M4DataVisualization-lab.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p style=\"text-align:center\">\n",
    "    <a href=\"https://skills.network/?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDA0321ENSkillsNetwork928-2023-01-01\">\n",
    "    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/assets/logos/SN_web_lightmode.png\" width=\"200\" alt=\"Skills Network Logo\"  />\n",
    "    </a>\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Data Visualization Lab**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Estimated time needed: **45 to 60** minutes\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this assignment you will be focusing on the visualization of data.\n",
    "\n",
    "The data set will be presented to you in the form of a RDBMS.\n",
    "\n",
    "You will have to use SQL queries to extract the data.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Objectives\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this lab you will perform the following:\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-   Visualize the distribution of data.\n",
    "\n",
    "-   Visualize the relationship between two features.\n",
    "\n",
    "-   Visualize composition of data.\n",
    "\n",
    "-   Visualize comparison of data.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to work with database\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download database file.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2023-09-03 11:44:26--  https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DA0321EN-SkillsNetwork/LargeData/m4_survey_data.sqlite\n",
      "Resolving cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud (cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud)... 169.63.118.104\n",
      "Connecting to cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud (cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud)|169.63.118.104|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 36679680 (35M) [application/octet-stream]\n",
      "Saving to: 'm4_survey_data.sqlite'\n",
      "\n",
      "m4_survey_data.sqli 100%[===================>]  34.98M   387KB/s    in 43s     \n",
      "\n",
      "2023-09-03 11:45:10 (824 KB/s) - 'm4_survey_data.sqlite' saved [36679680/36679680]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBM-DA0321EN-SkillsNetwork/LargeData/m4_survey_data.sqlite"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Connect to the database.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "conn = sqlite3.connect(\"m4_survey_data.sqlite\") # open a database connection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import pandas module.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to run an sql query\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>COUNT(*)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>11398</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   COUNT(*)\n",
       "0     11398"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print how many rows are there in the table named 'master'\n",
    "QUERY = \"\"\"\n",
    "SELECT COUNT(*)\n",
    "FROM master\n",
    "\"\"\"\n",
    "\n",
    "# the read_sql_query runs the sql query and returns the data as a dataframe\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to list all tables\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Table_Name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>EduOther</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DevType</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LastInt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>JobFactors</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>WorkPlan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>WorkChallenge</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>LanguageWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>LanguageDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>DatabaseWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>DatabaseDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>PlatformWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>PlatformDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>WebFrameWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>WebFrameDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>MiscTechWorkedWith</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>MiscTechDesireNextYear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>DevEnviron</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Containers</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>SOVisitTo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>SONewContent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Gender</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Sexuality</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Ethnicity</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>master</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Table_Name\n",
       "0                 EduOther\n",
       "1                  DevType\n",
       "2                  LastInt\n",
       "3               JobFactors\n",
       "4                 WorkPlan\n",
       "5            WorkChallenge\n",
       "6       LanguageWorkedWith\n",
       "7   LanguageDesireNextYear\n",
       "8       DatabaseWorkedWith\n",
       "9   DatabaseDesireNextYear\n",
       "10      PlatformWorkedWith\n",
       "11  PlatformDesireNextYear\n",
       "12      WebFrameWorkedWith\n",
       "13  WebFrameDesireNextYear\n",
       "14      MiscTechWorkedWith\n",
       "15  MiscTechDesireNextYear\n",
       "16              DevEnviron\n",
