,1000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12000,7900,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14900,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,5000,900,0,0,4000,7000,0,0,8000,0,5500,0,0,4000,0,4000,0,0,1000,550,5200,4888,1000,0,5500,0,5000,2500,2500,0,0,3000,0,0,3500,4500,0,0,5000,3630,2000,0,0,5000,0,0,0,0,0,6300,0,0,0,5697,4574,0,3000,5250,0,0,3276,3752,0,6000,0,5000,4180,7000,0,0,0,0,0,0,8296,0,0,0,0,0,0,0,0,0,4500,0,0,0,0,0,0,6150,3000,2500,2000,4636,4000,6382,0,4500,3500,0,0,0,2450,3000,0,5500,5000,5000,0,6341,0,6000,6172,0,7154,0,0,3472,0,0,0,5665,4000,6900,0,200,4621,0,4729,5000,0,5000,0,0,0,6819,0,4750,1500,0,5790,0,0,2000,5000,0,0,0,6000,2000,0,0,1845,0,0,0,4250,0,5407,0,0,4100,3650,5000,4385,4500,0,5832,0,0,0,1500,3714,4000,4000,3500,0,0,1378,0,0,4500,0,3000,4086,10211,0,0,0,0,0,0,0,0,0,0,3000,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4979,3000,6000,0,4500,0,0,0,0,2953,0,0,0,0,0,4000,0,0,5000,0,3300,0,0,0,2895,0,0,0,0,1800,0,0,0,3000,4500,0,4200,3950,5000,5300,0,0,3000,5000,5000,0,0,5000,0,0,0,0,0,0,0,6000,4074,0,2000,0,0,19200,0,0,3000,4000,0,0,0,0,0,0,0,0,500,500,0,0,0,950,6150,0,0,0,0,0,6500,0,0,0,0,0,2540,6000,2000,0,0,5500,2900,4600,1250,5000,0,0,0,0,0,0,4500,0,0,5100,0,0,8400,5000,6000,0,12740,1500,4200,0,0,0,5100,3000,3000,5000,4000,5000,0,0,0,6388,0,0,1500,1000,4526,0,6000,0,0,0,0,5000,0,0,0,0,5000,0,7500,4500,0,2600,0,4300,0,4655,0,5000,0,0,0,4700,0,6500,4172,3000,0,0,5500,3500,5000,6211,1200,8156,0,0,0,2000,0,5500,0,3450,0,0,0,0,0,0,0,4500,0,0,0,0,0,3133,2500,0,0,0,0,0,4500,0,0,0,0,0,0,0,0,0,0,0,0,6591,0,0,0,0,0,4000,1000,0,0,8000,0,0,0,0,0,0,2700,0,0,0,0,3500,0,0,500,4900,0,0,0,0,4260,0,0,0,0,0,0,0,5000,0,9599,0,0,0,0,0,0,7000,1300,5000,0,0,3125,1500,0,2000,0,0,1000,600,0,3500,6000,800,0,0,0,0,5000,0,0,5074,0,0,5000,0,0,0,0,7000,513,0,0,5000,0,0,7713,0,0,4493,0,3500,0,0,6600,50,1250,7417,0,5000,1000,4199,0,0,216,0,0,300,0,0,0,0,0,0,0,0,0,0,7500,0,0,0,0,5880,0,4900,3500,0,0,0,0,0,0,0,0,3000,0,0,2500,0,0,3750,2500,0,0,0,0,0,3893,0,0,0,0,0,0,0,0,0,0,0,1200,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,2500,5000,0,0,0,0,0,7500,0,8600,0,0,0,0,0,0,0,0,4000,0,0,4825,0,0,3670,0,10950,0,0,1500,0,0,0,0,0,0,3300,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,7500,1500,0,0,0,0,0,3000,2000,3408,0,0,0,0,0,4000,0,7500,0,0,0,0,1000,0,4000,0,0,3555,0,0,7000,0,3282,4936,0,3000,0,0,1304,0,0,4500,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,3835,0,1500,2000,1600,3000,4000,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,0,0,0,0,0,3500,0,5000,3080,0,0,0,0,1000,0,0,0,0,0,0,4100,0,1050,0,0,0,3500,4000,0,3150,0,0,0,0,0,0,0,0,4612,0,0,0,0,0,0,7663,0,0,0,0,0,0,0,0,0,11500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9300,0,0,0,0,0,0,0,0,0,1340,0,0,3250,0,5000,0,5000,0,3500,0,0,0,0,5000,500,2500,0,0,0,0,0,0,0,0,5000,4180,3500,2115,0,0,0,4000,0,0,0,4000,0,3000,3897,0,4200,0,0,0,3000,6000,0,5000,4000,4000,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,500,0,0,4500,0,1000,2640,0,2250,0,0,0,0,3000,0,0,0,0,2000,3927,0,3000,3900,0,0,3600,2500,2380,0,0,0,0,0,0,4100,0,0,0,6900,0,0,10000,0,0,7463,0,0,0,0,0,495,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,5000,13500,0,3000,0,0,0,0,0,2500,4500,0,0,0,4000,3000,3700,2700,3000,2000,2000,0,0,500,0,3307,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,0,3650,0,3500,0,0,3000,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,3500,0,0,0,0,1000,0,0,0,0,0,5000,0,0,0,6168,0,0,3500,0,5000,0,0,0,4313,0,3500,0,3700,0,0,0,0,0,1200,0,2000,4860,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3480,0,2000,0,10000,1000,0,0,12389,0,5000,0,875,0,2000,0,350,0,2000,6000,0,0,0,5000,0,0,0,0,0,0,1500,7706,3821,0,6500,0,4557,2250,0,0,3795,0,0,4800,5000,6750,0,0,4000,5000,0,1000,0,0,0,0,0,0,0,0,0,6580,5938,0,4125,0,0,0,10000,0,700,5000,0,0,0,0,0,0,0,0,0,5000,5834,0,0,0,0,2500,3500,0,0,0,0,3000,0,0,4000,2000,0,0,4000,0,2000,6158,0,0,5500,0,0,0,0,0,0,0,2500,0,0,0,4305,0,4000,2000,5000,0,0,3600,0,0,0,0,0,0,0,0,0,0,0,1000,2500,0,0,0,6000,0,0,0,0,3500,0,0,1000,2500,4040,0,0,4500,5500,4198,5024,4320,0,3500,0,3000,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,3200,0,0,0,0,0,5000,2140,0,0,5000,0,0,0,5000,0,0,4764,0,0,7500,4500,4000,700,0,0,0,0,5000,5000,3805,0,0,0,5000,320,2000,0,3000,0,6200,750,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7800,0,5000,0,2800,0,2500,0,0,0,0,0,0,0,3083,0,0,0,1398,3433,0,0,0,1000,4108,4600,3325,0,4000,0,1018,1800,0,0,0,5300,0,0,0,0,3000,0,0,0,0,0,0,14000,0,0,0,1500,0,0,0,0,0,0,0,0,0,0,4800,3000,3000,0,0,4950,0,0,5500,0,0,0,0,0,0,2000,7000,1500,0,0,0,0,0,1000,0,0,4342,0,4000,0,0,0,0,0,0,2500,4200,3000,6447,0,0,0,0,3200,0,0,0,2800,0,0,5000,0,0,5623,0,0,3600,0,2450,0,0,0,3000,0,0,0,7900,3000,0,0,0,1500,0,0,0,0,3000,0,0,0,5000,0,4000,2035,0,0,3000,2000,0,0,0,0,0,0,0,2000,0,0,0,1660,0,0,0,0,0,11000,5000,0,0,7000,0,0,5000,4000,4122,0,2000,1890,0,2500,0,0,0,5000,0,2620,0,0,0,0,0,3662,0,0,3050,0,0,3150,0,3500,2500,0,2000,0,0,3925,0,3500,0,5000,0,5000,5000,0,3500,0,0,0,0,0,0,0,0,600,6500,3000,0,5900,4000,3000,2000,5275,0,0,0,0,0,0,0,5850,0,6948,0,0,0,0,0,0,0,0,4897,0,0,0,0,4000,1000,0,0,0,0,4000,0,0,0,4000,0,0,3000,3500,2000,0,6800,3000,0,0,0,2250,0,0,0,0,0,0,4000,0,0,0,0,0,0,3870,0,0,4710,0,0,2779,0,0,3532,0,3500,0,0,0,4236,0,0,3000,0,0,5000,0,3609,0,0,0,0,0,0,2200,0,4500,7200,0,0,3200,1000,0,0,0,5000,0,3905,0,4400,0,0,2087,2000,4000,2200,0,0,3000,0,4000,5000,700,0,0,5400,1900,0,0,0,0,0,4500,0,3000,0,0,5500,4965,0,1350,0,0,0,0,0,0,0,0,0,0,2500,0,5199,4931,5215,0,0,0,0,4800,3000,0,2287,875,2560,0,0,0,5000,4290,0,5134,3800,0,0,5100,0,700,0,0,2553,0,0,3000,0,0,3000,0,0,0,0,0,3100,3000,0,4650,0,0,0,0,0,4327,0,0,0,0,0,0,0,0,3940,0,0,0,0,2700,3086,0,0,0,3000,0,0,4497,0,3823,2000,4800,0,0,0,0,0,0,2000,0,0,4560,0,0,0,0,0,0,0,3540,0,0,0,0,0,3100,0,0,0,0,3000,0,0,2000,2685,2100,0,0,0,0,3702,4625,4350,0,0,0,0,0,0,0,3750,0,0,0,0,2000,0,0,0,0,0,0,3100,0,1800,0,0,4600,0,0,0,0,5000,4400,2621,300,0,0,0,3000,0,0,0,0,0,3837,0,5000,0,0,0,0,0,0,0,2610,0,0,0,3206,2594,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,4800,0,3750,4000,0,0,3500,0,0,2340,1200,0,0,2500,0,0,2800,4000,0,0,2880,0,5000,2800,2610,3000,4000,0,0,0,0,0,5000,0,4987,4284,0,3986,3250,0,0,3000,0,0,0,0,9301,0,0,0,4573,0,3500,0,3500,4000,0,0,4000,0,0,0,0,0,2700,0,0,0,0,3495,0,1359,3000,0,2515,0,0,0,3720,2550,6609,1700,0,0,0,0,0,2757,0,0,3500,0,5370,0,0,0,0,0,3867,3500,0,2400,3500,1000,0,0,3100,0,2698,2847,0,1000,0,3255,0,0,0,0,0,0,0,2100,0,2000,0,1650,1352,0,0,2100,3780,4500,3921,0,0,0,0,0,3179,0,4000,4000,0,0,0,0,1000,0,5000,0,0,0,3353,0,4000,0,0,5000,0,0,0,0,4178,0,0,0,0,0,1000,0,0,0,0,0,1800,3150,0,0,3000,0,0,0,0,0,0,4950,3150,2000,0,3400,0,0,0,400,0,4500,0,2000,0,0,0,0,0,0,0,2846,0,3983,2806,0,0,0,0,0,0,0,0,4020,0,0,2600,0,0,3575,4000,2100,0,0,1000,0,0,0,0,0,3000,0,3747,0,0,0,0,0,1300,0,0,0,4000,122,3000,0,1920,0,0,5850,0,0,0,0,0,3475,3625,0,0,0,0,0,4500,0,0,2880,0,0,3747,0,0,1000,0,0,0,4000,5000,0,0,0,3691,5300,0,2500,3000,0,0,3500,0,0,2000,0,0,4000,1800,0,1940,0,0,0,3150,0,0,0,3000,0,3434,0,0,4200,5280,0,0,0,3060,3250,0,0,0,2208,4000,0,0,0,0,5600,0,3500,0,3000,0,0,0,0,4837,2000,0,0,0,0,0,0,1000,0,0,0,4000,0,0,0,0,0,0,0,3000,0,0,2000,0,0,0,0,0,0,0,0,2275,0,2800,2970,2500,4375,3500,0,0,3958,1000,0,0,5000,0,8100,0,0,0,0,0,0,0,0,7500,0,7500,0,3820,5000,5000,0,0,0,2500,2000,1810,0,0,0,0,3000,0,0,4000,0,0,0,0,0,0,0,0,4260,0,0,2000,4000,0,4000,0,0,0,1350,0,4200,0,2650,10000,2860,0,2600,0,6832,4266,6443,0,0,0,0,2000,2000,0,0,0,0,0,800,0,5000,0,4500,0,0,0,300,0,4500,0,4000,510,3500,4245,0,5500,3000,0,0,4843,7000,0,0,5000,1500,4500,2000,2736,0,3500,0,0,3553,0,1888,0,8500,0,5000,0,1310,3000,800,1000,5000,10000,0,5000,3400,0,0,3000,0,0,500,5000,0,9361,3525,5000,0,4800,6360,0,0,2750,6940,6000,0,0,0,0,0,0,0,6075,3500,0,0,0,0,0,5000,0,0,5000,5000,0,0,1333,500,0,3300,3000,5490,0,3000,0,10000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1800,0,3993,2185,1600,0,0,0,2000,5000,2500,0,0,3745,2411,0,2753,5000,2500,0,0,3200,3000,6144,4805,0,0,0,1500,0,0,0,0,0,0,6600,0,1591,6000,0,0,0,1000,0,1500,0,0,0,0,1250,0,2000,2500,0,0,5000,0,0,3750,5000,0,0,5000,0,0,0,0,4319,1250,5000,0,8750,5000,5000,0,5000,0,3000,0,3100,0,4500,4500,0,0,5000,0,0,7836,0,0,0,0,0,5000,7900,6000,300,3500,5000,7000,500,0,0,0,0,0,0,2824,0,0,0,5000,0,4000,2400,1070,0,4000,2000,3000,0,0,1734,0,0,0,0,0,0,0,5000,3000,0,0,0,0,2400,4950,0,0,10800,500,0,0,0,0,5000,6000,1500,0,2500,0,0,0,4500,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,6000,0,0,0,0,0,1500,0,0,0,0,0,0,5000,7725,0,1750,0,2500,5000,3349,0,0,4000,0,0,0,0,0,0,0,0,500,0,0,2260,0,11611,0,0,0,0,3310,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,900,0,12515,0,5000,0,0,7150,0,6700,5000,2500,0,0,3750,5000,4315,4600,0,3000,0,0,0,0,0,20000,0,0,0,8000,0,0,0,0,4800,0,875,3000,0,0,4000,1000,0,2065,0,5000,5000,0,3500,0,0,6000,0,4200,0,0,5500,0,3172,3000,0,0,3348,4400,0,3500,0,5000,0,250,0,2500,0,1500,1500,0,0,0,500,4082,1300,4125,5000,4500,0,0,6600,0,0,0,0,0,0,0,0,0,0,0,3500,5000,0,0,0,3239,5460,0,5200,0,0,0,0,0,0,0,0,0,4850,0,0,1232,4650,0,5000,0,0,5279,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,9506,3000,0,0,0,1800,3000,0,5000,0,0,0,900,0,0,6666,0,0,0,1600,500,0,0,0,5000,0,8000,0,0,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,900,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10000,0,0,11900,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3250,0,0,2500,0,0,0,0,0,0,0,0,6000,0,0,0,0,0,0,0,0,0,0,2500,0,1625,12000,0,11764,0,0,0,0,0,0,0,0,0,11800,0,0,5000,0,0,0,0,0,20000,0,0,0,0,0,0,10000,0,0,0,0,0,0,4500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3475,7500,0,0,0,0,0,0,0,0,0,0,0,2500,0,0,0,5000,0,0,0,0,0,11030,0,0,0,0,0,0,0,2100,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7000,0,0,0,0,0,0,40000,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,48000,10000,0,3500,0,5000,0,0,0,1500,0,8746,0,1000,0,0,0,0,0,0,0,0,0,0,0,0,11000,0,0,0,0,0,1600,0,3500,4865,2000,4400,4000,0,1000,5000,1000,0,0,0,2500,0,0,6000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2500,0,5000,0,0,0,0,0,1000,0,0,0,0,0,5000,5000,5000,0,0,0,0,0,2000,3500,9930,1925,0,0,0,7633,0,0,900,0,5000,0,5000,7500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1500,0,0,0,3370,5000,0,1300,0,6000,2000,0,0,0,4000,8085,0,0,0,0,0,0,0,8443,8792,0,2000,0,2900,0,0,0,3000,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,1500,0,0,0,0,0,3900,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4700,0,0,0,0,0,5000,0,0,4625,0,0,0,1585,0,1625,0,0,0,1200,0,0,0,0,0,0,0,0,0,5700,0,0,2200,0,0,0,0,0,0,0,0,0,0,860,0,0,0,0,0,9000,0,3000,0,0,0,10850,0,2000,0,5000,0,0,4900,0,3000,0,0,0,0,0,0,0,0,0,0,0,7000,0,0,1750,0,0,0,1650,0,0,0,0,0,7524,0,5000,7000,9500,0,0,0,0,0,0,4400,0,0,0,0,0,0,0,0,0,960,0,1345,0,0,0,3000,0,2500,0,0,0,0,0,0,0,0,0,850,7500,3890,0,0,0,0,3819,0,0,0,0,0,0,0,0,0,5000,5000,0,0,2000,0,0,0,0,0,1000,0,0,0,4000,0,0,0,0,0,0,0,870,0,0,7500,0,0,0,0,2375,0,0,0,2200,4000,4700,0,0,0,0,0,0,0,0,0,5000,3000,0,0,0,0,0,0,900,1000,0,0,2500,0,0,0,0,1600,0,0,0,0,1198,0,0,0,1875,0,0,0,0,0,0,0,0,6500,0,0,3620,0,0,0,0,10000,0,0,3500,0,2500,0,1039,0,0,0,0,0,0,0,0,6000,0,0,0,0,6000,2400,0,0,5000,0,0,0,0,0,14500,1000,7911,0,8098,0,0,1000,0,9200,11000,0,0,2500,0,0,4400,4750,7000,0,0,4400,0,0,0,0,0,0,0,1500,0,0,0,0,0,0,0,0,0,0,5000,1000,0,0,0,0,0,0,0,0,0,0,0,0,0,3900,0,0,0,0,0,0,0,0,1800,1950,0,4400,0,3535,0,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,0,0,0,4579,0,0,1925,2500,5500,0,700,2150,500,0,1900,0,8848,0,6000,0,2000,0,0,0,0,5000,0,7300,3000,0,0,0,0,0,0,0,0,0,0,3000,0,5800,0,0,483,0,4600,0,4000,6000,0,0,3120,0,0,0,0,0,0,9775,0,0,0,0,5000,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,3500,5000,0,0,0,0,1600,3902,0,4350,2500,0,0,0,3000,0,0,0,0,0,0,0,0,4000,0,300,1000,0,0,0,0,9000,0,0,425,3500,0,0,0,0,0,0,1000,0,400,3400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,2900,0,0,0,0,0,0,0,0,4500,4500,0,8300,0,0,4000,0,0,2000,0,0,0,0,0,0,0,0,0,300,3500,0,5575,0,0,0,0,0,0,0,0,0,0,0,0,6500,0,0,0,0,0,4500,0,6000,0,0,4000,0,4000,4000,120,0,0,9794,5000,0,4000,7000,0,0,0,0,2000,6000,2000,0,0,5000,6500,0,4902,0,4000,6000,0,0,9375,0,0,0,0,0,3000,0,5000,6000,500,5000,0,1000,0,4600,0,0,1000,0,0,0,0,0,0,4251,0,0,0,6500,8100,3500,4251,4750,0,5500,0,0,5000,6110,0,5800,6175,3850,0,3000,0,3000,0,0,0,500,2500,0,0,4980,0,0,0,0,0,0,2400,1500,0,2000,3000,360,0,0,0,0,5300,5000,5000,545,1950,0,0,0,1600,3500,0,0,0,0,4881,0,7000,4000,6000,2000,0,0,0,5500,4814,0,5000,4300,3000,3500,7000,0,5000,4500,0,0,7500,0,0,1816,5000,5000,0,0,5000,0,1000,0,0,0,0,500,0,5000,5000,0,0,5000,7500,0,0,3563,0,5150,0,0,0,0,0,0,0,2700,0,6777,4000,0,3000,0,4000,0,2998,0,0,2100,0,0,3645,0,2400,4000,0,0,5000,2830,0,0,2775,6000,0,5000,0,0,3500,0,0,0,4000,0,0,0,0,5000,0,6020,0,3830,3000,0,7168,3200,0,3000,0,0,0,0,4173,0,1700,0,4586,0,2500,0,0,4200,0,0,4783,0,2000,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,4148,0,5000,6000,0,0,2500,0,0,2000,0,2000,1215,4500,0,0,4677,0,1000,2636,4500,5890,0,4200,0,2670,1969,0,0,3000,0,0,4500,1840,0,0,3995,0,0,0,0,0,0,0,4611,0,0,0,0,4000,0,0,0,0,3500,0,0,0,0,4940,0,0,2500,2564,4768,4410,0,0,1850,1500,2500,0,0,2000,0,0,4900,0,0,0,4400,3500,0,0,0,0,3212,0,1500,0,0,0,0,0,0,0,0,0,0,0,3150,0,0,0,0,0,2130,0,0,2900,0,0,0,4500,0,0,0,0,0,0,3535,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3150,0,3297,0,0,0,4450,0,0,4450,0,0,4040,0,0,0,0,0,0,0,4170,0,0,2790,3500,0,0,450,0,4498,0,0,0,0,0,0,0,0,0,2972,0,0,3000,0,0,0,0,0,0,0,0,0,2000,0,0,4189,0,0,4500,0,0,3500,0,0,0,0,0,0,0,0,4400,0,3597,0,0,0,0,4500,4000,0,0,0,0,0,0,0,4200,0,0,2257,0,0,0,0,0,0,0,4800,0,0,0,0,0,0,0,0,4100,0,0,0,0,0,0,0,0,4800,0,0,0,3640,0,0,0,0,7190,0,0,0,0,2758,0,0,0,4050,0,0,0,0,0,0,0,0,1599,4750,0,0,0,0,0,0,0,5500,688,0,5000,0,0,4997,0,3900,0,0,0,0,3285,3830,0,0,0,820,0,0,4515,0,3000,0,4000,0,0,0,0,3920,0,0,0,0,1698,0,0,0,3500,0,0,5000,3000,2700,0,0,3000,0,0,5000,0,2526,0,0,0,3706,0,0,0,0,0,0,0,0,3500,0,0,1866,0,2250,0,4000,0,0,0,0,0,0,0,0,4410,0,0,5240,0,3120,0,0,0,3795,0,0,0,0,0,0,3042,5000,0,4541,0,7994,0,7000,0,0,4860,5140,0,0,3251,0,0,0,0,0,0,1932,0,0,0,4050,0,0,0,0,0,0,0,0,0,0,0,2530,0,0,0,4300,0,0,4400,4400,2880,0,0,4000,0,0,4946,0,257,0,0,0,0,3500,3000,0,3500,0,0,0,0,0,4950,4870,1500,0,0,0,0,3624,0,2254,2466,0,3290,0,0,0,0,4290,0,3480,3500,0,0,0,0,3500,0,0,4000,0,1300,4700,0,0,2807,0,3520,0,0,4000,0,0,4000,0,0,0,0,3000,0,4650,0,0,4500,0,400,0,0,0,0,4770,0,0,2400,0,0,0,0,0,0,0,2023,0,3750,0,3827,0,0,3600,0,2500,0,0,0,2500,0,4139,3000,0,3030,0,4800,0,0,2953,3500,0,2966,4300,0,4500,0,0,0,0,5000,0,4000,4978,0,4000,4000,0,0,0,3600,0,0,100,4117,0,3600,3570,2922,0,0,3300,808,1000,0,4900,3500,0,0,0,0,0,0,0,0,4000,3250,0,2530,0,0,3394,0,0,0,0,4774,4400,0,0,3000,5610,0,0,3000,3654,4115,0,1750,0,0,4650,0,4054,2775,0,0,1800,5000,0,0,2383,3660,3397,3840,4728,4598,0,3160,6000,0,0,3900,0,0,1290,3500,4375,0,0,0,3000,2413,0,0,3500,6800,12588,0,4818,0,0,0,0,4713,0,3404,0,0,0,0,0,3403,4500,0,4700,3125,0,0,1324,0,2411,0,3694,0,0,0,500,0,0,0,0,0,0,4000,4500,4778,2800,0,4000,0,2564,3300,4251,4047,0,0,0,0,5000,0,0,0,2000,0,0,1000,0,0,0,0,4000,0,0,0,4303,0,0,0,0,0,3000,2071,0,3780,0,0,1800,0,0,0,5553,0,0,0,0,0,0,0,0,0,0,0,0,4200,0,8615,4354,3014,3188,0,5250,0,1971,0,4600,3100,0,2000,3000,0,0,0,0,5300,3720,4950,0,0,3270,0,0,0,0,0,0,0,0,0,2550,5000,0,0,1800,0,0,0,0,0,0,0,0,0,4983,0,6952,1000,2741,3000,0,4913,0,0,4500,0,0,0,0,0,5000,0,5100,3210,3000,0,3750,0,2300,3500,0,0,0,0,2549,0,0,2610,0,5500,3450,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,4700,0,0,0,0,0,3000,2971,0,0,0,0,3960,0,0,0,0,0,0,3900,0,4100,0,5160,0,0,0,0,4500,0,4000,3350,4442,0,4000,0,0,0,0,0,3447,6200,2500,2088,0,807,4907,4000,0,1000,3800,0,0,6000,0,2500,0,2500,0,0,3736,2000,3936,0,0,1500,0,2817,4253,5750,5200,0,0,4400,3920,0,4500,0,4129,0,4350,0,2524,0,0,0,3000,3250,0,0,0,4000,4240,3500,0,0,4700,4500,5396,0,686,2500,3780,4450,0,0,0,3255,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,5000,6000,0,5000,0,4446,0,1415,0,0,0,0,0,1250,1000,0,1500,4000,0,0,4000,4000,0,0,0,0,0,500,4000,0,0,0,0,0,5000,0,4550,4000,0,0,2500,0,1000,3400,0,1300,0,5000,7500,0,0,0,0,0,0,0,0,0,0,5000,3983,2000,3500,0,0,0,0,0,0,0,0,0,0,0,6000,2000,10000,0,0,0,0,0,4700,0,0,0,0,0,0,5000,2750,3625,1000,0,0,3600,4900,0,0,0,0,0,0,0,3422,0,0,0,8000,0,0,6000,0,3000,0,2000,0,0,0,1500,3000,0,3000,7000,0,0,0,0,1000,3300,2500,5000,3000,0,0,8000,0,0,5000,5970,4000,450,0,5000,0,0,0,0,5000,7500,0,2500,0,0,4500,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,5650,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,2500,0,0,0,0,1300,500,5000,0,0,0,0,0,3000,0,0,0,5000,0,450,0,0,0,2500,0,0,0,0,2000,0,3000,0,0,5000,0,0,750,0,0,0,0,5760,0,3000,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,450,4450,1000,7993,2100,0,7700,0,1498,0,0,0,0,0,0,0,0,0,0,5000,0,500,0,4771,0,0,0,750,10000,0,0,3500,0,3800,5000,3000,5000,0,0,3000,5000,0,0,3500,1500,0,2500,6000,0,0,0,5000,0,0,0,500,1950,1000,0,0,0,3510,0,0,0,8500,0,0,0,5000,0,5000,2500,3252,0,3303,0,7000,0,0,0,0,0,0,0,0,0,0,7200,0,5000,0,0,0,0,0,0,0,0,2000,0,2700,15000,640,0,12072,7500,8964,0,0,0,0,1050,0,0,0,0,7500,10000,0,0,0,0,5000,900,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,4000,0,4000,0,0,2641,3000,3600,0,0,0,0,0,6600,4000,0,500,500,0,0,0,0,2000,0,2500,2500,4300,0,0,220,500,4590,1000,0,0,0,0,0,0,0,0,0,0,0,0,6000,0,0,0,0,0,0,0,0,6000,0,0,0,0,0,0,4000,0,4309,0,5000,3500,0,0,5500,2700,2000,0,2850,0,0,0,0,2000,0,0,0,0,0,0,0,0,3500,751,0,0,0,0,0,0,0,8000,0,0,6500,0,5000,0,2500,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1560,0,3175,3700,0,1000,0,0,0,0,0,0,0,0,4700,0,0,1600,200,5000,0,0,0,0,0,5500,0,0,3985,3500,6000,5500,4206,0,3033,0,2903,1515,0,5000,0,2000,0,4000,0,5430,0,0,0,0,0,0,4900,0,1500,0,5700,0,0,2850,0,3434,0,0,0,0,0,7670,0,0,0,0,0,0,0,1500,6200,0,0,0,1000,0,1500,0,0,3703,0,7279,0,0,1300,0,0,0,4927,0,0,322,0,0,0,3500,0,0,0,0,0,0,0,0,6500,0,0,0,0,0,5000,0,0,4000,0,5000,4500,0,0,0,0,0,0,0,0,0,0,1700,0,0,0,2000,6000,0,0,0,0,0,0,0,0,0,4000,2800,0,0,0,0,0,6000,0,0,0,0,0,0,0,21490,12800,0,0,0,0,400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,12000,0,0,820,0,0,0,0,0,0,0,0,0,0,0,15000,0,0,0,0,0,0,0,0,0,25000,7000,0,0,0,10000,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,500,0,0,0,0,200,0,0,0,0,0,0,0,0,850,0,0,0,0,0,0,0,0,0,0,0,4214,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,1000,0,4000,0,0,10000,0,0,0,0,0,7000,0,0,0,0,0,0,0,5000,0,0,0,0,0,500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,5300,0,6000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7500,0,0,0,0,0,0,0,0,0,0,3675,0,0,2500,0,0,0,0,0,0,0,0,0,5000,0,1500,0,5000,0,0,4000,2500,3000,0,0,4000,0,0,4000,0,0,7800,2000,4650,0,3457,0,0,0,2500,0,2500,0,1675,3700,5233,0,0,5900,0,800,0,0,9135,0,0,0,0,0,0,0,0,0,0,7800,0,0,750,0,0,0,0,0,0,4000,0,2500,2500,2700,2450,0,0,0,0,5000,2565,5500,0,1000,0,0,1500,6000,0,0,2500,0,0,500,5700,0,0,0,3000,4000,4000,0,0,0,0,4350,0,0,0,1500,0,0,0,0,0,3300,0,0,0,5000,0,0,0,0,850,1500,3300,8000,2198,2500,0,0,0,0,0,0,0,0,9300,0,0,0,0,3000,5000,1900,1500,1500,2982,0,0,5000,5400,0,3500,0,0,0,5800,0,0,0,0,0,0,0,3340,0,0,0,0,0,3175,0,3000,0,0,0,0,0,0,3385,0,0,0,5000,5500,2000,0,0,0,5000,4516,0,0,0,0,1150,0,0,0,0,0,6000,292,8250,0,0,4500,0,2500,0,0,0,1750,3045,6000,0,0,0,0,5000,1000,0,0,0,0,0,5000,0,0,0,0,7380,0,0,0,11880,4632,0,0,0,3585,0,7415,0,4000,5000,0,0,4800,2400,1500,5969,0,0,0,0,0,5500,0,0,0,2300,3000,0,0,0,0,0,0,0,3000,0,0,0,5000,4000,2000,0,5000,0,0,0,0,0,4000,0,3750,0,4000,0,5000,4786,0,1860,0,0,0,1513,0,8000,5000,0,3000,0,5000,0,0,0,2000,3000,0,0,0,0,0,10050,4000,4000,2750,0,0,0,5100,0,0,0,0,0,3500,0,0,0,0,5500,0,2800,0,0,0,0,0,5545,2000,5250,0,0,0,0,0,0,5000,0,0,5500,3000,0,0,0,0,0,0,1000,0,4428,4000,0,7546,10115,4000,0,3206,0,3000,0,0,3700,4000,0,0,4000,2000,3000,0,0,0,4000,0,0,0,0,0,0,0,0,0,3000,0,3921,1500,4800,4577,0,0,0,0,0,0,3500,0,0,5299,0,0,0,0,0,0,4232,0,0,4455,0,0,2000,1500,3500,0,0,4940,0,0,0,0,0,0,4000,0,4331,0,0,0,0,3900,0,0,5000,4750,0,0,2300,0,4497,4277,0,3285,0,0,2750,0,4000,4000,0,0,0,2500,4800,4871,4000,0,3150,0,0,3500,0,0,0,0,0,0,3182,0,0,4660,0,0,0,3000,3000,0,4000,0,4450,0,4500,3200,0,0,0,1500,0,3000,0,0,4723,0,3500,0,0,5000,5000,3000,0,0,3400,0,4440,2750,0,0,0,3375,4300,5000,0,0,0,0,0,4497,0,0,0,3652,4500,0,4900,0,0,0,4500,3000,0,5504,4600,4000,3540,4749,0,0,3324,3600,5025,0,0,0,4875,0,1500,3500,0,0,0,0,0,1500,0,0,4000,0,0,0,0,2634,0,0,3300,4005,0,3200,0,3000,0,3089,0,0,0,0,4375,2500,0,5250,5000,5000,0,0,627,0,4973,0,0,4932,0,5850,500,4000,0,950,0,0,0,2000,3600,0,6150,0,0,0,4050,2798,0,2300,0,0,0,5000,3000,0,4000,6000,0,5835,0,4000,0,0,5000,4000,0,0,0,0,5400,0,4500,0,4400,0,4044,0,0,4900,0,0,0,0,4452,0,1850,6000,6225,0,0,3700,0,5000,0,0,2124,0,0,0,0,0,0,4000,5054,4500,0,0,0,3557,5997,3450,4100,0,0,4500,0,0,3600,0,3812,4500,0,0,4800,0,0,5250,0,0,5000,0,0,4710,0,3800,4000,4731,0,5570,0,5000,0,0,4000,0,0,0,6250,0,0,450,0,0,5850,1500,0,0,4900,4450,0,4742,4300,0,3500,4000,5500,5211,0,0,0,0,5731,4500,0,4950,0,5000,1500,0,0,0,0,5000,0,3900,2000,0,3000,0,6800,4632,5200,0,0,0,4000,5000,0,0,5000,0,4500,0,0,4324,0,0,0,4199,0,3900,0,3200,0,0,0,0,0,0,4866,4785,0,0,0,5000,4000,0,2000,2611,0,0,4500,4631,0,0,4000,0,10440,0,4928,0,3789,4100,5982,0,5000,4296,0,0,5400,5000,0,0,4917,0,3000,2000,0,5176,0,5000,2200,3953,5000,0,4500,4000,0,0,5700,5000,0,0,4465,4500,5500,0,0,3000,0,2700,0,0,4500,4500,0,0,0,0,0,650,0,3465,4000,5955,5415,4000,3500,5100,0,4007,2500,0,5000,0,6000,13000,6000,0,3200,4386,3500,5162,4000,0,0,0,0,0,3000,0,0,4000,12000,0,0,4000,0,0,0,0,5326,5000,3310,2500,0,0,0,0,2500,4500,3783,5000,0,0,0,4000,0,6000,4500,600,0,5000,5000,4741,0,3668,6170,0,0,1000,4000,0,4500,2500,0,0,0,0,0,0,0,0,4034,0,0,5970,6000,0,0,0,4600,0,850,5555,6000,0,0,0,0,0,0,5000,5000,0,0,3900,0,0,0,0,4000,0,2143,4000,5000,4900,6325,0,0,3250,0,0,0,0,0,0,5000,0,0,0,0,0,1860,1000,1500,5217,0,2500,3810,0,0,0,3000,3500,0,0,0,0,0,0,3750,6200,3500,4200,0,0,5000,0,6340,0,6050,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,5000,0,0,2500,4000,6500,0,200,0,0,12000,3000,5860,0,0,0,6100,0,3800,0,0,0,5000,0,0,0,0,0,3000,0,0,2000,2500,3000,0,0,3806,3000,0,1500,0,0,4675,4000,0,0,1245,0,0,0,0,0,0,0,0,2161,675,4290,4483,2000,0,4600,0,0,7557,0,2700,0,0,1650,5000,0,0,0,0,4000,0,0,0,1000,0,0,500,5000,6500,0,0,0,0,3960,3600,0,0,0,0,5845,0,0,0,0,0,0,0,4700,6500,1550,5194,3000,0,0,7250,0,0,0,0,0,0,0,1200,0,1500,0,0,0,0,1000,0,0,0,330,0,625,0,0,3000,0,0,5000,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,10000,0,2500,6000,7000,0,0,1000