diff --git a/Soraia/DadosHoras.csv b/Soraia/DadosHoras.csv new file mode 100644 index 0000000..00b7556 --- /dev/null +++ b/Soraia/DadosHoras.csv @@ -0,0 +1,25 @@ +Hora,VENTO,TEMPERATURA,PRESSAO,PRECIPTACAO +00,1.5347150259067357,21.763639832125143,962.0728897338404,374.4 +01,1.6054021121039805,21.122827346465815,961.3016634429399,337.0 +02,1.483947157726181,20.665825688073397,962.9538520213578,487.8 +03,1.426293271100739,20.170653789004458,961.4847124304266,404.2 +04,1.3734502923976608,19.83814623338257,961.1079734219269,408.0 +05,1.3641105488516934,19.58221153846154,960.2399483585393,362.8 +06,1.3651845970623264,19.392464204973624,960.7759684091764,391.8 +07,1.2932474629195942,18.97025316455696,960.786895011169,551.4 +08,1.313283699059561,18.916044776119403,961.0587817638266,406.2 +09,1.2419681057954104,18.94470284237726,961.3613653136531,362.8 +10,1.4297257769652651,19.6926905673512,962.0185674547982,331.2 +11,1.8211888111888113,21.46132578281146,964.2766899766899,347.8 +12,2.2390503189227497,23.34516672280229,963.3867518493612,256.2 +13,2.38478883321403,24.829584599797364,965.4566745522135,260.8 +14,2.52451333813987,25.906612133606,963.6499316939891,252.6 +15,2.5568212824010916,27.025032637075718,963.8451120493667,323.8 +16,2.542911744266852,27.438210841370136,961.3747343957504,507.6 +17,2.4842141863699583,27.756082200861787,960.155901856764,536.8 +18,2.4824175824175825,27.627202680067,960.9855994641661,479.4 +19,2.3858755005460504,27.108557625948933,959.2343545611014,618.6 +20,2.1864992721979624,26.247936177592788,959.7346541536323,616.6 +21,1.7897227356746765,24.636204481792717,961.0435162530583,557.8 +22,1.6318563789152023,23.056170367673825,959.2438846294268,661.0 +23,1.5682316118935837,22.342056074766354,961.3903370786518,392.0 diff --git a/Soraia/Maria_qtdd_agua.csv b/Soraia/Maria_qtdd_agua.csv new file mode 100644 index 0000000..2797198 --- /dev/null +++ b/Soraia/Maria_qtdd_agua.csv @@ -0,0 +1,25 @@ +Dia,copos +0,0 +1,0 +2,0 +3,0 +4,0 +5,500 +6,0 +7,200 +8,200 +9,0 +10,300 +11,250 +12,200 +13,250 +14,0 +15,250 +16,0 +17,250 +18,0 +19,200 +20,200 +21,200 +22,0 +23,0 diff --git a/Soraia/Soraia_s011.ipynb b/Soraia/Soraia_s011.ipynb new file mode 100644 index 0000000..3586b44 --- /dev/null +++ b/Soraia/Soraia_s011.ipynb @@ -0,0 +1,403 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np #importando biblioteca" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "data = np.genfromtxt('temperatura_PE.csv', delimiter=',', skip_header=1) #importando os dados\n" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [], + "source": [ + "data = np.transpose(data) #transpondo os dados" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0. , 1. , 2. , 3. , 4. ,\n", + " 5. , 6. , 7. , 8. , 9. ,\n", + " 10. , 11. , 12. , 13. , 14. ,\n", + " 15. , 16. , 17. , 18. , 19. ,\n", + " 20. , 21. , 22. , 23. ],\n", + " [24.01187025, 23.51813311, 23.05712411, 22.6396529 , 22.25095564,\n", + " 21.91769249, 21.62634448, 21.3683532 , 21.15036675, 21.40047735,\n", + " 22.69491435, 24.27250625, 25.75271906, 27.07737767, 28.14563227,\n", + " 29.00884914, 29.56114329, 29.73186232, 29.505873 , 28.8045621 ,\n", + " 27.61490988, 26.26287676, 25.29598776, 24.58622449]])" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data #printando para melhor visualização" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "#atribuir valores aos parâmetros dos dados\n", + "#seguindo os índices\n", + "\n", + "hora = data[0]\n", + "temperatura_hora = data[1]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(25.05235035988917)" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#média\n", + "\n", + "np.mean(temperatura_hora)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(24.429365371461245)" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#mediana\n", + "\n", + "np.median(temperatura_hora)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(2.924118557254436)" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#desvio padrão\n", + "\n", + "np.std(temperatura_hora)" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "A temperatura mínima registrada foi: 21.15°C.