       "17              Containers\n",
       "18               SOVisitTo\n",
       "19            SONewContent\n",
       "20                  Gender\n",
       "21               Sexuality\n",
       "22               Ethnicity\n",
       "23                  master"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# print all the tables names in the database\n",
    "QUERY = \"\"\"\n",
    "SELECT name as Table_Name FROM\n",
    "sqlite_master WHERE\n",
    "type = 'table'\n",
    "\"\"\"\n",
    "# the read_sql_query runs the sql query and returns the data as a dataframe\n",
    "pd.read_sql_query(QUERY,conn)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to run a group by query\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>16.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>17.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>18.0</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19.0</td>\n",
       "      <td>78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20.0</td>\n",
       "      <td>109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>21.0</td>\n",
       "      <td>203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>22.0</td>\n",
       "      <td>406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>23.0</td>\n",
       "      <td>581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>24.0</td>\n",
       "      <td>679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>25.0</td>\n",
       "      <td>738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>26.0</td>\n",
       "      <td>720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>27.0</td>\n",
       "      <td>724</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>28.0</td>\n",
       "      <td>787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>29.0</td>\n",
       "      <td>697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>30.0</td>\n",
       "      <td>651</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>31.0</td>\n",
       "      <td>531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>32.0</td>\n",
       "      <td>489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>33.0</td>\n",
       "      <td>483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>34.0</td>\n",
       "      <td>395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>35.0</td>\n",
       "      <td>393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>36.0</td>\n",
       "      <td>308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>37.0</td>\n",
       "      <td>280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>38.0</td>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>39.0</td>\n",
       "      <td>232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>40.0</td>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>41.0</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>42.0</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>43.0</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>44.0</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>45.0</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>46.0</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>47.0</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>48.0</td>\n",
       "      <td>64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>49.0</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>50.0</td>\n",
       "      <td>57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>51.0</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>52.0</td>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>53.0</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>54.0</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>55.0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>56.0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>57.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>58.0</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>59.0</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>60.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>61.0</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>62.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>63.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>65.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>66.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>67.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>69.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>71.0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>72.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>99.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Age  count\n",
       "0    NaN    287\n",
       "1   16.0      3\n",
       "2   17.0      6\n",
       "3   18.0     29\n",
       "4   19.0     78\n",
       "5   20.0    109\n",
       "6   21.0    203\n",
       "7   22.0    406\n",
       "8   23.0    581\n",
       "9   24.0    679\n",
       "10  25.0    738\n",
       "11  26.0    720\n",
       "12  27.0    724\n",
       "13  28.0    787\n",
       "14  29.0    697\n",
       "15  30.0    651\n",
       "16  31.0    531\n",
       "17  32.0    489\n",
       "18  33.0    483\n",
       "19  34.0    395\n",
       "20  35.0    393\n",
       "21  36.0    308\n",
       "22  37.0    280\n",
       "23  38.0    279\n",
       "24  39.0    232\n",
       "25  40.0    187\n",
       "26  41.0    136\n",
       "27  42.0    162\n",
       "28  43.0    100\n",
       "29  44.0     95\n",
       "30  45.0     85\n",
       "31  46.0     66\n",
       "32  47.0     68\n",
       "33  48.0     64\n",
       "34  49.0     66\n",
       "35  50.0     57\n",
       "36  51.0     29\n",