,0,3794,0,0,0,0,0,0,3000,0,0,1000,5000,22500,0,0,0,0,0,0,0,7500,6600,0,0,1583,0,3920,0,0,0,0,0,2000,0,0,0,1750,1503,0,0,3488,5000,0,0,0,0,0,0,7000,0,0,0,1680,4500,3500,0,3617,3740,3000,2940,0,0,0,0,0,4035,3000,0,0,0,0,0,0,0,4170,2091,0,0,0,0,0,0,3750,2400,0,0,0,3796,0,1525,0,4982,0,2000,0,0,4000,0,0,0,0,2500,4208,0,0,0,0,0,4000,4323,3140,0,4307,0,0,2000,3000,0,0,0,0,0,4000,0,3262,0,0,11910,0,4037,4413,4214,0,5000,5000,0,0,0,0,0,0,0,0,0,0,0,5940,0,0,5400,0,0,3000,0,2219,0,1000,0,5500,4882,0,0,3320,0,3000,0,0,0,3000,500,2900,0,0,5600,0,0,0,0,200,7000,0,0,0,5000,0,0,0,0,0,0,0,0,8000,0,1500,0,0,0,0,0,0,0,0,8000,2700,3600,5100,0,0,0,0,0,0,0,0,700,0,0,0,0,0,0,0,700,500,540,0,0,4500,0,0,0,0,0,0,513,0,0,0,0,0,5000,12000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2386,5247,0,0,0,0,0,5151,0,5000,0,0,0,0,0,0,5000,6327,0,0,0,4000,0,7500,3000,0,0,0,0,0,4500,0,4500,5000,0,0,5000,3190,2500,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,2700,5000,6800,4400,4300,0,4500,0,4302,0,3200,0,0,20000,0,0,0,0,8000,0,0,0,0,3629,0,2500,4000,0,0,0,1280,3725,1500,0,0,0,5000,5500,4000,3700,0,0,0,0,500,0,0,0,10000,0,0,0,1000,4500,0,5000,4920,0,0,0,4800,0,0,0,0,0,2000,0,3300,0,0,0,5000,5940,0,5061,0,0,0,0,5000,0,0,0,0,0,500,4000,0,4800,6400,0,5500,5000,0,0,0,4000,0,0,0,0,0,0,0,0,1500,0,2500,0,3250,0,0,0,0,0,4400,0,1750,750,0,0,10935,0,3328,2500,0,0,0,0,0,2000,0,0,1500,3000,5500,6000,1250,0,0,0,3500,0,0,8000,0,2500,0,1300,4300,0,900,0,0,0,0,0,3500,0,6000,2000,6500,0,0,0,0,0,0,0,0,9670,0,0,0,0,0,1200,0,0,0,0,1500,0,0,0,0,0,0,0,0,0,0,4000,4059,0,0,6500,0,0,6000,600,0,0,0,0,3900,0,4788,0,0,0,0,0,0,0,0,0,0,2400,0,0,0,0,0,0,0,3380,0,0,0,0,0,0,0,0,4600,0,0,0,0,13350,0,0,4800,0,6000,0,0,0,0,0,3500,0,3500,0,4000,0,0,5500,1740,0,0,0,0,0,0,1100,0,0,4000,0,0,0,650,0,7000,5000,0,3400,0,0,995,2500,0,1850,6174,7000,0,5000,0,0,0,5000,0,6000,500,0,0,0,0,0,0,2000,2400,0,0,5500,4631,4000,0,1415,4500,5000,0,0,0,0,0,0,6500,0,0,0,0,8500,0,8500,6600,87,0,5000,3500,0,2830,0,4000,3000,5500,0,8000,0,11850,0,0,0,4500,2500,0,1000,0,0,0,0,0,10000,0,0,0,0,0,9819,0,500,0,7300,5000,0,0,0,7000,8492,0,0,4000,0,0,0,1000,0,0,0,0,0,3025,0,0,3000,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2222,0,0,0,0,0,0,0,0,7000,0,3000,0,5850,0,5000,0,0,0,0,0,0,700,0,1500,0,0,0,0,0,0,0,3300,3382,0,0,0,0,4000,0,0,0,5000,0,0,0,0,0,200,0,0,0,0,0,0,0,0,3600,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,3878,0,0,0,0,1000,0,0,0,0,0,0,0,0,0,0,0,9000,0,4100,0,0,0,0,6000,0,0,0,0,4500,0,3800,2500,0,0,15000,5000,0,0,12500,0,0,1500,0,0,0,0,0,0,0,0,0,4750,0,1400,3150,2865,0,4830,5000,1500,0,500,0,0,0,0,0,8837,4260,4000,0,1679,0,0,7500,695,0,0,0,0,0,0,0,0,0,0,10000,0,7000,7500,0,0,0,0,0,0,0,0,0,0,2000,600,0,5000,7000,0,0,0,350,14094,32100,2750,30000,0,10000,0,0,0,0,1500,5000,0,15000,500,0,0,0,0,0,10000,0,0,0,0,0,0,0,0,2489,0,1000,0,7000,0,2000,0,0,0,0,0,0,0,0,4500,0,2483,5760,0,3000,0,0,0,0,0,0,0,0,3000,0,1500,4100,0,0,0,0,0,4000,0,0,6950,2500,0,0,0,0,6457,0,0,0,0,5400,4000,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8500,0,0,0,0,0,0,0,0,0,0,0,0,7600,0,0,0,0,0,6242,0,0,2500,0,0,0,0,0,0,3146,0,0,0,500,5200,0,0,2900,0,3000,0,4000,6300,0,0,0,0,2000,2000,0,7000,0,0,0,0,0,6000,0,3500,0,4000,0,0,3000,0,0,4000,0,8085,6300,6600,4500,0,0,0,0,3980,5412,4000,0,4000,0,0,6000,0,0,0,6000,0,5900,0,0,6500,0,0,0,6700,0,0,0,0,0,0,0,0,4800,0,3964,0,0,0,0,0,0,0,3985,0,3000,8000,9078,0,1500,0,0,0,0,4040,0,0,0,0,0,0,7000,0,1200,0,0,0,0,0,0,0,3000,0,0,0,0,0,150,0,0,0,0,0,0,0,0,2000,0,0,0,3500,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,4000,0,0,0,4400,0,0,2385,0,0,0,0,3000,2000,0,6000,5000,2592,5500,0,0,6000,4460,0,5000,5500,10000,0,5000,5000,4000,5400,0,0,375,0,0,0,0,5000,0,0,3700,0,7000,0,0,4000,0,0,0,0,1000,0,0,6000,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,1100,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2500,0,1500,0,0,0,0,0,0,0,2675,0,0,0,0,0,0,0,0,429,6000,4400,0,3000,0,0,0,0,0,0,0,2000,0,2500,0,4190,7000,0,0,0,13137,0,0,1000,0,0,0,0,2000,0,0,0,0,1000,500,0,500,0,0,0,0,0,2800,0,0,0,0,0,0,0,0,0,0,0,5169,5500,5000,0,5000,0,2500,0,5250,2000,0,5000,6500,0,0,0,0,0,0,5000,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3537,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,1666,0,0,0,0,1410,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,1710,0,1747,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,0,0,0,0,2290,0,0,0,0,0,0,0,0,2000,0,0,1560,0,2500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1700,0,0,0,0,0,0,0,0,0,200,0,0,0,0,0,0,0,1175,0,0,0,2217,0,0,0,0,0,0,0,0,0,0,0,4350,0,0,0,0,0,3947,1500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1470,0,0,0,0,0,0,0,0,3850,0,0,0,0,0,0,0,0,0,2100,0,0,0,2760,2482,1050,0,0,0,0,0,0,0,1524,1950,0,0,0,0,2416,0,0,2040,0,0,0,3657,0,0,0,0,0,2000,0,0,0,1890,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1250,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2327,0,0,0,0,0,0,0,0,0,0,1500,0,0,3503,0,0,1800,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,0,0,1582,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,2025,0,0,0,0,0,0,0,0,0,0,0,0,0,2100,1044,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,0,0,0,3297,0,0,0,0,0,0,0,0,1000,0,0,0,500,0,0,3801,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,3597,0,0,0,3000,4000,0,0,0,0,8000,0,4200,2000,0,4000,5000,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2800,0,0,0,0,1640,2900,0,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,0,0,0,1250,0,0,1100,0,0,0,4139,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2100,2000,2330,2750,0,0,1500,0,0,0,0,2600,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,1500,0,4900,0,0,1500,3500,0,0,0,0,0,0,4000,0,0,0,0,6500,0,0,0,0,0,0,0,0,0,0,4005,0,0,0,4500,0,6500,0,5625,0,0,4477,0,0,500,7650,0,0,5000,1450,5000,5000,3239,1898,0,0,0,0,0,0,0,0,0,0,4890,0,0,0,0,0,4799,0,0,0,0,0,0,200,0,5000,5000,2500,3400,0,5500,0,0,250,0,0,873,5200,350,0,0,0,0,4625,500,0,3846,2790,1800,0,4000,0,0,6000,0,0,0,0,0,0,0,0,1500,0,0,0,5000,0,2000,0,1415,0,0,4000,3796,0,1000,3500,0,5000,1700,3959,0,0,0,5000,0,0,0,0,10800,4500,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,5705,0,0,0,0,400,1000,4000,0,0,0,0,0,0,6634,7490,3000,400,0,0,5000,0,0,0,0,0,0,0,0,6377,0,5278,0,0,0,0,0,4000,0,3700,0,5000,1000,0,0,0,6000,0,4000,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,1002,0,0,0,0,0,3700,1500,0,0,2839,0,4000,4113,4000,5500,6000,0,4000,5599,0,3200,0,0,0,6604,4000,6200,1000,3613,0,0,0,0,5190,0,0,5000,0,0,0,0,0,4000,8000,1500,0,0,0,0,0,0,3000,5500,0,3628,0,3770,3820,1000,5867,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,1500,0,0,0,3600,4526,6900,0,5000,0,0,4000,0,5600,6000,0,2250,0,2000,0,9100,7084,3500,850,5000,1300,2000,5000,0,6000,0,0,3000,0,0,0,11800,0,4500,0,9900,0,6500,0,0,2500,2000,0,0,0,2500,0,0,4500,0,0,0,4000,10448,0,5000,0,0,4400,2000,4000,4000,3250,0,0,0,4000,4310,0,0,4000,5000,0,0,0,4000,0,0,0,0,2850,0,0,0,0,0,0,0,3100,0,3000,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2200,2200,0,0,0,0,0,3500,0,0,0,0,4000,3150,0,2065,0,0,0,0,0,2600,0,0,4830,0,0,0,0,4500,3500,0,4200,0,9780,0,6375,0,4272,4000,0,0,0,0,0,6484,5100,0,0,4500,0,5934,4094,0,3077,5000,0,7000,0,0,0,5000,0,0,0,0,13500,0,6000,5900,4500,0,5500,1299,3000,5000,0,500,0,0,0,0,0,0,6000,5200,2000,0,0,0,4750,0,0,4000,0,0,1691,3000,3250,0,5000,0,0,552,0,1890,6800,8295,0,0,1200,0,7900,0,4258,4500,0,0,0,7000,0,5000,6000,7000,1050,8200,0,2000,5500,0,0,0,0,3000,10700,0,3000,0,0,3400,3297,0,6201,2750,2000,4187,3000,5450,0,0,0,0,0,4262,3500,5000,1200,2500,1500,0,0,2500,0,3864,0,3000,0,0,0,0,0,0,2000,4000,0,6145,3500,0,5000,0,3000,0,0,0,3600,4000,0,0,0,11375,0,0,0,4500,2520,3571,4000,0,3500,0,2460,0,2000,0,0,0,0,0,4250,0,0,3000,0,1200,5000,4021,0,5000,1000,0,0,0,4248,0,0,0,0,3500,0,2000,3000,0,1000,2000,0,3300,0,4350,0,0,0,4020,0,0,0,0,0,1500,5000,0,0,2000,3250,2751,4000,2700,0,1000,0,0,2500,0,2640,0,1800,0,1900,2550,0,0,0,0,0,0,0,3500,0,2500,0,0,0,0,0,0,0,0,0,2000,0,4443,0,0,3986,0,0,0,0,0,2000,0,0,4000,0,5000,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,500,0,2600,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7750,0,5000,0,0,0,0,0,0,0,4745,0,0,4222,1800,3000,1776,0,1750,0,0,1406,0,0,3771,5000,6200,0,5600,0,0,0,0,0,5000,500,0,0,0,4000,0,0,0,2000,1080,500,0,500,3320,0,0,0,4972,0,0,0,0,0,6646,0,0,1165,3000,0,4000,0,4546,0,5077,0,0,3240,5000,0,0,500,0,0,0,2500,0,0,0,0,0,0,0,0,0,0,1925,0,0,0,0,3000,0,2500,0,0,0,0,0,0,5682,0,0,4500,0,0,0,0,0,0,0,5000,6000,0,350,0,4000,9270,0,0,5000,4562,2750,0,0,5800,500,5000,0,0,0,0,0,0,0,4000,1217,0,0,0,1200,3885,4900,4500,0,4000,2000,0,0,0,3000,0,0,0,0,0,0,0,4000,5400,5000,7400,0,0,3772,0,4000,0,0,0,0,0,5394,0,0,0,0,3000,0,3000,0,0,0,0,0,0,0,3000,2000,5000,0,0,0,0,0,3914,0,0,0,0,0,0,4488,0,0,0,0,0,0,0,8500,0,0,0,0,4000,6500,3000,0,0,5321,0,5000,0,0,0,0,4000,0,0,3900,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,4600,4000,0,2800,5000,0,0,0,0,6750,0,500,0,0,0,0,0,0,0,3260,0,5700,0,6500,0,9000,0,0,5000,0,7500,0,8370,5000,5500,0,0,0,0,3500,0,3500,0,0,0,2000,0,0,0,5200,0,0,7051,2300,0,0,0,5000,4887,5000,0,4425,0,0,0,3150,4500,5474,7025,0,0,1500,3125,0,0,0,4000,0,0,8000,3500,1000,3900,0,0,3000,4819,1400,0,0,0,3175,0,6500,2000,5000,0,4000,3500,3246,0,3000,0,4000,1350,0,0,0,5000,0,0,0,5203,3300,0,0,1000,0,0,2600,1200,2850,0,6581,0,0,0,800,0,0,0,0,0,0,0,0,2000,918,0,0,0,3000,0,0,0,0,0,3000,0,0,0,3000,3875,0,0,0,3796,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,22000,5000,5300,0,2000,0,0,9447,0,0,0,0,0,0,2500,0,440,0,0,0,0,0,0,3000,0,0,7500,0,6000,0,3500,0,0,3200,0,0,3000,0,0,5100,5200,0,0,4500,0,0,0,0,0,0,2000,1400,0,0,0,0,4500,0,0,0,0,0,1250,0,1550,0,1000,0,0,1100,0,0,2200,0,2000,0,0,0,0,0,0,0,0,3195,3500,0,0,0,2750,3650,0,0,3000,0,1000,1420,0,0,2955,0,0,3600,0,0,3450,0,0,0,0,0,0,4300,0,0,0,0,0,0,1500,5000,8000,6817,4760,4000,4500,6000,7389,0,5550,6000,5556,6400,0,5000,0,2200,4898,5000,0,0,0,4765,4000,2900,0,5000,8000,5000,0,6700,0,5000,2500,3185,4700,0,0,4000,6313,5048,6000,4652,5000,5000,0,0,0,4500,1500,4904,0,0,3500,0,5000,5000,5340,0,0,0,0,0,0,0,2000,1680,0,0,0,0,0,0,0,0,0,0,3533,0,0,0,0,0,0,0,0,2368,0,0,0,0,0,3500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4597,385,5350,0,0,0,0,0,800,3000,0,3000,0,0,0,0,0,0,0,0,2380,0,0,2500,5500,6000,5622,0,5899,3000,0,0,0,2945,0,4434,0,0,6000,4200,6900,6700,0,0,0,3250,0,0,0,0,0,0,0,1500,0,2000,4000,2500,5360,1522,2361,3687,0,0,0,0,855,0,0,0,0,5624,0,0,0,2294,2500,0,0,0,0,5500,4000,5000,0,0,0,5400,4600,0,0,0,0,0,0,0,0,0,1000,0,2000,0,0,6341,3500,1000,5000,0,4356,4500,4170,0,1000,0,2500,7736,4000,4000,5000,5000,4500,1035,700,5624,0,5670,0,0,5500,0,0,0,0,400,0,0,3500,5000,0,2425,800,0,0,0,0,3566,2500,0,3500,6300,0,0,0,0,0,2000,3007,0,0,0,0,0,0,0,0,0,7636,14014,6926,16900,8040,6736,7402,8486,0,8198,6200,7796,7432,9061,6200,0,0,0,6200,0,0,3900,0,0,0,1900,1500,0,0,0,0,5000,1200,0,0,0,0,0,0,0,0,0,0,0,0,1874,0,0,0,2900,0,0,0,0,3660,0,0,0,0,0,4350,3600,0,0,0,4000,2000,2478,0,2000,0,1400,3000,0,0,0,4800,0,0,0,1176,0,13350,2050,2900,0,0,0,0,5000,2100,0,0,0,0,2500,3000,3200,0,0,3915,0,0,0,0,3747,2500,4000,6000,5969,11426,8860,10788,9704,0,10069,9845,10489,7979,0,8884,0,10739,0,0,3948,2500,0,2500,5500,4000,0,0,0,5000,6800,5000,3500,3000,5000,4000,0,5000,2031,0,6200,0,5334,0,0,5809,5000,500,0,10483,0,0,0,300,6000,0,7830,3000,0,0,5500,0,6000,0,0,0,0,3699,4560,5000,6000,2800,0,0,0,0,0,0,2500,0,6000,0,2000,7122,0,3200,6500,4000,0,0,745,0,0,0,0,900,0,4055,0,3000,0,3000,1449,0,4000,2400,4055,0,5000,0,3000,0,0,3500,5000,5200,0,3748,6650,4000,8715,10000,0,3716,8250,6960,0,0,0,0,0,8000,4500,1500,450,4500,0,0,3291,0,0,0,0,1200,0,0,0,0,0,0,0,0,0,0,0,0,0,1820,0,0,0,0,1000,0,1260,2913,1500,2700,2500,0,2500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3220,0,3870,0,0,1000,3697,6646,5000,5000,0,5600,0,0,1800,0,0,500,2500,0,5178,0,5000,0,0,3500,0,4000,0,3000,0,0,0,0,4000,1000,4650,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13500,0,0,0,0,0,0,0,6200,0,0,0,0,1500,0,0,0,0,0,0,0,0,0,500,0,0,1500,5000,0,0,1000,0,0,0,0,0,0,2000,0,0,0,0,10000,0,9975,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,6691,0,0,0,0,0,0,1330,0,700,0,5000,0,0,8220,5500,0,5000,2000,0,0,5100,0,0,8070,0,0,0,2860,0,100,0,5920,5000,0,0,4000,0,3200,0,0,0,0,0,0,0,0,5000,0,0,3000,0,5677,6000,9100,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6001,0,0,7389,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3620,0,0,0,0,0,0,6100,7950,3960,0,3000,0,0,0,0,1200,0,0,0,0,0,0,7800,0,1000,0,0,3000,0,0,0,5350,0,2000,0,5475,0,2000,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1950,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4500,0,0,1600,0,2500,6500,0,3641,0,0,0,0,0,0,3000,7200,0,0,500,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,5600,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,6910,5550,0,3700,0,3997,2069,0,4000,0,0,0,3000,0,5000,1912,5000,2000,0,3000,0,0,0,4440,4650,4500,5900,0,0,0,0,0,2345,1500,0,5000,0,4697,7000,0,0,0,1000,0,6522,0,0,0,0,0,5389,4736,4950,0,0,3194,945,0,0,0,0,0,5731,0,0,0,5247,0,0,4000,0,4500,3720,0,0,0,3650,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,3551,6900,0,6450,5400,2500,0,5000,0,0,6480,6000,0,0,0,0,5000,0,0,0,5000,5000,0,0,4043,0,3000,0,0,6000,0,0,3395,0,0,9700,0,0,6000,0,0,0,0,16600,2400,0,0,0,4000,4200,0,3500,0,0,0,5576,0,2000,0,4200,0,0,5000,0,6000,0,4200,3800,5000,5500,0,6500,0,5000,0,0,0,0,0,4000,5000,6400,350,5697,5000,0,0,1100,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7500,0,0,5000,2601,0,0,5340,0,0,7000,0,0,9000,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,2910,0,0,0,3100,1000,0,5000,0,4755,0,0,0,0,0,0,0,0,0,4900,2500,2600,2000,0,0,0,0,0,0,1100,0,5000,0,0,0,0,0,0,1000,0,0,0,0,0,0,511,6000,0,4884,0,0,0,0,0,5000,0,2418,2500,0,0,3900,0,0,4400,4000,0,0,3000,3000,3479,0,0,0,0,1601,0,0,6500,4147,2500,4000,0,0,4677,6150,4000,4655,5700,0,2000,0,0,0,5500,0,0,0,500,2500,5000,5059,0,2875,5200,4634,5953,0,0,5000,0,6595,3868,0,3990,4600,4800,0,0,4500,0,0,0,0,0,0,5500,900,0,3125,4800,0,5500,332,0,0,0,0,0,3000,0,6747,0,5000,6000,750,3800,0,0,4981,0,0,6900,4000,1800,0,0,0,0,0,0,0,2641,2000,0,3800,0,0,0,3900,0,0,0,0,0,0,0,0,0,1800,1500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1800,0,3797,0,0,2699,0,0,0,0,0,0,3500,0,0,0,2000,0,1500,1000,2500,0,0,0,0,4800,3936,2500,3656,4500,0,0,0,4000,0,0,3400,0,0,0,0,3695,1394,0,3000,2000,0,0,0,2280,0,2279,0,0,1320,0,0,0,0,0,0,0,0,0,0,3671,3000,0,0,0,3200,0,0,0,2500,5000,0,5000,5000,5000,0,5000,2500,0,0,0,4800,0,0,0,3000,0,0,0,0,6500,0,0,5250,0,0,0,0,0,0,0,5000,0,470,4604,0,0,0,5000,0,0,7000,250,0,0,7500,3500,3000,5588,0,0,4540,0,0,0,5000,6000,3000,0,4808,0,0,0,5879,8484,500,5500,0,0,0,1000,0,0,7000,0,0,0,8498,10100,5000,0,0,2500,0,300,0,0,8728,6176,0,0,0,0,0,0,0,800,2500,8000,1400,0,0,0,0,0,0,0,0,4500,0,0,0,0,0,0,3500,0,5000,0,0,0,0,0,0,0,0,1000],"yaxis":"y","type":"scattergl"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Built Before 1980 (1: Yes, 0: No)"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Deduction from the selling price"}},"legend":{"tracegroupgap":0},"title":{"text":"Deduction from the selling price v. before1980"}},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="9cf355a2-d61d-4eb6-80d4-5e460274372a" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("9cf355a2-d61d-4eb6-80d4-5e460274372a")) {                    Plotly.newPlot(                        "9cf355a2-d61d-4eb6-80d4-5e460274372a",                        [{"hovertemplate":"before1980=%{x}\u003cbr\u003ededuct=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","symbol":"circle"},"mode":"markers","name":"","showlegend":false,"x":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,0,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,0,0,0,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,0,0,1,1,0,1,1,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,0,0,0,1,0,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,1,1,0,1,1,0,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,1,0,1,1,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,1,0,0,0,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,1,0,0,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,0,0,0,0,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,0,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,0,0,0,0,1,1,1,1,0,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,0,0,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,0,1,0,0,1,1,0,1,1,0,0,1,1,1,1,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,0,0,1,0,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,0,1,0,0,1,1,1,1,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,1,1,0,1,0,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,0,0,0,0,0,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,0,1,1,0,0,0,1,0,0,1,1,1,1,1,1,0,1,1,1,0,0,0,1,0,1,0,1,0,0,0,0,1,0,0,0,0,1,0,0,1,0,0,0,0,1,1,0,1,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,0,1,0,1,1,1,1,1,0,0,0,1,1,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,0,0,1,1,0,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,0,1,1,1,1,1,0,1,1,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,0,0,0,1,1,0,0,0,1,0,1,0,1,0,0,1,0,0,0,0,1,1,1,0,0,0,0,1,1,1,1,0,1,1,1,1,1,0,0,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,1,0,0,1,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,1,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,0,1,1,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,0,0,0,0,1,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,0,1,1,1,1,1,0,0,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,0,0,1,1,0,0,1,1,0,0,1,0,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,0,0,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,1,1,1,0,0,1,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,1,0,1,1,1,1,0,0,0,0,1,0,0,1,0,1,0,0,0,0,0,1,0,1,0,1,1,1,0,0,0,0,1,0,0,1,0,0,1,1,0,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,1,1,0,1,0,1,1,1,0,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,1,1,1,0,1,1,1,0,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,0,1,0,1,1,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,1,0,1,1,1,0,1,1,0,1,1,1,1,0,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,0,1,0,1,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,0,0,0,1,1,1,0,1,1,0,1,1,0,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,0,0,0,1,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,1,1,1,1,1,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,1,0,0,0,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],"xaxis":"x","y":[0,0,0,3220,0,1000,0,0,0,0,0,0,0,0,5300,4200,0,4600,0,3750,3200,0,4500,4350,4312,3270,0,2000,5000,0,4300,4095,4035,0,4860,3960,1490,4000,0,0,0,0,3000,0,4000,3317,2700,0,5500,0,4000,4396,4440,5800,0,2990,0,0,0,1630,4500,0,0,0,6000,0,3000,3500,0,0,0,5280,5252,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,0,0,0,8281,0,5000,3742,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6375,500,7550,3981,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,5440,5157,5000,0,0,0,0,500,0,0,7470,0,0,0,0,1688,6960,0,0,0,0,0,4980,1560,6535,2613,0,0,3400,0,0,4995,0,5000,0,4460,1294,13975,0,0,0,2755,3930,0,0,0,0,3580,3390,0,0,0,0,0,4200,0,0,1500,0,0,8000,4921,8000,3500,0,5198,5970,5285,5000,0,0,0,2362,3660,3476,0,0,0,0,1051,6000,0,2250,0,5921,3500,0,2000,4900,0,3500,5000,6500,5000,4899,0,2670,5720,2100,0,5000,0,0,0,2000,3356,2522,0,0,0,0,2940,0,0,0,0,0,3700,0,0,0,1000,0,0,1800,2500,0,3500,1780,1600,0,1900,0,1980,0,0,0,3260,5500,3815,0,4620,0,351,3013,4500,0,3750,0,3600,0,4723,0,4800,0,0,0,0,0,4500,4290,4000,4050,0,3900,6860,0,0,0,0,5418,4999,0,7000,3500,5056,0,0,0,0,5500,0,0,0,0,0,0,5295,0,0,3500,0,4050,5597,0,4000,0,1620,0,0,6220,0,4000,0,4400,5500,2289,6000,0,1000,0,3700,9537,5322,4000,0,5000,0,0,5000,0,5500,5910,2800,5530,0,3188,3600,3000,4290,0,4300,3897,0,0,4740,0,3630,0,0,0,4000,4655,5500,3000,0,6922,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4860,0,4000,5000,3212,5585,0,0,0,0,0,0,0,5250,1600,5000,0,5000,0,0,5100,0,4267,7634,6000,0,5000,6000,0,0,0,0,6500,0,0,1000,4758,0,5280,300,5280,5850,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3723,0,0,0,0,0,3578,0,5000,0,5000,0,3844,5846,6500,5000,5000,4116,0,0,0,0,0,6140,4500,5000,0,5000,0,0,7600,0,0,0,5000,0,4921,0,0,0,0,5000,0,5000,6500,0,3926,0,0,0,0,0,6500,0,3000,0,5000,0,4292,0,0,0,3247,5000,6000,0,5000,0,4971,5000,0,3292,0,0,0,0,4163,7390,0,0,6025,1320,3500,0,3559,0,0,0,4347,0,5250,3000,0,2000,3294,4950,0,5100,3678,0,1000,3750,10900,4200,3900,4616,4500,0,0,0,4500,4243,4000,4947,3815,3325,0,0,3783,0,3900,7879,0,0,0,0,3150,3540,0,4300,0,4122,0,1279,3635,805,3400,0,3585,0,0,0,0,0,0,0,0,4380,3600,4393,3000,0,0,0,0,0,0,0,0,4164,3903,5000,3450,3920,0,2547,2400,2500,4400,2000,1500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1984,0,0,0,0,0,0,0,0,0,0,4734,0,0,3030,0,0,0,0,1500,0,0,2000,0,0,0,3000,3593,0,4068,4800,0,3540,3600,0,2187,0,0,5000,4500,1565,0,0,3297,0,2090,5546,4200,0,0,0,4928,0,4000,3500,0,3750,0,4500,0,0,0,3000,0,4000,0,0,8000,0,1892,0,0,0,0,2700,3800,0,0,0,0,0,0,1000,0,0,3870,0,0,0,4200,0,3541,0,0,0,3900,0,0,4440,4000,2495,0,1675,4000,4950,2398,1500,2000,0,0,0,0,3000,0,4647,4000,8500,0,1500,4000,4800,0,1400,1100,5550,0,4894,5100,4050,3200,5000,2700,3000,0,2817,0,0,0,0,3863,985,0,3000,3685,0,0,5000,4300,0,0,0,2500,2640,0,3000,0,4000,0,0,3299,0,2850,0,4600,2600,0,4671,2800,3913,0,3800,0,0,3373,0,0,0,0,2150,0,3600,3900,0,0,6100,2940,0,0,0,0,0,0,4753,0,0,4197,3800,0,1530,5000,2000,0,0,0,0,3747,2956,1180,5000,3064,0,0,0,4515,2000,3630,0,752,4548,4454,0,0,0,0,0,2890,0,0,0,0,1515,0,1525,0,0,0,2973,0,4500,3100,0,0,0,0,3500,984,2727,4000,0,0,0,3096,0,3300,5000,3570,0,3520,4000,0,0,0,0,0,0,1436,0,0,0,0,0,0,0,0,0,0,3897,0,0,0,2000,0,0,4000,3500,3600,2250,4000,0,0,0,3897,4500,0,0,4500,4819,0,0,3900,0,2912,3900,0,0,0,0,4533,4000,3750,0,4700,4400,5423,2000,4500,0,3200,0,3750,0,0,0,3750,0,0,4360,1000,0,3000,3093,0,0,0,1677,5000,0,0,4000,0,4500,3382,0,0,0,0,0,0,0,0,8014,0,1500,2000,0,0,0,2500,2900,3060,0,0,3520,4500,0,4000,1025,0,3922,1000,1015,4200,3728,3000,0,4575,4000,2821,0,0,3000,0,0,0,1100,0,4025,4500,4437,0,3147,0,5000,0,2000,0,4017,0,0,0,4000,0,3800,2522,0,0,3450,3600,2670,4000,0,3349,3297,4200,0,0,3450,4600,0,0,3660,3555,1114,0,0,0,4500,0,0,0,3675,3894,1710,0,0,0,0,2000,0,0,0,2500,3645,0,0,0,3390,0,3507,2900,5452,0,0,4050,0,0,2000,3784,3923,0,0,0,4185,0,3000,3223,0,400,0,0,0,1720,4000,3813,3369,5940,5000,3000,6540,4000,0,1415,0,0,3840,4050,0,0,0,0,4050,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,4474,0,3150,3750,4000,2129,0,5425,0,0,4200,0,3900,5000,0,0,3000,0,0,0,3000,0,0,0,5852,0,0,4000,0,6000,0,0,0,4500,3000,3600,3000,0,0,0,0,0,2800,3000,4651,3240,0,4500,0,0,0,0,5000,0,5946,1370,4900,4385,1500,0,0,4500,4182,5926,0,0,0,0,6250,3800,0,1822,1500,0,0,0,3825,2383,3741,4400,3900,0,0,0,0,0,0,0,5000,1758,0,3600,3600,0,0,3161,9695,5000,0,4500,4000,0,0,0,0,4800,0,3300,3185,0,5160,0,0,5056,5100,0,0,2600,4000,1053,6000,0,3500,0,2580,5300,0,0,5900,0,0,6222,0,1953,6300,5000,0,0,0,2000,0,5100,5200,0,6800,0,500,4999,5500,0,0,0,0,4000,0,0,5760,3840,4855,0,5700,4128,1370,0,0,0,6274,2700,0,3000,5000,5320,3800,3900,5000,5500,0,0,0,0,1800,1000,5000,3308,0,0,0,0,0,3690,0,5400,0,4500,0,4600,0,2850,0,0,3500,0,2900,4000,4000,3484,0,0,0,0,3636,3000,0,3615,4890,0,970,0,0,2800,0,0,0,3240,0,2000,4200,0,0,1017,0,0,0,0,0,4500,1000,0,0,2000,2000,0,0,0,0,6000,0,5500,0,0,6000,5553,6000,3450,0,0,0,5446,7625,4859,0,0,0,4677,0,0,0,0,2500,5200,0,0,6366,0,3000,2391,3815,0,0,0,0,0,0,0,0,0,6000,0,6000,0,2600,0,5400,0,0,0,3283,6825,0,5280,5000,4000,3000,4980,0,0,2980,0,3500,6000,2500,0,5000,4283,5057,1880,0,5940,3000,3200,0,5500,4306,5640,4925,0,3900,5400,4150,5180,4890,0,0,0,0,2500,1567,0,4260,5000,5460,0,0,0,4500,0,0,0,4000,1510,4846,1440,0,4050,0,0,1370,1500,4350,0,4000,450,5643,3257,0,0,0,3687,4800,2437,0,0,0,4215,0,3750,0,3677,0,0,4200,4500,1380,4999,0,0,4422,3000,4350,2000,3800,3897,0,1637,0,3828,4800,0,4196,0,0,4983,5500,0,1280,0,0,3610,0,0,3700,4000,0,0,4500,0,3647,4400,0,4300,0,3500,2460,2615,0,3200,3000,4000,3660,0,2114,0,0,2913,0,2500,3458,0,0,0,3250,0,0,4500,0,2000,0,0,0,2663,4400,0,0,0,3200,5626,2200,0,0,5029,0,0,2266,5500,3592,5700,0,4350,3960,3297,0,5000,5775,0,4107,0,0,0,0,4537,0,0,0,5800,0,2469,0,3000,0,5690,0,5190,1750,4030,0,0,0,0,0,0,0,3600,0,0,0,0,4416,3467,2500,0,0,0,0,3897,0,4515,0,4050,0,3660,1350,0,0,3003,0,0,0,4680,0,0,0,3000,3552,0,0,0,0,0,3100,0,0,0,0,0,0,2790,0,4200,0,0,0,0,0,0,0,3493,0,0,4500,0,2972,4125,0,0,0,0,0,0,3676,360,2050,0,0,0,0,0,0,0,3051,4500,2608,3100,4110,0,0,0,4721,2904,4025,0,0,0,4000,0,0,0,3709,750,3500,4195,4400,0,0,2500,3750,0,2500,0,5000,3510,0,5438,0,0,0,0,0,5500,0,0,0,4500,0,3615,2365,2100,2675,0,1210,0,0,0,4400,0,0,0,3700,0,0,3342,0,4590,0,0,0,4550,0,4784,0,2387,9200,0,0,4260,0,0,4000,0,0,0,0,0,0,0,2188,0,1810,2999,5112,0,3000,0,3700,4375,0,4041,0,0,0,0,5023,0,0,0,0,5000,8450,0,0,1530,0,0,0,2700,0,5100,0,1200,0,5000,3267,0,3636,0,3570,2790,0,0,0,0,5400,0,4350,5250,0,4015,0,0,4375,0,0,2451,0,0,3500,2574,0,0,0,3500,4500,0,3200,1780,0,0,2000,0,3500,0,0,0,0,0,0,0,2000,3000,0,4375,0,5000,0,1582,2480,0,3030,1200,0,2600,2604,3100,3062,2670,2677,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5700,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3300,0,4750,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,500,0,0,0,6100,0,8332,0,0,0,3500,0,0,2720,0,0,0,6500,0,0,3000,5446,0,11500,5000,0,0,2000,0,0,0,0,0,2500,2350,0,2500,4800,10000,1500,0,0,9955,0,0,0,5000,6000,0,3000,0,8000,0,0,7500,0,0,0,0,0,0,0,0,0,0,7266,3747,0,4851,6000,0,0,0,0,0,0,0,0,0,0,700,0,0,0,0,5000,0,2000,5500,0,0,0,0,0,1000,0,0,1300,0,0,0,0,6050,0,0,0,3600,0,0,0,4180,0,0,1000,0,6500,0,0,0,7000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6800,0,5800,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3045,0,0,0,3670,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,5250,0,0,1000,0,4000,4000,0,0,0,0,0,0,0,0,0,0,0,4305,0,0,0,550,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,6154,0,0,3600,4500,4000,3500,0,750,0,0,0,0,0,0,5500,0,0,250,0,0,0,8000,0,0,0,3700,0,2500,0,3000,0,0,0,0,4400,0,0,0,0,0,0,0,1500,0,0,0,0,0,0,0,0,4500,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,1000,0,0,5000,0,6163,0,0,3000,5000,1373,2000,0,0,0,0,0,0,0,0,0,0,0,6500,5500,6350,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1400,0,0,0,0,0,3000,0,0,0,0,0,1500,3000,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3070,0,0,5000,0,0,0,4850,3863,5000,4000,0,0,1410,4000,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,6000,10000,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8000,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5300,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5940,0,0,0,0,8356,1600,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2820,0,4000,0,2500,0,0,0,0,0,0,0,0,0,0,0,6750,0,0,0,4300,0,2500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,2500,0,350,0,0,0,0,0,0,0,1003,0,2500,0,0,0,1500,0,0,0,0,0,3500,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,4322,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8998,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,5000,0,6000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4879,5000,0,2500,4500,0,5025,1246,5000,3386,0,0,0,0,6084,0,0,4000,0,0,0,2625,4571,0,0,0,0,0,0,4000,0,0,0,0,5340,0,0,0,0,0,0,0,0,5425,0,5600,3700,0,0,5900,5000,0,0,0,0,3000,0,5000,5000,0,2500,0,2820,0,3258,0,5886,0,2630,0,3750,6100,0,0,0,0,5000,0,0,1100,0,0,0,0,5700,3400,0,0,0,4000,0,4000,3655,0,3500,0,3500,4000,4000,0,0,5204,0,0,5000,0,0,0,0,0,0,0,0,0,2000,0,0,0,5050,0,3202,5000,0,0,5850,4000,5438,0,6900,0,4500,3000,5000,1750,0,0,0,4000,0,0,0,1750,0,4000,0,0,750,0,0,1554,0,0,0,0,6800,5000,0,4000,0,0,0,0,2500,0,938,700,5000,3800,0,1443,0,0,0,0,0,0,0,0,1500,0,4500,0,2000,0,0,4000,0,0,0,0,0,0,0,4000,0,1000,2000,0,7000,2410,0,1000,5000,1500,0,0,0,0,10432,6000,0,0,0,3348,5000,0,1800,6000,0,0,0,3200,0,0,0,0,0,0,0,4815,0,0,0,3000,0,0,4000,2745,0,0,0,0,0,0,0,4260,4500,3500,0,4500,5000,0,0,0,0,0,0,5500,0,0,0,0,5000,0,6500,0,0,0,0,0,5346,0,6437,0,5300,0,0,0,0,5337,0,4476,4000,0,0,4380,0,3525,0,0,0,5653,0,0,0,5284,5000,4500,0,0,1400,3000,0,0,0,0,0,6000,3330,0,0,4000,5100,0,4000,0,0,4000,0,0,0,0,5250,5000,0,0,0,0,0,0,0,0,0,0,0,4000,0,5834,0,4410,0,2700,0,0,5250,6081,0,0,0,0,0,0,3250,0,0,6000,7300,3450,0,0,4459,3000,0,0,0,0,0,0,0,0,0,7250,5835,0,4200,410,0,3000,0,0,5620,3800,3450,0,2925,5000,7500,2500,6500,0,0,0,2000,324,10000,7000,5000,0,6700,3400,0,0,0,0,2500,4000,0,4350,0,0,8000,0,0,0,4873,0,0,0,0,0,5000,0,0,800,900,5000,4800,3000,2000,0,0,5000,0,1028,5500,0,0,0,0,0,6000,0,0,3500,0,0,0,0,1457,0,3000,0,0,2000,2000,0,0,0,0,0,6000,3500,0,0,0,5000,0,0,0,0,0,0,0,5000,0,3543,0,1000,0,0,0,3482,1000,2500,0,0,0,0,0,4000,0,3000,0,0,0,0,7000,0,0,0,4125,5500,0,4600,5000,0,8000,0,0,0,8500,0,0,0,0,0,0,5000,0,0,0,7171,500,5000,0,0,9900,0,0,5000,0,4400,0,3000,3894,6000,0,0,2500,0,0,0,0,0,0,0,5650,7500,3000,0,0,0,4850,6500,3000,0,2125,6500,4254,1500,3900,0,0,0,0,1345,4416,0,0,4000,6000,0,0,0,0,0,0,0,0,0,6000,4500,0,6500,0,5500,6470,2700,0,0,7500,1200,0,0,0,9000,0,0,0,0,0,0,1500,0,3300,0,5000,7500,0,0,3000,0,0,0,0,0,5000,0,0,0,0,3916,0,6000,3000,0,4000,0,1250,0,0,0,0,8700,0,4000,0,850,3000,500,7000,0,0,4200,7000,2000,2100,0,0,3400,0,5000,5000,0,0,0,0,0,6000,0,5000,7000,2700,0,7750,0,9000,0,3000,7500,5000,0,0,5000,0,0,5000,6000,0,5000,0,4000,5550,0,500,641,4066,4600,0,2500,0,0,0,0,5500,0,6800,0,1500,0,0,0,0,4000,0,0,0,0,0,7000,5000,0,0,0,3000,500,0,3802,0,0,0,0,2850,5000,6600,1500,0,0,0,0,0,0,0,0,0,0,2500,5000,4400,0,5500,0,0,0,0,0,0,0,0,0,0,3200,0,0,4000,2500,0,0,3500,7500,0,0,0,0,0,0,0,1000,0,0,5000,0,4000,0,0,0,0,500,0,0,0,0,0,5000,5000,2500,2000,6800,10000,5000,0,7000,0,0,0,0,4000,0,3277,5000,0,0,0,0,0,5000,0,2550,0,0,4342,1700,0,1900,0,3300,5125,5000,5520,0,522,0,0,4500,0,4000,0,0,0,2200,0,0,0,0,4159,0,0,0,4500,0,2851,0,0,0,0,0,2700,3000,4000,1500,0,5000,0,0,0,0,0,0,0,5900,3217,3500,3589,0,4459,0,3000,0,4812,0,0,0,0,3000,5000,1000,0,0,5700,9000,0,800,0,1000,0,0,5000,0,10365,0,0,3600,0,0,0,2500,2700,2000,2500,0,0,0,4200,0,0,0,0,0,0,0,0,4000,0,5000,0,7500,7805,5000,3000,0,0,0,0,0,0,3750,0,5500,0,0,0,0,5400,0,0,0,0,0,0,6398,150,0,192,1000,0,0,1500,5000,0,0,0,0,0,9925,0,0,0,0,0,0,0,3000,0,5000,0,0,0,0,5000,0,0,0,8000,0,0,0,0,1195,0,2160,0,500,0,4350,1800,0,8355,750,0,0,0,4000,2495,5460,0,0,0,0,0,0,0,0,3000,0,3500,0,930,0,0,0,0,0,2000,5989,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3614,0,0,4665,0,0,0,6000,0,0,750,3350,5000,0,0,2000,0,4985,3000,0,8000,5000,7750,0,0,0,5000,0,3000,0,3645,5000,0,4000,6000,0,0,6000,4459,0,0,0,0,0,4330,0,0,0,0,7500,4686,0,0,5000,0,0,0,0,0,0,0,0,0,0,5000,5000,0,5000,5500,0,0,0,0,0,0,0,6750,0,0,0,0,0,0,0,0,4200,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1650,0,5000,4000,0,0,0,5000,6500,0,5000,5000,0,0,0,0,3000,0,0,0,5000,0,0,5000,0,0,0,0,0,5113,0,0,0,6500,0,0,0,0,0,6500,0,4500,0,2500,0,0,0,0,4900,7000,0,5000,0,5000,9900,3200,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3500,0,4600,0,4000,0,0,3950,0,4930,0,2000,3500,0,0,4900,0,5200,4000,0,0,0,0,0,0,0,0,0,2000,5000,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4700,0,0,0,0,0,0,0,0,0,4365,0,0,0,0,7500,0,0,0,0,0,0,3740,0,2500,0,2421,5000,7020,1014,3600,0,0,0,0,0,0,0,0,0,0,0,0,2500,5000,0,2500,0,0,0,2500,0,0,2550,4137,5300,4600,2000,5000,0,0,0,0,7220,0,3000,0,0,0,4826,4000,4200,3000,0,3200,3000,0,0,0,0,6200,2000,5000,0,0,3750,1000,0,0,4800,1200,0,450,0,2930,0,0,6600,0,0,4725,4900,0,0,5000,2000,0,2000,3000,0,0,0,1000,4546,0,3000,0,0,3542,4500,0,0,3000,0,0,4000,4120,0,0,0,0,0,0,0,4300,0,0,0,0,0,5000,0,0,0,0,0,5000,0,0,0,5000,0,1000,3483,0,0,0,4691,0,2913,4920,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,3375,0,0,0,3000,0,0,0,0,0,3270,0,3800,0,0,0,5000,1200,0,0,0,0,0,0,0,5000,6000,0,4000,0,700,10000,0,0,0,0,0,0,0,4400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3378,0,2385,0,1322,4000,0,0,0,0,0,0,0,0,0,0,3285,2380,3300,0,0,0,0,0,3000,0,0,0,0,3693,4625,5070,0,5500,0,2500,3500,0,0,0,5263,0,3200,0,1161,5000,0,0,6300,0,0,0,4500,4000,0,0,0,0,2532,2900,4000,4350,0,2900,0,5500,0,2000,0,0,0,4000,0,3500,0,0,5700,0,5300,0,0,3330,3500,0,0,3767,4828,0,0,0,4545,0,5100,5000,0,3000,0,3300,0,3868,0,0,0,0,3800,0,0,3207,0,0,3000,0,2000,0,5000,0,3066,3922,5658,0,0,4500,0,0,2375,0,5000,4000,0,0,4000,0,0,0,0,0,0,2902,2025,0,4000,0,5000,0,3200,0,0,550,0,0,3800,0,0,0,0,0,0,0,0,0,4800,0,4047,0,0,0,0,0,0,3772,3000,0,0,0,0,571,3500,0,3340,0,0,0,0,6000,4000,0,2600,0,0,1200,4000,0,0,0,4633,3800,0,1935,2500,0,5580,0,5000,0,4497,0,0,3375,0,0,0,0,5000,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,5771,0,0,0,0,0,0,0,0,0,0,3450,0,2484,2000,0,0,0,2500,0,0,4400,1917,0,0,0,5500,0,4906,6000,5000,0,0,2000,0,0,3000,5000,3000,0,2275,6000,0,4000,0,0,4000,7446,0,0,1000,5500,5000,0,7500,0,4000,5000,3500,0,5000,0,0,5000,0,0,0,4795,0,3900,0,0,0,0,0,0,0,0,7644,0,0,4000,0,3000,0,5000,0,4500,0,7147,0,4000,3000,0,5907,0,7500,0,0,0,0,3100,3000,0,0,4500,7484,3000,1000,2000,0,0,8000,3845,0,0,5000,0,5000,5000,0,6200,4322,0,1500,0,0,5000,0,0,4000,0,8364,0,0,0,1300,0,6580,0,750,4500,0,3000,0,0,0,1175,0,5364,0,4200,0,7500,0,1500,3500,2500,850,0,0,5000,3600,0,1650,5000,3800,7825,0,0,4050,0,3200,3200,0,0,9100,0,0,0,0,0,0,0,0,0,5000,0,0,4000,5000,2800,4157,0,0,2500,0,5000,0,5000,0,0,0,2391,0,0,4000,590,4625,0,0,3489,2500,0,0,9500,0,5000,0,4320,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3750,0,2038,0,0,3250,3262,0,0,1950,0,0,3900,0,3150,2593,0,3500,1000,0,6500,5000,3180,0,0,0,0,5000,5000,0,5314,3720,4632,0,0,0,0,0,0,2255,0,0,0,0,5000,0,4000,0,5000,1250,0,0,3469,0,0,7000,4000,0,4000,5000,0,1636,0,4500,0,0,4500,0,0,8500,4500,0,5000,9500,7500,0,0,0,0,0,8067,6000,0,0,0,6000,0,0,0,5800,4000,4936,0,0,5000,0,0,0,0,0,1115,0,5850,0,0,5000,0,5000,0,0,0,10000,0,6000,4000,0,850,0,4147,2000,2300,0,4000,0,6800,0,0,0,0,0,0,0,0,0,0,0,0,410,0,6000,0,3750,3383,2000,5000,6200,0,4058,0,0,0,2300,0,5719,5000,2000,0,0,0,6500,0,0,0,0,4000,0,0,0,0,0,0,6000,0,0,0,0,0,5000,0,0,3858,0,6409,0,3289,3299,0,0,1250,4000,0,3237,4000,0,0,0,0,3400,0,3505,0,0,0,0,0,0,5692,0,0,0,4799,2960,0,0,0,2000,0,0,0,0,0,0,0,2796,5100,0,0,0,3700,0,0,4000,0,6300,0,0,3000,4900,0,3000,5000,0,5000,0,0,0,0,0,0,3500,6800,0,0,0,0,0,0,1750,0,6000,1000,4000,0,7200,4940,3450,0,2731,5000,0,0,774,0,0,0,0,5500,7000,0,0,0,7500,0,0,0,0,0,4650,5000,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,6800,0,0,4700,4500,0,0,0,0,0,2600,3000,2000,0,2800,0,0,0,0,6330,4392,900,5000,0,0,0,0,0,0,0,6925,0,0,3000,5750,0,0,0,0,0,8550,0,8000,0,5000,0,2000,0,0,4000,7500,3000,0,0,5000,0,1000,0,5000,0,0,0,0,0,1847,0,5000,0,2000,0,4000,0,5000,0,0,4245,6500,0,0,0,0,878,3000,0,5000,0,7000,4150,2600,0,0,1616,0,0,1500,0,0,2000,0,0,0,875,0,0,420,0,0,0,2700,0,4000,3300,0,0,2500,3300,0,2500,3600,0,0,0,2500,0,0,4000,12139,0,5000,0,5000,0,9453,0,0,5000,0,6469,3618,0,0,0,0,0,3900,3500,0,5000,10261,3310,0,0,5000,0,6963,0,0,0,2500,0,4150,3500,0,850,0,3000,6000,0,0,1000,0,0,5663,0,0,5000,750,0,0,0,0,0,0,0,0,0,1000,0,0,0,5612,0,6651,4500,0,0,3000,0,5250,0,0,0,5000,0,100,4440,0,0,0,0,5000,0,0,0,0,0,0,2100,0,0,0,0,2000,0,1000,6605,6600,0,0,2000,5000,3400,0,0,2765,1800,3721,0,0,6000,0,4500,0,2500,4700,6000,0,3500,0,2500,0,5000,5000,0,0,1000,0,7000,0,0,0,5000,4540,0,1125,2397,5000,5000,0,4000,0,0,0,1768,6000,3000,5000,0,0,5000,0,2500,3883,2600,4095,4000,0,0,0,0,0,0,0,4350,5000,5000,0,2500,1000,0,0,0,6500,3500,0,0,0,0,0,0,3905,2650,0,7000,0,0,0,0,0,4000,5000,2913,0,4810,0,3200,0,0,0,0,0,0,5000,0,0,0,0,0,0,3534,6000,0,0,0,5300,3700,0,0,13000,4226,0,0,0,0,4500,0,2500,0,6000,5000,0,5000,0,0,11950,3000,0,0,0,1800,0,3500,0,2500,0,0,4767,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,3780,0,1710,0,0,0,0,0,2000,0,0,0,0,0,0,1800,665,0,0,0,0,4000,0,0,0,1000,0,0,0,0,0,4730,0,0,0,0,0,0,0,0,0,0,0,0,0,4500,0,0,0,2500,0,0,0,1500,0,0,0,3100,0,0,4500,0,3450,0,0,0,0,4500,0,0,0,0,0,2227,3298,0,0,4300,7000,4000,0,2000,0,0,3960,5905,0,0,0,750,0,0,5000,0,2700,0,0,0,0,0,0,0,1800,0,0,0,0,0,0,0,0,0,0,0,0,3000,2000,0,4000,0,0,0,6000,0,840,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3700,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,3900,3481,0,0,4000,2000,0,0,3125,4650,0,0,3900,0,0,0,4000,0,0,0,0,0,3600,0,0,5667,5250,8000,0,0,2000,4205,4000,0,0,5000,4850,0,0,0,0,5000,0,0,0,5000,0,4500,0,0,3210,0,0,3500,0,0,2719,5000,4000,4000,0,0,0,4430,0,0,0,4700,0,3500,0,5040,0,3750,0,0,0,0,0,0,5000,0,0,6912,0,0,0,100,5000,0,5000,0,4000,0,2723,0,4500,4470,4800,0,5239,0,4120,0,4000,2500,0,0,0,0,3435,0,0,0,0,0,4586,0,0,0,0,4000,3000,4000,4605,4000,0,0,0,5770,0,0,0,2400,0,0,0,0,0,0,4000,5000,0,0,0,5000,0,0,0,0,0,5524,0,0,0,0,3000,0,0,0,1250,5152,0,0,6755,0,4960,0,1000,2548,3000,0,0,0,0,2500,0,4000,0,4000,0,3359,3000,4000,6000,0,3904,0,4000,0,5000,0,0,0,0,4000,5000,0,0,0,0,0,0,4900,2000,1000,7000,5000,0,0,5732,0,0,0,4923,0,0,0,0,0,3390,5000,5000,0,5308,0,5000,0,5801,0,0,0,0,6300,5600,0,1900,0,6500,3750,0,4440,0,3000,0,0,4440,0,0,5316,2500,0,0,4000,0,4500,0,0,5000,0,0,0,0,0,2500,0,0,7000,0,0,4678,2776,0,4000,5000,7347,0,2500,0,5777,0,0,4000,0,0,4500,0,3743,1500,0,5700,4500,0,4000,0,5500,0,4500,0,0,5500,800,0,0,4000,4300,0,3000,0,2000,0,5500,0,4300,6200,0,0,0,0,2895,0,3720,0,0,5900,0,6000,0,6420,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3269,0,0,0,5000,0,0,0,0,0,0,0,0,2000,0,5000,0,0,0,2500,4100,5000,0,0,5000,0,3829,0,4260,0,1852,4480,0,3492,0,4000,0,0,0,0,5500,0,7620,0,3000,5000,0,0,0,0,3000,4500,0,3500,3500,0,3928,0,0,0,4450,0,0,3700,0,0,3940,0,0,4000,2400,0,3500,0,0,3500,4500,4608,9210,4405,0,0,6483,0,0,0,0,0,2200,5000,3500,0,0,3000,0,0,0,0,6500,0,0,0,0,0,0,0,0,0,6000,3000,3594,0,0,0,0,2300,0,4000,0,0,3960,0,5000,0,0,0,0,5000,0,0,0,0,0,0,4410,0,5190,5000,0,0,0,0,0,3795,0,0,5600,0,0,0,5000,0,4000,4080,0,4000,8670,0,5500,5000,0,0,3300,600,4000,0,4500,2000,4000,0,0,0,0,0,0,0,0,4500,0,3000,2500,0,0,0,0,0,0,0,0,0,2700,900,0,6800,4000,0,1000,10850,600,3650,0,0,0,0,0,7000,995,0,5000,0,4000,0,2997,0,0,7415,0,0,4908,2222,2571,2500,2500,0,0,0,3000,5000,1500,0,4000,0,0,1280,7650,0,0,0,0,0,0,0,6000,0,0,0,3200,10545,0,0,0,0,0,9600,0,4025,0,0,0,0,0,5299,6000,570,0,3445,0,0,0,0,3697,0,3500,0,0,0,5000,3041,8000,2979,4000,0,0,3000,0,4000,0,0,3500,6000,0,0,2600,4000,0,0,0,0,0,4000,0,0,0,0,0,0,0,5000,0,0,4546,0,4625,0,5000,0,4835,2200,6750,0,3149,0,6312,2602,5724,5397,0,1000,0,5800,0,5000,3500,4800,4560,1000,1000,0,5000,0,3230,0,0,0,0,4000,0,0,0,0,0,0,6000,0,0,0,5000,0,1137,0,0,6400,0,0,5000,0,7500,0,5500,5000,7000,0,0,0,0,0,4000,1770,1760,0,0,0,0,3000,0,4350,0,0,0,0,0,0,0,0,1200,0,0,0,0,0,0,0,0,0,5000,3000,0,0,0,10496,6000,0,4500,8020,0,4223,0,0,2000,0,0,0,8000,8000,7500,0,5000,0,2000,6000,0,1906,0,3500,0,3000,0,0,3000,7630,0,0,0,0,0,0,4475,0,0,0,0,5000,0,25000,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,10097,0,0,0,0,0,11250,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,5000,0,5000,0,0,7000,0,0,0,0,0,0,5000,0,0,0,0,4000,0,0,0,0,0,0,0,0,4000,3000,0,0,0,0,3386,3541,0,0,3901,0,0,5000,0,0,0,0,0,0,0,0,0,0,4931,2130,0,1070,3000,5650,0,3500,5000,0,3000,0,300,0,0,3000,0,0,0,0,0,0,0,2500,5000,5000,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,5000,0,6000,0,0,2500,0,1840,0,6000,5000,4500,5000,0,0,0,4000,6500,3575,5000,0,0,0,0,0,0,0,0,2600,5000,0,5000,5433,0,0,0,0,0,0,1754,5000,0,5000,10000,5000,0,0,0,0,0,3000,3500,0,6250,0,0,2000,6250,0,0,0,0,4000,0,0,0,4000,0,0,3500,4004,0,0,0,0,0,0,0,800,3500,6500,0,0,5100,5000,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7000,0,0,0,0,7000,0,6000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,10000,0,0,0,0,6908,0,0,7800,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,3000,0,4000,6000,5000,0,0,0,0,0,0,7000,0,0,3000,0,0,5400,5500,0,0,0,0,5725,0,0,0,0,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,10000,0,0,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,6000,0,5000,5000,0,0,0,0,0,0,5000,4000,0,3000,0,0,0,1000,0,2025,4000,0,2000,1000,6000,0,0,0,0,0,0,0,5000,0,3500,0,1695,0,0,0,0,3734,2000,4000,0,0,0,0,0,3000,0,6465,0,0,0,6550,0,0,5440,0,0,0,0,3500,0,0,0,0,0,2800,0,4000,0,0,0,1685,0,0,7200,0,0,0,3500,5000,0,0,0,5700,4000,0,0,0,0,0,0,0,0,0,0,5757,0,0,0,1200,0,5000,0,0,0,9850,7386,785,0,475,0,1500,0,0,0,1000,1900,2000,0,0,2500,6500,0,0,5500,0,4500,0,0,0,0,0,3400,0,0,5000,2800,0,0,0,0,6000,0,1000,4800,4000,1000,0,0,2000,0,200,1500,3297,3000,0,0,0,0,0,1500,0,0,8000,0,1000,0,0,3100,0,0,0,0,8200,6000,0,2000,4000,0,0,0,0,0,0,5000,1000,1000,0,2694,5000,0,2000,5000,2100,5000,0,1500,0,1000,0,0,0,0,0,0,5000,5750,0,0,5000,0,0,1000,0,0,0,0,0,0,5000,4000,3400,0,5000,5000,0,0,3500,6000,0,0,10104,2500,0,0,0,7000,1700,0,0,0,0,0,5500,0,10000,0,0,3500,0,0,3050,3000,8000,0,0,0,0,5324,0,3500,0,3377,0,3500,1000,0,0,0,0,1250,4000,0,4100,0,0,5000,5000,4000,0,0,0,0,2839,5000,6500,0,0,0,0,3000,0,0,0,0,7500,5000,5000,0,5000,4625,5000,0,0,0,4500,0,1000,0,0,0,0,0,0,0,4000,0,0,0,0,0,5000,0,7838,0,0,5070,0,4000,0,9000,0,5580,0,0,0,0,4000,4515,0,0,0,2300,0,0,0,1500,2500,0,0,0,4000,9000,3217,0,0,2000,0,8000,5000,4000,6000,0,0,0,0,4500,8000,6000,0,4748,0,0,0,0,0,5500,0,5000,4500,5000,3000,0,2500,2000,0,0,0,0,0,0,0,0,0,6935,0,0,1500,5000,0,0,0,0,0,0,0,4300,0,3257,0,0,0,7350,7000,6200,0,0,0,5350,0,0,4000,0,0,0,0,0,2700,2000,0,0,0,0,3000,4000,5000,4000,2000,0,2000,5355,5000,3305,5000,0,3640,0,5000,0,7293,0,4000,0,7450,0,0,0,5500,0,9800,0,4000,7170,4500,6000,2000,4000,2333,0,0,4000,4000,5000,0,2300,0,0,0,0,0,0,3000,0,3940,0,0,0,2500,0,0,0,0,1000,0,0,0,6000,2500,0,1000,0,0,0,3000,4500,0,0,4800,500,0,1622,5500,3500,0,0,0,0,0,0,0,0,2000,5000,3606,0,6700,5000,0,0,0,0,0,0,0,0,0,0,2100,0,0,4302,0,0,0,3200,2000,3000,2500,0,0,0,3057,0,3500,6600,3500,6000,0,250,10000,0,0,0,0,5000,500,0,3000,7000,4000,0,0,6100,0,0,0,1499,5930,0,0,0,0,4600,4000,0,0,9888,5600,2500,0,0,0,0,0,0,5527,2000,8455,3500,5830,1350,0,1380,0,707,0,4300,0,5000,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,3000,0,0,4000,2000,4000,0,2350,0,3000,0,0,4500,4000,0,0,6000,425,0,0,500,1411,0,0,5000,0,4000,0,0,0,0,0,0,7000,4000,0,5000,0,0,0,0,0,0,0,6200,0,0,3600,0,0,0,4500,0,0,2825,0,0,5000,0,2000,0,0,5000,2000,2775,4360,0,0,0,0,3000,0,0,0,1000,5000,0,0,7000,0,2500,0,1500,3000,0,2160,0,6000,9000,6400,1900,0,0,4110,0,0,3000,5259,0,1000,0,2000,0,4361,4600,0,4000,0,0,4912,0,750,0,5000,0,2879,0,5000,0,4000,7605,5000,0,900,2500,0,0,0,0,11970,3000,0,0,0,0,0,0,5500,0,0,10227,8183,0,0,2000,0,0,0,0,0,0,1600,6000,2500,0,0,0,1000,4000,0,0,0,4000,800,0,5000,0,0,1000,0,0,0,0,4000,0,0,0,0,5000,0,0,0,0,6394,0,0,0,2000,0,5000,5000,0,2000,0,0,0,5000,5917,0,3105,0,0,0,5500,4217,3000,0,0,0,6000,0,0,6000,0,0,11700,0,4000,0,0,4000,6500,0,0,3342,3375,6000,0,0,6250,1951,0,2500,1247,1000,0,5550,3000,8000,2000,0,0,0,0,6000,7653,0,3211,0,0,0,3829,0,0,350,600,1250,0,4000,0,0,0,6100,0,4500,0,0,5993,5000,0,0,0,9000,0,0,0,0,2675,0,3000,0,0,0,0,0,5000,0,0,0,0,3000,0,6000,5000,3500,0,0,0,0,4000,0,0,3000,0,0,0,2000,0,0,0,6500,9488,10048,0,3000,5000,0,0,0,0,0,0,2700,0,0,0,0,0,3500,0,0,7000,2400,3500,0,0,1500,0,0,0,0,3500,4500,0,0,4000,6000,0,5000,0,1500,6350,0,0,5000,4800,0,0,5000,5000,0,3990,0,0,0,2000,0,0,0,0,0,4500,5376,0,0,7000,0,5000,4000,0,0,1600,0,0,0,3500,0,2500,0,0,0,4000,0,0,0,3000,3500,0,0,0,0,0,0,0,6389,0,0,2000,6152,4500,5000,0,1700,0,0,0,2000,0,0,0,0,1500,0,7009,6000,3223,0,0,0,0,0,4690,0,4000,5000,1000,1100,0,5000,0,0,0,0,0,6250,1250,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,5000,0,0,0,0,1000,0,0,0,0,0,3200,5400,4500,0,4000,0,0,0,0,0,0,0,5000,3500,6000,0,0,0,0,6000,799,3000,0,0,0,0,5400,2750,0,2500,0,3750,5000,4957,4000,7000,0,0,0,3000,0,3000,2246,2419,4000,0,0,3500,0,1200,4000,6460,0,9000,0,0,0,0,3000,4394,0,5000,5000,3000,2753,3464,5000,0,4170,0,0,0,0,2500,5900,7900,3000,0,0,0,5000,5000,9000,0,2000,0,0,2000,0,0,0,0,2500,0,0,1500,530,7475,4928,0,0,0,0,0,0,0,8000,9600,0,0,2145,0,6320,0,0,0,0,0,0,0,3337,5300,0,0,0,1860,0,0,4800,0,3000,3600,2445,2999,0,0,4890,4800,4759,0,0,0,12000,0,0,0,9021,0,0,0,0,0,0,0,0,0,0,0,0,0,7200,0,0,5343,0,0,0,0,2900,0,0,0,0,0,3700,4000,0,5862,0,0,7000,0,0,0,0,0,8250,0,0,4000,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,3000,0,0,0,0,0,6930,0,0,10337,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,5700,0,0,6000,0,0,0,0,0,0,0,0,7200,10000,0,0,0,0,0,0,0,0,0,0,2500,0,0,10500,0,3000,0,0,0,0,0,0,0,8000,10000,0,0,0,0,0,0,0,0,0,0,0,0,5000,2700,0,0,0,2518,3400,0,4673,0,0,0,0,0,3500,0,0,0,0,0,8000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2028,5000,0,0,0,0,0,0,9300,0,3600,6600,0,0,0,0,0,0,0,0,0,0,9000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,2194,0,0,0,0,0,0,0,0,0,1500,0,0,0,6500,0,6000,0,0,9649,2500,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9600,4296,4032,0,7000,0,0,0,6000,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8000,0,6900,0,0,2000,3030,3000,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,3500,0,2570,0,4500,0,2750,0,6288,6000,0,1000,0,0,0,5000,0,0,0,0,48266,0,0,68195,0,0,64133,0,69480,9249,67500,83162,0,58500,14249,0,51425,9249,62840,0,0,9249,48309,41208,0,0,0,53950,57016,0,0,0,0,34421,0,17703,101809