       "37  52.0     41\n",
       "38  53.0     32\n",
       "39  54.0     26\n",
       "40  55.0     13\n",
       "41  56.0     16\n",
       "42  57.0     11\n",
       "43  58.0     12\n",
       "44  59.0     11\n",
       "45  60.0      2\n",
       "46  61.0     10\n",
       "47  62.0      5\n",
       "48  63.0      7\n",
       "49  65.0      2\n",
       "50  66.0      1\n",
       "51  67.0      1\n",
       "52  69.0      1\n",
       "53  71.0      2\n",
       "54  72.0      1\n",
       "55  99.0      1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "QUERY = \"\"\"\n",
    "SELECT Age,COUNT(*) as count\n",
    "FROM master\n",
    "group by age\n",
    "order by age\n",
    "\"\"\"\n",
    "pd.read_sql_query(QUERY,conn)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Demo: How to describe a table\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CREATE TABLE \"master\" (\n",
      "\"index\" INTEGER,\n",
      "  \"Respondent\" INTEGER,\n",
      "  \"MainBranch\" TEXT,\n",
      "  \"Hobbyist\" TEXT,\n",
      "  \"OpenSourcer\" TEXT,\n",
      "  \"OpenSource\" TEXT,\n",
      "  \"Employment\" TEXT,\n",
      "  \"Country\" TEXT,\n",
      "  \"Student\" TEXT,\n",
      "  \"EdLevel\" TEXT,\n",
      "  \"UndergradMajor\" TEXT,\n",
      "  \"OrgSize\" TEXT,\n",
      "  \"YearsCode\" TEXT,\n",
      "  \"Age1stCode\" TEXT,\n",
      "  \"YearsCodePro\" TEXT,\n",
      "  \"CareerSat\" TEXT,\n",
      "  \"JobSat\" TEXT,\n",
      "  \"MgrIdiot\" TEXT,\n",
      "  \"MgrMoney\" TEXT,\n",
      "  \"MgrWant\" TEXT,\n",
      "  \"JobSeek\" TEXT,\n",
      "  \"LastHireDate\" TEXT,\n",
      "  \"FizzBuzz\" TEXT,\n",
      "  \"ResumeUpdate\" TEXT,\n",
      "  \"CurrencySymbol\" TEXT,\n",
      "  \"CurrencyDesc\" TEXT,\n",
      "  \"CompTotal\" REAL,\n",
      "  \"CompFreq\" TEXT,\n",
      "  \"ConvertedComp\" REAL,\n",
      "  \"WorkWeekHrs\" REAL,\n",
      "  \"WorkRemote\" TEXT,\n",
      "  \"WorkLoc\" TEXT,\n",
      "  \"ImpSyn\" TEXT,\n",
      "  \"CodeRev\" TEXT,\n",
      "  \"CodeRevHrs\" REAL,\n",
      "  \"UnitTests\" TEXT,\n",
      "  \"PurchaseHow\" TEXT,\n",
      "  \"PurchaseWhat\" TEXT,\n",
      "  \"OpSys\" TEXT,\n",
      "  \"BlockchainOrg\" TEXT,\n",
      "  \"BlockchainIs\" TEXT,\n",
      "  \"BetterLife\" TEXT,\n",
      "  \"ITperson\" TEXT,\n",
      "  \"OffOn\" TEXT,\n",
      "  \"SocialMedia\" TEXT,\n",
      "  \"Extraversion\" TEXT,\n",
      "  \"ScreenName\" TEXT,\n",
      "  \"SOVisit1st\" TEXT,\n",
      "  \"SOVisitFreq\" TEXT,\n",
      "  \"SOFindAnswer\" TEXT,\n",
      "  \"SOTimeSaved\" TEXT,\n",
      "  \"SOHowMuchTime\" TEXT,\n",
      "  \"SOAccount\" TEXT,\n",
      "  \"SOPartFreq\" TEXT,\n",
      "  \"SOJobs\" TEXT,\n",
      "  \"EntTeams\" TEXT,\n",
      "  \"SOComm\" TEXT,\n",
      "  \"WelcomeChange\" TEXT,\n",
      "  \"Age\" REAL,\n",
      "  \"Trans\" TEXT,\n",
      "  \"Dependents\" TEXT,\n",
      "  \"SurveyLength\" TEXT,\n",
      "  \"SurveyEase\" TEXT\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "table_name = 'master'  # the table you wish to describe\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT sql FROM sqlite_master\n",
    "WHERE name= '{}'\n",
    "\"\"\".format(table_name)\n",
    "\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "print(df.iat[0,0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hands-on Lab\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing distribution of data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Histograms\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot a histogram of `ConvertedComp.`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "import seaborn as sns\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT ConvertedComp\n",
    "FROM master\n",
    "\"\"\"\n",
    "df_CC = pd.read_sql_query(QUERY,conn)\n",
    "histplot = sns.histplot(df['ConvertedComp'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Box Plots\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot a box plot of `Age.`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT Age\n",
    "FROM master\n",
    "\"\"\"\n",
    "df_Age = pd.read_sql_query(QUERY, conn)\n",
    "df_Age.boxplot()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing relationships in data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scatter Plots\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a scatter plot of `Age` and `WorkWeekHrs.`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT Age, WorkWeekHrs\n",
    "FROM master\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY, conn)\n",
    "scatterplot  = sns.scatterplot(data=df, x='Age', y='WorkWeekHrs')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bubble Plots\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a bubble plot of `WorkWeekHrs` and `CodeRevHrs`, use `Age` column as bubble size.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT WorkWeekHrs, CodeRevHrs, Age FROM master\n",
    "\"\"\"\n",
    "df1=pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "sns.scatterplot(data=df1, x='WorkWeekHrs', y='CodeRevHrs', size='Age', hue='Age', alpha=0.5, sizes=(10, 500)) \n",
    "\n",
    "plt.title('WorkWeekHrs and CodeRevHrs Grouped by Age', size=14) \n",
    "plt.xlabel('WorkWeekHrs', size=10) \n",
    "plt.ylabel('CodeRevHrs', size=10)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing composition of data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pie Charts\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a pie chart of the top 5 databases that respondents wish to learn next year. Label the pie chart with database names. Display percentages of each database on the pie chart.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "QUERY = \"\"\" \n",