,14000,99749,44206,34421,18603,0,0,63900,32025,17211,42206,34309,39656,26603,35309,39421,0,31809,34421,15000,18603,95427,34421,0,0,0,0,0,0,0,0,0,0,0,0,0,3500,0,5000,0,0,0,0,1000,1600,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,6000,0,0,5647,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4500,0,0,0,0,0,0,5500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5100,0,0,0,0,3500,0,0,0,0,4000,0,0,0,0,2680,5000,0,0,0,0,6500,0,0,0,6000,5000,0,0,0,0,0,1800,2000,0,0,0,0,0,0,4000,5000,0,0,0,0,0,0,0,0,0,5800,0,3000,7729,0,2500,6500,0,0,2000,0,0,0,5000,0,4000,0,0,0,0,4979,1500,4500,0,5000,5000,0,0,0,0,3000,0,2500,0,0,9000,8000,5600,0,0,2500,4600,0,3000,5000,0,5000,0,0,0,0,0,0,0,5300,4000,0,0,0,2000,2500,4000,2000,600,4000,0,0,6269,3500,6000,0,3750,0,0,4771,10000,0,450,0,0,3720,0,9900,0,0,10000,1500,0,0,0,0,0,0,5000,0,0,0,0,3500,0,0,0,0,0,0,0,0,1276,0,0,4000,5460,0,0,7300,3000,0,6500,6000,0,4088,0,4000,0,0,4000,4000,0,0,0,0,0,0,0,10000,0,0,0,0,0,4910,0,3000,0,0,0,0,0,0,0,5370,5297,5000,4000,0,4000,16430,7000,4988,3561,0,4000,5700,0,900,0,5500,5000,0,0,0,1500,0,0,0,0,0,4000,5989,4410,0,5500,0,0,4000,5000,9000,2500,0,4900,0,4000,5000,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,9418,0,0,0,0,3000,0,0,4000,0,0,0,0,0,0,0,3000,0,0,0,0,6795,4200,0,0,0,0,0,3000,0,0,0,0,0,0,4300,0,0,0,4472,3473,7000,3500,4000,2500,0,3500,1500,0,5500,8000,6500,0,3000,3850,0,0,3900,0,0,0,0,0,0,0,3000,1800,11535,4500,0,0,7630,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,2000,5000,0,0,3500,4000,5000,0,0,6500,0,0,0,0,0,0,0,0,3000,0,3000,0,0,2500,1250,0,4500,0,0,4540,0,0,0,6000,7417,0,5000,6000,0,0,0,5000,6500,0,2000,0,0,3000,1500,0,0,0,0,7425,500,2000,0,0,2039,5000,0,0,5200,0,0,0,3550,3792,0,0,0,6800,0,250,0,0,0,5104,0,0,0,6897,3550,3876,5000,4056,0,500,0,0,0,0,0,0,0,0,0,0,0,2500,2600,1825,4000,0,0,0,0,0,0,6000,0,0,0,5000,0,0,0,0,5000,4170,0,2938,0,0,3000,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,1000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12000,7900,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14900,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,5000,900,0,0,4000,7000,0,0,8000,0,5500,0,0,4000,0,4000,0,0,1000,550,5200,4888,1000,0,5500,0,5000,2500,2500,0,0,3000,0,0,3500,4500,0,0,5000,3630,2000,0,0,5000,0,0,0,0,0,6300,0,0,0,5697,4574,0,3000,5250,0,0,3276,3752,0,6000,0,5000,4180,7000,0,0,0,0,0,0,8296,0,0,0,0,0,0,0,0,0,4500,0,0,0,0,0,0,6150,3000,2500,2000,4636,4000,6382,0,4500,3500,0,0,0,2450,3000,0,5500,5000,5000,0,6341,0,6000,6172,0,7154,0,0,3472,0,0,0,5665,4000,6900,0,200,4621,0,4729,5000,0,5000,0,0,0,6819,0,4750,1500,0,5790,0,0,2000,5000,0,0,0,6000,2000,0,0,1845,0,0,0,4250,0,5407,0,0,4100,3650,5000,4385,4500,0,5832,0,0,0,1500,3714,4000,4000,3500,0,0,1378,0,0,4500,0,3000,4086,10211,0,0,0,0,0,0,0,0,0,0,3000,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4979,3000,6000,0,4500,0,0,0,0,2953,0,0,0,0,0,4000,0,0,5000,0,3300,0,0,0,2895,0,0,0,0,1800,0,0,0,3000,4500,0,4200,3950,5000,5300,0,0,3000,5000,5000,0,0,5000,0,0,0,0,0,0,0,6000,4074,0,2000,0,0,19200,0,0,3000,4000,0,0,0,0,0,0,0,0,500,500,0,0,0,950,6150,0,0,0,0,0,6500,0,0,0,0,0,2540,6000,2000,0,0,5500,2900,4600,1250,5000,0,0,0,0,0,0,4500,0,0,5100,0,0,8400,5000,6000,0,12740,1500,4200,0,0,0,5100,3000,3000,5000,4000,5000,0,0,0,6388,0,0,1500,1000,4526,0,6000,0,0,0,0,5000,0,0,0,0,5000,0,7500,4500,0,2600,0,4300,0,4655,0,5000,0,0,0,4700,0,6500,4172,3000,0,0,5500,3500,5000,6211,1200,8156,0,0,0,2000,0,5500,0,3450,0,0,0,0,0,0,0,4500,0,0,0,0,0,3133,2500,0,0,0,0,0,4500,0,0,0,0,0,0,0,0,0,0,0,0,6591,0,0,0,0,0,4000,1000,0,0,8000,0,0,0,0,0,0,2700,0,0,0,0,3500,0,0,500,4900,0,0,0,0,4260,0,0,0,0,0,0,0,5000,0,9599,0,0,0,0,0,0,7000,1300,5000,0,0,3125,1500,0,2000,0,0,1000,600,0,3500,6000,800,0,0,0,0,5000,0,0,5074,0,0,5000,0,0,0,0,7000,513,0,0,5000,0,0,7713,0,0,4493,0,3500,0,0,6600,50,1250,7417,0,5000,1000,4199,0,0,216,0,0,300,0,0,0,0,0,0,0,0,0,0,7500,0,0,0,0,5880,0,4900,3500,0,0,0,0,0,0,0,0,3000,0,0,2500,0,0,3750,2500,0,0,0,0,0,3893,0,0,0,0,0,0,0,0,0,0,0,1200,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,2500,5000,0,0,0,0,0,7500,0,8600,0,0,0,0,0,0,0,0,4000,0,0,4825,0,0,3670,0,10950,0,0,1500,0,0,0,0,0,0,3300,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,7500,1500,0,0,0,0,0,3000,2000,3408,0,0,0,0,0,4000,0,7500,0,0,0,0,1000,0,4000,0,0,3555,0,0,7000,0,3282,4936,0,3000,0,0,1304,0,0,4500,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,3835,0,1500,2000,1600,3000,4000,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,0,0,0,0,0,3500,0,5000,3080,0,0,0,0,1000,0,0,0,0,0,0,4100,0,1050,0,0,0,3500,4000,0,3150,0,0,0,0,0,0,0,0,4612,0,0,0,0,0,0,7663,0,0,0,0,0,0,0,0,0,11500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9300,0,0,0,0,0,0,0,0,0,1340,0,0,3250,0,5000,0,5000,0,3500,0,0,0,0,5000,500,2500,0,0,0,0,0,0,0,0,5000,4180,3500,2115,0,0,0,4000,0,0,0,4000,0,3000,3897,0,4200,0,0,0,3000,6000,0,5000,4000,4000,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,500,0,0,4500,0,1000,2640,0,2250,0,0,0,0,3000,0,0,0,0,2000,3927,0,3000,3900,0,0,3600,2500,2380,0,0,0,0,0,0,4100,0,0,0,6900,0,0,10000,0,0,7463,0,0,0,0,0,495,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,5000,13500,0,3000,0,0,0,0,0,2500,4500,0,0,0,4000,3000,3700,2700,3000,2000,2000,0,0,500,0,3307,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,0,3650,0,3500,0,0,3000,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,3500,0,0,0,0,1000,0,0,0,0,0,5000,0,0,0,6168,0,0,3500,0,5000,0,0,0,4313,0,3500,0,3700,0,0,0,0,0,1200,0,2000,4860,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3480,0,2000,0,10000,1000,0,0,12389,0,5000,0,875,0,2000,0,350,0,2000,6000,0,0,0,5000,0,0,0,0,0,0,1500,7706,3821,0,6500,0,4557,2250,0,0,3795,0,0,4800,5000,6750,0,0,4000,5000,0,1000,0,0,0,0,0,0,0,0,0,6580,5938,0,4125,0,0,0,10000,0,700,5000,0,0,0,0,0,0,0,0,0,5000,5834,0,0,0,0,2500,3500,0,0,0,0,3000,0,0,4000,2000,0,0,4000,0,2000,6158,0,0,5500,0,0,0,0,0,0,0,2500,0,0,0,4305,0,4000,2000,5000,0,0,3600,0,0,0,0,0,0,0,0,0,0,0,1000,2500,0,0,0,6000,0,0,0,0,3500,0,0,1000,2500,4040,0,0,4500,5500,4198,5024,4320,0,3500,0,3000,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,3200,0,0,0,0,0,5000,2140,0,0,5000,0,0,0,5000,0,0,4764,0,0,7500,4500,4000,700,0,0,0,0,5000,5000,3805,0,0,0,5000,320,2000,0,3000,0,6200,750,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7800,0,5000,0,2800,0,2500,0,0,0,0,0,0,0,3083,0,0,0,1398,3433,0,0,0,1000,4108,4600,3325,0,4000,0,1018,1800,0,0,0,5300,0,0,0,0,3000,0,0,0,0,0,0,14000,0,0,0,1500,0,0,0,0,0,0,0,0,0,0,4800,3000,3000,0,0,4950,0,0,5500,0,0,0,0,0,0,2000,7000,1500,0,0,0,0,0,1000,0,0,4342,0,4000,0,0,0,0,0,0,2500,4200,3000,6447,0,0,0,0,3200,0,0,0,2800,0,0,5000,0,0,5623,0,0,3600,0,2450,0,0,0,3000,0,0,0,7900,3000,0,0,0,1500,0,0,0,0,3000,0,0,0,5000,0,4000,2035,0,0,3000,2000,0,0,0,0,0,0,0,2000,0,0,0,1660,0,0,0,0,0,11000,5000,0,0,7000,0,0,5000,4000,4122,0,2000,1890,0,2500,0,0,0,5000,0,2620,0,0,0,0,0,3662,0,0,3050,0,0,3150,0,3500,2500,0,2000,0,0,3925,0,3500,0,5000,0,5000,5000,0,3500,0,0,0,0,0,0,0,0,600,6500,3000,0,5900,4000,3000,2000,5275,0,0,0,0,0,0,0,5850,0,6948,0,0,0,0,0,0,0,0,4897,0,0,0,0,4000,1000,0,0,0,0,4000,0,0,0,4000,0,0,3000,3500,2000,0,6800,3000,0,0,0,2250,0,0,0,0,0,0,4000,0,0,0,0,0,0,3870,0,0,4710,0,0,2779,0,0,3532,0,3500,0,0,0,4236,0,0,3000,0,0,5000,0,3609,0,0,0,0,0,0,2200,0,4500,7200,0,0,3200,1000,0,0,0,5000,0,3905,0,4400,0,0,2087,2000,4000,2200,0,0,3000,0,4000,5000,700,0,0,5400,1900,0,0,0,0,0,4500,0,3000,0,0,5500,4965,0,1350,0,0,0,0,0,0,0,0,0,0,2500,0,5199,4931,5215,0,0,0,0,4800,3000,0,2287,875,2560,0,0,0,5000,4290,0,5134,3800,0,0,5100,0,700,0,0,2553,0,0,3000,0,0,3000,0,0,0,0,0,3100,3000,0,4650,0,0,0,0,0,4327,0,0,0,0,0,0,0,0,3940,0,0,0,0,2700,3086,0,0,0,3000,0,0,4497,0,3823,2000,4800,0,0,0,0,0,0,2000,0,0,4560,0,0,0,0,0,0,0,3540,0,0,0,0,0,3100,0,0,0,0,3000,0,0,2000,2685,2100,0,0,0,0,3702,4625,4350,0,0,0,0,0,0,0,3750,0,0,0,0,2000,0,0,0,0,0,0,3100,0,1800,0,0,4600,0,0,0,0,5000,4400,2621,300,0,0,0,3000,0,0,0,0,0,3837,0,5000,0,0,0,0,0,0,0,2610,0,0,0,3206,2594,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,4800,0,3750,4000,0,0,3500,0,0,2340,1200,0,0,2500,0,0,2800,4000,0,0,2880,0,5000,2800,2610,3000,4000,0,0,0,0,0,5000,0,4987,4284,0,3986,3250,0,0,3000,0,0,0,0,9301,0,0,0,4573,0,3500,0,3500,4000,0,0,4000,0,0,0,0,0,2700,0,0,0,0,3495,0,1359,3000,0,2515,0,0,0,3720,2550,6609,1700,0,0,0,0,0,2757,0,0,3500,0,5370,0,0,0,0,0,3867,3500,0,2400,3500,1000,0,0,3100,0,2698,2847,0,1000,0,3255,0,0,0,0,0,0,0,2100,0,2000,0,1650,1352,0,0,2100,3780,4500,3921,0,0,0,0,0,3179,0,4000,4000,0,0,0,0,1000,0,5000,0,0,0,3353,0,4000,0,0,5000,0,0,0,0,4178,0,0,0,0,0,1000,0,0,0,0,0,1800,3150,0,0,3000,0,0,0,0,0,0,4950,3150,2000,0,3400,0,0,0,400,0,4500,0,2000,0,0,0,0,0,0,0,2846,0,3983,2806,0,0,0,0,0,0,0,0,4020,0,0,2600,0,0,3575,4000,2100,0,0,1000,0,0,0,0,0,3000,0,3747,0,0,0,0,0,1300,0,0,0,4000,122,3000,0,1920,0,0,5850,0,0,0,0,0,3475,3625,0,0,0,0,0,4500,0,0,2880,0,0,3747,0,0,1000,0,0,0,4000,5000,0,0,0,3691,5300,0,2500,3000,0,0,3500,0,0,2000,0,0,4000,1800,0,1940,0,0,0,3150,0,0,0,3000,0,3434,0,0,4200,5280,0,0,0,3060,3250,0,0,0,2208,4000,0,0,0,0,5600,0,3500,0,3000,0,0,0,0,4837,2000,0,0,0,0,0,0,1000,0,0,0,4000,0,0,0,0,0,0,0,3000,0,0,2000,0,0,0,0,0,0,0,0,2275,0,2800,2970,2500,4375,3500,0,0,3958,1000,0,0,5000,0,8100,0,0,0,0,0,0,0,0,7500,0,7500,0,3820,5000,5000,0,0,0,2500,2000,1810,0,0,0,0,3000,0,0,4000,0,0,0,0,0,0,0,0,4260,0,0,2000,4000,0,4000,0,0,0,1350,0,4200,0,2650,10000,2860,0,2600,0,6832,4266,6443,0,0,0,0,2000,2000,0,0,0,0,0,800,0,5000,0,4500,0,0,0,300,0,4500,0,4000,510,3500,4245,0,5500,3000,0,0,4843,7000,0,0,5000,1500,4500,2000,2736,0,3500,0,0,3553,0,1888,0,8500,0,5000,0,1310,3000,800,1000,5000,10000,0,5000,3400,0,0,3000,0,0,500,5000,0,9361,3525,5000,0,4800,6360,0,0,2750,6940,6000,0,0,0,0,0,0,0,6075,3500,0,0,0,0,0,5000,0,0,5000,5000,0,0,1333,500,0,3300,3000,5490,0,3000,0,10000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1800,0,3993,2185,1600,0,0,0,2000,5000,2500,0,0,3745,2411,0,2753,5000,2500,0,0,3200,3000,6144,4805,0,0,0,1500,0,0,0,0,0,0,6600,0,1591,6000,0,0,0,1000,0,1500,0,0,0,0,1250,0,2000,2500,0,0,5000,0,0,3750,5000,0,0,5000,0,0,0,0,4319,1250,5000,0,8750,5000,5000,0,5000,0,3000,0,3100,0,4500,4500,0,0,5000,0,0,7836,0,0,0,0,0,5000,7900,6000,300,3500,5000,7000,500,0,0,0,0,0,0,2824,0,0,0,5000,0,4000,2400,1070,0,4000,2000,3000,0,0,1734,0,0,0,0,0,0,0,5000,3000,0,0,0,0,2400,4950,0,0,10800,500,0,0,0,0,5000,6000,1500,0,2500,0,0,0,4500,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,6000,0,0,0,0,0,1500,0,0,0,0,0,0,5000,7725,0,1750,0,2500,5000,3349,0,0,4000,0,0,0,0,0,0,0,0,500,0,0,2260,0,11611,0,0,0,0,3310,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,900,0,12515,0,5000,0,0,7150,0,6700,5000,2500,0,0,3750,5000,4315,4600,0,3000,0,0,0,0,0,20000,0,0,0,8000,0,0,0,0,4800,0,875,3000,0,0,4000,1000,0,2065,0,5000,5000,0,3500,0,0,6000,0,4200,0,0,5500,0,3172,3000,0,0,3348,4400,0,3500,0,5000,0,250,0,2500,0,1500,1500,0,0,0,500,4082,1300,4125,5000,4500,0,0,6600,0,0,0,0,0,0,0,0,0,0,0,3500,5000,0,0,0,3239,5460,0,5200,0,0,0,0,0,0,0,0,0,4850,0,0,1232,4650,0,5000,0,0,5279,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,9506,3000,0,0,0,1800,3000,0,5000,0,0,0,900,0,0,6666,0,0,0,1600,500,0,0,0,5000,0,8000,0,0,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,900,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10000,0,0,11900,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3250,0,0,2500,0,0,0,0,0,0,0,0,6000,0,0,0,0,0,0,0,0,0,0,2500,0,1625,12000,0,11764,0,0,0,0,0,0,0,0,0,11800,0,0,5000,0,0,0,0,0,20000,0,0,0,0,0,0,10000,0,0,0,0,0,0,4500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3475,7500,0,0,0,0,0,0,0,0,0,0,0,2500,0,0,0,5000,0,0,0,0,0,11030,0,0,0,0,0,0,0,2100,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7000,0,0,0,0,0,0,40000,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,48000,10000,0,3500,0,5000,0,0,0,1500,0,8746,0,1000,0,0,0,0,0,0,0,0,0,0,0,0,11000,0,0,0,0,0,1600,0,3500,4865,2000,4400,4000,0,1000,5000,1000,0,0,0,2500,0,0,6000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2500,0,5000,0,0,0,0,0,1000,0,0,0,0,0,5000,5000,5000,0,0,0,0,0,2000,3500,9930,1925,0,0,0,7633,0,0,900,0,5000,0,5000,7500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1500,0,0,0,3370,5000,0,1300,0,6000,2000,0,0,0,4000,8085,0,0,0,0,0,0,0,8443,8792,0,2000,0,2900,0,0,0,3000,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,1500,0,0,0,0,0,3900,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4700,0,0,0,0,0,5000,0,0,4625,0,0,0,1585,0,1625,0,0,0,1200,0,0,0,0,0,0,0,0,0,5700,0,0,2200,0,0,0,0,0,0,0,0,0,0,860,0,0,0,0,0,9000,0,3000,0,0,0,10850,0,2000,0,5000,0,0,4900,0,3000,0,0,0,0,0,0,0,0,0,0,0,7000,0,0,1750,0,0,0,1650,0,0,0,0,0,7524,0,5000,7000,9500,0,0,0,0,0,0,4400,0,0,0,0,0,0,0,0,0,960,0,1345,0,0,0,3000,0,2500,0,0,0,0,0,0,0,0,0,850,7500,3890,0,0,0,0,3819,0,0,0,0,0,0,0,0,0,5000,5000,0,0,2000,0,0,0,0,0,1000,0,0,0,4000,0,0,0,0,0,0,0,870,0,0,7500,0,0,0,0,2375,0,0,0,2200,4000,4700,0,0,0,0,0,0,0,0,0,5000,3000,0,0,0,0,0,0,900,1000,0,0,2500,0,0,0,0,1600,0,0,0,0,1198,0,0,0,1875,0,0,0,0,0,0,0,0,6500,0,0,3620,0,0,0,0,10000,0,0,3500,0,2500,0,1039,0,0,0,0,0,0,0,0,6000,0,0,0,0,6000,2400,0,0,5000,0,0,0,0,0,14500,1000,7911,0,8098,0,0,1000,0,9200,11000,0,0,2500,0,0,4400,4750,7000,0,0,4400,0,0,0,0,0,0,0,1500,0,0,0,0,0,0,0,0,0,0,5000,1000,0,0,0,0,0,0,0,0,0,0,0,0,0,3900,0,0,0,0,0,0,0,0,1800,1950,0,4400,0,3535,0,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,0,0,0,4579,0,0,1925,2500,5500,0,700,2150,500,0,1900,0,8848,0,6000,0,2000,0,0,0,0,5000,0,7300,3000,0,0,0,0,0,0,0,0,0,0,3000,0,5800,0,0,483,0,4600,0,4000,6000,0,0,3120,0,0,0,0,0,0,9775,0,0,0,0,5000,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,3500,5000,0,0,0,0,1600,3902,0,4350,2500,0,0,0,3000,0,0,0,0,0,0,0,0,4000,0,300,1000,0,0,0,0,9000,0,0,425,3500,0,0,0,0,0,0,1000,0,400,3400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,2900,0,0,0,0,0,0,0,0,4500,4500,0,8300,0,0,4000,0,0,2000,0,0,0,0,0,0,0,0,0,300,3500,0,5575,0,0,0,0,0,0,0,0,0,0,0,0,6500,0,0,0,0,0,4500,0,6000,0,0,4000,0,4000,4000,120,0,0,9794,5000,0,4000,7000,0,0,0,0,2000,6000,2000,0,0,5000,6500,0,4902,0,4000,6000,0,0,9375,0,0,0,0,0,3000,0,5000,6000,500,5000,0,1000,0,4600,0,0,1000,0,0,0,0,0,0,4251,0,0,0,6500,8100,3500,4251,4750,0,5500,0,0,5000,6110,0,5800,6175,3850,0,3000,0,3000,0,0,0,500,2500,0,0,4980,0,0,0,0,0,0,2400,1500,0,2000,3000,360,0,0,0,0,5300,5000,5000,545,1950,0,0,0,1600,3500,0,0,0,0,4881,0,7000,4000,6000,2000,0,0,0,5500,4814,0,5000,4300,3000,3500,7000,0,5000,4500,0,0,7500,0,0,1816,5000,5000,0,0,5000,0,1000,0,0,0,0,500,0,5000,5000,0,0,5000,7500,0,0,3563,0,5150,0,0,0,0,0,0,0,2700,0,6777,4000,0,3000,0,4000,0,2998,0,0,2100,0,0,3645,0,2400,4000,0,0,5000,2830,0,0,2775,6000,0,5000,0,0,3500,0,0,0,4000,0,0,0,0,5000,0,6020,0,3830,3000,0,7168,3200,0,3000,0,0,0,0,4173,0,1700,0,4586,0,2500,0,0,4200,0,0,4783,0,2000,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,4148,0,5000,6000,0,0,2500,0,0,2000,0,2000,1215,4500,0,0,4677,0,1000,2636,4500,5890,0,4200,0,2670,1969,0,0,3000,0,0,4500,1840,0,0,3995,0,0,0,0,0,0,0,4611,0,0,0,0,4000,0,0,0,0,3500,0,0,0,0,4940,0,0,2500,2564,4768,4410,0,0,1850,1500,2500,0,0,2000,0,0,4900,0,0,0,4400,3500,0,0,0,0,3212,0,1500,0,0,0,0,0,0,0,0,0,0,0,3150,0,0,0,0,0,2130,0,0,2900,0,0,0,4500,0,0,0,0,0,0,3535,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3150,0,3297,0,0,0,4450,0,0,4450,0,0,4040,0,0,0,0,0,0,0,4170,0,0,2790,3500,0,0,450,0,4498,0,0,0,0,0,0,0,0,0,2972,0,0,3000,0,0,0,0,0,0,0,0,0,2000,0,0,4189,0,0,4500,0,0,3500,0,0,0,0,0,0,0,0,4400,0,3597,0,0,0,0,4500,4000,0,0,0,0,0,0,0,4200,0,0,2257,0,0,0,0,0,0,0,4800,0,0,0,0,0,0,0,0,4100,0,0,0,0,0,0,0,0,4800,0,0,0,3640,0,0,0,0,7190,0,0,0,0,2758,0,0,0,4050,0,0,0,0,0,0,0,0,1599,4750,0,0,0,0,0,0,0,5500,688,0,5000,0,0,4997,0,3900,0,0,0,0,3285,3830,0,0,0,820,0,0,4515,0,3000,0,4000,0,0,0,0,3920,0,0,0,0,1698,0,0,0,3500,0,0,5000,3000,2700,0,0,3000,0,0,5000,0,2526,0,0,0,3706,0,0,0,0,0,0,0,0,3500,0,0,1866,0,2250,0,4000,0,0,0,0,0,0,0,0,4410,0,0,5240,0,3120,0,0,0,3795,0,0,0,0,0,0,3042,5000,0,4541,0,7994,0,7000,0,0,4860,5140,0,0,3251,0,0,0,0,0,0,1932,0,0,0,4050,0,0,0,0,0,0,0,0,0,0,0,2530,0,0,0,4300,0,0,4400,4400,2880,0,0,4000,0,0,4946,0,257,0,0,0,0,3500,3000,0,3500,0,0,0,0,0,4950,4870,1500,0,0,0,0,3624,0,2254,2466,0,3290,0,0,0,0,4290,0,3480,3500,0,0,0,0,3500,0,0,4000,0,1300,4700,0,0,2807,0,3520,0,0,4000,0,0,4000,0,0,0,0,3000,0,4650,0,0,4500,0,400,0,0,0,0,4770,0,0,2400,0,0,0,0,0,0,0,2023,0,3750,0,3827,0,0,3600,0,2500,0,0,0,2500,0,4139,3000,0,3030,0,4800,0,0,2953,3500,0,2966,4300,0,4500,0,0,0,0,5000,0,4000,4978,0,4000,4000,0,0,0,3600,0,0,100,4117,0,3600,3570,2922,0,0,3300,808,1000,0,4900,3500,0,0,0,0,0,0,0,0,4000,3250,0,2530,0,0,3394,0,0,0,0,4774,4400,0,0,3000,5610,0,0,3000,3654,4115,0,1750,0,0,4650,0,4054,2775,0,0,1800,5000,0,0,2383,3660,3397,3840,4728,4598,0,3160,6000,0,0,3900,0,0,1290,3500,4375,0,0,0,3000,2413,0,0,3500,6800,12588,0,4818,0,0,0,0,4713,0,3404,0,0,0,0,0,3403,4500,0,4700,3125,0,0,1324,0,2411,0,3694,0,0,0,500,0,0,0,0,0,0,4000,4500,4778,2800,0,4000,0,2564,3300,4251,4047,0,0,0,0,5000,0,0,0,2000,0,0,1000,0,0,0,0,4000,0,0,0,4303,0,0,0,0,0,3000,2071,0,3780,0,0,1800,0,0,0,5553,0,0,0,0,0,0,0,0,0,0,0,0,4200,0,8615,4354,3014,3188,0,5250,0,1971,0,4600,3100,0,2000,3000,0,0,0,0,5300,3720,4950,0,0,3270,0,0,0,0,0,0,0,0,0,2550,5000,0,0,1800,0,0,0,0,0,0,0,0,0,4983,0,6952,1000,2741,3000,0,4913,0,0,4500,0,0,0,0,0,5000,0,5100,3210,3000,0,3750,0,2300,3500,0,0,0,0,2549,0,0,2610,0,5500,3450,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,4700,0,0,0,0,0,3000,2971,0,0,0,0,3960,0,0,0,0,0,0,3900,0,4100,0,5160,0,0,0,0,4500,0,4000,3350,4442,0,4000,0,0,0,0,0,3447,6200,2500,2088,0,807,4907,4000,0,1000,3800,0,0,6000,0,2500,0,2500,0,0,3736,2000,3936,0,0,1500,0,2817,4253,5750,5200,0,0,4400,3920,0,4500,0,4129,0,4350,0,2524,0,0,0,3000,3250,0,0,0,4000,4240,3500,0,0,4700,4500,5396,0,686,2500,3780,4450,0,0,0,3255,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,5000,6000,0,5000,0,4446,0,1415,0,0,0,0,0,1250,1000,0,1500,4000,0,0,4000,4000,0,0,0,0,0,500,4000,0,0,0,0,0,5000,0,4550,4000,0,0,2500,0,1000,3400,0,1300,0,5000,7500,0,0,0,0,0,0,0,0,0,0,5000,3983,2000,3500,0,0,0,0,0,0,0,0,0,0,0,6000,2000,10000,0,0,0,0,0,4700,0,0,0,0,0,0,5000,2750,3625,1000,0,0,3600,4900,0,0,0,0,0,0,0,3422,0,0,0,8000,0,0,6000,0,3000,0,2000,0,0,0,1500,3000,0,3000,7000,0,0,0,0,1000,3300,2500,5000,3000,0,0,8000,0,0,5000,5970,4000,450,0,5000,0,0,0,0,5000,7500,0,2500,0,0,4500,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,5650,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,2500,0,0,0,0,1300,500,5000,0,0,0,0,0,3000,0,0,0,5000,0,450,0,0,0,2500,0,0,0,0,2000,0,3000,0,0,5000,0,0,750,0,0,0,0,5760,0,3000,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,450,4450,1000,7993,2100,0,7700,0,1498,0,0,0,0,0,0,0,0,0,0,5000,0,500,0,4771,0,0,0,750,10000,0,0,3500,0,3800,5000,3000,5000,0,0,3000,5000,0,0,3500,1500,0,2500,6000,0,0,0,5000,0,0,0,500,1950,1000,0,0,0,3510,0,0,0,8500,0,0,0,5000,0,5000,2500,3252,0,3303,0,7000,0,0,0,0,0,0,0,0,0,0,7200,0,5000,0,0,0,0,0,0,0,0,2000,0,2700,15000,640,0,12072,7500,8964,0,0,0,0,1050,0,0,0,0,7500,10000,0,0,0,0,5000,900,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,4000,0,4000,0,0,2641,3000,3600,0,0,0,0,0,6600,4000,0,500,500,0,0,0,0,2000,0,2500,2500,4300,0,0,220,500,4590,1000,0,0,0,0,0,0,0,0,0,0,0,0,6000,0,0,0,0,0,0,0,0,6000,0,0,0,0,0,0,4000,0,4309,0,5000,3500,0,0,5500,2700,2000,0,2850,0,0,0,0,2000,0,0,0,0,0,0,0,0,3500,751,0,0,0,0,0,0,0,8000,0,0,6500,0,5000,0,2500,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1560,0,3175,3700,0,1000,0,0,0,0,0,0,0,0,4700,0,0,1600,200,5000,0,0,0,0,0,5500,0,0,3985,3500,6000,5500,4206,0,3033,0,2903,1515,0,5000,0,2000,0,4000,0,5430,0,0,0,0,0,0,4900,0,1500,0,5700,0,0,2850,0,3434,0,0,0,0,0,7670,0,0,0,0,0,0,0,1500,6200,0,0,0,1000,0,1500,0,0,3703,0,7279,0,0,1300,0,0,0,4927,0,0,322,0,0,0,3500,0,0,0,0,0,0,0,0,6500,0,0,0,0,0,5000,0,0,4000,0,5000,4500,0,0,0,0,0,0,0,0,0,0,1700,0,0,0,2000,6000,0,0,0,0,0,0,0,0,0,4000,2800,0,0,0,0,0,6000,0,0,0,0,0,0,0,21490,12800,0,0,0,0,400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,12000,0,0,820,0,0,0,0,0,0,0,0,0,0,0,15000,0,0,0,0,0,0,0,0,0,25000,7000,0,0,0,10000,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,500,0,0,0,0,200,0,0,0,0,0,0,0,0,850,0,0,0,0,0,0,0,0,0,0,0,4214,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,1000,0,4000,0,0,10000,0,0,0,0,0,7000,0,0,0,0,0,0,0,5000,0,0,0,0,0,500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,5300,0,6000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7500,0,0,0,0,0,0,0,0,0,0,3675,0,0,2500,0,0,0,0,0,0,0,0,0,5000,0,1500,0,5000,0,0,4000,2500,3000,0,0,4000,0,0,4000,0,0,7800,2000,4650,0,3457,0,0,0,2500,0,2500,0,1675,3700,5233,0,0,5900,0,800,0,0,9135,0,0,0,0,0,0,0,0,0,0,7800,0,0,750,0,0,0,0,0,0,4000,0,2500,2500,2700,2450,0,0,0,0,5000,2565,5500,0,1000,0,0,1500,6000,0,0,2500,0,0,500,5700,0,0,0,3000,4000,4000,0,0,0,0,4350,0,0,0,1500,0,0,0,0,0,3300,0,0,0,5000,0,0,0,0,850,1500,3300,8000,2198,2500,0,0,0,0,0,0,0,0,9300,0,0,0,0,3000,5000,1900,1500,1500,2982,0,0,5000,5400,0,3500,0,0,0,5800,0,0,0,0,0,0,0,3340,0,0,0,0,0,3175,0,3000,0,0,0,0,0,0,3385,0,0,0,5000,5500,2000,0,0,0,5000,4516,0,0,0,0,1150,0,0,0,0,0,6000,292,8250,0,0,4500,0,2500,0,0,0,1750,3045,6000,0,0,0,0,5000,1000,0,0,0,0,0,5000,0,0,0,0,7380,0,0,0,11880,4632,0,0,0,3585,0,7415,0,4000,5000,0,0,4800,2400,1500,5969,0,0,0,0,0,5500,0,0,0,2300,3000,0,0,0,0,0,0,0,3000,0,0,0,5000,4000,2000,0,5000,0,0,0,0,0,4000,0,3750,0,4000,0,5000,4786,0,1860,0,0,0,1513,0,8000,5000,0,3000,0,5000,0,0,0,2000,3000,0,0,0,0,0,10050,4000,4000,2750,0,0,0,5100,0,0,0,0,0,3500,0,0,0,0,5500,0,2800,0,0,0,0,0,5545,2000,5250,0,0,0,0,0,0,5000,0,0,5500,3000,0,0,0,0,0,0,1000,0,4428,4000,0,7546,10115,4000,0,3206,0,3000,0,0,3700,4000,0,0,4000,2000,3000,0,0,0,4000,0,0,0,0,0,0,0,0,0,3000,0,3921,1500,4800,4577,0,0,0,0,0,0,3500,0,0,5299,0,0,0,0,0,0,4232,0,0,4455,0,0,2000,1500,3500,0,0,4940,0,0,0,0,0,0,4000,0,4331,0,0,0,0,3900,0,0,5000,4750,0,0,2300,0,4497,4277,0,3285,0,0,2750,0,4000,4000,0,0,0,2500,4800,4871,4000,0,3150,0,0,3500,0,0,0,0,0,0,3182,0,0,4660,0,0,0,3000,3000,0,4000,0,4450,0,4500,3200,0,0,0,1500,0,3000,0,0,4723,0,3500,0,0,5000,5000,3000,0,0,3400,0,4440,2750,0,0,0,3375,4300,5000,0,0,0,0,0,4497,0,0,0,3652,4500,0,4900,0,0,0,4500,3000,0,5504,4600,4000,3540,4749,0,0,3324,3600,5025,0,0,0,4875,0,1500,3500,0,0,0,0,0,1500,0,0,4000,0,0,0,0,2634,0,0,3300,4005,0,3200,0,3000,0,3089,0,0,0,0,4375,2500,0,5250,5000,5000,0,0,627,0,4973,0,0,4932,0,5850,500,4000,0,950,0,0,0,2000,3600,0,6150,0,0,0,4050,2798,0,2300,0,0,0,5000,3000,0,4000,6000,0,5835,0,4000,0,0,5000,4000,0,0,0,0,5400,0,4500,0,4400,0,4044,0,0,4900,0,0,0,0,4452,0,1850,6000,6225,0,0,3700,0,5000,0,0,2124,0,0,0,0,0,0,4000,5054,4500,0,0,0,3557,5997,3450,4100,0,0,4500,0,0,3600,0,3812,4500,0,0,4800,0,0,5250,0,0,5000,0,0,4710,0,3800,4000,4731,0,5570,0,5000,0,0,4000,0,0,0,6250,0,0,450,0,0,5850,1500,0,0,4900,4450,0,4742,4300,0,3500,4000,5500,5211,0,0,0,0,5731,4500,0,4950,0,5000,1500,0,0,0,0,5000,0,3900,2000,0,3000,0,6800,4632,5200,0,0,0,4000,5000,0,0,5000,0,4500,0,0,4324,0,0,0,4199,0,3900,0,3200,0,0,0,0,0,0,4866,4785,0,0,0,5000,4000,0,2000,2611,0,0,4500,4631,0,0,4000,0,10440,0,4928,0,3789,4100,5982,0,5000,4296,0,0,5400,5000,0,0,4917,0,3000,2000,0,5176,0,5000,2200,3953,5000,0,4500,4000,0,0,5700,5000,0,0,4465,4500,5500,0,0,3000,0,2700,0,0,4500,4500,0,0,0,0,0,650,0,3465,4000,5955,5415,4000,3500,5100,0,4007,2500,0,5000,0,6000,13000,6000,0,3200,4386,3500,5162,4000,0,0,0,0,0,3000,0,0,4000,12000,0,0,4000,0,0,0,0,5326,5000,3310,2500,0,0,0,0,2500,4500,3783,5000,0,0,0,4000,0,6000,4500,600,0,5000,5000,4741,0,3668,6170,0,0,1000,4000,0,4500,2500,0,0,0,0,0,0,0,0,4034,0,0,5970,6000,0,0,0,4600,0,850,5555,6000,0,0,0,0,0,0,5000,5000,0,0,3900,0,0,0,0,4000,0,2143,4000,5000,4900,6325,0,0,3250,0,0,0,0,0,0,5000,0,0,0,0,0,1860,1000,1500,5217,0,2500,3810,0,0,0,3000,3500,0,0,0,0,0,0,3750,6200,3500,4200,0,0,5000,0,6340,0,6050,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,5000,0,0,2500,4000,6500,0,200,0,0,12000,3000,5860,0,0,0,6100,0,3800,0,0,0,5000,0,0,0,0,0,3000,0,0,2000,2500,3000,0,0,3806,3000,0,1500,0,0,4675,4000,0,0,1245,0,0,0,0,0,0,0,0,2161,675,4290,4483,2000,0,4600,0,0,7557,0,2700,0,0,1650,5000,0,0,0,0,4000,0,0,0,1000,0,0,500,5000,6500,0,0,0,0,3960,3600,0,0,0,0,5845,0,0,0,0,0,0,0,4700,6500,1550,5194,3000,0,0,7250,0,0,0,0,0,0,0,1200,0,1500,0,0,0,0,1000,0,0,0,330,0,625,0,0,3000,0,0,5000,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,10000,0,2500,6000,7000,0,0,1000,0,3794,0,0,0,0,0,0,3000,0,0,1000,5000,22500,0,0,0,0,0,0,0,7500,6600,0,0,1583,0,3920,0,0,0,0,0,2000,0,0,0,1750,1503,0,0,3488,5000,0,0,0,0,0,0,7000,0,0,0,1680,4500,3500,0,3617,3740,3000,2940,0,0,0,0,0,4035,3000,0,0,0,0,0,0,0,4170,2091,0,0,0,0,0,0,3750,2400,0,0,0,3796,0,1525,0,4982,0,2000,0,0,4000,0,0,0,0,2500,4208,0,0,0,0,0,4000,4323,3140,0,4307,0,0,2000,3000,0,0,0,0,0,4000,0,3262,0,0,11910,0,4037,4413,4214,0,5000,5000,0,0,0,0,0,0,0,0,0,0,0,5940,0,0,5400,0,0,3000,0,2219,0,1000,0,5500,4882,0,0,3320,0,3000,0,0,0,3000,500,2900,0,0,5600,0,0,0,0,200,7000,0,0,0,5000,0,0,0,0,0,0,0,0,8000,0,1500,0,0,0,0,0,0,0,0,8000,2700,3600,5100,0,0,0,0,0,0,0,0,700,0,0,0,0,0,0,0,700,500,540,0,0,4500,0,0,0,0,0,0,513,0,0,0,0,0,5000,12000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2386,5247,0,0,0,0,0,5151,0,5000,0,0,0,0,0,0,5000,6327,0,0,0,4000,0,7500,3000,0,0,0,0,0,4500,0,4500,5000,0,0,5000,3190,2500,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,2700,5000,6800,4400,4300,0,4500,0,4302,0,3200,0,0,20000,0,0,0,0,8000,0,0,0,0,3629,0,2500,4000,0,0,0,1280,3725,1500,0,0,0,5000,5500,4000,3700,0,0,0,0,500,0,0,0,10000,0,0,0,1000,4500,0,5000,4920,0,0,0,4800,0,0,0,0,0,2000,0,3300,0,0,0,5000,5940,0,5061,0,0,0,0,5000,0,0,0,0,0,500,4000,0,4800,6400,0,5500,5000,0,0,0,4000,0,0,0,0,0,0,0,0,1500,0,2500,0,3250,0,0,0,0,0,4400,0,1750,750,0,0,10935,0,3328,2500,0,0,0,0,0,2000,0,0,1500,3000,5500,6000,1250,0,0,0,3500,0,0,8000,0,2500,0,1300,4300,0,900,0,0,0,0,0,3500,0,6000,2000,6500,0,0,0,0,0,0,0,0,9670,0,0,0,0,0,1200,0,0,0,0,1500,0,0,0,0,0,0,0,0,0,0,4000,4059,0,0,6500,0,0,6000,600,0,0,0,0,3900,0,4788,0,0,0,0,0,0,0,0,0,0,2400,0,0,0,0,0,0,0,3380,0,0,0,0,0,0,0,0,4600,0,0,0,0,13350,0,0,4800,0,6000,0,0,0,0,0,3500,0,3500,0,4000,0,0,5500,1740,0,0,0,0,0,0,1100,0,0,4000,0,0,0,650,0,7000,5000,0,3400,0,0,995,2500,0,1850,6174,7000,0,5000,0,0,0,5000,0,6000,500,0,0,0,0,0,0,2000,2400,0,0,5500,4631,4000,0,1415,4500,5000,0,0,0,0,0,0,6500,0,0,0,0,8500,0,8500,6600,87,0,5000,3500,0,2830,0,4000,3000,5500,0,8000,0,11850,0,0,0,4500,2500,0,1000,0,0,0,0,0,10000,0,0,0,0,0,9819,0,500,0,7300,5000,0,0,0,7000,8492,0,0,4000,0,0,0,1000,0,0,0,0,0,3025,0,0,3000,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2222,0,0,0,0,0,0,0,0,7000,0,3000,0,5850,0,5000,0,0,0,0,0,0,700,0,1500,0,0,0,0,0,0,0,3300,3382,0,0,0,0,4000,0,0,0,5000,0,0,0,0,0,200,0,0,0,0,0,0,0,0,3600,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,3878,0,0,0,0,1000,0,0,0,0,0,0,0,0,0,0,0,9000,0,4100,0,0,0,0,6000,0,0,0,0,4500,0,3800,2500,0,0,15000,5000,0,0,12500,0,0,1500,0,0,0,0,0,0,0,0,0,4750,0,1400,3150,2865,0,4830,5000,1500,0,500,0,0,0,0,0,8837,4260,4000,0,1679,0,0,7500,695,0,0,0,0,0,0,0,0,0,0,10000,0,7000,7500,0,0,0,0,0,0,0,0,0,0,2000,600,0,5000,7000,0,0,0,350,14094,32100,2750,30000,0,10000,0,0,0,0,1500,5000,0,15000,500,0,0,0,0,0,10000,0,0,0,0,0,0,0,0,2489,0,1000,0,7000,0,2000,0,0,0,0,0,0,0,0,4500,0,2483,5760,0,3000,0,0,0,0,0,0,0,0,3000,0,1500,4100,0,0,0,0,0,4000,0,0,6950,2500,0,0,0,0,6457,0,0,0,0,5400,4000,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8500,0,0,0,0,0,0,0,0,0,0,0,0,7600,0,0,0,0,0,6242,0,0,2500,0,0,0,0,0,0,3146,0,0,0,500,5200,0,0,2900,0,3000,0,4000,6300,0,0,0,0,2000,2000,0,7000,0,0,0,0,0,6000,0,3500,0,4000,0,0,3000,0,0,4000,0,8085,6300,6600,4500,0,0,0,0,3980,5412,4000,0,4000,0,0,6000,0,0,0,6000,0,5900,0,0,6500,0,0,0,6700,0,0,0,0,0,0,0,0,4800,0,3964,0,0,0,0,0,0,0,3985,0,3000,8000,9078,0,1500,0,0,0,0,4040,0,0,0,0,0,0,7000,0,1200,0,0,0,0,0,0,0,3000,0,0,0,0,0,150,0,0,0,0,0,0,0,0,2000,0,0,0,3500,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,4000,0,0,0,4400,0,0,2385,0,0,0,0,3000,2000,0,6000,5000,2592,5500,0,0,6000,4460,0,5000,5500,10000,0,5000,5000,4000,5400,0,0,375,0,0,0,0,5000,0,0,3700,0,7000,0,0,4000,0,0,0,0,1000,0,0,6000,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,1100,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2500,0,1500,0,0,0,0,0,0,0,2675,0,0,0,0,0,0,0,0,429,6000,4400,0,3000,0,0,0,0,0,0,0,2000,0,2500,0,4190,7000,0,0,0,13137,0,0,1000,0,0,0,0,2000,0,0,0,0,1000,500,0,500,0,0,0,0,0,2800,0,0,0,0,0,0,0,0,0,0,0,5169,5500,5000,0,5000,0,2500,0,5250,2000,0,5000,6500,0,0,0,0,0,0,5000,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3537,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,1666,0,0,0,0,1410,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,1710,0,1747,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,0,0,0,0,2290,0,0,0,0,0,0,0,0,2000,0,0,1560,0,2500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1700,0,0,0,0,0,0,0,0,0,200,0,0,0,0,0,0,0,1175,0,0,0,2217,0,0,0,0,0,0,0,0,0,0,0,4350,0,0,0,0,0,3947,1500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1470,0,0,0,0,0,0,0,0,3850,0,0,0,0,0,0,0,0,0,2100,0,0,0,2760,2482,1050,0,0,0,0,0,0,0,1524,1950,0,0,0,0,2416,0,0,2040,0,0,0,3657,0,0,0,0,0,2000,0,0,0,1890,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1250,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2327,0,0,0,0,0,0,0,0,0,0,1500,0,0,3503,0,0,1800,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,0,0,1582,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,2025,0,0,0,0,0,0,0,0,0,0,0,0,0,2100,1044,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,0,0,0,3297,0,0,0,0,0,0,0,0,1000,0,0,0,500,0,0,3801,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,3597,0,0,0,3000,4000,0,0,0,0,8000,0,4200,2000,0,4000,5000,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2800,0,0,0,0,1640,2900,0,0,0,0,0,0,0,0,0,0,2500,0,0,0,0,0,0,0,0,0,0,0,1250,0,0,1100,0,0,0,4139,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2100,2000,2330,2750,0,0,1500,0,0,0,0,2600,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,1500,0,4900,0,0,1500,3500,0,0,0,0,0,0,4000,0,0,0,0,6500,0,0,0,0,0,0,0,0,0,0,4005,0,0,0,4500,0,6500,0,5625,0,0,4477,0,0,500,7650,0,0,5000,1450,5000,5000,3239,1898,0,0,0,0,0,0,0,0,0,0,4890,0,0,0,0,0,4799,0,0,0,0,0,0,200,0,5000,5000,2500,3400,0,5500,0,0,250,0,0,873,5200,350,0,0,0,0,4625,500,0,3846,2790,1800,0,4000,0,0,6000,0,0,0,0,0,0,0,0,1500,0,0,0,5000,0,2000,0,1415,0,0,4000,3796,0,1000,3500,0,5000,1700,3959,0,0,0,5000,0,0,0,0,10800,4500,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,5705,0,0,0,0,400,1000,4000,0,0,0,0,0,0,6634,7490,3000,400,0,0,5000,0,0,0,0,0,0,0,0,6377,0,5278,0,0,0,0,0,4000,0,3700,0,5000,1000,0,0,0,6000,0,4000,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,1002,0,0,0,0,0,3700,1500,0,0,2839,0,4000,4113,4000,5500,6000,0,4000,5599,0,3200,0,0,0,6604,4000,6200,1000,3613,0,0,0,0,5190,0,0,5000,0,0,0,0,0,4000,8000,1500,0,0,0,0,0,0,3000,5500,0,3628,0,3770,3820,1000,5867,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5000,0,0,1500,0,0,0,3600,4526,6900,0,5000,0,0,4000,0,5600,6000,0,2250,0,2000,0,9100,7084,3500,850,5000,1300,2000,5000,0,6000,0,0,3000,0,0,0,11800,0,4500,0,9900,0,6500,0,0,2500,2000,0,0,0,2500,0,0,4500,0,0,0,4000,10448,0,5000,0,0,4400,2000,4000,4000,3250,0,0,0,4000,4310,0,0,4000,5000,0,0,0,4000,0,0,0,0,2850,0,0,0,0,0,0,0,3100,0,3000,0,0,0,0,0,0,0,3500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2200,2200,0,0,0,0,0,3500,0,0,0,0,4000,3150,0,2065,0,0,0,0,0,2600,0,0,4830,0,0,0,0,4500,3500,0,4200,0,9780,0,6375,0,4272,4000,0,0,0,0,0,6484,5100,0,0,4500,0,5934,4094,0,3077,5000,0,7000,0,0,0,5000,0,0,0,0,13500,0,6000,5900,4500,0,5500,1299,3000,5000,0,500,0,0,0,0,0,0,6000,5200,2000,0,0,0,4750,0,0,4000,0,0,1691,3000,3250,0,5000,0,0,552,0,1890,6800,8295,0,0,1200,0,7900,0,4258,4500,0,0,0,7000,0,5000,6000,7000,1050,8200,0,2000,5500,0,0,0,0,3000,10700,0,3000,0,0,3400,3297,0,6201,2750,2000,4187,3000,5450,0,0,0,0,0,4262,3500,5000,1200,2500,1500,0,0,2500,0,3864,0,3000,0,0,0,0,0,0,2000,4000,0,6145,3500,0,5000,0,3000,0,0,0,3600,4000,0,0,0,11375,0,0,0,4500,2520,3571,4000,0,3500,0,2460,0,2000,0,0,0,0,0,4250,0,0,3000,0,1200,5000,4021,0,5000,1000,0,0,0,4248,0,0,0,0,3500,0,2000,3000,0,1000,2000,0,3300,0,4350,0,0,0,4020,0,0,0,0,0,1500,5000,0,0,2000,3250,2751,4000,2700,0,1000,0,0,2500,0,2640,0,1800,0,1900,2550,0,0,0,0,0,0,0,3500,0,2500,0,0,0,0,0,0,0,0,0,2000,0,4443,0,0,3986,0,0,0,0,0,2000,0,0,4000,0,5000,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,500,0,2600,0,0,5000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7750,0,5000,0,0,0,0,0,0,0,4745,0,0,4222,1800,3000,1776,0,1750,0,0,1406,0,0,3771,5000,6200,0,5600,0,0,0,0,0,5000,500,0,0,0,4000,0,0,0,2000,1080,500,0,500,3320,0,0,0,4972,0,0,0,0,0,6646,0,0,1165,3000,0,4000,0,4546,0,5077,0,0,3240,5000,0,0,500,0,0,0,2500,0,0,0,0,0,0,0,0,0,0,1925,0,0,0,0,3000,0,2500,0,0,0,0,0,0,5682,0,0,4500,0,0,0,0,0,0,0,5000,6000,0,350,0,4000,9270,0,0,5000,4562,2750,0,0,5800,500,5000,0,0,0,0,0,0,0,4000,1217,0,0,0,1200,3885,4900,4500,0,4000,2000,0,0,0,3000,0,0,0,0,0,0,0,4000,5400,5000,7400,0,0,3772,0,4000,0,0,0,0,0,5394,0,0,0,0,3000,0,3000,0,0,0,0,0,0,0,3000,2000,5000,0,0,0,0,0,3914,0,0,0,0,0,0,4488,0,0,0,0,0,0,0,8500,0,0,0,0,4000,6500,3000,0,0,5321,0,5000,0,0,0,0,4000,0,0,3900,0,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,4600,4000,0,2800,5000,0,0,0,0,6750,0,500,0,0,0,0,0,0,0,3260,0,5700,0,6500,0,9000,0,0,5000,0,7500,0,8370,5000,5500,0,0,0,0,3500,0,3500,0,0,0,2000,0,0,0,5200,0,0,7051,2300,0,0,0,5000,4887,5000,0,4425,0,0,0,3150,4500,5474,7025,0,0,1500,3125,0,0,0,4000,0,0,8000,3500,1000,3900,0,0,3000,4819,1400,0,0,0,3175,0,6500,2000,5000,0,4000,3500,3246,0,3000,0,4000,1350,0,0,0,5000,0,0,0,5203,3300,0,0,1000,0,0,2600,1200,2850,0,6581,0,0,0,800,0,0,0,0,0,0,0,0,2000,918,0,0,0,3000,0,0,0,0,0,3000,0,0,0,3000,3875,0,0,0,3796,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,22000,5000,5300,0,2000,0,0,9447,0,0,0,0,0,0,2500,0,440,0,0,0,0,0,0,3000,0,0,7500,0,6000,0,3500,0,0,3200,0,0,3000,0,0,5100,5200,0,0,4500,0,0,0,0,0,0,2000,1400,0,0,0,0,4500,0,0,0,0,0,1250,0,1550,0,1000,0,0,1100,0,0,2200,0,2000,0,0,0,0,0,0,0,0,3195,3500,0,0,0,2750,3650,0,0,3000,0,1000,1420,0,0,2955,0,0,3600,0,0,3450,0,0,0,0,0,0,4300,0,0,0,0,0,0,1500,5000,8000,6817,4760,4000,4500,6000,7389,0,5550,6000,5556,6400,0,5000,0,2200,4898,5000,0,0,0,4765,4000,2900,0,5000,8000,5000,0,6700,0,5000,2500,3185,4700,0,0,4000,6313,5048,6000,4652,5000,5000,0,0,0,4500,1500,4904,0,0,3500,0,5000,5000,5340,0,0,0,0,0,0,0,2000,1680,0,0,0,0,0,0,0,0,0,0,3533,0,0,0,0,0,0,0,0,2368,0,0,0,0,0,3500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4597,385,5350,0,0,0,0,0,800,3000,0,3000,0,0,0,0,0,0,0,0,2380,0,0,2500,5500,6000,5622,0,5899,3000,0,0,0,2945,0,4434,0,0,6000,4200,6900,6700,0,0,0,3250,0,0,0,0,0,0,0,1500,0,2000,4000,2500,5360,1522,2361,3687,0,0,0,0,855,0,0,0,0,5624,0,0,0,2294,2500,0,0,0,0,5500,4000,5000,0,0,0,5400,4600,0,0,0,0,0,0,0,0,0,1000,0,2000,0,0,6341,3500,1000,5000,0,4356,4500,4170,0,1000,0,2500,7736,4000,4000,5000,5000,4500,1035,700,5624,0,5670,0,0,5500,0,0,0,0,400,0,0,3500,5000,0,2425,800,0,0,0,0,3566,2500,0,3500,6300,0,0,0,0,0,2000,3007,0,0,0,0,0,0,0,0,0,7636,14014,6926,16900,8040,6736,7402,8486,0,8198,6200,7796,7432,9061,6200,0,0,0,6200,0,0,3900,0,0,0,1900,1500,0,0,0,0,5000,1200,0,0,0,0,0,0,0,0,0,0,0,0,1874,0,0,0,2900,0,0,0,0,3660,0,0,0,0,0,4350,3600,0,0,0,4000,2000,2478,0,2000,0,1400,3000,0,0,0,4800,0,0,0,1176,0,13350,2050,2900,0,0,0,0,5000,2100,0,0,0,0,2500,3000,3200,0,0,3915,0,0,0,0,3747,2500,4000,6000,5969,11426,8860,10788,9704,0,10069,9845,10489,7979,0,8884,0,10739,0,0,3948,2500,0,2500,5500,4000,0,0,0,5000,6800,5000,3500,3000,5000,4000,0,5000,2031,0,6200,0,5334,0,0,5809,5000,500,0,10483,0,0,0,300,6000,0,7830,3000,0,0,5500,0,6000,0,0,0,0,3699,4560,5000,6000,2800,0,0,0,0,0,0,2500,0,6000,0,2000,7122,0,3200,6500,4000,0,0,745,0,0,0,0,900,0,4055,0,3000,0,3000,1449,0,4000,2400,4055,0,5000,0,3000,0,0,3500,5000,5200,0,3748,6650,4000,8715,10000,0,3716,8250,6960,0,0,0,0,0,8000,4500,1500,450,4500,0,0,3291,0,0,0,0,1200,0,0,0,0,0,0,0,0,0,0,0,0,0,1820,0,0,0,0,1000,0,1260,2913,1500,2700,2500,0,2500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3220,0,3870,0,0,1000,3697,6646,5000,5000,0,5600,0,0,1800,0,0,500,2500,0,5178,0,5000,0,0,3500,0,4000,0,3000,0,0,0,0,4000,1000,4650,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13500,0,0,0,0,0,0,0,6200,0,0,0,0,1500,0,0,0,0,0,0,0,0,0,500,0,0,1500,5000,0,0,1000,0,0,0,0,0,0,2000,0,0,0,0,10000,0,9975,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,6691,0,0,0,0,0,0,1330,0,700,0,5000,0,0,8220,5500,0,5000,2000,0,0,5100,0,0,8070,0,0,0,2860,0,100,0,5920,5000,0,0,4000,0,3200,0,0,0,0,0,0,0,0,5000,0,0,3000,0,5677,6000,9100,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6001,0,0,7389,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3620,0,0,0,0,0,0,6100,7950,3960,0,3000,0,0,0,0,1200,0,0,0,0,0,0,7800,0,1000,0,0,3000,0,0,0,5350,0,2000,0,5475,0,2000,0,3000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1950,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4500,0,0,1600,0,2500,6500,0,3641,0,0,0,0,0,0,3000,7200,0,0,500,0,0,0,0,0,0,0,0,0,0,0,0,1000,0,0,0,0,0,0,0,5600,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3400,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,6910,5550,0,3700,0,3997,2069,0,4000,0,0,0,3000,0,5000,1912,5000,2000,0,3000,0,0,0,4440,4650,4500,5900,0,0,0,0,0,2345,1500,0,5000,0,4697,7000,0,0,0,1000,0,6522,0,0,0,0,0,5389,4736,4950,0,0,3194,945,0,0,0,0,0,5731,0,0,0,5247,0,0,4000,0,4500,3720,0,0,0,3650,0,0,0,0,0,0,0,0,0,0,0,2000,0,0,0,0,0,0,0,0,0,3551,6900,0,6450,5400,2500,0,5000,0,0,6480,6000,0,0,0,0,5000,0,0,0,5000,5000,0,0,4043,0,3000,0,0,6000,0,0,3395,0,0,9700,0,0,6000,0,0,0,0,16600,2400,0,0,0,4000,4200,0,3500,0,0,0,5576,0,2000,0,4200,0,0,5000,0,6000,0,4200,3800,5000,5500,0,6500,0,5000,0,0,0,0,0,4000,5000,6400,350,5697,5000,0,0,1100,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7500,0,0,5000,2601,0,0,5340,0,0,7000,0,0,9000,0,0,4000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4000,0,0,2910,0,0,0,3100,1000,0,5000,0,4755,0,0,0,0,0,0,0,0,0,4900,2500,2600,2000,0,0,0,0,0,0,1100,0,5000,0,0,0,0,0,0,1000,0,0,0,0,0,0,511,6000,0,4884,0,0,0,0,0,5000,0,2418,2500,0,0,3900,0,0,4400,4000,0,0,3000,3000,3479,0,0,0,0,1601,0,0,6500,4147,2500,4000,0,0,4677,6150,4000,4655,5700,0,2000,0,0,0,5500,0,0,0,500,2500,5000,5059,0,2875,5200,4634,5953,0,0,5000,0,6595,3868,0,3990,4600,4800,0,0,4500,0,0,0,0,0,0,5500,900,0,3125,4800,0,5500,332,0,0,0,0,0,3000,0,6747,0,5000,6000,750,3800,0,0,4981,0,0,6900,4000,1800,0,0,0,0,0,0,0,2641,2000,0,3800,0,0,0,3900,0,0,0,0,0,0,0,0,0,1800,1500,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1800,0,3797,0,0,2699,0,0,0,0,0,0,3500,0,0,0,2000,0,1500,1000,2500,0,0,0,0,4800,3936,2500,3656,4500,0,0,0,4000,0,0,3400,0,0,0,0,3695,1394,0,3000,2000,0,0,0,2280,0,2279,0,0,1320,0,0,0,0,0,0,0,0,0,0,3671,3000,0,0,0,3200,0,0,0,2500,5000,0,5000,5000,5000,0,5000,2500,0,0,0,4800,0,0,0,3000,0,0,0,0,6500,0,0,5250,0,0,0,0,0,0,0,5000,0,470,4604,0,0,0,5000,0,0,7000,250,0,0,7500,3500,3000,5588,0,0,4540,0,0,0,5000,6000,3000,0,4808,0,0,0,5879,8484,500,5500,0,0,0,1000,0,0,7000,0,0,0,8498,10100,5000,0,0,2500,0,300,0,0,8728,6176,0,0,0,0,0,0,0,800,2500,8000,1400,0,0,0,0,0,0,0,0,4500,0,0,0,0,0,0,3500,0,5000,0,0,0,0,0,0,0,0,1000],"yaxis":"y","type":"scattergl"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"Built Before 1980 (1: Yes, 0: No)"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"Deduction from the selling price"}},"legend":{"tracegroupgap":0},"title":{"text":"Deduction from the selling price v. before1980"}},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('1a5c20ce-234e-4701-8288-91a60d6e4491');
+var gd = document.getElementById('9cf355a2-d61d-4eb6-80d4-5e460274372a');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -5004,7 +5004,7 @@ <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
 <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <p>Build a classification model labeling houses as being built “before 1980” or “during or after 1980”. Your goal is to reach or exceed 90% accuracy. Explain your final model choice (algorithm, tuning parameters, etc) and describe what other models you tried.</p>
 <p>I chose to use the RandomForestClassifier for my model. I used it becouse out of the twentey or so models I tried it had the highest accuracy, without overfiting. I also chhose to use a 30/70 for my perameter, this seemed to work the best and is very commonly recoginized a being genreally a good ratio in the inductry.</p>
-<div id="c2e1e21d" class="cell" data-execution_count="4">
+<div id="91fb8806" class="cell" data-execution_count="4">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
@@ -5073,7 +5073,7 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <span id="cb3-64"><a href="#cb3-64" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="st">&quot;Accuracy:&quot;</span>, accuracy)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-stdout">
-<pre><code>Accuracy: 0.9470468431771895</code></pre>
+<pre><code>Accuracy: 0.9502473086994472</code></pre>
 </div>
 </div>
 <p><strong>Summery/Findings</strong></p>
@@ -5094,7 +5094,7 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <li><p>abstrprd</p></li>
 <li><p>gartype_Att</p></li>
 </ol>
-<div id="2759c2f3" class="cell" data-execution_count="5">
+<div id="7a6fc59e" class="cell" data-execution_count="5">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="co">#%%</span></span>
@@ -5198,19 +5198,19 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <span id="cb5-99"><a href="#cb5-99" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(feature_importance_df.head())</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-stdout">
-<pre><code>Accuracy: 0.9282804771603143
+<pre><code>Accuracy: 0.9349723596159442
 Top 5 features:
                Feature  Importance
-0               parcel    0.265625
-38  arcstyle_ONE-STORY    0.239251
-23           quality_C    0.153528
-26         gartype_Att    0.062257
-1             abstrprd    0.060159</code></pre>
+0               parcel    0.268134
+38  arcstyle_ONE-STORY    0.233912
+23           quality_C    0.153616
+1             abstrprd    0.063377
+26         gartype_Att    0.057019</code></pre>
 </div>
 <div class="cell-output cell-output-display">
 <div>
 <figure class="figure">
-<p><img src="data:image/png;base64,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" width="1034" height="523" class="figure-img"></p>
+<p><img src="data:image/png;base64,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" width="1034" height="523" class="figure-img"></p>
 </figure>
 </div>
 </div>
diff --git a/Projects/project5.html b/Projects/project5.html
index e74574a..1b15c04 100644
--- a/Projects/project5.html
+++ b/Projects/project5.html
@@ -4896,7 +4896,7 @@ <h2 class="anchored" data-anchor-id="elevator-pitch">Elevator pitch</h2>
 <h2 class="anchored" data-anchor-id="questiontask-1">QUESTION|TASK 1</h2>
 <p>Shorten the column names and clean them up for easier use with pandas. Provide a table or list that exemplifies how you fixed the names.</p>
 <p>I cleaned the data so that it is much easier to understand and makes more seance. This included renaming all columns, convverting yeses to 1 and nos to 0 and many more little things to make it cleaner and earier for pandas.</p>
-<div id="3bab73c4" class="cell" data-execution_count="3">
+<div id="474e4b99" class="cell" data-execution_count="3">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="co">#%%</span></span>
@@ -5079,7 +5079,7 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <li>2.1 Filter the dataset to respondents that have seen at least one film.</li>
 </ul>
 <p>Completed</p>
-<div id="8ae8fa18" class="cell" data-execution_count="4">
+<div id="8f6a0215" class="cell" data-execution_count="4">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a>data <span class="op">=</span> data[data[<span class="st">&#39;Seen_any_SW&#39;</span>] <span class="op">!=</span> <span class="dv">0</span>]</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
@@ -5089,7 +5089,7 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <li>2.2 Create a new column that converts the age ranges to a single number. Drop the age range categorical column.</li>
 </ul>
 <p>Completed</p>
-<div id="6d40b0cc" class="cell" data-execution_count="5">
+<div id="90244672" class="cell" data-execution_count="5">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="co">#make into int-able</span></span>
@@ -5140,7 +5140,7 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <li>2.3 Create a new column that converts the education groupings to a single number. Drop the school categorical column</li>
 </ul>
 <p>Completed</p>
-<div id="04ae556f" class="cell" data-execution_count="6">
+<div id="3b6372ea" class="cell" data-execution_count="6">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb6"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a>edu_dic <span class="op">=</span> {</span>