    "SELECT DatabaseDesireNextYear, COUNT(*) as count \n",
    "from DatabaseDesireNextYear \n",
    "group by DatabaseDesireNextYear \n",
    "order by count(DatabaseDesireNextYear) DESC LIMIT 5 \n",
    "\"\"\" \n",
    "\n",
    "df=pd.read_sql_query(QUERY,conn)  \n",
    "df.set_index('DatabaseDesireNextYear', inplace=True) \n",
    "\n",
    "colors_list=['gold', 'yellowgreen', 'lightcoral', 'lightskyblue', 'lightgreen', 'pink']\n",
    "\n",
    "df['count'].plot(kind='pie', figsize=(20,6), autopct='%1.1f%%', labels=None, startangle=90, colors=colors_list, shadow=True, pctdistance=1.12)  \n",
    "\n",
    "plt.legend(labels=df.index, loc='upper right')\n",
    "plt.title('Top 5 Databases Respondents Wish To Learn') \n",
    "plt.axis('equal')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Stacked Charts\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a stacked chart of median `WorkWeekHrs` and `CodeRevHrs` for the age group 30 to 35.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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YhIQEExwcbFq0aGGSkpKcy129P7j6cnV/OR6PiIgI07ZtWzN37lwzb948c/ToUfPEE08YX19fM3LkSLN8+XIzb948M3z4cDNmzJhr/o+zup8pWrSoady4sZkzZ46ZM2eOKV++vAkODjYnTpxwLuvo2RYtWphvv/3WTJ061ZQoUcJERkaaIkWKXLOe6dOnG0lm3Lhx11zOIbN9dvbsWVOmTBkTGBhoxowZYxYvXmyeeeYZ5777yteDZcuWGS8vL1OrVi0zc+ZMs2jRItO1a9c0y13dnw7z5s0zksy7777rnLZ582YTGBhoypcvbz777DOzZMkS07dvX+Pm5mYGDx7sXK5Vq1YmMjLSpKSkuKyzX79+xsvLy/z7778u2545c2a6vdOzZ880r0lFihQx4eHhplixYmbChAlm+fLl5ueffzarVq0yNpvNPPDAA2bBggVm2bJlZuLEiaZTp04ZPu7nz583q1evNhUqVDDFihVz7qtPnjxpzp07Z2JiYoyfn5955513zJIlS8zAgQONh4eHadq0qct6HP0cExNjpk+fbpYtW2b++OOPDLd79W179eqV7rwuXboYLy8vU6ZMGfPOO++Y7777zrz66qvGZrOZ1157zblcZmvNzGOU2f3/tfz0008u+9GHH37Y2Gw2s3PnTpflfv/9d+Pt7W1iYmLMjBkzzNy5c03Tpk1N0aJF07xeDBkyxNhsNtOtWzczb948M2vWLBMbG2v8/PzM5s2bM/VYp6ammkuXLpljx46ZGTNmGD8/P9O/f3/n/LNnzxqbzeas+0pjx441ksy2bdsyXP+13hNm9jl+PcnJyeb8+fNmy5YtpkWLFiYkJMTs3bvXZRlJJjg42Hh7exsvLy9TsWJFM2HChExv43ZHsLkB//77r6lZs6aRZCQZT09PU716dTNs2DBz+vRpl2XvuusuExcXd911Jicnm0uXLplHH33UVKhQwTn9hx9+MJLMgAEDrnl7R7A5e/asadOmjQkMDHR5E5KUlGTy5s1r7rvvPpfbpaSkmLvvvttUrVrVOa1atWqmYMGC5ty5c85pp06dMnnz5s10sHE8NldewsPDzcqVKzP1ONSrV8+0atXKOd3xhqN48eIZBskrPfnkk0aS2bp163WXNeb/3qT07NnTZfqIESOMJHPw4MF0b+fYEa5YscJIMr///rtznuNxSG+H0axZs+u++XHYsmVLurWtXbvWSDIvv/yyc9rVbzav5cplJ06caOx2uzl69KhJTk424eHhzjciV7/xHDZsmHFzczPr1q1zWd9XX31lJJkFCxYYY4xZuHChkeQSwI25/AKUmWBzJcfjvGfPHiPJfPPNN2nux4gRI1xu07NnT+Pt7X3dF9o5c+a4BIavv/7aeHh4mNOnT5tTp04Zd3d3M2/ePGOMMZMnT3a5jy+99JKRZNauXeuyzh49ehibzeZ8kbtW/175xvHXX381BQsWNLVq1TJHjx51We7YsWPGzc3NPP7448aY/wtgixYtMsYYU7VqVfP8888bY/4vgPXr188YY8zq1avTvAk15nKI8vHxcS6Xlf3Elf0zZcoU4+XlZZ555pk0b1Yz2h9ceUkv2NSuXTvN/6pcuXKmZcuWaaZn1fX2M+XLlzfJycnO6T///LORZD7//HPn41GwYEFTsWJFl/7avXu38fT0vO5ze/jw4c4PIDIjs302bty4NM8PYy6H2qsDS+nSpU2FChXMpUuXXJZt3ry5CQ8Pd/4frw4XZ8+eNT/99JMpVaqUKVu2rDl+/Ljzto0aNTKFChVyfhDg8NRTTxlvb29z7NgxY4wxc+fONZLMkiVLnMskJyebggULmjZt2jinObZ9vcuVihQpYtzd3dO8wXznnXeMJJdwmllxcXHmrrvucpk2fvx4I8l88cUXLtPfeuutNPdNkgkMDHTe/6y4XrBJr4amTZuaUqVKZbnWzDxGmd3/X0u3bt2MJLNlyxZjzP/9nwcOHOiyXLt27Yyfn5/L61lKSoopW7asy+vF3r17jYeHh3n66addbn/69GkTFhbm8qHdtQwbNszZUzabLc37rn/++cdIMsOGDUtzW8eHFatWrbrmNjJ6T5jZ5/j12O12530oWbKk+fPPP9Ms07FjRzNt2jTzww8/mK+++so0adLESDKvvPJKprZxu+NUtBuQL18+/fjjj1q3bp2GDx+uFi1aaPv27erfv7/Kly9/3VGCHL788kvVqFFD/v7+8vDwkKenpz799FNt2bLFuczChQslSb169bru+o4ePaq6devq559/1sqVK1WvXj3nvFWrVunYsWPq0qWLkpOTnZfU1FQ1btxY69atU1JSkpKSkrRu3Tq1bt1a3t7eztsHBATovvvuy+xDJB8fH61bt07r1q3T2rVrNWvWLJUsWVJNmzZ1fiHSYfz48apYsaK8vb2dj8P333/v8jg43H///Tn6Zfb777/f5brjVJA9e/Y4p+3cuVMdO3ZUWFiY3N3d5enpqbi4OElKt+Y2bdrcVE2O05WuHjmqatWqKlOmTKZOEbqedu3aycvLS9OmTdOCBQuUmJiY4UhV8+bNU7ly5XTPPfe49FKjRo1cTtNw1H31eemZPY/68OHDevLJJxUZGensC8fh/4x640oxMTE6f/78dU+JiouLk5ubm7PuhIQEVa5cWf7+/goICFDFihWd9yUhIUEeHh6qWbOmJGnZsmUqW7asqlat6rLOrl27yhijZcuWpakxo/5dvHixatWqpdq1a2vp0qXKmzevy/zg4GDdfffdzjpXrFghd3d31ahRw3k/HHVe/f2aefPmyWaz6eGHH3b5n4WFhbmsM7P7iSsNGTJEXbt21fDhwzVq1CiX03EdrtwfXH3J6LsP6T1vqlatqoULF+qll15SQkJClr6DkpX9TLNmzVxOP7l6P7Bt2zYdOHBAHTt2dDmNtEiRIqpevXqma8qszPbZ8uXLFRAQkOa5cPVzbseOHdq6davzuXnl/7pp06Y6ePBgmi8cd+jQQZ6ens5TE0+dOqX58+c7R148f/68vv/+e7Vq1Uq+vr5p1nn+/Hnn6XxNmjRRWFiYy6Alixcv1oEDB9I9Neytt95Kt3fat2+f7uMVExOjkiVLukyrUqWKJKl9+/b64osvbnoQm2XLlsnPz09t27Z1me7Yb169X65bt26OfKfTZrOleW2OiYlxec3KbK2ZeYwyu//PyJkzZ/TFF1+oevXqKl26tKTL+67ixYtr0qRJLqddrVixQnXr1lX+/Pmd09zc3NL83xcvXqzk5GR17tzZpSZvb2/FxcVdt6YrH49169Zp8eLF6tevn95++209/fTTaZa71qnjNzpKX1ZfSzKyatUqrV69WlOnTlVAQIDi4+PTjIw2bdo0dezYUbVq1VKbNm20YMECNW/eXMOHD9eRI0duqP7byR124l32qly5svM840uXLunFF1/Ue++9pxEjRlx3EIFZs2apffv2ateunV544QWFhYXJw8ND48aNcznX9MiRI3J3d1dYWNh169m+fbuOHz+uxx57TOXKlXOZ5zgP+uod25WOHTsmm82m1NTUdLeXmRoc3NzcnI+NQ6NGjRQZGak+ffo4w83IkSPVt29fPfnkk3rjjTeUP39+ubu7a+DAgem+4cjsqFmO787s2rVLpUqVynTd+fLlc7nu+MKg4w3UmTNnVKtWLXl7e+vNN99UyZIl5evrq3379ql169Zp3mj5+voqT548md5+eo4ePSop/ftesGBBlxewG+Xn56cOHTpowoQJKlKkiOrXr+9yDvGVDh06pB07dmT4Bt0R7I8ePSoPD480j2lm+ig1NVUNGzbUgQMHNHDgQJUvX15+fn5KTU3Vvffem+4b2uv97zISFBSke+65xyUUNGvWzDn/6sBQuXJlBQQEOO9jekP7FixY0Dn/Stfq3zlz5ujcuXPq0aNHhgNixMfHa+TIkTpw4ICWL1+uSpUqOYd7jYuL07vvvquTJ09q+fLlLgHs0KFDMsYoNDQ03fUWK1bMuZx0/f2En5+f8/rUqVMVERHhMvjC1dLbH1w5Lz3pPVajR49WoUKFNHPmTL311lvy9vZWo0aN9Pbbbys6OjrD7Wd1P3O9XnL8XzPaT15v2PIr90+Zkdk+O3r0aLr/46vrdPyfn3/+eT3//PPpbvPqD+jeeust1a1bV2fPntWSJUs0bNgwtWzZUmvXrpXdbtfRo0eVnJysMWPGaMyYMddcp4eHhzp16qQxY8boxIkTCgoK0qRJkxQeHq5GjRqluV2xYsXS7Z+MBhxJr3dq166tOXPmaPTo0ercubMuXLigu+66SwMGDNCDDz6Y7nqu5ejRowoLC0vzRjYkJEQeHh5Zeu7fDF9fX5cPIaXL/XrlKGOZrTUzj1Fm9/8ZmTlzps6cOaP27dvrxIkTzunt27fXsGHDtHTpUmcPZNTPV09z9LMjmF0to33M1cLCwpzPlYYNGyo4OFgvvfSSunXrpgoVKig4OFg2my3N/1a6vF+UlOYDqczK6mtJRhzD+9977726//77VaJECb388svpfn/7Sg8//LDmzZun9evXq0mTJlkr/jZDsMkmnp6eGjRokN57771M/VbL1KlTFRUVpZkzZ7rsbK7+Il+BAgWUkpKixMTE6+4YY2Nj1a5dOz366KOSpHHjxjmf0I5PPMaMGZPhSBihoaHO0YfS+7JpRl9AzSxfX18VL17cZYjlqVOnqk6dOho3bpzLsld+CfpKmf00pFGjRnr55Zc1Z84clxGtbtayZct04MABJSQkOI/SSHLZQV8pO35jwfEm6+DBgypUqJDLvAMHDrh8mnUzunXrpk8++UQbN27UtGnTMlwuf/781/yyp6OefPnyKTk5WUePHnV5o5iZPvrjjz/0+++/a9KkSerSpYtz+o4dOzJ7d7IkPj5e7777rjZu3KjNmze7fDARFxenkSNHauPGjdq9e7fLm6B8+fK5fJnfwTHgxNX/m2v1w3vvvaeZM2eqSZMmmj17tho2bJhunSNHjlRCQoISEhLUtGlT5zxHiPnhhx+cgwo4Qk/+/Plls9n0448/phuaHNMyu5+40qJFi9ShQwfVqlVL33//fYaBOKvSe6z8/Pz02muv6bXXXtOhQ4ecR2/uu+8+bd26NcN1ZXU/cz2Ofr7R/WR8fLw8PT01Z86cNMPJZrS9zPRZvnz5nINNXKsmx/L9+/dX69at093m1R8IXRkuateuLR8fH73yyisaM2aMnn/+eQUHB8vd3V2dOnXK8AyDqKgo59+PPPKI3n77bc2YMUMdOnTQ3Llz1bt3b5cjZTcqo+dZixYt1KJFC124cEFr1qzRsGHD1LFjRxUtWlSxsbFZ2ka+fPm0du1aGWNctnf48GElJydn6bmf07JS6/Ueo8zu/zPy6aefSpJ69+6t3r17pzvfEWzy5cuXZnAKKeN+/uqrr7Jt/yPJefRk+/btqlChgnx8fFSiRAlt2rQpzbKbNm2Sj4+P80OirMrqa0lmBAQEqHTp0ukO2HM1Y4ykzIfA25n170EuSK/5pP87PcaRsKXLbxjS+8TYZrPJy8vLZSeTmJiYJlU7kvPVL8gZ6dKli2bMmKGJEyeqc+fOSklJkSTVqFFDQUFB+vPPP51Hmq6+eHl5yc/PT1WrVtWsWbNcPvE5ffr0Tf+mwpkzZ7Rjxw6XYYhtNluaN1obN25Mc7paVlWsWFFNmjTRp59+muEh3PXr12vv3r1ZWq/j/3V1zR999FGW1pNRX6THMarb1KlTXaavW7dOW7ZscTnl8GbExsaqW7duatWqlVq1apXhcs2bN9fff/+tfPnypdtHjk+dHKdBXR2Spk+fft1asutxzixHrY4hrx0hQfq/wOAYWenK4ZPr1aunP//8M82Ps3322Wey2WxZGmrZ29tbs2bNUvPmzXX//fen+wlb7dq15e7urq+++kqbN29WnTp1nPMCAwN1zz33aPLkydq9e7fLtps3by5jjP755590/2fly5eXlPn9xJWKFCniDEy1atW6Zb9rEhoaqq5du+rBBx/Utm3bdPbs2QyXze79TKlSpRQeHq7PP//c+YZAunyq2qpVq657+7CwMHXv3l2LFy/OcCS1v//+Wxs3bpSU+T6Lj4/X6dOn04yYefVzrlSpUoqOjtbvv/+e4f/ZcVQyI/369VOJEiU0fPhwnT59Wr6+voqPj9evv/6qmJiYdNd55QccZcqUUbVq1TRx4kRNnz5dFy5c0COPPHLdxy472O12xcXF6a233pKkGxo5q169ejpz5ozmzJnjMt3x/8yu/XJ2uJFaM3qMMrv/T8+WLVu0evVqtWnTRsuXL09zqVevnr755hvn0Ym4uDgtW7bM5ShQamqqvvzyS5f1NmrUSB4eHvr7778z7Ocb4ThSX6JECee0Vq1aadmyZdq3b59z2unTpzVr1izdf//91x2BLKPX/ux8LXH4999/tWnTJpf6MzJlyhR5enqqUqVKWd7O7YYjNjegUaNGKlSokO677z6VLl1aqamp+u233/Tuu+/K399fzz77rHPZ8uXLa8aMGZo5c6aKFSsmb29vlS9f3jkcZc+ePdW2bVvt27dPb7zxhsLDw13eGNSqVUudOnXSm2++qUOHDql58+ay2+369ddf5evrm+75n23btpWvr6/atm2rc+fO6fPPP5e/v7/GjBmjLl266NixY2rbtq1CQkJ05MgR/f777zpy5IgzPL3xxhtq3LixGjRooL59+yolJUVvvfWW/Pz8nIdbryc1NdV5PnVqaqr++ecfjR49WsePH3cZgrh58+Z64403NGjQIMXFxWnbtm16/fXXFRUVlenf+MjIZ599psaNG6tJkybq1q2bmjRpouDgYB08eFDffvutPv/8c23YsCHNkM/XUr16dQUHB+vJJ5/UoEGD5OnpqWnTpmX5hz7Lly+vWbNmady4capUqdI1T9UpVaqUHn/8cY0ZM0Zubm5q0qSJdu/erYEDByoyMlLPPfdclrZ9LY5P066ld+/e+vrrr1W7dm0999xziomJUWpqqvbu3aslS5aob9++qlatmho2bKjatWurX79+SkpKUuXKlfXTTz9pypQp191G6dKlVbx4cb300ksyxihv3rz69ttvXYakzk6OwDB79uw0b+qCgoJ09913a/bs2fL09HR+p0WSnnvuOX322Wdq1qyZXn/9dRUpUkTz58/Xhx9+qB49eqQ5z/96PD099fnnn6t79+5q27atPvvsM5cjRHny5FHFihU1Z84cubm5udQiXX4j4Pjh1ytfCGvUqKHHH39cjzzyiNavX6/atWvLz89PBw8e1MqVK1W+fHn16NEjS/uJK4WHh2vFihVq1KiR8ztCV58Omx2qVaum5s2bKyYmRsHBwdqyZYumTJmi2NjYa/4+VHbvZ9zc3PTGG2+oe/fuatWqlR577DGdOHFCgwcPzvQpuyNHjtTOnTvVtWtXLV68WK1atVJoaKj+/fdfLV26VBMnTtSMGTMUExOT6T7r3Lmz3nvvPXXu3FlDhgxRdHS0FixYoMWLF6fZ/kcffaQmTZqoUaNG6tq1qyIiInTs2DFt2bJFv/zyS5o3j1fz9PTU0KFD1b59e40aNUqvvPKKRo0apZo1a6pWrVrq0aOHihYtqtOnT2vHjh369ttv03zI1K1bNz3xxBM6cOCAqlevnqXThrPq1Vdf1f79+1WvXj0VKlRIJ06c0KhRo1y+I5kVnTt31gcffKAuXbpo9+7dKl++vFauXKmhQ4eqadOmql+/fg7cixuT2Voz8xhldv+fHsfrS79+/dJ8l0S6HBC+//57TZ06Vc8++6wGDBigb7/9VvXq1dOAAQPk4+Oj8ePHO7/n5zi6ULRoUb3++usaMGCAdu7cqcaNGys4OFiHDh3Szz//7DzSm5FBgwbp0KFDql27tiIiInTixAktWrRIH3/8sdq1a+fyZv/555/XlClTnM9Fu92u4cOH6/z585n6eYWM3hPezGvJyZMn1aBBA3Xs2FHR0dHy8fHR9u3bNWrUKF24cMHlJz/efvtt/fnnn87/8eHDh/Xpp59qyZIlGjx4cLadAZKrcmvUAiubOXOm6dixo4mOjjb+/v7G09PTFC5c2HTq1CnNCBS7d+82DRs2NAEBAUaSy2g5w4cPN0WLFjV2u92UKVPGfPzxx86Rhq6UkpJi3nvvPVOuXDnj5eVlAgMDTWxsrPn222+dy1w53LPD8uXLjb+/v2ncuLE5e/asMcaYFStWmGbNmpm8efMaT09PExERYZo1a5ZmKM+5c+eamJgY4+XlZQoXLmyGDx+ebm3pSW8UpJCQEBMXF2dmz57tsuyFCxfM888/byIiIoy3t7epWLGimTNnjunSpYvLY+UYrejtt9++7vavdO7cOTN69GgTGxtr8uTJYzw8PEzBggVN69atXYbGdYzKdfVIL47RWq4cEnbVqlUmNjbW+Pr6mgIFCpju3bubX375Jc2oQ45hbtNz7Ngx07ZtWxMUFGRsNtt1H9eUlBTz1ltvmZIlSxpPT0+TP39+8/DDD6cZzvlGR0W7lqtHRTPGmDNnzphXXnnFlCpVytmT5cuXN88995zL0MEnTpww3bp1M0FBQcbX19c0aNDAbN26NVOjov3555+mQYMGJiAgwAQHB5t27do5R/u68rYZ3Y/rjbR2tapVqxpJzpHFrtS7d28jydSoUSPNvD179piOHTuafPnyGU9PT1OqVCnz9ttvu4wOdq3+TW843dTUVPPMM88YNzc38/HHH7ss369fPyPJVK5cOc26HCO8eXl5uQy57DBhwgRTrVo14+fnZ3x8fEzx4sVN586dzfr1612Wy8x+Ir3H/cSJE6ZGjRomb968zufStZ4HxqTtr4yGFzbm8shBlStXNsHBwcZut5tixYqZ5557zjk8cEayYz9zdd8ZY8wnn3xioqOjjZeXlylZsqSZMGFCmnVeS3Jyspk8ebKpW7euyZs3r/Hw8DAFChQwTZo0MdOnT3fpocz0mTHG7N+/37Rp08b4+/ubgIAA06ZNG7Nq1ao0+ydjLg+n2759exMSEmI8PT1NWFiYqVu3rhk/frxzmWv9P4y5PIrmlUNh79q1y3Tr1s1EREQYT09PU6BAAVO9enXz5ptvprntyZMnjY+Pj5GUps8zs+1evXqlOyra1a+FxlwenrpJkyYmIiLCeHl5mZCQENO0aVPz448/prvuK6U3Kpoxxhw9etQ8+eSTJjw83Hh4eJgiRYqY/v37m/Pnz7ssp2uMbHY917ptRs+t9F6rM1NrZh+jzO7/r3Tx4kUTEhJi7rnnngzva3JysilUqJApX768c9qPP/5oqlWrZux2uwkLCzMvvPCCczS3q0dvmzNnjomPjzd58uQxdrvdFClSxLRt29ZlhNj0zJ0719SvX9+EhoYaDw8P4+/vb6pWrWpGjx6dZtRAY4zZsWOHadmypcmTJ4/x9fU19erVMxs2bLjmNhyu9Z4ws8/xq50/f950797dlClTxvj7+xsPDw9TqFAh8/DDD6cZ6nru3LmmZs2apkCBAsbDw8MEBASYWrVqOUd8/C+wGXPFcXQAAADgNtWwYUPt3r07U98dwZ2HU9EAAABw2+nTp48qVKigyMhIHTt2TNOmTdPSpUszddo07kwEGwAAANx2UlJS9OqrryoxMVE2m01ly5bVlClT9PDDD+d2abhNcSoaAAAAAMtjuGcAAAAAlkewAQAAAGB5BBsAAAAAlnfbDR6QmpqqAwcOKCAgwPnr4wAAAADuPMYYnT59WgULFnT+MGtGbrtgc+DAAUVGRuZ2GQAAAABuE/v27VOhQoWuucxtF2wCAgIkXS4+T548uVwNAAAAgNxy6tQpRUZGOjPCtdx2wcZx+lmePHkINgAAAAAy9RUVBg8AAAAAYHkEGwAAAACWR7ABAAAAYHm33XdsAAAAYC3GGCUnJyslJSW3S4EFubu7y8PD46Z/6oVgAwAAgBt28eJFHTx4UGfPns3tUmBhvr6+Cg8Pl5eX1w2vg2ADAACAG5Kamqpdu3bJ3d1dBQsWlJeXFz+wjiwxxujixYs6cuSIdu3apejo6Ov+EGdGCDYAAAC4IRcvXlRqaqoiIyPl6+ub2+XAonx8fOTp6ak9e/bo4sWL8vb2vqH1MHgAAAAAbsqNfsIOOGRHD9GFAAAAACyPYAMAAADA8viODQAAALJd0Zfm37Jt7R7e7JZtK6u6du2qEydOaM6cObldiovbta6