@@ -5185,7 +5185,7 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <li>2.4 Create a new column that converts the income ranges to a single number. Drop the income range categorical column.</li>
 </ul>
 <p>Completed</p>
-<div id="56659f24" class="cell" data-execution_count="7">
+<div id="c892ac7b" class="cell" data-execution_count="7">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb7"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a>income_dic <span class="op">=</span> {</span>
@@ -5214,7 +5214,7 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <li>2.5 Create your target (also known as “y” or “label”) column based on the new income range column.</li>
 </ul>
 <p>Completed</p>
-<div id="ff1bc6b9" class="cell" data-execution_count="8">
+<div id="08727386" class="cell" data-execution_count="8">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb8"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
@@ -5243,7 +5243,7 @@ <h2 class="anchored" data-anchor-id="questiontask-2">QUESTION|TASK 2</h2>
 <span id="cb8-24"><a href="#cb8-24" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="st">&quot;Accuracy:&quot;</span>, accuracy)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-stdout">
-<pre><code>Accuracy: 0.29537366548042704</code></pre>
+<pre><code>Accuracy: 0.2597864768683274</code></pre>
 </div>
 </div>
 <ul>
@@ -5256,7 +5256,7 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <p>Validate that the data provided on GitHub lines up with the article by recreating 2 of the visuals from the article.</p>
 <p>The graphs I made is not exactly like the ones in the ardicle, but they are very close in looks and in the numbers, althought they are not perfect matches, they are very close, and the discresamcys are propbily due to slitly differant clean ‘styles’, and the software used to make the graphs.</p>
 <p>Graph 1</p>
-<div id="00731ab4" class="cell" data-execution_count="9">
+<div id="40b7dca1" class="cell" data-execution_count="9">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb10"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" aria-hidden="true" tabindex="-1"></a><span class="co">#%%</span></span>
@@ -5315,9 +5315,9 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <span id="cb10-54"><a href="#cb10-54" aria-hidden="true" tabindex="-1"></a>fig.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="a53d33b2-9638-4dc3-8307-91b86ca945c5" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("a53d33b2-9638-4dc3-8307-91b86ca945c5")) {                    Plotly.newPlot(                        "a53d33b2-9638-4dc3-8307-91b86ca945c5",                        [{"alignmentgroup":"True","hovertemplate":"Number of People Watched=%{x}\u003cbr\u003eEpisode=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"h","showlegend":false,"textposition":"auto","x":[739,759,608,551,572,674],"xaxis":"x","y":["Return of the Jedi","The Empire Strikes Back","A New Hope","Revenge of the Sith","Attack of the Clones","The Phantom Menace"],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{},"showgrid":false,"showticklabels":false},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{}},"legend":{"tracegroupgap":0},"title":{"text":"Which 'Star Wars' Movies Have You Seen?"},"barmode":"relative","annotations":[{"font":{"color":"black"},"showarrow":false,"text":"87.87%","x":739,"y":"Return of the Jedi"},{"font":{"color":"black"},"showarrow":false,"text":"90.00%","x":759,"y":"The Empire Strikes Back"},{"font":{"color":"black"},"showarrow":false,"text":"73.89%","x":608,"y":"A New Hope"},{"font":{"color":"black"},"showarrow":false,"text":"67.80%","x":551,"y":"Revenge of the Sith"},{"font":{"color":"black"},"showarrow":false,"text":"70.05%","x":572,"y":"Attack of the Clones"},{"font":{"color":"black"},"showarrow":false,"text":"80.93%","x":674,"y":"The Phantom Menace"}]},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="6b37caf8-438e-4f61-83ee-c026b362239b" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("6b37caf8-438e-4f61-83ee-c026b362239b")) {                    Plotly.newPlot(                        "6b37caf8-438e-4f61-83ee-c026b362239b",                        [{"alignmentgroup":"True","hovertemplate":"Number of People Watched=%{x}\u003cbr\u003eEpisode=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"h","showlegend":false,"textposition":"auto","x":[739,759,608,551,572,674],"xaxis":"x","y":["Return of the Jedi","The Empire Strikes Back","A New Hope","Revenge of the Sith","Attack of the Clones","The Phantom Menace"],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{},"showgrid":false,"showticklabels":false},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{}},"legend":{"tracegroupgap":0},"title":{"text":"Which 'Star Wars' Movies Have You Seen?"},"barmode":"relative","annotations":[{"font":{"color":"black"},"showarrow":false,"text":"87.87%","x":739,"y":"Return of the Jedi"},{"font":{"color":"black"},"showarrow":false,"text":"90.00%","x":759,"y":"The Empire Strikes Back"},{"font":{"color":"black"},"showarrow":false,"text":"73.89%","x":608,"y":"A New Hope"},{"font":{"color":"black"},"showarrow":false,"text":"67.80%","x":551,"y":"Revenge of the Sith"},{"font":{"color":"black"},"showarrow":false,"text":"70.05%","x":572,"y":"Attack of the Clones"},{"font":{"color":"black"},"showarrow":false,"text":"80.93%","x":674,"y":"The Phantom Menace"}]},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('a53d33b2-9638-4dc3-8307-91b86ca945c5');
+var gd = document.getElementById('6b37caf8-438e-4f61-83ee-c026b362239b');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -5343,7 +5343,7 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 </div>
 </div>
 <p>Graph 2</p>
-<div id="234dc334" class="cell" data-execution_count="10">
+<div id="d44ea2d3" class="cell" data-execution_count="10">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb11"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" aria-hidden="true" tabindex="-1"></a><span class="co">#%%</span></span>
@@ -5411,9 +5411,9 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <span id="cb11-63"><a href="#cb11-63" aria-hidden="true" tabindex="-1"></a>fig.show()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-display">
-<div>                            <div id="118afcef-9481-4665-aa66-470cfdd1a32f" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("118afcef-9481-4665-aa66-470cfdd1a32f")) {                    Plotly.newPlot(                        "118afcef-9481-4665-aa66-470cfdd1a32f",                        [{"alignmentgroup":"True","hovertemplate":"Number of People ranked it 1=%{x}\u003cbr\u003eEpisode=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"h","showlegend":false,"textposition":"auto","x":[82,169,128,27,18,47],"xaxis":"x","y":["Return of the Jedi","The Empire Strikes Back","A New Hope","Revenge of the Sith","Attack of the Clones","The Phantom Menace"],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{},"showgrid":false,"showticklabels":false},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{}},"legend":{"tracegroupgap":0},"title":{"text":"What's the Best 'Star Wars' Movie?"},"barmode":"relative","annotations":[{"font":{"color":"black"},"showarrow":false,"text":"17.37%","x":82,"y":"Return of the Jedi"},{"font":{"color":"black"},"showarrow":false,"text":"35.81%","x":169,"y":"The Empire Strikes Back"},{"font":{"color":"black"},"showarrow":false,"text":"27.12%","x":128,"y":"A New Hope"},{"font":{"color":"black"},"showarrow":false,"text":"5.72%","x":27,"y":"Revenge of the Sith"},{"font":{"color":"black"},"showarrow":false,"text":"3.81%","x":18,"y":"Attack of the Clones"},{"font":{"color":"black"},"showarrow":false,"text":"9.96%","x":47,"y":"The Phantom Menace"}]},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="c6cb05bf-c66f-4121-a25d-f4a7a6759417" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("c6cb05bf-c66f-4121-a25d-f4a7a6759417")) {                    Plotly.newPlot(                        "c6cb05bf-c66f-4121-a25d-f4a7a6759417",                        [{"alignmentgroup":"True","hovertemplate":"Number of People ranked it 1=%{x}\u003cbr\u003eEpisode=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"h","showlegend":false,"textposition":"auto","x":[82,169,128,27,18,47],"xaxis":"x","y":["Return of the Jedi","The Empire Strikes Back","A New Hope","Revenge of the Sith","Attack of the Clones","The Phantom Menace"],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{},"showgrid":false,"showticklabels":false},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{}},"legend":{"tracegroupgap":0},"title":{"text":"What's the Best 'Star Wars' Movie?"},"barmode":"relative","annotations":[{"font":{"color":"black"},"showarrow":false,"text":"17.37%","x":82,"y":"Return of the Jedi"},{"font":{"color":"black"},"showarrow":false,"text":"35.81%","x":169,"y":"The Empire Strikes Back"},{"font":{"color":"black"},"showarrow":false,"text":"27.12%","x":128,"y":"A New Hope"},{"font":{"color":"black"},"showarrow":false,"text":"5.72%","x":27,"y":"Revenge of the Sith"},{"font":{"color":"black"},"showarrow":false,"text":"3.81%","x":18,"y":"Attack of the Clones"},{"font":{"color":"black"},"showarrow":false,"text":"9.96%","x":47,"y":"The Phantom Menace"}]},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('118afcef-9481-4665-aa66-470cfdd1a32f');
+var gd = document.getElementById('c6cb05bf-c66f-4121-a25d-f4a7a6759417');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -5443,7 +5443,7 @@ <h2 class="anchored" data-anchor-id="questiontask-3">QUESTION|TASK 3</h2>
 <h2 class="anchored" data-anchor-id="questiontask-4">QUESTION|TASK 4</h2>
 <p>Build a machine learning model that predicts whether a person makes more than $50k. Describe your model and report the accuracy.</p>
 <p>I tried like 20 differant classifers, however the highest Accuracy I ever got was abouut 28%. I ended up useing the MLPClassifier classifier. This probibly means that the corralation isn’t very high between these facts about liking, watching etc. about starwars and our income. It is also posible the the data set isn’t big enough, but I kind of doubt it.</p>
-<div id="2c8b548e" class="cell" data-execution_count="11">
+<div id="09f17d7b" class="cell" data-execution_count="11">
 <details class="code-fold">
 <summary>Show the code</summary>
 <div class="sourceCode cell-code" id="cb12"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb12-1"><a href="#cb12-1" aria-hidden="true" tabindex="-1"></a><span class="co">#%%</span></span>
@@ -5498,7 +5498,7 @@ <h2 class="anchored" data-anchor-id="questiontask-4">QUESTION|TASK 4</h2>
 <span id="cb12-50"><a href="#cb12-50" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="st">&quot;Accuracy:&quot;</span>, accuracy)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </details>
 <div class="cell-output cell-output-stdout">
-<pre><code>Accuracy: 0.2704626334519573</code></pre>
+<pre><code>Accuracy: 0.11743772241992882</code></pre>
 </div>
 </div>
 
diff --git a/Templates/DS250_Template.html b/Templates/DS250_Template.html
index b0e131e..8e59296 100644
--- a/Templates/DS250_Template.html
+++ b/Templates/DS250_Template.html
@@ -4815,9 +4815,9 @@ <h3 class="anchored" data-anchor-id="uncomment-the-entire-section-to-use-this-te
 ::: {#q1-chart .cell-output .cell-output-display}
 
 ```{=html}
-<div>                            <div id="ce2b7bd2-d480-4873-83bb-46769067456d" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("ce2b7bd2-d480-4873-83bb-46769067456d")) {                    Plotly.newPlot(                        "ce2b7bd2-d480-4873-83bb-46769067456d",                        [{"alignmentgroup":"True","hovertemplate":"name=%{x}\u003cbr\u003eAK=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"v","showlegend":false,"textposition":"auto","x":["Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron"],"xaxis":"x","y":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,5.0,7.0,10.0,10.0,9.0,7.0,14.0,10.0,13.0,8.0,12.0,12.0,11.0,12.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,6.0,6.0,9.0,8.0,17.0,26.0,37.0,23.0,33.0,42.0,41.0,35.0,53.0,54.0,52.0,55.0,59.0,54.0,54.0,62.0,61.0,58.0,60.0,44.0,56.0,57.0,55.0,35.0,42.0,30.0,35.0,33.0,29.0,24.0,25.0,22.0,29.0,22.0,10.0],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"name"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"AK"}},"legend":{"tracegroupgap":0},"barmode":"relative"},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="8d138ef4-7da0-459a-bf52-a5bcea2c51e5" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("8d138ef4-7da0-459a-bf52-a5bcea2c51e5")) {                    Plotly.newPlot(                        "8d138ef4-7da0-459a-bf52-a5bcea2c51e5",                        [{"alignmentgroup":"True","hovertemplate":"name=%{x}\u003cbr\u003eAK=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"v","showlegend":false,"textposition":"auto","x":["Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron"],"xaxis":"x","y":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,5.0,7.0,10.0,10.0,9.0,7.0,14.0,10.0,13.0,8.0,12.0,12.0,11.0,12.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,6.0,6.0,9.0,8.0,17.0,26.0,37.0,23.0,33.0,42.0,41.0,35.0,53.0,54.0,52.0,55.0,59.0,54.0,54.0,62.0,61.0,58.0,60.0,44.0,56.0,57.0,55.0,35.0,42.0,30.0,35.0,33.0,29.0,24.0,25.0,22.0,29.0,22.0,10.0],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"name"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"AK"}},"legend":{"tracegroupgap":0},"barmode":"relative"},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('ce2b7bd2-d480-4873-83bb-46769067456d');
+var gd = document.getElementById('8d138ef4-7da0-459a-bf52-a5bcea2c51e5');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -4954,12 +4954,12 @@ <h3 class="anchored" data-anchor-id="uncomment-the-entire-section-to-use-this-te
 </div>
 ``` ::: ::: ## QUESTION|TASK 2 __COPY PASTE QUESTION|TASK 2 FROM THE PROJECT HERE__ _type your results and analysis here_ ::: {#q2 .cell execution_count=6} ``` {.python .cell-code code-summary="Read and format data"} # Include and execute your code here ``` ::: _include figures in chunks and discuss your findings in the figure._ ::: {#cell-Q2 chart .cell execution_count=7} ``` {.python .cell-code code-summary="plot example"} # Include and execute your code here chart = px.bar(df.head(200), x="name", y="AK" ) chart.show() ``` ::: {#q2-chart .cell-output .cell-output-display} ```{=html}
 <div>
-<div id="8629af02-1837-4570-a202-4a2d17d99f89" class="plotly-graph-div" style="height:525px; width:100%;">
+<div id="f9e2f97e-1e2f-4578-aeb2-6e40ee84a6ce" class="plotly-graph-div" style="height:525px; width:100%;">
 
 </div>
-<script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("8629af02-1837-4570-a202-4a2d17d99f89")) {                    Plotly.newPlot(                        "8629af02-1837-4570-a202-4a2d17d99f89",                        [{"alignmentgroup":"True","hovertemplate":"name=%{x}\u003cbr\u003eAK=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"v","showlegend":false,"textposition":"auto","x":["Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron"],"xaxis":"x","y":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,5.0,7.0,10.0,10.0,9.0,7.0,14.0,10.0,13.0,8.0,12.0,12.0,11.0,12.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,6.0,6.0,9.0,8.0,17.0,26.0,37.0,23.0,33.0,42.0,41.0,35.0,53.0,54.0,52.0,55.0,59.0,54.0,54.0,62.0,61.0,58.0,60.0,44.0,56.0,57.0,55.0,35.0,42.0,30.0,35.0,33.0,29.0,24.0,25.0,22.0,29.0,22.0,10.0],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"name"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"AK"}},"legend":{"tracegroupgap":0},"barmode":"relative"},                        {"responsive": true}                    ).then(function(){
+<script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("f9e2f97e-1e2f-4578-aeb2-6e40ee84a6ce")) {                    Plotly.newPlot(                        "f9e2f97e-1e2f-4578-aeb2-6e40ee84a6ce",                        [{"alignmentgroup":"True","hovertemplate":"name=%{x}\u003cbr\u003eAK=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"v","showlegend":false,"textposition":"auto","x":["Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron"],"xaxis":"x","y":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,5.0,7.0,10.0,10.0,9.0,7.0,14.0,10.0,13.0,8.0,12.0,12.0,11.0,12.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,6.0,6.0,9.0,8.0,17.0,26.0,37.0,23.0,33.0,42.0,41.0,35.0,53.0,54.0,52.0,55.0,59.0,54.0,54.0,62.0,61.0,58.0,60.0,44.0,56.0,57.0,55.0,35.0,42.0,30.0,35.0,33.0,29.0,24.0,25.0,22.0,29.0,22.0,10.0],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"name"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"AK"}},"legend":{"tracegroupgap":0},"barmode":"relative"},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('8629af02-1837-4570-a202-4a2d17d99f89');
+var gd = document.getElementById('f9e2f97e-1e2f-4578-aeb2-6e40ee84a6ce');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
@@ -5108,9 +5108,9 @@ <h3 class="anchored" data-anchor-id="uncomment-the-entire-section-to-use-this-te
 ::: {#q3-chart .cell-output .cell-output-display}
 
 ```{=html}
-<div>                            <div id="1a114db1-3a5d-41df-b297-bf0b43db6acf" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("1a114db1-3a5d-41df-b297-bf0b43db6acf")) {                    Plotly.newPlot(                        "1a114db1-3a5d-41df-b297-bf0b43db6acf",                        [{"alignmentgroup":"True","hovertemplate":"name=%{x}\u003cbr\u003eAK=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"v","showlegend":false,"textposition":"auto","x":["Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron"],"xaxis":"x","y":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,5.0,7.0,10.0,10.0,9.0,7.0,14.0,10.0,13.0,8.0,12.0,12.0,11.0,12.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,6.0,6.0,9.0,8.0,17.0,26.0,37.0,23.0,33.0,42.0,41.0,35.0,53.0,54.0,52.0,55.0,59.0,54.0,54.0,62.0,61.0,58.0,60.0,44.0,56.0,57.0,55.0,35.0,42.0,30.0,35.0,33.0,29.0,24.0,25.0,22.0,29.0,22.0,10.0],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"name"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"AK"}},"legend":{"tracegroupgap":0},"barmode":"relative"},                        {"responsive": true}                    ).then(function(){
+<div>                            <div id="be8a2112-6158-4aed-9e21-4ec9382d17e9" class="plotly-graph-div" style="height:525px; width:100%;"></div>            <script type="text/javascript">                require(["plotly"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById("be8a2112-6158-4aed-9e21-4ec9382d17e9")) {                    Plotly.newPlot(                        "be8a2112-6158-4aed-9e21-4ec9382d17e9",                        [{"alignmentgroup":"True","hovertemplate":"name=%{x}\u003cbr\u003eAK=%{y}\u003cextra\u003e\u003c\u002fextra\u003e","legendgroup":"","marker":{"color":"#636efa","pattern":{"shape":""}},"name":"","offsetgroup":"","orientation":"v","showlegend":false,"textposition":"auto","x":["Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aaden","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aadhya","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aaliyah","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aamir","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aanya","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarav","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aarna","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron","Aaron"],"xaxis":"x","y":[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,5.0,0.0,5.0,7.0,10.0,10.0,9.0,7.0,14.0,10.0,13.0,8.0,12.0,12.0,11.0,12.0,10.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,6.0,0.0,0.0,5.0,7.0,0.0,0.0,0.0,0.0,6.0,6.0,9.0,8.0,17.0,26.0,37.0,23.0,33.0,42.0,41.0,35.0,53.0,54.0,52.0,55.0,59.0,54.0,54.0,62.0,61.0,58.0,60.0,44.0,56.0,57.0,55.0,35.0,42.0,30.0,35.0,33.0,29.0,24.0,25.0,22.0,29.0,22.0,10.0],"yaxis":"y","type":"bar"}],                        {"template":{"data":{"histogram2dcontour":[{"type":"histogram2dcontour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"choropleth":[{"type":"choropleth","colorbar":{"outlinewidth":0,"ticks":""}}],"histogram2d":[{"type":"histogram2d","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmap":[{"type":"heatmap","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"heatmapgl":[{"type":"heatmapgl","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"contourcarpet":[{"type":"contourcarpet","colorbar":{"outlinewidth":0,"ticks":""}}],"contour":[{"type":"contour","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"surface":[{"type":"surface","colorbar":{"outlinewidth":0,"ticks":""},"colorscale":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]]}],"mesh3d":[{"type":"mesh3d","colorbar":{"outlinewidth":0,"ticks":""}}],"scatter":[{"fillpattern":{"fillmode":"overlay","size":10,"solidity":0.2},"type":"scatter"}],"parcoords":[{"type":"parcoords","line":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolargl":[{"type":"scatterpolargl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"bar":[{"error_x":{"color":"#2a3f5f"},"error_y":{"color":"#2a3f5f"},"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"bar"}],"scattergeo":[{"type":"scattergeo","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterpolar":[{"type":"scatterpolar","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"histogram":[{"marker":{"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"histogram"}],"scattergl":[{"type":"scattergl","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatter3d":[{"type":"scatter3d","line":{"colorbar":{"outlinewidth":0,"ticks":""}},"marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattermapbox":[{"type":"scattermapbox","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scatterternary":[{"type":"scatterternary","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"scattercarpet":[{"type":"scattercarpet","marker":{"colorbar":{"outlinewidth":0,"ticks":""}}}],"carpet":[{"aaxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"baxis":{"endlinecolor":"#2a3f5f","gridcolor":"white","linecolor":"white","minorgridcolor":"white","startlinecolor":"#2a3f5f"},"type":"carpet"}],"table":[{"cells":{"fill":{"color":"#EBF0F8"},"line":{"color":"white"}},"header":{"fill":{"color":"#C8D4E3"},"line":{"color":"white"}},"type":"table"}],"barpolar":[{"marker":{"line":{"color":"#E5ECF6","width":0.5},"pattern":{"fillmode":"overlay","size":10,"solidity":0.2}},"type":"barpolar"}],"pie":[{"automargin":true,"type":"pie"}]},"layout":{"autotypenumbers":"strict","colorway":["#636efa","#EF553B","#00cc96","#ab63fa","#FFA15A","#19d3f3","#FF6692","#B6E880","#FF97FF","#FECB52"],"font":{"color":"#2a3f5f"},"hovermode":"closest","hoverlabel":{"align":"left"},"paper_bgcolor":"white","plot_bgcolor":"#E5ECF6","polar":{"bgcolor":"#E5ECF6","angularaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"radialaxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"ternary":{"bgcolor":"#E5ECF6","aaxis":{"gridcolor":"white","linecolor":"white","ticks":""},"baxis":{"gridcolor":"white","linecolor":"white","ticks":""},"caxis":{"gridcolor":"white","linecolor":"white","ticks":""}},"coloraxis":{"colorbar":{"outlinewidth":0,"ticks":""}},"colorscale":{"sequential":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"sequentialminus":[[0.0,"#0d0887"],[0.1111111111111111,"#46039f"],[0.2222222222222222,"#7201a8"],[0.3333333333333333,"#9c179e"],[0.4444444444444444,"#bd3786"],[0.5555555555555556,"#d8576b"],[0.6666666666666666,"#ed7953"],[0.7777777777777778,"#fb9f3a"],[0.8888888888888888,"#fdca26"],[1.0,"#f0f921"]],"diverging":[[0,"#8e0152"],[0.1,"#c51b7d"],[0.2,"#de77ae"],[0.3,"#f1b6da"],[0.4,"#fde0ef"],[0.5,"#f7f7f7"],[0.6,"#e6f5d0"],[0.7,"#b8e186"],[0.8,"#7fbc41"],[0.9,"#4d9221"],[1,"#276419"]]},"xaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"yaxis":{"gridcolor":"white","linecolor":"white","ticks":"","title":{"standoff":15},"zerolinecolor":"white","automargin":true,"zerolinewidth":2},"scene":{"xaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"yaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2},"zaxis":{"backgroundcolor":"#E5ECF6","gridcolor":"white","linecolor":"white","showbackground":true,"ticks":"","zerolinecolor":"white","gridwidth":2}},"shapedefaults":{"line":{"color":"#2a3f5f"}},"annotationdefaults":{"arrowcolor":"#2a3f5f","arrowhead":0,"arrowwidth":1},"geo":{"bgcolor":"white","landcolor":"#E5ECF6","subunitcolor":"white","showland":true,"showlakes":true,"lakecolor":"white"},"title":{"x":0.05},"mapbox":{"style":"light"},"margin":{"b":0,"l":0,"r":0,"t":30}}},"xaxis":{"anchor":"y","domain":[0.0,1.0],"title":{"text":"name"}},"yaxis":{"anchor":"x","domain":[0.0,1.0],"title":{"text":"AK"}},"legend":{"tracegroupgap":0},"barmode":"relative"},                        {"responsive": true}                    ).then(function(){
                             
-var gd = document.getElementById('1a114db1-3a5d-41df-b297-bf0b43db6acf');
+var gd = document.getElementById('be8a2112-6158-4aed-9e21-4ec9382d17e9');
 var x = new MutationObserver(function (mutations, observer) {{
         var display = window.getComputedStyle(gd).display;
         if (!display || display === 'none') {{
diff --git a/search.json b/search.json
index bf3448c..d900762 100644
--- a/search.json
+++ b/search.json
@@ -271,7 +271,7 @@
     "href": "Projects/project4.html#questiontask-2",
     "title": "Project 4: Can you predict that?",
     "section": "QUESTION|TASK 2",
-    "text": "QUESTION|TASK 2\nBuild a classification model labeling houses as being built “before 1980” or “during or after 1980”. Your goal is to reach or exceed 90% accuracy. Explain your final model choice (algorithm, tuning parameters, etc) and describe what other models you tried.\nI chose to use the RandomForestClassifier for my model. I used it becouse out of the twentey or so models I tried it had the highest accuracy, without overfiting. I also chhose to use a 30/70 for my perameter, this seemed to work the best and is very commonly recoginized a being genreally a good ratio in the inductry.\n\n\nShow the code\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.linear_model import LogisticRegression\n\nfrom sklearn import metrics\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.ensemble import RandomForestRegressor\n\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.tree import DecisionTreeRegressor\n\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\n\n\n# Remove year built, and before 1980 from data to be trained.\n\n# number bedrooms and number of bathrooms\n\n# corr()\n# df = df.drop('parcel', axis = 1)\n# \n\n\n\n# Read the CSV file into a DataFrame\ndf = pd.read_csv('dwellings_ml.csv')\n\n\n# Remove the '-' characters from the 'parcel' column\ndf['parcel'] = df['parcel'].str.replace('-', '')\n\n\n# Convert the 'parcel' column to integer\ndf['parcel'] = df['parcel'].astype(int)\n\ndf = df.drop('yrbuilt', axis = 1)\n\ndf.columns\n\n# Define features and target\nfeatures = df.drop('before1980', axis=1)  # Drop the target column\ntarget = df['before1980']\n\n# Split data into training and testing sets\ntrain_data, test_data, train_targets, test_targets = train_test_split(features, target, test_size = .3)\n                                                                      \n\n# Instantiate Gaussian Naive Bayes classifier\nclassifier = RandomForestClassifier()\n# classifier = DecisionTreeClassifier()\n# classifier = GradientBoostingClassifier()\n# classifier = tree(max_depth=10, n_estimators=500)\n\n# Train the classifier\nclassifier.fit(train_data, train_targets)\n\n# Predict using the trained classifier\ntargets_predicted = classifier.predict(test_data)\n\n# Calculate accuracy\naccuracy = metrics.accuracy_score(test_targets, targets_predicted)\nprint(\"Accuracy:\", accuracy)\n\n\nAccuracy: 0.9470468431771895\n\n\nSummery/Findings\n\nthis model is 93-95% accurate\nIt uses the GradientBoostingClassifier formula\nIt seporates it 30%-70% training and checking",
+    "text": "QUESTION|TASK 2\nBuild a classification model labeling houses as being built “before 1980” or “during or after 1980”. Your goal is to reach or exceed 90% accuracy. Explain your final model choice (algorithm, tuning parameters, etc) and describe what other models you tried.\nI chose to use the RandomForestClassifier for my model. I used it becouse out of the twentey or so models I tried it had the highest accuracy, without overfiting. I also chhose to use a 30/70 for my perameter, this seemed to work the best and is very commonly recoginized a being genreally a good ratio in the inductry.\n\n\nShow the code\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.linear_model import LogisticRegression\n\nfrom sklearn import metrics\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.ensemble import RandomForestRegressor\n\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.tree import DecisionTreeRegressor\n\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\n\n\n# Remove year built, and before 1980 from data to be trained.\n\n# number bedrooms and number of bathrooms\n\n# corr()\n# df = df.drop('parcel', axis = 1)\n# \n\n\n\n# Read the CSV file into a DataFrame\ndf = pd.read_csv('dwellings_ml.csv')\n\n\n# Remove the '-' characters from the 'parcel' column\ndf['parcel'] = df['parcel'].str.replace('-', '')\n\n\n# Convert the 'parcel' column to integer\ndf['parcel'] = df['parcel'].astype(int)\n\ndf = df.drop('yrbuilt', axis = 1)\n\ndf.columns\n\n# Define features and target\nfeatures = df.drop('before1980', axis=1)  # Drop the target column\ntarget = df['before1980']\n\n# Split data into training and testing sets\ntrain_data, test_data, train_targets, test_targets = train_test_split(features, target, test_size = .3)\n                                                                      \n\n# Instantiate Gaussian Naive Bayes classifier\nclassifier = RandomForestClassifier()\n# classifier = DecisionTreeClassifier()\n# classifier = GradientBoostingClassifier()\n# classifier = tree(max_depth=10, n_estimators=500)\n\n# Train the classifier\nclassifier.fit(train_data, train_targets)\n\n# Predict using the trained classifier\ntargets_predicted = classifier.predict(test_data)\n\n# Calculate accuracy\naccuracy = metrics.accuracy_score(test_targets, targets_predicted)\nprint(\"Accuracy:\", accuracy)\n\n\nAccuracy: 0.9502473086994472\n\n\nSummery/Findings\n\nthis model is 93-95% accurate\nIt uses the GradientBoostingClassifier formula\nIt seporates it 30%-70% training and checking",
     "crumbs": [
       "DS250 Projects",
       "Project 4"
@@ -282,7 +282,7 @@
     "href": "Projects/project4.html#questiontask-3",
     "title": "Project 4: Can you predict that?",
     "section": "QUESTION|TASK 3",
-    "text": "QUESTION|TASK 3\nJustify your classification model by discussing the most important features selected by your model. This discussion should include a chart and a description of the features.\nAcording to my caculations the top five features are as follows:\n\nParcel\narcstyle_TWO-STORY\nquality_C\nabstrprd\ngartype_Att\n\n\n\nShow the code\n#%%\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.linear_model import LogisticRegression\n\nfrom sklearn import metrics\nfrom sklearn.tree import DecisionTreeClassifier\n\nfrom sklearn.tree import DecisionTreeRegressor\n\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\n\n#%%\n# Remove year built, and before 1980 from data to be trained.\n\n# number bedrooms and number of bathrooms\n\n# corr()\n# df = df.drop('parcel', axis = 1)\n# \n\n\n#%%\n# Read the CSV file into a DataFrame\ndf = pd.read_csv('dwellings_ml.csv')\n\n#%%\n# Remove the '-' characters from the 'parcel' column\ndf['parcel'] = df['parcel'].str.replace('-', '')\n\n#%%\n# Convert the 'parcel' column to integer\ndf['parcel'] = df['parcel'].astype(int)\n\n\n\n#%%\n\ndf = df.drop('yrbuilt', axis = 1)\n\ndf.columns\n\n#%%\n# Define features and target\nfeatures = df.drop('before1980', axis=1)  # Drop the target column\ntarget = df['before1980']\n\n# Split data into training and testing sets\ntrain_data, test_data, train_targets, test_targets = train_test_split(features, target, test_size = .3)\n                                                                      \n\n# Instantiate Gaussian Naive Bayes classifier\nclassifier = GradientBoostingClassifier()\n# classifier = tree(max_depth=10, n_estimators=500)\n\n# Train the classifier\nclassifier.fit(train_data, train_targets)\n\n# Predict using the trained classifier\ntargets_predicted = classifier.predict(test_data)\n\n# Calculate accuracy\naccuracy = metrics.accuracy_score(test_targets, targets_predicted)\nprint(\"Accuracy:\", accuracy)\n\n\n\n#%%\n\nimport matplotlib.pyplot as plt\n\n# Get feature importances\nfeature_importances = classifier.feature_importances_\n\n# Get the names of the features\nfeature_names = features.columns\n\n# Create a DataFrame to hold feature names and their importances\nfeature_importance_df = pd.DataFrame({\n    'Feature': feature_names,\n    'Importance': feature_importances\n})\n\n# Sort the DataFrame by importance\nfeature_importance_df = feature_importance_df.sort_values(by='Importance', ascending=False)\n\n# Plotting the feature importance\nplt.figure(figsize=(10, 6))\nplt.barh(feature_importance_df['Feature'], feature_importance_df['Importance'])\nplt.xlabel('Importance')\nplt.ylabel('Feature')\nplt.title('Feature Importance')\nplt.show()\n\n# Display top 5 features\nprint(\"Top 5 features:\")\nprint(feature_importance_df.head())\n\n\nAccuracy: 0.9282804771603143\nTop 5 features:\n               Feature  Importance\n0               parcel    0.265625\n38  arcstyle_ONE-STORY    0.239251\n23           quality_C    0.153528\n26         gartype_Att    0.062257\n1             abstrprd    0.060159",
+    "text": "QUESTION|TASK 3\nJustify your classification model by discussing the most important features selected by your model. This discussion should include a chart and a description of the features.\nAcording to my caculations the top five features are as follows:\n\nParcel\narcstyle_TWO-STORY\nquality_C\nabstrprd\ngartype_Att\n\n\n\nShow the code\n#%%\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.linear_model import LogisticRegression\n\nfrom sklearn import metrics\nfrom sklearn.tree import DecisionTreeClassifier\n\nfrom sklearn.tree import DecisionTreeRegressor\n\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\n\n#%%\n# Remove year built, and before 1980 from data to be trained.\n\n# number bedrooms and number of bathrooms\n\n# corr()\n# df = df.drop('parcel', axis = 1)\n# \n\n\n#%%\n# Read the CSV file into a DataFrame\ndf = pd.read_csv('dwellings_ml.csv')\n\n#%%\n# Remove the '-' characters from the 'parcel' column\ndf['parcel'] = df['parcel'].str.replace('-', '')\n\n#%%\n# Convert the 'parcel' column to integer\ndf['parcel'] = df['parcel'].astype(int)\n\n\n\n#%%\n\ndf = df.drop('yrbuilt', axis = 1)\n\ndf.columns\n\n#%%\n# Define features and target\nfeatures = df.drop('before1980', axis=1)  # Drop the target column\ntarget = df['before1980']\n\n# Split data into training and testing sets\ntrain_data, test_data, train_targets, test_targets = train_test_split(features, target, test_size = .3)\n                                                                      \n\n# Instantiate Gaussian Naive Bayes classifier\nclassifier = GradientBoostingClassifier()\n# classifier = tree(max_depth=10, n_estimators=500)\n\n# Train the classifier\nclassifier.fit(train_data, train_targets)\n\n# Predict using the trained classifier\ntargets_predicted = classifier.predict(test_data)\n\n# Calculate accuracy\naccuracy = metrics.accuracy_score(test_targets, targets_predicted)\nprint(\"Accuracy:\", accuracy)\n\n\n\n#%%\n\nimport matplotlib.pyplot as plt\n\n# Get feature importances\nfeature_importances = classifier.feature_importances_\n\n# Get the names of the features\nfeature_names = features.columns\n\n# Create a DataFrame to hold feature names and their importances\nfeature_importance_df = pd.DataFrame({\n    'Feature': feature_names,\n    'Importance': feature_importances\n})\n\n# Sort the DataFrame by importance\nfeature_importance_df = feature_importance_df.sort_values(by='Importance', ascending=False)\n\n# Plotting the feature importance\nplt.figure(figsize=(10, 6))\nplt.barh(feature_importance_df['Feature'], feature_importance_df['Importance'])\nplt.xlabel('Importance')\nplt.ylabel('Feature')\nplt.title('Feature Importance')\nplt.show()\n\n# Display top 5 features\nprint(\"Top 5 features:\")\nprint(feature_importance_df.head())\n\n\nAccuracy: 0.9349723596159442\nTop 5 features:\n               Feature  Importance\n0               parcel    0.268134\n38  arcstyle_ONE-STORY    0.233912\n23           quality_C    0.153616\n1             abstrprd    0.063377\n26         gartype_Att    0.057019",
     "crumbs": [
       "DS250 Projects",
       "Project 4"
@@ -302,9 +302,53 @@
   {
     "objectID": "Projects/project3.html",
     "href": "Projects/project3.html",
-    "title": "Client Report - [Insert Project Title]",
+    "title": "Finding Relationships in Baseball - Project 3",
+    "section": "",
+    "text": "Overall this data shows that you have to be careful with averages because if one person did one thing once and succeeded then they will have a perfect average, but that does not mean that they are the best. This data also shows that teams/players that are good usually stay good and that teams/players that are bad usually stay bad. Overall I think this data is a warning to know our data set and which values you don’t want to include because it will just mess with the averages, and how if you don’t have enough information on a player, team, etc you really shouldn’t make averages with thoughts numbers until you have enough data for it too be meaningful.\n\n\nRead and format project data\n# Include and execute your code here\nimport sqlite3\n\n# Path to your SQLite database file\ndb_file = \"https://byuistats.github.io/DS250-Course/Data/lahmansbaseballdb.sqlite\"",
+    "crumbs": [
+      "DS250 Projects",
+      "Project 3"
+    ]
+  },
+  {
+    "objectID": "Projects/project3.html#elevator-pitch",
+    "href": "Projects/project3.html#elevator-pitch",
+    "title": "Finding Relationships in Baseball - Project 3",
     "section": "",
-    "text": "Paste in a template\n\n\n\n\n Back to top",
+    "text": "Overall this data shows that you have to be careful with averages because if one person did one thing once and succeeded then they will have a perfect average, but that does not mean that they are the best. This data also shows that teams/players that are good usually stay good and that teams/players that are bad usually stay bad. Overall I think this data is a warning to know our data set and which values you don’t want to include because it will just mess with the averages, and how if you don’t have enough information on a player, team, etc you really shouldn’t make averages with thoughts numbers until you have enough data for it too be meaningful.\n\n\nRead and format project data\n# Include and execute your code here\nimport sqlite3\n\n# Path to your SQLite database file\ndb_file = \"https://byuistats.github.io/DS250-Course/Data/lahmansbaseballdb.sqlite\"",
+    "crumbs": [
+      "DS250 Projects",
+      "Project 3"
+    ]
+  },
+  {
+    "objectID": "Projects/project3.html#questiontask-1",
+    "href": "Projects/project3.html#questiontask-1",
+    "title": "Finding Relationships in Baseball - Project 3",
+    "section": "QUESTION|TASK 1",
+    "text": "QUESTION|TASK 1\nWrite an SQL query to create a new dataframe about baseball players who attended BYU-Idaho. The new table should contain five columns: playerID, schoolID, salary, and the yearID/teamID associated with each salary. Order the table by salary (highest to lowest) and print out the table in your report.\n\n\nShow the code\n# Connect to the SQLite database\nfile = 'lahmansbaseballdb.sqlite'\ncon = sqlite3.connect(file)\n\n# Execute the SQL query and store the results in a DataFrame\nquery = \"\"\"\nSELECT \n    s.playerID,\n    sl.schoolID,\n    s.salary,\n    s.yearID || '/' || s.teamID AS year_team\nFROM \n    schools sl\nJOIN\n    collegeplaying cp ON cp.schoolID = sl.schoolID\nJOIN\n    salaries s ON s.playerID = cp.playerID\nWHERE \n    sl.schoolID = 'idbyuid'\nORDER BY \n    s.salary DESC;\n\"\"\"\ndf = pd.read_sql_query(query, con)\n\n# Set display options to show all rows and columns\npd.set_option('display.max_rows', None)\npd.set_option('display.max_columns', None)\n\n# Print the DataFrame\nprint(\"DataFrame with the data:\")\nprint(df)\n\n\nDataFrame with the data:\n     playerID schoolID     salary year_team\n0   lindsma01  idbyuid  4000000.0  2014/CHA\n1   lindsma01  idbyuid  4000000.0  2014/CHA\n2   lindsma01  idbyuid  3600000.0  2012/BAL\n3   lindsma01  idbyuid  3600000.0  2012/BAL\n4   lindsma01  idbyuid  2800000.0  2011/COL\n5   lindsma01  idbyuid  2800000.0  2011/COL\n6   lindsma01  idbyuid  2300000.0  2013/CHA\n7   lindsma01  idbyuid  2300000.0  2013/CHA\n8   lindsma01  idbyuid  1625000.0  2010/HOU\n9   lindsma01  idbyuid  1625000.0  2010/HOU\n10  stephga01  idbyuid  1025000.0  2001/SLN\n11  stephga01  idbyuid  1025000.0  2001/SLN\n12  stephga01  idbyuid   900000.0  2002/SLN\n13  stephga01  idbyuid   900000.0  2002/SLN\n14  stephga01  idbyuid   800000.0  2003/SLN\n15  stephga01  idbyuid   800000.0  2003/SLN\n16  stephga01  idbyuid   550000.0  2000/SLN\n17  stephga01  idbyuid   550000.0  2000/SLN\n18  lindsma01  idbyuid   410000.0  2009/FLO\n19  lindsma01  idbyuid   410000.0  2009/FLO\n20  lindsma01  idbyuid   395000.0  2008/FLO\n21  lindsma01  idbyuid   395000.0  2008/FLO\n22  lindsma01  idbyuid   380000.0  2007/FLO\n23  lindsma01  idbyuid   380000.0  2007/FLO\n24  stephga01  idbyuid   215000.0  1999/SLN\n25  stephga01  idbyuid   215000.0  1999/SLN\n26  stephga01  idbyuid   185000.0  1998/PHI\n27  stephga01  idbyuid   185000.0  1998/PHI\n28  stephga01  idbyuid   150000.0  1997/PHI\n29  stephga01  idbyuid   150000.0  1997/PHI\n\n\nSummary/Findings\n\nThere are only 2 people in this database who have played for BYU-Idaho baseball.\nThe most money made by either was $4,000,000.00\nThe least amount made by either player was $150,000.00",
+    "crumbs": [
+      "DS250 Projects",
+      "Project 3"
+    ]
+  },
+  {
+    "objectID": "Projects/project3.html#questiontask-2",
+    "href": "Projects/project3.html#questiontask-2",
+    "title": "Finding Relationships in Baseball - Project 3",
+    "section": "QUESTION|TASK 2",