bwREbAAAA3FHGjx+vgIAAJScnO6edOXNGnp6eqlWrlsuyP/74o2w2m7Zv357tdWzdulU2m01r1651mV6tWjXZ7XaXIbQvXrwoX19f/e9//8v2OtIzadIkBQUFpTvPZrPdloGIYAMAAIA7Snx8vM6cOaP169c7p/34448KCwvTunXrXAJFQkKCChYsqJIlS2ZpGykpKUpNTb3mMqVLl1Z4eLiWL1/unHbmzBn9+uuvCgkJ0apVq5zT165dq3Pnzik+Pj5LdeSGS5cu5cp2CTYAAAC4o5QqVUoFCxZUQkKCc1pCQoJatGih4sWLuwSKhIQExcfH6/jx4+rcubOCg4Pl6+urJk2a6K+//nIu5zjCMW/ePJUtW1Z2u1179uxJs+0NGzYoJCREQ4YMkSTVqVPHpY4ff/xRJUuW1P3335+mvoiICEVHR0uSJk6cqDJlysjb21ulS5fWhx9+6LKdf/75Rx06dFBwcLDy5cunFi1aaPfu3Rk+JlfXlVm7d++WzWbTF198oTp16sjb21tTp07Vnj17dN999yk4OFh+fn666667tGDBgiytO6sINgAAALjj1KlTx+VIyfLly1WnTh3FxcU5p1+8eFGrV69WfHy8unbtqvXr12vu3LlavXq1jDFq2rSpy9GJs2fPatiwYfrkk0+0efNmhYSEuGwzISFB9erV02uvvaYBAwZIunz0aOXKlc7T4tKrwzHdcbTm448/1oABAzRkyBBt2bJFQ4cO1cCBAzV58mRnHfHx8fL399cPP/yglStXyt/fX40bN9bFixfTPBbp1ZVVL774op555hlt2bJFjRo1Uq9evXThwgX98MMP2rRpk9566y35+/vf0Lozi8EDAAAAcMepU6eOnnvuOSUnJ+vcuXP69ddfVbt2baWkpGj06NGSpDVr1ujcuXOqWbOmunfvrp9++knVq1eXJE2bNk2RkZGaM2eO2rVrJ+nyKVgffvih7r777jTb++abb9SpUyd99NFHevDBB13qSEpK0rp16xQbG6uEhAS98MILql27tjp16qSzZ8/Kw8NDa9as0dixYyVJb7zxht599121bt1akhQVFaU///xTH330kbp06aIZM2bIzc1Nn3zyiWw2m6TLR3iCgoKUkJCghg0bXrcuSTp58mSmw0jv3r2d9UjS3r171aZNG5UvX16SVKxYsUyt52YQbAAAAHDHiY+PdwaK48ePq2TJkgoJCVFcXJw6deqkpKQkJSQkqHDhwtq2bZs8PDxUrVo15+3z5cunUqVKacuWLc5pXl5eiomJSbOttWvXat68efryyy/VqlUrl3nR0dEqVKiQEhISdNddd+nXX39VXFycQkJCFBUVpZ9++kl2u13nzp1T3bp1deTIEe3bt0+PPvqoHnvsMed6kpOTFRgYKOnyaWU7duxQQECAy7bOnz+vv//+O1N1SVJAQIB++eWXNNMdp8NdqXLlyi7Xn3nmGfXo0UNLlixR/fr11aZNm3Qfm+xEsAEAAMAdp0SJEipUqJCWL1+u48ePKy4uTpIUFhbmDBTLly9X3bp1ZYxJdx3GGOcREUny8fFxue5QvHhx5cuXTxMmTFCzZs3k5eXlMt9xWlxMTIyio6Odp7A5Tkez2+0qUqSIihYtqkOHDkm6fDralUFLktzd3SVJqampqlSpkqZNm5amlgIFCmS6Ljc3N5UoUSL9B/Aqfn5+Lte7d++uRo0aaf78+VqyZImGDRumd999V08//XSm1ncj+I4NAAAA7kjx8fFKSEhQQkKC6tSp45weFxenxYsXa82aNYqPj1fZsmWVnJzsMizz0aNHtX37dpUpU+a628mfP7+WLVumv//+Wx06dEgzalh8fLxWrVqlpUuXpqnDUV/dunUlSaGhoYqIiNDOnTtVokQJl0tUVJQkqWLFivrrr78UEhKSZhnHUZ3M1HWzIiMj9eSTT2rWrFnq27evPv7442xd/9U4YpORwYHXX+a/bPDJ3K4g993pPSDRB/QAPUAP0AP0wH+6B+Lj49WrVy9dunTJecRGuhwoevToofPnzys+Pl6R7v+qRaM6euyRTvrorQEK8PPTS8NGKyI0v1pUKSwd+FU6vkcyKZf/vtLZY9L50wpJ/kfLpo9SfLvH9WDLJpoxbpg8PC6/FY8vG6KkpCRN+PQTfTziFec64krlU9f16+Tu7q5ureo6pw/u3U3PDByqPOaUmsTX0IWLF7V+4586fuK0+jzxsB6qe5feDgpQi8b19PoLT6pQeKj2/pOoWQuX6YUnO6tQwdDr13Xl/SlYIcuPbe/evdWkSROVLFlSx48f17JlyzIVAm8GwQYAAADZbvfwZrldwnXFx8fr3LlzKl26tEJDQ53T4+LidPr0aRUvXlyRkZHSgX81ceRgPfvq22re5VldvJis2vdW0IIpY+Tp6Znp7YWF5NeyLz5SnbaP66GnBmj6B0Pl7u6uqMIRKlIoXHv2H1RcbCXn8hHhISocEaa/d+9XfPUqzundO7aSr4+33h73mfoNGSU/Xx+VL11Cvbt3lCT5+vjoh1mf6MUho9W6+/M6nXRWEWEhqlezivIE+GWqrpuVkpKiXr16af/+/cqTJ48aN26s995776bXey02k9FJg7nk1KlTCgwM1MmTJ5UnT57cK+RO/4TmP/zpTKbd6T0g0Qf0AD1AD9AD9MA1e+D8+fPatWuXoqKi5O3tfQuLusWuPgpzp7mBIzZZlVEvZSUb8B0bAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJbnkdsFAAAA4D9ocOAt3NbJW7et6xj87njNWZSg35bOyO1S7jgcsQEAAMAdKTExUU8//bSKFSsmu92uyMhI3Xffffr+++9vaR22iIrOi390Dd1dv4MmzZybrdvYve+AbBEV9dsf29LMq9P2MfV+9e1s3V5u4IgNAAAA7ji7d+9WjRo1FBQUpBEjRigmJkaXLl3S4sWL1atXL23duvWW1jNx5GA1jq+upLPnNHPuEj3SZ7DCQ/OrUZ3qt7SO9Fy8eFFeXl65XcZ1ccQGAAAAd5yePXvKZrPp559/Vtu2bVWyZEnddddd6tOnj9asWSNJ2rt3r1q0aCH/6BrKU6qW2j/xog4dOeqynuFjJyr07voKKFlTj/Z9TecvXEyzrYkzv1GZuNbyLnavStdurQ8nfZFmmaDAAIWF5FfxopF6+ZlHlTcoUEtWrHHOP3nqtB7v94ZCYuopT6laqtvucf2+ebskaduO3bJFVNTWHbtc1jnyo6kqWq2ZjDFZemyKVmumN9//RF17D1Jg6dp67LHHdPHiRT311FMKDw+Xt7e3ihYtqmHDhmVpvTmNYAMAAIA7yrFjx7Ro0SL16tVLfn5+aeYHBQXJGKOWLVvq2LFjWvH1x1r6+Yf6e88+dejxknO5L+Yu0aB3x2vIi720fsFUhYfk14eTv3RZ18fTZmnAWx9oyIu9tCXhaw19qZcGvj1Ok7/4Nt3aUlJS9MXcJTp24qQ8PS+fXGWMUbPOzyrx8FEtmDJGGxZOU8XyZVSvw5M6dvykSpUoqkoxZTRt1kKXdU2fs1AdWzaWzWbL8mP09vjPVK50cW1YOFUDBw7U6NGjNXfuXH3xxRfatm2bpk6dqqJFi2Z5vTmJU9EAAABwR9mxY4eMMSpdunSGy3z33XfauHGjdu3apUj3fyVJU0a/qbvi22rdb5tV5Z679P4n09WtQwt179hKkvTmi7303Y9rXY7avPH+J3r31T5q3bSeJCmqcIT+3L5LH039Wl3a3+dc7sFeL8vdzU3nL1xUSkqK8gYFqvuDLSVJy39ap01bd+jw79/Jbr98Stg7rz6nOYuX66v53+nxh9vooVZNNHbSF3qjX09J0va/92jDxi36bNQbLvereotH5ObmGnTOnb+ge8qWdJlWt0YVPf9k58tXCpbQ3r17FR0drZo1a8pms6lIkSKZeqxvJYINAAAA7iiOU7OudSRjy5YtioyMVGRkpHTgcrApW7KYggIDtOWvXapyz13asmOXnuzU1uV2sZVitHzVeknSkaPHte9Aoh7t+7oee+H/AkZySooCA/xdbvfeoL6qX6uq9h04pD6vjdRzjz2kElGFJUkbNm3RmaSzylcu3uU2585f0N979kuSHmjRSC+8OUprNmzUvZViNG32At1zVymVLVnM5TYzxw1Tmegol2kPPf1KmvtfOaaMy/WuXbuqQYMGKlWqlBo3bqzmzZurYcOGGT5+uYFgAwAAgDtKdHS0bDabtmzZopYtW6a7jDEm3eBzeXrmtpOamipJ+vjtV1StQjmXee7u7i7Xw0LyqURUYZWIKqwvP3pLFRp1VOW7y6psyWJKTTUKD8mvhK/+l2YbQYEBkqTw0AKKr15Z0+cs0r2VYvT5nMV64uE2aZaPLBjmDEwOPt72NMv5+fq4XK9YsaJ27dqlhQsX6rvvvlP79u1Vv359ffXVV5l4JG4NvmMDAACAO0revHnVqFEjffDBB0pKSkoz/8SJEypbtqz27t2rffv2Oaf/uX2nTp46ozLRl4+ClCkRpTW/bHK57ZXXQwvkU0RYiHbu+ccZWhyXqMIRGdZXIqqw2jStp/7DxkiSKpYvrcQjR+Xh4ZFmPfnzBjtv91CrJpo5d4lWr/9df+/ZrwdaNLqxBygDefLkUYcOHfTxxx9r5syZ+vrrr3Xs2LFs3cbNINgAAADgjvPhhx8qJSVFVatW1ddff62//vpLW7Zs0ejRoxUbG6v69esrJiZGDz30kH7ZtEU///qHOj87UHGxlVT57rKSpGcffVATZn6jCTPmaPvfezTonXHavH2ny3YG931Cw8ZO1KhPpmv733u0actfmjjzG438aOo16+v7xMP6dukPWv/7n6pfq5piK5VXy259tDhhlXbvO6BV637XK299oPW//+m8TeumdXXqTJJ69B+m+OqVFREekm2P13vvvacZM2Zo69at2r59u7788kuFhYUpKCgo27ZxszgVDQAAANlv8MncruCaoqKi9Msvv2jIkCHq27evDh48qAIFCqhSpUoaN26cbDab5syZo6efflq1W3eXm5ubGteprjFv9nOuo0OLRvp7z369OGS0zl+4qDZN66lH57ZanLDauUz3jq3k6+Ott8d9pn5DRsnP10flS5dQ7+4dr1lf+TLRql+rml59Z5wWTBmjBVPGaMBbH6hb39d05OhxhRXIr9r3VlBo/rzO2+QJ8Nd99Wvry3lLNWHkoGx9vPz9/fXWW2/pr7/+kru7u6pUqaIFCxbIze32OU5iM1kd2DqHnTp1SoGBgTp58qTy5MmTe4UMDsy9bd8ObvOd0S1xp/eARB/QA/QAPUAP0APX7IHz589r165dioqKkre39y0s6hY78GtuV5C7ClbI8U1k1EtZyQa3T8QCAAAAgBtEsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAA3JTbbCwqWFB29BDBBgAAADfE09NTknT27NlcrgRW5+ghR0/dCH7HBgAAADfE3d1dQUFBOnz4sCTJ19dXNpstl6vKAcl3+BGp8+dzbNXGGJ09e1aHDx9WUFCQ3N3db3hdBBsAAADcsLCwMElyhpv/pBNHcruC3JW0K8c3ERQU5OylG0WwAQAAwA2z2WwKDw9XSEiILl26lNvl5Iyx7XK7gtz11PocXb2np+dNHalxINgAAADgprm7u2fLm9Pb0pl9uV1B7vL2zu0KMoXBAwAAAABYHsEGAAAAgOXdVLAZNmyYbDabevfu7ZxmjNHgwYNVsGBB+fj4qE6dOtq8efPN1gkAAAAAGbrhYLNu3Tr973//U0xMjMv0ESNGaOTIkRo7dqzWrVunsLAwNWjQQKdPn77pYgEAAAAgPTcUbM6cOaOHHnpIH3/8sYKDg53TjTF6//33NWDAALVu3VrlypXT5MmTdfbsWU2fPj3bigYAAACAK91QsOnVq5eaNWum+vXru0zftWuXEhMT1bBhQ+c0u92uuLg4rVq1Kt11XbhwQadOnXK5AAAAAEBWZHm45xkzZuiXX37RunXr0sxLTEyUJIWGhrpMDw0N1Z49e9Jd37Bhw/Taa69ltYwcV/T8nX2EaXduF3AbuNN7QKIP6AF6gB6gB+gBekCiD3bndgGZlKUjNvv27dOzzz6rqVOnyvsa41nbbDaX68aYNNMc+vfvr5MnTzov+/bd4eOEAwAAAMiyLB2x2bBhgw4fPqxKlSo5p6WkpOiHH37Q2LFjtW3bNkmXj9yEh4c7lzl8+HCaozgOdrtddrv9RmoHAAAAAElZPGJTr149bdq0Sb/99pvzUrlyZT300EP67bffVKxYMYWFhWnp0qXO21y8eFErVqxQ9erVs714AAAAAJCyeMQmICBA5cqVc5nm5+enfPnyOaf37t1bQ4cOVXR0tKKjozV06FD5+vqqY8eO2Vc1AAAAAFwhy4MHXE+/fv107tw59ezZU8ePH1e1atW0ZMkSBQQEZPemAAAAAEBSNgSbhIQEl+s2m02DBw/W4MGDb3bVAAAAAJApN/Q7NgAAAABwOyHYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAyyPYAAAAALA8gg0AAAAAy8tSsBk3bpxiYmKUJ08e5cmTR7GxsVq4cKFzvjFGgwcPVsGCBeXj46M6depo8+bN2V40AAAAAFwpS8GmUKFCGj58uNavX6/169erbt26atGihTO8jBgxQiNHjtTYsWO1bt06hYWFqUGDBjp9+nSOFA8AAAAAUhaDzX333aemTZuqZMmSKlmypIYMGSJ/f3+tWbNGxhi9//77GjBggFq3bq1y5cpp8uTJOnv2rKZPn55T9QMAAADAjX/HJiUlRTNmzFBSUpJiY2O1a9cuJSYmqmHDhs5l7Ha74uLitGrVqgzXc+HCBZ06dcrlAgAAAABZkeVgs2nTJvn7+8tut+vJJ5/U7NmzVbZsWSUmJkqSQkNDXZYPDQ11zkvPsGHDFBgY6LxERkZmtSQAAAAAd7gsB5tSpUrpt99+05o1a9SjRw916dJFf/75p3O+zWZzWd4Yk2balfr376+TJ086L/v27ctqSQAAAADucB5ZvYGXl5dKlCghSapcubLWrVunUaNG6cUXX5QkJSYmKjw83Ln84cOH0xzFuZLdbpfdbs9qGQAAAADgdNO/Y2OM0YULFxQVFaWwsDAtXbrUOe/ixYtasWKFqlevfrObAQAAAIAMZemIzcsvv6wmTZooMjJSp0+f1owZM5SQkKBFixbJZrOpd+/eGjp0qKKjoxUdHa2hQ4fK19dXHTt2zKn6AQAAACBrwebQoUPq1KmTDh48qMDAQMXExGjRokVq0KCBJKlfv346d+6cevbsqePHj6tatWpasmSJAgICcqR4AAAAAJCyGGw+/fTTa8632WwaPHiwBg8efDM1AQAAAECW3PR3bAAAAAAgtxFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5RFsAAAAAFgewQYAAACA5WUp2AwbNkxVqlRRQECAQkJC1LJlS23bts1lGWOMBg8erIIFC8rHx0d16tTR5s2bs7VoAAAAALhSloLNihUr1KtXL61Zs0ZLly5VcnKyGjZsqKSkJOcyI0aM0MiRIzV27FitW7dOYWFhatCggU6fPp3txQMAAACAJHlkZeFFixa5XJ84caJCQkK0YcMG1a5dW8YYvf/++xowYIBat24tSZo8ebJCQ0M1ffp0PfHEE9lXOQAAAAD8fzf1HZuTJ09KkvLmzStJ2rVrlxITE9WwYUPnMna7XXFxcVq1alW667hw4YJOnTrlcgEAAACArLjhYGOMUZ8+fVSzZk2VK1dOkpSYmChJCg0NdVk2NDTUOe9qw4YNU2BgoPMSGRl5oyUBAAAAuEPdcLB56qmntHHjRn3++edp5tlsNpfrxpg00xz69++vkydPOi/79u270ZIAAAAA3KGy9B0bh6efflpz587VDz/8oEKFCjmnh4WFSbp85CY8PNw5/fDhw2mO4jjY7XbZ7fYbKQMAAAAAJGXxiI0xRk899ZRmzZqlZcuWKSoqymV+VFSUwsLCtHTpUue0ixcvasWKFapevXr2VAwAAAAAV8nSEZtevXpp+vTp+uabbxQQEOD83kxgYKB8fHxks9nUu3dvDR06VNHR0YqOjtbQoUPl6+urjh075sgdAAAAAIAsBZtx48ZJkurUqeMyfeLEierataskqV+/fjp37px69uyp48ePq1q1alqyZIkCAgKypWAAAAAAuFqWgo0x5rrL2Gw2DR48WIMHD77RmgAAAAAgS27qd2wAAAAA4HZAsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJZHsAEAAABgeQQbAAAAAJaX5WDzww8/6L777lPBggVls9k0Z84cl/nGGA0ePFgFCxaUj4+P6tSpo82bN2dXvQAAAACQRpaDTVJSku6++26NHTs23fkjRozQyJEjNXbsWK1bt05hYWFq0KCBTp8+fdPFAgAAAEB6PLJ6gyZNmqhJkybpzjPG6P3339eAAQPUunVrSdLkyZMVGhqq6dOn64knnri5agEAAAAgHdn6HZtdu3YpMTFRDRs2dE6z2+2Ki4vTqlWr0r3NhQsXdOrUKZcLAAAAAGRFtgabxMRESVJoaKjL9NDQUOe8qw0bNkyBgYHOS2RkZHaWBAAAAOAOkCOjotlsNpfrxpg00xz69++vkydPOi/79u3LiZIAAAAA/Idl+Ts21xIWFibp8pGb8PBw5/TDhw+nOYrjYLfbZbfbs7MMAAAAAHeYbD1iExUVpbCwMC1dutQ57eLFi1qxYoWqV6+enZsCAAAAAKcsH7E5c+aMduzY4by+a9cu/fbbb8qbN68KFy6s3r17a+jQoYqOjlZ0dLSGDh0qX19fdezYMVsLBwAAAACHLAeb9evXKz4+3nm9T58+kqQuXbpo0qRJ6tevn86dO6eePXvq+PHjqlatmpYsWaKAgIDsqxoAAAAArpDlYFOnTh0ZYzKcb7PZNHjwYA0ePPhm6gIAAACATMuRUdEAAAAA4FYi2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMsj2AAAAACwPIINAAAAAMvLsWDz4YcfKioqSt7e3qpUqZJ+/PHHnNoUAAAAgDtcjgSbmTNnqnfv3howYIB+/fVX1apVS02aNNHevXtzYnMAAAAA7nA5EmxGjhypRx99VN27d1eZMmX0/vvvKzIyUuPGjcuJzQEAAAC4w3lk9wovXryoDRs26KWXXnKZ3rBhQ61atSrN8hcuXNCFCxec10+ePClJOnXqVHaXliWpF87m6vZzW24//reDO70HJPqAHqAH6AF6gB6gByT6IDd7wLFtY8x1l832YPPvv/8qJSVFoaGhLtNDQ0OVmJiYZvlhw4bptddeSzM9MjIyu0tDFgS+n9sV4HZAH4AeAD0AegC3Qw+cPn1agYGB11wm24ONg81mc7lujEkzTZL69++vPn36OK+npqbq2LFjypcvX7rL3wlOnTqlyMhI7du3T3ny5MntcpAL6AHQA5DoA9ADoAeMMTp9+rQKFix43WWzPdjkz59f7u7uaY7OHD58OM1RHEmy2+2y2+0u04KCgrK7LEvKkyfPHdnA+D/0AOgBSPQB6AHc2T1wvSM1Dtk+eICXl5cqVaqkpUuXukxfunSpqlevnt2bAwAAAICcORWtT58+6tSpkypXrqzY2Fj973//0969e/Xkk0/mxOYAAAAA3OFyJNh06NBBR48e1euvv66DBw+qXLlyWrBggYoUKZITm/vPsdvtGjRoUJpT9HDnoAdAD0CiD0APgB7ICpvJzNhpAAAAAHAby5Ef6AQAAACAW4lgAwAAAMDyCDYAAAAALI9gAwAAAMDyCDYAAAAALI9gAwAAAMDyCDYAAAAALI9gcxtYt26dHnroIUVFRcnHx0e+vr6KiorSQw89pPXr1+d2ebgF6AHQA5DoA9ADoAduBj/QmcvmzJmj9u3bq169emrUqJFCQ0NljNHhw4e1ZMkSff/99/riiy/UokWL3C4VOYQeAD0AiT4APQB64KYZ5Kq77rrLDBs2LMP5w4cPN2XLlr2FFeFWowdAD8AY+gD0AOiBm8URm1zm7e2tjRs3qmTJkunO37Ztm+6++26dP3/+FleGW4UeAD0AiT4APQB64GbxHZtcVrx4cc2ZMyfD+d98842KFSt26wrCLUcPgB6ARB+AHgA9cLM8cruAO93rr7+uBx54QCtWrFDDhg0VGhoqm82mxMRELV26VEuWLNGMGTNyu0zkIHoA9AAk+gD0AOiBm8WpaLeB1atXa9SoUVq9erUSExMlSWFhYYqNjdWzzz6r2NjYXK4QOY0eAD0AiT4APQB64GYQbAAAAABYHt+xAQAAAGB5BJvb3Msvv6xu3brldhnIRfQA6AFI9AHoAdAD18PgAbe5f/75R/v27cvtMpCL6AHQA5DoA9ADoAeuh+/YAAAAALA8TkUDAAAAYHmcinYbSEpK0vTp07Vq1SolJibKZrMpNDRUNWrU0IMPPig/P7/cLhG56NChQ/roo4/06quv5nYpyGH79+9XUFCQ/P39XaZfunRJq1evVu3atXOpMtwqR48e1caNG3X33Xcrb968+vfff/Xpp5/qwoULateuncqUKZPbJSIXFCtWTIsXL1Z0dHRul4Jb7NKlS5o/f77++usvhYeHq1WrVrwvvAZORctlf/75pxo0aKCzZ88qLi5OoaGhMsbo8OHDWrFihfz8/LRkyRKVLVs2t0tFLvn9999VsWJFpaSk5HYpyCEHDx5UixYttGHDBtlsNj300EP64IMPnAHn0KFDKliwID3wH/fzzz+rYcOGOnXqlIKCgrR06VK1a9dOHh4eMsbon3/+0cqVK1WxYsXcLhU5ZPTo0elO79Onj/r166ewsDBJ0jPPPHMry8ItVL16dS1YsEBBQUE6cuSI6tWrp23btqlIkSLat2+fQkJCtGrVKkVEROR2qbclgk0ui4+PV1hYmCZPniwvLy+XeRcvXlTXrl118OBBLV++PJcqRE7buHHjNedv3bpVDz74IG9q/8O6dOmi7du3a8yYMTpx4oT69+8vY4yWLl2q4OBgHTp0SOHh4UpNTc3tUpGDGjRooKJFi2rkyJH66KOPNGrUKDVu3Fgff/yxJKl79+46evSoZs+encuVIqe4ubkpIiJCHh6uJ9Ts2bNHBQsWlKenp2w2m3bu3JlLFSKnubm5KTExUSEhIXr88ce1bt06LVy4UGFhYTp69Kjuv/9+lS5dWp9++mlul3pbItjkMl9fX61fvz7DIzJ//