+    "text": "QUESTION|TASK 2\nThis three-part question requires you to calculate batting average (number of hits divided by the number of at-bats)\nQUESTION|TASK 2.1\nWrite an SQL query that provides playerID, yearID, and batting average for players with at least 1 at bat that year. Sort the table from highest batting average to lowest, and then by playerid alphabetically. Show the top 5 results in your report.\n\n\nShow the code\n# Connect to the SQLite database\nfile = 'lahmansbaseballdb.sqlite'\ncon = sqlite3.connect(file)\n\n# Execute the SQL query and store the results in a DataFrame\nquery = \"\"\"\nSELECT\n    playerID,\n    yearID,\n    CAST(H AS REAL) / AB AS batting_average\nFROM\n    Batting\nWHERE\n    AB &gt; 0\nORDER BY\n    batting_average DESC,\n    playerID DESC\nLIMIT 5;\n\"\"\"\n\n\ndf = pd.read_sql_query(query, con)\n# Show the data\nprint(df)\n\n\n    playerID  yearID  batting_average\n0  zearfda01    1898              1.0\n1  zannido01    1966              1.0\n2  yantzge01    1912              1.0\n3    yanes01    2000              1.0\n4    yanes01    2003              1.0\n\n\nSummary/Findings\n\nEveryone in the top 5 had a 100% average, which means that they probably didn’t bat much.\nThe years don’t seem to show a pattern, at least for the top 5 shown.\n\nQUESTION|TASK 2.2\nUse the same query as above, but only include players with at least 10 at bats that year. Print the top 5 results.\n\n\nShow the code\n# Connect to the SQLite database\nfile = 'lahmansbaseballdb.sqlite'\ncon = sqlite3.connect(file)\n\n# Execute the SQL query and store the results in a DataFrame\nquery = \"\"\"\nSELECT\n    playerID,\n    yearID,\n    CAST(H AS REAL) / AB AS batting_average\nFROM\n    Batting\nWHERE\n    AB &gt; 9\nORDER BY\n    batting_average DESC,\n    playerID ASC\nLIMIT 5;\n\"\"\"\n\n\ndf = pd.read_sql_query(query, con)\n# Show the data\nprint(df)\n\n\n    playerID  yearID  batting_average\n0  nymanny01    1974         0.642857\n1  carsoma01    2013         0.636364\n2  altizda01    1910         0.600000\n3  johnsde01    1975         0.600000\n4  silvech01    1948         0.571429\n\n\nSummary/Findings\n\nThe batting averages dropped substantially went you exclude the people that have batted less than 10 times that year.\nAll of the top averages are around 60%.\nAgain the years don’t show a clear pattern with the data shown.\n\nQUESTION|TASK 2.3\nNow calculate the batting average for players over their entire careers (all years combined). Only include players with at least 100 at bats, and print the top 5 results.\n\n\nShow the code\n# Connect to the SQLite database\nfile = 'lahmansbaseballdb.sqlite'\ncon = sqlite3.connect(file)\n\n# Execute the SQL query and store the results in a DataFrame\nquery = \"\"\"\nSELECT\n    s.playerID,\n    SUM(H) AS total_hits,\n    SUM(AB) AS total_at_bats,\n    CAST(SUM(H) AS REAL) / NULLIF(SUM(AB), 0) AS career_batting_average\nFROM\n    Salaries s\nJOIN\n    Batting b ON s.playerID = b.playerID\nGROUP BY\n    s.playerID\nHAVING\n    total_at_bats &gt;= 100\nORDER BY\n    career_batting_average DESC\nLIMIT 5;\n\"\"\"\n\ndf = pd.read_sql_query(query, con)\n\n# Show the data\nprint(df.head())\n\n\n    playerID  total_hits  total_at_bats  career_batting_average\n0  kruegbi01          42            105                0.400000\n1  forstte01          62            156                0.397436\n2  mathete01          54            144                0.375000\n3  gwynnto01       53397         157896                0.338178\n4  pemberu01          45            134                0.335821\n\n\nSummary/Findings\n\nThe highest batting average is 40%.\nThe most impressive of these top 5 is gwynnto01 (), because he has batted substantially more then all of the others, therefore the average will even out to a more true average taking out outliners, like hitting every time in one game because of a bad pitcher.\nFrom the 1st to the 5th it drops quitly, almost 7%.",
+    "crumbs": [
+      "DS250 Projects",
+      "Project 3"
+    ]
+  },
+  {
+    "objectID": "Projects/project3.html#questiontask-3",
+    "href": "Projects/project3.html#questiontask-3",
+    "title": "Finding Relationships in Baseball - Project 3",
+    "section": "QUESTION|TASK 3",
+    "text": "QUESTION|TASK 3\nPick any two baseball teams and compare them using a metric of your choice (average salary, home runs, number of wins, etc). Write an SQL query to get the data you need, then make a graph using Plotly Express to visualize the comparison. What do you learn?\n\n\nShow the code\nimport sqlite3\nimport pandas as pd\nimport plotly.express as px\nimport numpy as np\nfrom sklearn.linear_model import LinearRegression\n\n# Connect to the SQLite database\nfile = 'lahmansbaseballdb.sqlite'\ncon = sqlite3.connect(file)\n\n# Execute the SQL query and store the results in a DataFrame\nquery = \"\"\"\nSELECT\n    t.W AS wins,\n    t.yearID,\n    s.schoolID\nFROM\n    schools s\nJOIN\n    collegeplaying cp ON s.schoolID = cp.schoolID\nJOIN\n    batting b ON b.playerID = cp.playerID\nJOIN\n    teams t ON t.teamID = b.teamID\nWHERE\n    s.schoolID IN ('weberst', 'sfaustin')  -- Use IN to specify multiple schools\nORDER BY\n    t.yearID ASC;  -- Order by yearID in ascending order\n\"\"\"\n\ndf = pd.read_sql_query(query, con)\n\n# Group the data by school and calculate linear regression for each school\ntrendlines = {}\nfor school, data in df.groupby('schoolID'):\n    X = data['yearID'].values.reshape(-1, 1)\n    y = data['wins'].values.reshape(-1, 1)\n    model = LinearRegression()\n    model.fit(X, y)\n    trendlines[school] = model.predict(X)\n\n# Create a line plot using Plotly Express\nfig = px.line(df, x='yearID', y='wins', color='schoolID',\n              title='Wins Over Years for Weber State and Stephen F. Austin',\n              color_discrete_map = {'weberst': 'purple', 'sfaustin': 'red'},  labels={'yearID': 'Year', 'wins': 'Wins', 'schoolID': 'Schools'})\n\n# Define colors for trend lines\ntrendline_colors = {'weberst': 'blue', 'sfaustin': 'green'}\n\n# Add trend lines to the plot with different colors\nfor school, trendline in trendlines.items():\n    fig.add_scatter(x=df[df['schoolID'] == school]['yearID'], y=trendline.flatten(), mode='lines',\n                    name=f'Trendline ({school})', line=dict(color=trendline_colors[school], width=3))\n\n# Update the opacity of the \"normal\" lines\nfor trace in fig.data:\n    if 'Trendline' not in trace['name']:\n        trace['opacity'] = 0.5\n\n# Define custom legend labels\nlegend_labels = {\n    'weberst': 'Weber State',\n    'sfaustin': 'Stephen F. Austin',\n}\n\n# Update the legend labels for trendlines\nfor trace in fig.data:\n    if 'Trendline' in trace['name']:\n        # Extract the school name from the trace name\n        school_start_idx = trace['name'].find('(') + 1\n        school_end_idx = trace['name'].find(')')\n        school = trace['name'][school_start_idx:school_end_idx].lower()\n        trace['legendgroup'] = f'{school}_trendline'\n        trace['name'] = f'{legend_labels.get(school, school)} (Trendline)'\n\n# Update the legend labels for normal lines\nfor trace in fig.data:\n    if 'Trendline' not in trace['name']:\n        school = trace['name'].split()[0].lower()\n        trace['legendgroup'] = school\n        trace['name'] = legend_labels.get(school, school)\n\nfig.show()\n\n\n                                                \n\n\nSummary/Findings\n\nStephen F. Austin University is doing better overall as far as wins.\nThese two schools are very well matched to each other, and win about the same amount.\nThey both pass each other frequently in the number of wins year to year.\nWeber more frequently drops down and jumps in the number of wins.\nStephen F. Austin has stayed relatively steady over the years.\nBoth teams are improving although very slowly.",
     "crumbs": [
       "DS250 Projects",
       "Project 3"
@@ -348,7 +392,7 @@
     "href": "Projects/project5.html#questiontask-2",
     "title": "Client Report - Project 5: The war with Star Wars",
     "section": "QUESTION|TASK 2",
-    "text": "QUESTION|TASK 2\nClean and format the data so that it can be used in a machine learning model. As you format the data, you should complete each item listed below. In your final report provide example(s) of the reformatted data with a short description of the changes made.\n\n2.1 Filter the dataset to respondents that have seen at least one film.\n\nCompleted\n\n\nShow the code\ndata = data[data['Seen_any_SW'] != 0]\n\n\n\n2.2 Create a new column that converts the age ranges to a single number. Drop the age range categorical column.\n\nCompleted\n\n\nShow the code\n#make into int-able\nage_dic = {\n    '18-29': 1,\n    '30-44': 2,\n    '45-60': 3,\n    '&gt; 60': 4  \n}\n\ndata['Age'] = data['Age'].replace('Response', 1)\n# Fill NaN values in the 'Age' column with 0\ndata['Age'] = data['Age'].fillna(0)\n\ndata['Age'] = data['Age'].replace(age_dic)\n#cast as int\ndata['Age'] = data['Age'].astype(int)\n\nage_dummies = pd.get_dummies(data['Age'])\n\nage_dummies.columns = ['NaN','18-29', '30-44', '45-60', '&gt; 60']\n\ndata = pd.concat([data, age_dummies], axis=1)\n\n# YN_dic = {'True': 1, 'False': 0}\n# age_dic = {'NaN','18-29','30-44','45-60','&gt; 60'}\n\n# data[age_dic] = data[age_dic].replace(YN_dic)\n\nTF_dic = {'True': 1, 'False': 0}\n\ndata.replace(TF_dic, inplace=True)\n\nTF_dic = {'True': 1, 'False': 0}\n\nTrue_False_columns = ['NaN', '18-29', '30-44', '45-60', '&gt; 60']\n\ndata[True_False_columns] = data[True_False_columns].astype(int)\n\ndata[True_False_columns] = data[True_False_columns].replace(TF_dic)\n\ndata.drop('Age', axis=1, inplace=True)\n\ndata.to_csv(\"cleaned_data.csv\", index=False)\n\n\n\n2.3 Create a new column that converts the education groupings to a single number. Drop the school categorical column\n\nCompleted\n\n\nShow the code\nedu_dic = {\n    'Response': 1,\n    'nan': 2,\n    'Less than high school degree': 3,\n    'High school degree': 4,\n    'Some college or Associate degree': 5,\n    'Bachelor degree': 6,\n    'Graduate degree': 7,\n}\n\ndata['education'] = data['education'].fillna(0)\n\ndata['education'] = data['education'].replace(edu_dic)\n#cast as int\ndata['education'] = data['education'].astype(int)\n\nage_dummies = pd.get_dummies(data['education'])\n\nage_dummies.columns = ['Response', 'edu_NaN','edu_less_HS', 'edu_HS', 'edu_Some_collage/AD', 'edu_BD', 'edu_GD']\n\ndata = pd.concat([data, age_dummies], axis=1)\n\n\ndata.replace(TF_dic, inplace=True)\n\nTF_dic = {'True': 1, 'False': 0}\n\nnames_columns = ['Response','edu_NaN','edu_less_HS', 'edu_HS', 'edu_Some_collage/AD', 'edu_BD', 'edu_GD']\n\ndata[names_columns] = data[names_columns].astype(int)\n\ndata[names_columns] = data[names_columns].replace(TF_dic)\n\ndata.drop('education', axis=1, inplace=True)\n\ndata.to_csv(\"cleaned_data.csv\", index=False)\n\n\n\n2.4 Create a new column that converts the income ranges to a single number. Drop the income range categorical column.\n\nCompleted\n\n\nShow the code\nincome_dic = {\n    'Response': 0,\n    'nan': 1,\n    '$0 - $24,999': 2,\n    '$100,000 - $149,999': 3,\n    '$25,000 - $49,999': 4,\n    '$50,000 - $99,999': 5,\n    '$150,000+': 6,\n}\n\n# Fill missing values in 'income' column with 0\ndata['income'] = data['income'].fillna(0)\n\n# Replace income categories with numerical values\ndata['income'] = data['income'].replace(income_dic)\n\n# Cast 'income' column as int\ndata['income'] = data['income'].astype(int)\n\ndata.to_csv(\"cleaned_data.csv\", index=False)\n\n\n\n2.5 Create your target (also known as “y” or “label”) column based on the new income range column.\n\nCompleted\n\n\nShow the code\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.neural_network import MLPClassifier  # For Neural Networks (Multi-layer Perceptron)\nfrom sklearn import metrics\n\ndf = pd.read_csv('cleaned_data.csv', encoding='latin-1')\ndf.drop(['1st_shot', 'gender', 'location', 'NaN', 'Response'], axis=1, inplace=True)\ndf.fillna(0, inplace=True)  \ndf.drop(0, inplace=True)\n\n# Split the data into features (X) and target (y)\nX = df.drop(['income'], axis=1)\ny = df['income']\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)\n\nclassifier = MLPClassifier()\nclassifier.fit(X_train, y_train)\n\n# Predict on the test set\ny_pred = classifier.predict(X_test)\n\n# Calculate accuracy\naccuracy = metrics.accuracy_score(y_test, y_pred)\nprint(\"Accuracy:\", accuracy)\n\n\nAccuracy: 0.29537366548042704\n\n\n\n2.6 One-hot encode all remaining categorical columns.\n\nCompleted above.",
+    "text": "QUESTION|TASK 2\nClean and format the data so that it can be used in a machine learning model. As you format the data, you should complete each item listed below. In your final report provide example(s) of the reformatted data with a short description of the changes made.\n\n2.1 Filter the dataset to respondents that have seen at least one film.\n\nCompleted\n\n\nShow the code\ndata = data[data['Seen_any_SW'] != 0]\n\n\n\n2.2 Create a new column that converts the age ranges to a single number. Drop the age range categorical column.\n\nCompleted\n\n\nShow the code\n#make into int-able\nage_dic = {\n    '18-29': 1,\n    '30-44': 2,\n    '45-60': 3,\n    '&gt; 60': 4  \n}\n\ndata['Age'] = data['Age'].replace('Response', 1)\n# Fill NaN values in the 'Age' column with 0\ndata['Age'] = data['Age'].fillna(0)\n\ndata['Age'] = data['Age'].replace(age_dic)\n#cast as int\ndata['Age'] = data['Age'].astype(int)\n\nage_dummies = pd.get_dummies(data['Age'])\n\nage_dummies.columns = ['NaN','18-29', '30-44', '45-60', '&gt; 60']\n\ndata = pd.concat([data, age_dummies], axis=1)\n\n# YN_dic = {'True': 1, 'False': 0}\n# age_dic = {'NaN','18-29','30-44','45-60','&gt; 60'}\n\n# data[age_dic] = data[age_dic].replace(YN_dic)\n\nTF_dic = {'True': 1, 'False': 0}\n\ndata.replace(TF_dic, inplace=True)\n\nTF_dic = {'True': 1, 'False': 0}\n\nTrue_False_columns = ['NaN', '18-29', '30-44', '45-60', '&gt; 60']\n\ndata[True_False_columns] = data[True_False_columns].astype(int)\n\ndata[True_False_columns] = data[True_False_columns].replace(TF_dic)\n\ndata.drop('Age', axis=1, inplace=True)\n\ndata.to_csv(\"cleaned_data.csv\", index=False)\n\n\n\n2.3 Create a new column that converts the education groupings to a single number. Drop the school categorical column\n\nCompleted\n\n\nShow the code\nedu_dic = {\n    'Response': 1,\n    'nan': 2,\n    'Less than high school degree': 3,\n    'High school degree': 4,\n    'Some college or Associate degree': 5,\n    'Bachelor degree': 6,\n    'Graduate degree': 7,\n}\n\ndata['education'] = data['education'].fillna(0)\n\ndata['education'] = data['education'].replace(edu_dic)\n#cast as int\ndata['education'] = data['education'].astype(int)\n\nage_dummies = pd.get_dummies(data['education'])\n\nage_dummies.columns = ['Response', 'edu_NaN','edu_less_HS', 'edu_HS', 'edu_Some_collage/AD', 'edu_BD', 'edu_GD']\n\ndata = pd.concat([data, age_dummies], axis=1)\n\n\ndata.replace(TF_dic, inplace=True)\n\nTF_dic = {'True': 1, 'False': 0}\n\nnames_columns = ['Response','edu_NaN','edu_less_HS', 'edu_HS', 'edu_Some_collage/AD', 'edu_BD', 'edu_GD']\n\ndata[names_columns] = data[names_columns].astype(int)\n\ndata[names_columns] = data[names_columns].replace(TF_dic)\n\ndata.drop('education', axis=1, inplace=True)\n\ndata.to_csv(\"cleaned_data.csv\", index=False)\n\n\n\n2.4 Create a new column that converts the income ranges to a single number. Drop the income range categorical column.\n\nCompleted\n\n\nShow the code\nincome_dic = {\n    'Response': 0,\n    'nan': 1,\n    '$0 - $24,999': 2,\n    '$100,000 - $149,999': 3,\n    '$25,000 - $49,999': 4,\n    '$50,000 - $99,999': 5,\n    '$150,000+': 6,\n}\n\n# Fill missing values in 'income' column with 0\ndata['income'] = data['income'].fillna(0)\n\n# Replace income categories with numerical values\ndata['income'] = data['income'].replace(income_dic)\n\n# Cast 'income' column as int\ndata['income'] = data['income'].astype(int)\n\ndata.to_csv(\"cleaned_data.csv\", index=False)\n\n\n\n2.5 Create your target (also known as “y” or “label”) column based on the new income range column.\n\nCompleted\n\n\nShow the code\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.neural_network import MLPClassifier  # For Neural Networks (Multi-layer Perceptron)\nfrom sklearn import metrics\n\ndf = pd.read_csv('cleaned_data.csv', encoding='latin-1')\ndf.drop(['1st_shot', 'gender', 'location', 'NaN', 'Response'], axis=1, inplace=True)\ndf.fillna(0, inplace=True)  \ndf.drop(0, inplace=True)\n\n# Split the data into features (X) and target (y)\nX = df.drop(['income'], axis=1)\ny = df['income']\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)\n\nclassifier = MLPClassifier()\nclassifier.fit(X_train, y_train)\n\n# Predict on the test set\ny_pred = classifier.predict(X_test)\n\n# Calculate accuracy\naccuracy = metrics.accuracy_score(y_test, y_pred)\nprint(\"Accuracy:\", accuracy)\n\n\nAccuracy: 0.2597864768683274\n\n\n\n2.6 One-hot encode all remaining categorical columns.\n\nCompleted above.",
     "crumbs": [
       "DS250 Projects",
       "Project 5"
@@ -370,7 +414,7 @@
     "href": "Projects/project5.html#questiontask-4",
     "title": "Client Report - Project 5: The war with Star Wars",
     "section": "QUESTION|TASK 4",
-    "text": "QUESTION|TASK 4\nBuild a machine learning model that predicts whether a person makes more than $50k. Describe your model and report the accuracy.\nI tried like 20 differant classifers, however the highest Accuracy I ever got was abouut 28%. I ended up useing the MLPClassifier classifier. This probibly means that the corralation isn’t very high between these facts about liking, watching etc. about starwars and our income. It is also posible the the data set isn’t big enough, but I kind of doubt it.\n\n\nShow the code\n#%%\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.linear_model import LogisticRegression\n\nfrom sklearn import metrics\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.ensemble import RandomForestRegressor\n\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.tree import DecisionTreeRegressor\n\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.ensemble import RandomForestClassifier #31\nfrom sklearn.svm import SVC  # For Support Vector Machines\nfrom sklearn.ensemble import GradientBoostingClassifier # 32\n\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn import metrics\n\n# Read the cleaned data\ndata = pd.read_csv('cleaned_data.csv', encoding='latin-1')\n# data.drop(['1st_shot', 'gender', 'location', 'NaN', 'Response'], axis=1, inplace=True)\ndata.drop(['1st_shot', 'gender', 'location'], axis=1, inplace=True)\ndata.fillna(0, inplace=True)  \n\ndata.drop(0, inplace=True)\n\n# Split the data into features (X) and target (y)\nX = data.drop(['income'], axis=1)\ny = data['income']\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)\n\nclassifier = MLPClassifier()\nclassifier.fit(X_train, y_train)\n\n# Predict on the test set\ny_pred = classifier.predict(X_test)\n\n# Calculate accuracy\naccuracy = metrics.accuracy_score(y_test, y_pred)\nprint(\"Accuracy:\", accuracy)\n\n\nAccuracy: 0.2704626334519573",
+    "text": "QUESTION|TASK 4\nBuild a machine learning model that predicts whether a person makes more than $50k. Describe your model and report the accuracy.\nI tried like 20 differant classifers, however the highest Accuracy I ever got was abouut 28%. I ended up useing the MLPClassifier classifier. This probibly means that the corralation isn’t very high between these facts about liking, watching etc. about starwars and our income. It is also posible the the data set isn’t big enough, but I kind of doubt it.\n\n\nShow the code\n#%%\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.linear_model import LogisticRegression\n\nfrom sklearn import metrics\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.ensemble import RandomForestRegressor\n\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.tree import DecisionTreeRegressor\n\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.ensemble import GradientBoostingClassifier\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.tree import DecisionTreeClassifier\nfrom sklearn.ensemble import RandomForestClassifier #31\nfrom sklearn.svm import SVC  # For Support Vector Machines\nfrom sklearn.ensemble import GradientBoostingClassifier # 32\n\nimport pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn import metrics\n\n# Read the cleaned data\ndata = pd.read_csv('cleaned_data.csv', encoding='latin-1')\n# data.drop(['1st_shot', 'gender', 'location', 'NaN', 'Response'], axis=1, inplace=True)\ndata.drop(['1st_shot', 'gender', 'location'], axis=1, inplace=True)\ndata.fillna(0, inplace=True)  \n\ndata.drop(0, inplace=True)\n\n# Split the data into features (X) and target (y)\nX = data.drop(['income'], axis=1)\ny = data['income']\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3)\n\nclassifier = MLPClassifier()\nclassifier.fit(X_train, y_train)\n\n# Predict on the test set\ny_pred = classifier.predict(X_test)\n\n# Calculate accuracy\naccuracy = metrics.accuracy_score(y_test, y_pred)\nprint(\"Accuracy:\", accuracy)\n\n\nAccuracy: 0.11743772241992882",
     "crumbs": [
       "DS250 Projects",
       "Project 5"
diff --git a/sitemap.xml b/sitemap.xml
index 4a379d0..04be19d 100644
--- a/sitemap.xml
+++ b/sitemap.xml
@@ -2,66 +2,66 @@
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/ml.html</loc>
-    <lastmod>2024-04-02T00:00:23.832Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.220Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/exploration.html</loc>
-    <lastmod>2024-04-02T00:00:23.832Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.220Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/index.html</loc>
-    <lastmod>2024-04-02T00:00:23.832Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.220Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/full_stack.html</loc>
-    <lastmod>2024-04-02T00:00:23.832Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.220Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/cleansing.html</loc>
-    <lastmod>2024-04-02T00:00:23.832Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.220Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/Projects/project1.html</loc>
-    <lastmod>2024-04-02T00:00:23.824Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.212Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/Projects/project2.html</loc>
-    <lastmod>2024-04-02T00:00:23.824Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.212Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/Templates/DS250_Template.html</loc>
-    <lastmod>2024-04-02T00:00:23.824Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.212Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/Templates/DS350_Template.html</loc>
-    <lastmod>2024-04-02T00:00:23.824Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.212Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/Projects/project4.html</loc>
-    <lastmod>2024-04-02T00:00:23.824Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.212Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/Projects/project3.html</loc>
-    <lastmod>2024-04-02T00:00:23.824Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.212Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/Projects/project5.html</loc>
-    <lastmod>2024-04-02T00:00:23.824Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.212Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/projects.html</loc>
-    <lastmod>2024-04-02T00:00:23.832Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.220Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/competition.html</loc>
-    <lastmod>2024-04-02T00:00:23.832Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.220Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/story_telling.html</loc>
-    <lastmod>2024-04-02T00:00:23.832Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.220Z</lastmod>
   </url>
   <url>
     <loc>https://byuids-resumes.github.io/ball-portfolio/resume.html</loc>
-    <lastmod>2024-04-02T00:00:23.832Z</lastmod>
+    <lastmod>2024-04-02T00:01:39.220Z</lastmod>
   </url>
 </urlset>