PGHqlatqrNnz97iynCruLm5yWazKb2nomO6zWYj2PyHRUREaPbs2apataok6cKFC+rQoYP27Nmj77//XpcuXeKIzR0gb968+umnn1SmTBldunRJ3t7eWr16tbMvfv31V913333av39/LleKnPLEE0/o559/1vTp011OO/T09NTvv//O2Rt3gCuDTalSpTRy5Eg1a9bMOT8hIUGPPPKIdu3alYtV3r4YPCCXBQcH66+//spw/o4dOxQcHHwLK8Ktli9fPn388cfatWtXmsvOnTs1b9683C4ROezkyZMuz3O73a6vvvpKRYsWVXx8vA4fPpyL1eFWuXjxonx8fCRdfiPr6+ur/PnzO+fny5dPR48eza3ycAt89NFHGjRokBo1aqSxY8fmdjnIJTabTZJ04sQJRUVFucyLiorSwYMHc6MsS2DwgFz22GOPqUuXLnrllVfUoEEDhYaGymazKTExUUuXLtXQoUPVu3fv3C4TOahSpUo6cOCAihQpku78EydOpHs0B/8dxYoV08aNG12+GOzh4aEvv/xS7dq1U/PmzXOxOtwqkZGR2rlzp4oWLSpJmjFjhsLDw53zDx486BJ08N/UsmVLValSRZ07d9b8+fM1ceLE3C4Jt1jXrl1lt9t16dIl7dmzx+VI3cGDBxUUFJR7xd3mCDa5bPDgwfLx8dHIkSPVr18/Z0o3xigsLEwvvfSS+vXrl8tVIic98cQTSkpKynB+4cKFeWH7j2vSpIn+97//qU2bNi7THeGmTZs2nH50B3jggQdcjs5defqJJM2dO9d5Whr+2yIiIvTdd99p+PDhqlChAh9u3UG6dOni/LtFixY6c+aMy/yvv/5a99xzzy2uyjr4js1tZNeuXUpMTJQkhYWFpTn8COC/KTk5WWfPnlWePHnSnZ+SkqL9+/dneFQPd4azZ8/K3d1ddrs9t0vBLbRhwwatXLlSnTt35tR0KCkpSe7u7vL29s7tUm5LfMfmNrBlyxZNnDhRFy9eVGxsrIKDgzVixAh169ZNy5Yty+3ycAs4emDr1q2SLo+E1qNHD3rgDuHh4aF//vknwx5YsWIFoeYOca19wZo1awg1d4Cre8DPz09bt25V3759eT24Qzh6YNu2bZJc9wNr164l1FyLQa5auHCh8fLyMnnz5jXe3t5m4cKFpkCBAqZ+/fqmXr16xsPDw3z//fe5XSZyED0AegDG0AegB0AP3CyCTS6LjY01AwYMMMYY8/nnn5vg4GDz8ssvO+e//PLLpkGDBrlVHm4BegD0AIyhD0APgB64WXzHJpcFBgZqw4YNKlGihFJTU2W327V27VrnL0v/8ccfql+/vvO7N/jvoQdAD0CiD0APgB64WXzH5jbi5uYmb29vl2H8AgICdPLkydwrCrcUPQB6ABJ9AHoA9MCNINjksqJFi2rHjh3O66tXr1bhwoWd1/ft2+fyOwb476EHQA9Aog9AD4AeuFn8jk0u69Gjh1JSUpzXy5Ur5zJ/4cKFqlu37q0uC7cQPQB6ABJ9AHoA9MDN4js2AAAAACyPU9EAAAAAWB7BBgAAAIDlEWwAAAAAWB7BBgAAAIDlEWwAAAAAWB7BBgBwy61atUru7u5q3LhxbpcCAPiPYLhnAMAt1717d/n7++uTTz7Rn3/+6fIDdAAA3AiO2AAAbqmkpCR98cUX6tGjh5o3b65Jkya5zJ87d66io6Pl4+Oj+Ph4TZ48WTabTSdOnHAus2rVKtWuXVs+Pj6KjIzUM888o6SkpFt7RwAAtxWCDQDglpo5c6ZKlSqlUqVK6eGHH9bEiRPlOHlg9+7datu2rVq2bKnffvtNTzzxhAYMGOBy+02bNqlRo0Zq3bq1Nm7cqJkzZ2rlypV66qmncuPuAABuE5yKBgC4pWrUqKH27dvr2WefVXJyssLDw/X555+rfv36eumllzR//nxt2rTJufwrr7yiIUOG6Pjx4woKClLnzp3l4+Ojjz76yLnMypUrFRcXp6SkJHl7e+fG3QIA5DKO2AAAbplt27bp559/1gMPPCBJ8vDwUIcOHTRhwgTn/CpVqrjcpmrVqi7XN2zYoEmTJsnf3995adSokVJTU7Vr165bc0cAALcdj9wuAABw5/j000+VnJysiIgI5zRjjDw9PXX8+HEZY2Sz2Vxuc/WJBampqXriiSf0zDPPpFk/gxAAwJ2LYAMAuCWSk5P12Wef6d1331XDhg1d5rVp00bTpk1T6dKltWDBApd569evd7lesWJFbd68WSVKlMjxmgEA1sF3bAAAt8ScOXPUoUMHHT58WIGBgS7zBgwYoAULFmjWrFkqVaqUnnvuOT366KP67bff1LdvX+3fv18nTpxQYGCgNm7cqHvvvVePPPKIHnvsMfn5+WnLli1aunSpxowZk0v3DgCQ2/iODQDglvj0009Vv379NKFGunzE5rffftPx48f11VdfadasWYqJidG4ceOco6LZ7XZJUkxMjFasWKG//vpLtWrVUoUKFTRw4ECFh4ff0vsDALi9cMQGAHBbGzJkiMaPH699+/bldikAgNsY37EBANxWPvzwQ1WpUkX58uXTTz/9pLfffpvfqAEAXBfBBgBwW/nrr7/05ptv6tixYypcuLD69u2r/v3753ZZAIDbHKeiAQAAALA8Bg8AAAAAYHkEGwAAAACWR7ABAAAAYHkEGwAAAACWR7ABAAAAYHkEGwAAAACWR7ABAAAAYHkEGwAAAACW9/8At/UbgP7sv/UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT WorkWeekHrs, CodeRevHrs, Age FROM master\n",
    "WHERE Age BETWEEN 30 AND 35\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "df1 = df.groupby('Age').median()\n",
    "\n",
    "df1.plot(kind='bar', figsize=(10, 6), stacked=True)\n",
    "\n",
    "plt.title('Stacked Bar Chart of Median WorkWeekHrs and CodeRevHrs for Those Age 30 to 35')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizing comparison of data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Line Chart\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot the median `ConvertedComp` for all ages from 45 to 60.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT ConvertedComp, Age FROM master\n",
    "WHERE Age BETWEEN 45 AND 60\n",
    "\"\"\"\n",
    "df = pd.read_sql_query(QUERY,conn)\n",
    "df1 = df.groupby('Age').median()\n",
    "\n",
    "df1.plot(kind='line', figsize=(20, 6))\n",
    "\n",
    "plt.title('Median ConvertedComp for Those Age 45 to 60')\n",
    "plt.ylabel('ConvertedComp')\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bar Chart\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a horizontal bar chart using column `MainBranch.`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# your code goes here\n",
    "\n",
    "QUERY = \"\"\"\n",
    "SELECT MainBranch, COUNT(*) as MainBranch\n",
    "from master\n",
    "group by MainBranch\n",
    "\"\"\"\n",
    "\n",
    "df=pd.read_sql_query(QUERY,conn)\n",
    "\n",
    "df.plot(kind='barh')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Close the database connection.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Authors\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ramesh Sannareddy\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Other Contributors\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Rav Ahuja\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Change Log\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "| Date (YYYY-MM-DD) | Version | Changed By        | Change Description                 |\n",
    "| ----------------- | ------- | ----------------- | ---------------------------------- |\n",
    "| 2020-10-17        | 0.1     | Ramesh Sannareddy | Created initial version of the lab |\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " Copyright © 2020 IBM Corporation. This notebook and its source code are released under the terms of the [MIT License](https://cognitiveclass.ai/mit-license?utm_medium=Exinfluencer&utm_source=Exinfluencer&utm_content=000026UJ&utm_term=10006555&utm_id=NA-SkillsNetwork-Channel-SkillsNetworkCoursesIBMDA0321ENSkillsNetwork928-2023-01-01&cm_mmc=Email_Newsletter-_-Developer_Ed%2BTech-_-WW_WW-_-SkillsNetwork-Courses-IBM-DA0321EN-SkillsNetwork-21426264&cm_mmca1=000026UJ&cm_mmca2=10006555&cm_mmca3=M12345678&cvosrc=email.Newsletter.M12345678&cvo_campaign=000026UJ).\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}