\n", + " O primeiro quartil é igual a: 22.54°C.\n", + " O segundo quartil é igual a: 24.43°C.\n", + " O terceiro quartil é igual a: 27.75°C.\n", + " A temperatura máxima registrada foi: 29.73°C.\n", + "\n" + ] + } + ], + "source": [ + "#quartis e min e máx\n", + "min = np.min(temperatura_hora)\n", + "q1 = np.quantile(temperatura_hora, 0.25)\n", + "q2 = np.quantile(temperatura_hora, 0.5)\n", + "q3 = np.quantile(temperatura_hora, 0.75)\n", + "max = np.max(temperatura_hora)\n", + "\n", + "print(f\"A temperatura mínima registrada foi: {min:.2f}°C.\\n O primeiro quartil é igual a: {q1:.2f}°C.\\n O segundo quartil é igual a: {q2:.2f}°C.\\n O terceiro quartil é igual a: {q3:.2f}°C.\\n A temperatura máxima registrada foi: {max:.2f}°C.\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [], + "source": [ + "def temperatura_hora_estado(estado):\n", + " data_estado = np.genfromtxt('temperatura_' + estado + '.csv', delimiter=',', skip_header=1)\n", + " data_estado = np.transpose(data_estado)\n", + " return data_estado[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 0, 'Pernambuco')" + ] + }, + "execution_count": 65, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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AAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXC4lAk5aWpuTkZEVFRSk2NlZDhw5VTk6OT5v8/HzddNNNiouLU2RkpDp37qyXX345SBUDAIBQEhKBZt26dUpNTdWmTZu0Zs0aFRcXq1+/fjp8+PCJNqNGjVJOTo5eeeUVbd++XcOGDdP111+vDz74IIiVAwCAUFAn2AVI0urVq322Fy5cqNjYWGVlZSklJUWS9N577yk9PV1du3aVJN19992aO3eusrKydPnll9d4zQAAIHSExAjNqQoKCiRJjRo1OrGve/fuev7553XgwAGVlJRo2bJlOnr0qHr37l1uH0VFRfJ4PD4PAABwdgq5QFNSUqJJkyapR48eat++/Yn9L7zwgoqLi9W4cWOFh4dr3LhxysjIUNu2bcvtJy0tTTExMSce8fHxNfUVAABADQu5QJOamqodO3Zo2bJlPvtnzJihgwcP6s0339TWrVs1ZcoUXX/99dq+fXu5/UyfPl0FBQUnHrm5uTVRPgAACIKQmENTavz48Vq1apXWr1+vFi1anNj/6aef6vHHH9eOHTt06aWXSpI6duyod955R0888YSefPLJMn2Fh4crPDy8xmoHAADBExKBxhijCRMmKCMjQ5mZmWrdurXP8cLCQklSrVq+A0q1a9dWSUlJjdUJAABCU0gEmtTUVC1dulQrVqxQVFSU8vPzJUkxMTGKiIhQYmKi2rZtq3Hjxumhhx5S48aNtXz5cq1Zs0arVq0KcvUAACDYQmIOTXp6ugoKCtS7d281a9bsxOP555+XJNWtW1evvfaamjRposGDB6tDhw7617/+pUWLFunaa68NcvUAACDYQmKExhhTaZuLLrqIlYEBAEC5QmKEBgAAoDoINAAAwPVC4pQTAHfZvXu3Dh06FOwyTti5c6fPc6iIiorSRRddFOwygHMCgQZAlezevVsXX3xxsMso18iRI4NdQhm7du0i1AA1gEADoEpKR2YWL16spKSkIFdjHTlyRPv27VOrVq0UERER7HIk2dGikSNHhtRIFnA2I9AAcCQpKUmdO3cOdhkn9OjRI9glAAgiJgUDAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXI9AAAADXq36gOXpU+uor6dixAJQDAABQdc4CzeuvSyNHSs2aSZGRUvPm0nnnSS1aSLfeKv3nPwEuEwAAoGJVuznl2rXS5MnSjh1St27SjTdKrVrZUPPdd9IXX0gbNkiLFkkdOkgPPCBdc82ZqRwAAOBH/gea1FTplVekSZNskGnevOK2+fnS009LY8ZIQ4ZI8+dXu1AAAICK+H/K6YILpF27pDvvPH2YkaS4OGnGDCknR2rcuJolAgAAnJ7/IzT33FP13hs0kObMqfr7AAAAqqDqk4K/+Ub69NOy+x991J5qAgAAqGFVCzTPPmsnAf/97777v/jCzq1p3Vp68cWAFQcAAOAP/wPNu+9KN98s9eol3XST77EWLaRt26SUFDtheOvWAJcJAABQMf8DzV/+Il19tfTaa9Jll5U93qmTXZ/miiuk++8PXIUAAACV8D/QZGVJ48ZV0lstafx4RmgAAECN8j/QHDzo3yXY8fHS/v3OKwIAAKgi/wNNQoJdV6Yyu3bZdWgAAABqiP+BZvBge2l2UVHFbY4elR57TOrTJwClAQAA+Mf/QDN5sl2Dpm9fO5/mVNu2Sf37S3v32tWEAQAAaoj/KwU3ayZlZEi//rXUtavUtKldk+b4cenzz6Wvv7b7/v1vKSnpzFUMAABwiqrdbbtHD2n7dns37TfekHJzpTp1bMDp318aOVKKjj5DpQIAAJSvaoFGks4/364KPGlSwIsBAABwomq3Pjhw4AyVAQAA4Jx/gWbzZunii6V+/aSWLe08GQAAgBDhX6AZNcqeYtq6VVqyRPrNb6SCgjNbGQAAgJ/8CzT799uF9ST7XFQkHTp0BssCAADwn3+Tgu+/X7rtNmn9entzyttvt3fYBgAACAH+BZqxY+2Cetu2STfeKF1++RkuCwAAwH/+X7b9k5/YBwAAQIjx/7LtXr2kjz6qWu9bt0o//WkVSwIAAKga/wPNxIl2NeAhQ6QXXpAKC8tvd+iQ9OKL9hTVgAH2fQAAAGeQ/6echg+XUlKkOXOk3/5WOnZMuuQSqXVrKTJSOnjQ3gphxw6pbl3p1lvtJd5Nm5656gEAAFTVlYKbNJEefVTat0+aN88utpebaxfe27/f3pTy6aftvkcfJcwAAIAaUfV7OUnSBRdI48bZBwAAQJBVbYQGAAAgBBFoAACA6xFoAACA6xFoAACA6xFoAACA6zm7ykmS8vLsSsAHD5Z/fNQox10DAABUhbNA8/zz0pgxUlFR+cfDwgg0AACgxjgLNHffLXXtKs2dKzVuHOCSAAAAqsZZoMnLk556SurcOcDlAAAAVJ2zScHdulX9ztsAAABniLMRmvnzpcGDpYICe+opMrJsm5SUapYGAADgH2eBZtcuKT9fuuceux0W5j1mjN0+fjwA5QEAAFTOWaC56y6pTRtp2jTuqA0AAILOWaD57DNp5Uqpb98AlwMAAFB1ziYFX3aZlJsb4FIAAACccTZCM3euNGKEdOyYveIpOrpsm4SEapYGAADgH2eBpm9fqbhYGjfOd0LwyZgUDAAAaoizQPPkkwEuAwAAwDlngWb06ACXAQAA4JyzScGSvTFlero0bJidR5OdbUdu3n8/gOUBAABUzlmg+fZbKTlZmjhR2rPHhpjCQmnVKql3b2njxsBWCQAAcBrOAs1dd0kej7Rzp7Rtm10dWJJeeskGnZkzq9RdWlqakpOTFRUVpdjYWA0dOlQ5OTll2m3cuFFXX321IiMjFR0drZSUFB05csTRVwAAAGcPZ4Fm5Urpvvuktm19r3I67zwbdrKyqtTdunXrlJqaqk2bNmnNmjUqLi5Wv379dPjw4RNtNm7cqAEDBqhfv356//33tWXLFo0fP161ajk/awYAAM4OziYFHz0qNWpUQY91pB9+qFJ3q1ev9tleuHChYmNjlZWVpZQfb3I5efJkTZw4UdOmTTvRrl27dlWrGwAAnJWcDW8kJ9s7bpdnyRLpiiuqUZJUUFAgSWr0Y2j6+uuvtXnzZsXGxqp79+5q2rSpevXqpQ0bNlTYR1FRkTwej88DAACcnZwFmjlzpDVrpE6dpBkz7Gmn556TBg+WXnhBmjXLcUElJSWaNGmSevToofbt20uS/vvf/0qSZs+erd/97ndavXq1OnfurJ/97GfavXt3uf2kpaUpJibmxCM+Pt5xTQAAILQ5CzQ9e9pAExkp/fWvdlLwI49I+fnSq69Kffo4Lig1NVU7duzQsmXLTuwrKSmRJI0bN04333yzLr/8cs2dO1ft2rXTM888U24/06dPV0FBwYlHLveeAgDgrOVsDo0kpaRI774rHTkiffedvZ9TgwbVKmb8+PFatWqV1q9frxYtWpzY36xZM0nSJZdc4tM+KSlJn3/+ebl9hYeHKzw8vFr1AAAAd6j+JUIREVLz5tUKM8YYjR8/XhkZGXr77bfVunVrn+OtWrVS8+bNy1zKvWvXLrVs2dLx5wIAgLOD8xGaAEpNTdXSpUu1YsUKRUVFKT8/X5IUExOjiIgIhYWFaerUqZo1a5Y6duyoTp06adGiRcrOztZLL70U5OoBAECwhUSgSU9PlyT17t3bZ/+CBQs0ZswYSdKkSZN09OhRTZ48WQcOHFDHjh21Zs0atWnTpoarBQAAoSYkAo0pXWm4EtOmTfNZhwYAAEAKxBwaAACAIHM+QrNli7R2rb3rdukIS0mJdPiw9M470qZNASoRAADg9JwFmvnzpQkTvEHmZLVqSf37V7MsAAAA/zk75fTYY9LAgdL+/fZmlGPH2pGZF1+0l3GPHBngMgEAACrmLNDs3Svdfrt0/vn2vk3vvGODzPDh0rRp0rx5AS4TAACgYs4CTb16Uv369nXbttLu3VJxsd3+6U+lXbsCVB4AAEDlnAWaTp2klSvt63bt7GTg0knAX3wRmMoAAAD85GxS8JQp0rBh0sGD0j//KQ0ZIt10kz3ltGSJvXklAABADXE2QjN0qB2hSUqy2089JV18sfTkk3bf448HrkIAAIBKOBuhWbRIuuYaadAgu924sfSf/wSwLAAAAP85G6FJTZU2bw5wKQAAAM44CzTx8ZLHE+BSAAAAnHF2ymnsWOmOO6T33pM6dpQaNCjbZtSoapYGAADgH2eB5s477fPTT5d/PCyMQAMAAGqMs0Czd2+AywAAAHDOWaBp2TLAZQAAADjnLNDce2/lbWbOdNQ1AABAVTkLNLNnV3wsOlpq3pxAAwAAaoyzy7ZLSso+Dh2SXnvN3oH7sccCXCYAAEDFnAWa8kRGSgMG2JGZqVMD1i0AAEBlAhdoSiUkSDt3BrxbAACAijibQ1MeY6QvvpAefFBq1Spg3QIAAFTGWaCpVcsunlceY6Rnn61GSQAAAFXjLNDMnFk20ISF2SucBg2SLrooAKUBAAD4x1mg+e1vpbg4qV69sseOHrX3eOrevZqlAQAA+MfZpODWraWPPir/2PvvS337VqMkAACAqvF/hOauu6QDB+xrY+xqwU2alG33wQdSTEyAygMAAKic/4EmKUm67z77OixMysqSwsN929SuLTVsKM2dG7gKAQAAKuF/oLnlFvuQ7CmnjAypU6czUxUAAEAVOJsUvHfv6Y97PPaKJwAAgBrgLNAUFUnz5kmZmfa1MXZ/SYl0+LD08cdSYWHgqgQAADgNZ4HmD3+wN6C87DLp66+liAg7QXj7dumHH05/N24AAIAAc3bZ9ssvS3feaS/dnjBBuuIKafNmafdue9uDkpLAVgkAAHAazgLN119LAwfa15ddZteekaQLL5SmT5eWLQtQeQAAAJVzFmgaNrRzZySpbVspN1c6dMhuX3SR9PnngakOAADAD84CTc+e0qOP2om/F10kRUbay7glaeNGFtYDAAA1ylmgmTXLBpdBg6Q6daTbb5fGjpW6dJHuvlsaPjzAZQIAAFTM2VVOHTpI2dn2qiZJSkuz6868+670i1/YeTQAAAA1xFmgGTvWrhp8zTV2OyxM+tOfAlgWAACA/5ydclq82DsJGAAAIMicBZru3aW1awNcCgAAgDPO59A89JD04ov2BpUNGvgeDwuT/vnP6lcHAADgB2eBJiNDat5cKi6WtmwpezwsrJplAQAA+O/M3G0bAACgBjmbQ1OqpET6v/+TVq+WPB7pwIEAlQUAAOA/54Fm8WIpIcHOoRk0SNqzRxozxi6q98MPASsQAACgMs4CzQsvSKNGSVdfLT3/vGSM3f/LX0qvvSbNmRPAEgEAAE7P2RyaP/9Z+v3vpfnzpePHvftvvln65hvpqacINQAAoMY4G6HJybGjMeW58krpf/+rRkkAAABV4yzQxMZKO3eWf2znTnscAACghjgLNDfcIM2cKb30klRUZPeFhUlZWfZU069+FcASAQAATs/ZHJo5c+ydtq+/Xqr1Yybq3Vv6/nupZ0/mzwAAgBrlLNCEh0uvvy6tWSO99ZZdf6ZhQ6lXL+naa1kpGAAA1ChngabUNddIKSnSwYNSo0ZS3bqBqQoAAKAKnAea1aule++V3n/frkNTu7b3dFP37gEsEUCoiWsQpoiDu6S86i02fjaLOLhLcQ0YrQZqirNA8/LLdv5Mx47S7Nn2qqb8fOnf/5b69JHefNOGGwBnpXFd6ilp/ThpfbArCV1Jsr8TgJoRZkzpMr9V0LGjlJhoVwk+1fDh0ldfSRs2BKC8wPF4PIqJiVFBQYGio6ODXQ7gWtu2bdOgXlfo7RVLlZSYGOxyQtbO7GxdPWSEXl23VZ07dw52OYBr+fv329kIze7d0oMPln9s7Fhp2DBH3QJwh/zvjY40vFhq3inYpYSsI/klyv++6v9/EYAzzk6AJyVJW7aUfywnR2rduholAQAAVI2zEZr0dGnwYHt59qhRUvPm0v790vLldsG99HTp88+97RMSAlMtAABAOZwFmquuss933y3NmOHdXzodZ+RI3/Yn38ASAAAgwJwFmmeeYfE8AAAQMpwFmjFjAlsFAABANThfWC8vT9q61a4SfKqwMOmmm5xXBQAAUAXOAs3zz9tRmtI7bZ+KQAMAAGqQs0Bz991S167S3LlS48YBLgkAAKBqnAWavDzpqackVr8EAAAhwNnCet26SR99FLAi0tLSlJycrKioKMXGxmro0KHKyckpt60xRgMHDlRYWJiWL18esBoAAIB7ORuhmT/fLqxXUGBPPUVGlm2TkuJ3d+vWrVNqaqqSk5N17Ngx/elPf1K/fv30ySefKPKUvv/2t78pjEvGAQDASZwFml277N2177nHbp8cMIyx21VYTG/16tU+2wsXLlRsbKyysrKUclIw+vDDD/Xwww9r69atatasmaPSAQDA2cdZoLnrLqlNG2naNKlp0wCXJBUUFEiSGjVqdGJfYWGhRowYoSeeeEJxcXGV9lFUVKSik67C8ng8Aa8TAACEBmeB5rPPpJUrpb59A1yOVFJSokmTJqlHjx5q3779if2TJ09W9+7dNWTIEL/6SUtL0z2lI0gAAOCs5izQXHaZlJsb4FKs1NRU7dixQxs2bDix75VXXtHbb7+tDz74wO9+pk+frilTppzY9ng8io+PD2itAAAgNDgLNHPnSiNGSMeO2SueoqPLtnFwh+3x48dr1apVWr9+vVq0aHFi/9tvv61PP/1UDRs29Gk/fPhw9ezZU5mZmWX6Cg8PV3h4eJVrAAAA7uMs0PTtKxUXS+PGVXyTyipMCjbGaMKECcrIyFBmZqZat27tc3zatGm69dZbffZddtllmjt3rgYPHlzl8gEAwNnFWaB58smAFpGamqqlS5dqxYoVioqKUn5+viQpJiZGERERiouLK3cicEJCQpnwAwAAzj3OAs3o0QEtIj09XZLUu3dvn/0LFizQGO7sDQAAKuH8bttFRdIzz0hr1khffiktWCBlZtrbIXTtWqWujDFV/ngn7wEAAGcnZ7c++PZbKTlZmjhR2rNHev99qbBQWrVK6t1b2rgxsFUCAACchrNAc9ddkscj7dwpbdtmVweWpJdeskFn5swAlggAAHB6zgLNypXSffdJbdv6XuV03nk27GRlBag8AACAyjkLNEePSifdlsBHnTrSDz9UoyQAAICqcRZokpPtHbfLs2SJdMUV1SgJAACgapxd5TRnjl1cr1Mn6dpr7Wmn556TZs2S3njDPgAAAGqI/yM0V18tZWfb1z172su1IyOlv/7VTgp+5BEpP1969VWpT58zVC4AAEBZ/o/QZGbaK5tKpaRI774rHTkiffedvZ9TgwaBrxAAAKASzhfWKxURYR8AAABBUrVJwRXdiBIAACCIqjZCM3SoFB5eebuwMOnTT51VBAAAUEVVCzSXXy41aXKGSgEAAHCmaoFm5swq33gSAADgTHO2sB4AAEAIIdAAAADX8z/QjB7N/BkAABCS/J9Ds2DBGSwDAADAOU45AQAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA16sT7AIAuEthYaEkadu2bUGuxOvIkSPat2+fWrVqpYiIiGCXI0nauXNnsEsAzikEGgBVkp2dLUn63e9+F+RK3CEqKirYJQDnBAINgCoZOnSoJCkxMVH169cPbjE/2rlzp0aOHKnFixcrKSkp2OWcEBUVpYsuuijYZQDnBAINgCq54IILdOuttwa7jHIlJSWpc+fOwS4DQBAwKRgAALgegQYAALgegQYAALgegQYAALgegQYAALgegQYAALgegQYAALgegQYAALgegQYAALgegQYAALgegQYAALgegQYAALgegQYAALgegQYAALheSASatLQ0JScnKyoqSrGxsRo6dKhycnJOHD9w4IAmTJigdu3aKSIiQgkJCZo4caIKCgqCWDUAAAgVIRFo1q1bp9TUVG3atElr1qxRcXGx+vXrp8OHD0uS8vLylJeXp4ceekg7duzQwoULtXr1at1yyy1BrhwAAISCMGOMCXYRp/rmm28UGxurdevWKSUlpdw2L774okaOHKnDhw+rTp06lfbp8XgUExOjgoICRUdHB7pkAEG0bds2denSRVlZWercuXOwywEQQP7+/Q6JEZpTlZ5KatSo0WnbREdH+xVmAADA2S3k0kBJSYkmTZqkHj16qH379uW2+fbbbzVnzhyNHTu2wn6KiopUVFR0Ytvj8QS8VgAAEBpCboQmNTVVO3bs0LJly8o97vF4NGjQIF1yySWaPXt2hf2kpaUpJibmxCM+Pv4MVQwAAIItpALN+PHjtWrVKq1du1YtWrQoc/zQoUMaMGCAoqKilJGRobp161bY1/Tp01VQUHDikZubeyZLBwAAQRQSp5yMMZowYYIyMjKUmZmp1q1bl2nj8XjUv39/hYeH65VXXtF555132j7Dw8MVHh5+pkoGAAAhJCQCTWpqqpYuXaoVK1YoKipK+fn5kqSYmBhFRETI4/GoX79+Kiws1OLFi+XxeE7MiWnSpIlq164dzPIBAECQhUSgSU9PlyT17t3bZ/+CBQs0ZswYbdu2TZs3b5YktW3b1qfN3r171apVq5ooEwAAhKiQCDSVLYXTu3fvStsAAIBzV0hNCgYAAHCCQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyPQAMAAFyvTrALAHBuKiwsVHZ2dkD62rlzp89zICQmJqp+/foB6w/AmUWgARAU2dnZ6tKlS0D7HDlyZMD6ysrKUufOnQPWH4Azi0ADICgSExOVlZUVkL6OHDmiffv2qVWrVoqIiAhIn4mJiQHpB0DNCDPGmGAXURM8Ho9iYmJUUFCg6OjoYJcDAAD84O/fbyYFAwAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA1yPQAAAA16sT7AJqSulNxT0eT5ArAQAA/ir9u136d7wi50ygOXTokCQpPj4+yJUAAICqOnTokGJiYio8HmYqizxniZKSEuXl5SkqKkphYWHBLgdAAHk8HsXHxys3N1fR0dHBLgdAABljdOjQITVv3ly1alU8U+acCTQAzl4ej0cxMTEqKCgg0ADnKCYFAwAA1yPQAAAA1yPQAHC98PBwzZo1S+Hh4cEuBUCQMIcGAAC4HiM0AADA9Qg0AADA9Qg0AADA9Qg0AADA9Qg0AFxr/fr1Gjx4sJo3b66wsDAtX7482CUBCBICDQDXOnz4sDp27Kgnnngi2KUACLJz5uaUAM4+AwcO1MCBA4NdBoAQwAgNAABwPQINAABwPQINAABwPQINAABwPQINAABwPa5yAuBa33//vfbs2XNie+/evfrwww/VqFEjJSQkBLEyADWNu20DcK3MzEz16dOnzP7Ro0dr4cKFNV8QgKAh0AAAANdjDg0AAHA9Ag0AAHA9Ag0AAHA9Ag0AAHA9Ag0AAHA9Ag0AAHA9Ag0AAHA9Ag0AX717S2Fhvo969aSEBCk1Vfruu2BXWH0LF9rvtW9fsCsBECDc+gBAWZdfLs2f793+4QcpK0v605+kDz6Q3n3XBgIACBEEGgBlRUdLV13luy8lRfr+e2nmTGnz5rLHASCIOOUEwH9XXGGfP/vMPq9YYfedd54UFyfdcYd0+LC3/ezZUtu20r33So0aSc2a2VNWrVpJs2ZJU6dKTZtKERHSgAHS7t2+n/ePf9j+IyNtm06dpBdf9B5fuNB+9oYNUnKyfd2unbRypZSTI/3sZ1L9+raGZcvKfp9337WjUeHhUvv20vPPe49lZtpRqMxM3/f07m0fpYyR5s6VkpJsjW3bSg89ZPeXWrNG6tlTiomRGjeWRoyQcnMr/70B+I1AA8B/OTn2uU0baelSaehQKTFRWr7chpdnn5WGDPH9Y/7ZZ9Krr9qwMHeudP75dv+8edLOnTaU/OMf0tat0qhR3vc98YQ0bpz9jFdflZYsscFjxAjpiy+87YqLpRtvtG1fecUGmN/8Rvr5z6VBg2y4ad5cGj3a932SNHasdP31Npi1by/dcIP9LlXxhz/YYPaLX9jPuuUW6Y9/lB54wB5/9lmpXz8pPl567jn7G2zcKHXrJn39ddU+C0DFDACcrFcvY1JSjCku9j6++sqYF14wpnFjY7p1M6akxJgWLYwZMMD3vW++aYxkzKpVdnvWLLv9zju+7Vq2NKZVK2OOHfPuu+ce2/bbb+32lCnG/PGPvu/LyrJtnnvObi9YYLfT071tli2z+2bM8O7butXuy8jwfd+DD/r2f/nlxnTpYl+vXWvbrF1b9vfp1cu+/u47Y+rUMWbSJN82Eyfa3+b4cWPi4ozp39/3+J49xtSrZ8zUqQZAYDCHBkBZ69dLdev67qtVS+rbV3rqKTtS88UXdpLwsWPeNr162fk3a9bY0ZFSnTqV/YzkZKl2be92ixb2+fBhe1rm4Yft9sGDUna2tGePtHat3VdU5NtX9+7e102b2ucrr/Tua9zY29fJfv1r3+1f/tKeCvv++7L1lmfTJvv9hw3z3T9vnn3euVPKz/eO1pRq08aO0Jx6OguAYwQaAGV17iz9/e/2dViYnZuSkCBFRdl9775rn2+/3T5OlZfnu92gQdk29ev7btf68Qx4SYl9/vRTexrprbfsZeOJiVLHjvbYyae0JBuiThUZWf53O1lcnO92bKztu6Cg8vdK0v793veV58CB8j+ndN+2bf59DoBKEWgAlBUV5Z0AXJ6GDe3zgw/6TpAtVTpPxqmSEjvCU6+etGWLHeGpU0f65BM7JyVQDhzwjuhIdjSldm07gbn0svTjx33f8/333oBW+jt8842djFzq889tILvgAm+/p/ryS+9xANXGpGAAVZeYaEcl9u61waf0ceGF0rRpdq2a6vj2W3ta65ZbbL91fvz/Xq+/bp9LR3Gq69VXva9LSuwVVFddZa9WKh31OXki8Xff2VBV6sor7am5lSt9+334YTvB+NJL7UjMc8/5Hv/vf+3E4J/+NDDfAwAjNAAcqF1b+vOf7Smh2rWlwYPt/JQ5c2wA6NKlev3HxtpLux9/3M6tOf98afVq6W9/s8dPvjS8Ov7f/7NzYBISpPR0G6LefNMe69DBXpl077023NSqJd1/v++prAsukCZNkh55xF6B1auXXaNn/nx76XatWlJamnTzzfbqrJtusmFt9mw7CjRlSmC+BwBGaAA4dOutduThvfdsoLntNql1a2ndOvtcXcuX2xGfMWPspdWbNtmRkMRE6Z13qt+/ZC8ZnzfPXmr+xRd2BKhXL3usdm3p5ZftCMuNN0oTJ9rn4cN9+/jLX2xoWbrUniZ79lkbxO64wx4fM0Z66SVp1y57CfqUKXYS85Yt5c+tAeBImDGnzq4DAABwF0ZoAACA6xFoAACA6xFoAACA6xFoAACA6xFoAACA6xFoAACA6xFoAACA6xFoAACA6xFoAACA6xFoAACA6xFoAACA6xFoAACA6/1/TDiiyjSfePgAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "tmp_pe = temperatura_hora_estado('PE')\n", + "plt.boxplot([tmp_pe])\n", + "ax1 = plt.subplot(1, 1, 1)\n", + "\n", + "font1 = {'family':'arial','color':'red','size':15}\n", + "font2 = {'family':'arial','color':'red','size':12}\n", + "\n", + "plt.title('Temperatura por hora', fontdict = font1)\n", + "ax1.set_title('Temperatura por hora')\n", + "\n", + "ax1.set_ylabel('Temperatura em (°C)')\n", + "plt.ylabel('Temperatura em (°C)', fontdict = font2)\n", + "\n", + "ax1.set_xlabel('Pernambuco')\n", + "plt.xlabel('Pernambuco', fontdict = font2) \n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Bônus" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data_bonus = np.genfromtxt('Maria_qtdd_agua.csv', delimiter=',', skip_header=1) \n", + "data_bonus\n", + "#os dados são a quantidade em mls de quanto \"maria\" bebe de agua ao longo do dia!" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [], + "source": [ + "data_bonus = np.transpose(data_bonus) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data_bonus" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "dia = data_bonus[0]\n", + "quantidade_de_agua_por_dia = data_bonus[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Quantidade de água em 24h que Maria consome')" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.bar(dia, quantidade_de_agua_por_dia)\n", + "\n", + "\n", + "font1 = {'family':'arial','color':'red','size':20}\n", + "font2 = {'family':'arial','color':'red','size':15}\n", + "\n", + "plt.xlabel('Horas', fontdict = font2)\n", + "plt.ylabel('Quantidade de água (ml)', fontdict = font2)\n", + "plt.title('Quantidade de água em 24h que Maria consome', fontdict = font1)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Quantidade de água em 24h que Maria consome')" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(dia, quantidade_de_agua_por_dia)\n", + "\n", + "\n", + "font1 = {'family':'arial','color':'red','size':20}\n", + "font2 = {'family':'arial','color':'red','size':15}\n", + "\n", + "plt.xlabel('Horas', fontdict = font2)\n", + "plt.ylabel('Quantidade de água (ml)', fontdict = font2)\n", + "plt.title('Quantidade de água em 24h que Maria consome', fontdict = font1)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Os dois gráficos podem ser úteis para mostrar a quantidade de água que Maria bebe!" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Soraia/codigo_sala.ipynb b/Soraia/codigo_sala.ipynb new file mode 100644 index 0000000..0e19f08 --- /dev/null +++ b/Soraia/codigo_sala.ipynb @@ -0,0 +1,1059 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: pip in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (24.2)\n" + ] + } + ], + "source": [ + "!python.exe -m pip install --upgrade pip" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: numpy in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (2.0.1)\n" + ] + } + ], + "source": [ + "!pip install numpy" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "data = np.genfromtxt('DadosHoras.csv', delimiter=',', skip_header=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0. , 1.53471503, 21.76363983, 962.07288973,\n", + " 374.4 ],\n", + " [ 1. , 1.60540211, 21.12282735, 961.30166344,\n", + " 337. ],\n", + " [ 2. , 1.48394716, 20.66582569, 962.95385202,\n", + " 487.8 ],\n", + " [ 3. , 1.42629327, 20.17065379, 961.48471243,\n", + " 404.2 ],\n", + " [ 4. , 1.37345029, 19.83814623, 961.10797342,\n", + " 408. ],\n", + " [ 5. , 1.36411055, 19.58221154, 960.23994836,\n", + " 362.8 ],\n", + " [ 6. , 1.3651846 , 19.3924642 , 960.77596841,\n", + " 391.8 ],\n", + " [ 7. , 1.29324746, 18.97025316, 960.78689501,\n", + " 551.4 ],\n", + " [ 8. , 1.3132837 , 18.91604478, 961.05878176,\n", + " 406.2 ],\n", + " [ 9. , 1.24196811, 18.94470284, 961.36136531,\n", + " 362.8 ],\n", + " [ 10. , 1.42972578, 19.69269057, 962.01856745,\n", + " 331.2 ],\n", + " [ 11. , 1.82118881, 21.46132578, 964.27668998,\n", + " 347.8 ],\n", + " [ 12. , 2.23905032, 23.34516672, 963.38675185,\n", + " 256.2 ],\n", + " [ 13. , 2.38478883, 24.8295846 , 965.45667455,\n", + " 260.8 ],\n", + " [ 14. , 2.52451334, 25.90661213, 963.64993169,\n", + " 252.6 ],\n", + " [ 15. , 2.55682128, 27.02503264, 963.84511205,\n", + " 323.8 ],\n", + " [ 16. , 2.54291174, 27.43821084, 961.3747344 ,\n", + " 507.6 ],\n", + " [ 17. , 2.48421419, 27.7560822 , 960.15590186,\n", + " 536.8 ],\n", + " [ 18. , 2.48241758, 27.62720268, 960.98559946,\n", + " 479.4 ],\n", + " [ 19. , 2.3858755 , 27.10855763, 959.23435456,\n", + " 618.6 ],\n", + " [ 20. , 2.18649927, 26.24793618, 959.73465415,\n", + " 616.6 ],\n", + " [ 21. , 1.78972274, 24.63620448, 961.04351625,\n", + " 557.8 ],\n", + " [ 22. , 1.63185638, 23.05617037, 959.24388463,\n", + " 661. ],\n", + " [ 23. , 1.56823161, 22.34205607, 961.39033708,\n", + " 392. ]])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "data = np.transpose(data) #inverte a posição dos dados em listas array" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 0. , 1. , 2. , 3. ,\n", + " 4. , 5. , 6. , 7. ,\n", + " 8. , 9. , 10. , 11. ,\n", + " 12. , 13. , 14. , 15. ,\n", + " 16. , 17. , 18. , 19. ,\n", + " 20. , 21. , 22. , 23. ],\n", + " [ 1.53471503, 1.60540211, 1.48394716, 1.42629327,\n", + " 1.37345029, 1.36411055, 1.3651846 , 1.29324746,\n", + " 1.3132837 , 1.24196811, 1.42972578, 1.82118881,\n", + " 2.23905032, 2.38478883, 2.52451334, 2.55682128,\n", + " 2.54291174, 2.48421419, 2.48241758, 2.3858755 ,\n", + " 2.18649927, 1.78972274, 1.63185638, 1.56823161],\n", + " [ 21.76363983, 21.12282735, 20.66582569, 20.17065379,\n", + " 19.83814623, 19.58221154, 19.3924642 , 18.97025316,\n", + " 18.91604478, 18.94470284, 19.69269057, 21.46132578,\n", + " 23.34516672, 24.8295846 , 25.90661213, 27.02503264,\n", + " 27.43821084, 27.7560822 , 27.62720268, 27.10855763,\n", + " 26.24793618, 24.63620448, 23.05617037, 22.34205607],\n", + " [962.07288973, 961.30166344, 962.95385202, 961.48471243,\n", + " 961.10797342, 960.23994836, 960.77596841, 960.78689501,\n", + " 961.05878176, 961.36136531, 962.01856745, 964.27668998,\n", + " 963.38675185, 965.45667455, 963.64993169, 963.84511205,\n", + " 961.3747344 , 960.15590186, 960.98559946, 959.23435456,\n", + " 959.73465415, 961.04351625, 959.24388463, 961.39033708],\n", + " [374.4 , 337. , 487.8 , 404.2 ,\n", + " 408. , 362.8 , 391.8 , 551.4 ,\n", + " 406.2 , 362.8 , 331.2 , 347.8 ,\n", + " 256.2 , 260.8 , 252.6 , 323.8 ,\n", + " 507.6 , 536.8 , 479.4 , 618.6 ,\n", + " 616.6 , 557.8 , 661. , 392. ]])" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data #pegar o indice q vc quer" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[21.76363983 21.12282735 20.66582569 20.17065379 19.83814623 19.58221154\n", + " 19.3924642 18.97025316 18.91604478 18.94470284 19.69269057 21.46132578\n", + " 23.34516672 24.8295846 25.90661213 27.02503264 27.43821084 27.7560822\n", + " 27.62720268 27.10855763 26.24793618 24.63620448 23.05617037 22.34205607]\n" + ] + } + ], + "source": [ + "temperatura_hora = data [2] #se ligar no índice\n", + "print(temperatura_hora)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "hora = data[0]\n", + "temperatura_hora = data [2]\n", + "vento_ms = data[1]\n", + "pressao = data[3]\n", + "preciptacao = data[4]" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(22.82665009621074)" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.mean(temperatura_hora)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(22.05284795344575)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.median(temperatura_hora)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(3.145988349822262)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.std(temperatura_hora)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "18.916044776119403 19.80178231687473 22.05284795344575 25.991943144602697 27.756082200861787\n" + ] + } + ], + "source": [ + "min = np.min(temperatura_hora)\n", + "q1 = np.quantile(temperatura_hora, 0.25)\n", + "q2 = np.quantile(temperatura_hora, 0.5)\n", + "q3 = np.quantile(temperatura_hora, 0.75)\n", + "max = np.max(temperatura_hora)\n", + "\n", + "print(min,q1, q2, q3, max)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: matplotlib in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (3.9.1.post1)\n", + "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib) (1.2.1)\n", + "Requirement already satisfied: cycler>=0.10 in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib) (0.12.1)\n", + "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib) (4.53.1)\n", + "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib) (1.4.5)\n", + "Requirement already satisfied: numpy>=1.23 in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib) (2.0.1)\n", + "Requirement already satisfied: packaging>=20.0 in c:\\users\\bru\\appdata\\roaming\\python\\python312\\site-packages (from matplotlib) (24.1)\n", + "Requirement already satisfied: pillow>=8 in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib) (10.4.0)\n", + "Requirement already satisfied: pyparsing>=2.3.1 in c:\\users\\bru\\appdata\\local\\programs\\python\\python312\\lib\\site-packages (from matplotlib) (3.1.2)\n", + "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\bru\\appdata\\roaming\\python\\python312\\site-packages (from matplotlib) (2.9.0.post0)\n", + "Requirement already satisfied: six>=1.5 in c:\\users\\bru\\appdata\\roaming\\python\\python312\\site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n" + ] + } + ], + "source": [ + "!pip install matplotlib" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'whiskers': [,\n", + " ],\n", + " 'caps': [,\n", + " ],\n", + " 'boxes': [],\n", + " 'medians': [],\n", + " 'fliers': [],\n", + " 'means': []}" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.boxplot(temperatura_hora)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "def temperatura_hora_estado(estado):\n", + " data_estado = np.genfromtxt('temperatura_' + estado + '.csv', delimiter=',', skip_header=1)\n", + " data_estado = np.transpose(data_estado)\n", + " return data_estado[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "ename": "FileNotFoundError", + "evalue": "temperatura_SP.csv not found.", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[21], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m tmp_sp \u001b[38;5;241m=\u001b[39m \u001b[43mtemperatura_hora_estado\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mSP\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m 2\u001b[0m tmp_rj \u001b[38;5;241m=\u001b[39m temperatura_hora_estado(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mRJ\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m 3\u001b[0m tmp_mg \u001b[38;5;241m=\u001b[39m temperatura_hora_estado(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMG\u001b[39m\u001b[38;5;124m'\u001b[39m)\n", + "Cell \u001b[1;32mIn[20], line 2\u001b[0m, in \u001b[0;36mtemperatura_hora_estado\u001b[1;34m(estado)\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mtemperatura_hora_estado\u001b[39m(estado):\n\u001b[1;32m----> 2\u001b[0m data_estado \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgenfromtxt\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtemperatura_\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mestado\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m.csv\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdelimiter\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m,\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mskip_header\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m 3\u001b[0m data_estado \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mtranspose(data_estado)\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m data_estado[\u001b[38;5;241m1\u001b[39m]\n", + "File \u001b[1;32mc:\\Users\\Bru\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\numpy\\lib\\_npyio_impl.py:1989\u001b[0m, in \u001b[0;36mgenfromtxt\u001b[1;34m(fname, dtype, comments, delimiter, skip_header, skip_footer, converters, missing_values, filling_values, usecols, names, excludelist, deletechars, replace_space, autostrip, case_sensitive, defaultfmt, unpack, usemask, loose, invalid_raise, max_rows, encoding, ndmin, like)\u001b[0m\n\u001b[0;32m 1987\u001b[0m fname \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mfspath(fname)\n\u001b[0;32m 1988\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(fname, \u001b[38;5;28mstr\u001b[39m):\n\u001b[1;32m-> 1989\u001b[0m fid \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_datasource\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mrt\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 1990\u001b[0m fid_ctx \u001b[38;5;241m=\u001b[39m contextlib\u001b[38;5;241m.\u001b[39mclosing(fid)\n\u001b[0;32m 1991\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n", + "File \u001b[1;32mc:\\Users\\Bru\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\numpy\\lib\\_datasource.py:192\u001b[0m, in \u001b[0;36mopen\u001b[1;34m(path, mode, destpath, encoding, newline)\u001b[0m\n\u001b[0;32m 155\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m 156\u001b[0m \u001b[38;5;124;03mOpen `path` with `mode` and return the file object.\u001b[39;00m\n\u001b[0;32m 157\u001b[0m \n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 188\u001b[0m \n\u001b[0;32m 189\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m 191\u001b[0m ds \u001b[38;5;241m=\u001b[39m DataSource(destpath)\n\u001b[1;32m--> 192\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mds\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnewline\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnewline\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[1;32mc:\\Users\\Bru\\AppData\\Local\\Programs\\Python\\Python312\\Lib\\site-packages\\numpy\\lib\\_datasource.py:532\u001b[0m, in \u001b[0;36mDataSource.open\u001b[1;34m(self, path, mode, encoding, newline)\u001b[0m\n\u001b[0;32m 529\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _file_openers[ext](found, mode\u001b[38;5;241m=\u001b[39mmode,\n\u001b[0;32m 530\u001b[0m encoding\u001b[38;5;241m=\u001b[39mencoding, newline\u001b[38;5;241m=\u001b[39mnewline)\n\u001b[0;32m 531\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 532\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpath\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not found.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[1;31mFileNotFoundError\u001b[0m: temperatura_SP.csv not found." + ] + } + ], + "source": [ + "tmp_sp = temperatura_hora_estado('SP')\n", + "tmp_rj = temperatura_hora_estado('RJ')\n", + "tmp_mg = temperatura_hora_estado('MG')\n", + "tmp_es = temperatura_hora_estado('ES')\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'whiskers': [,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ],\n", + " 'caps': [,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ,\n", + " ],\n", + " 'boxes': [,\n", + " ,\n", + " ,\n", + " ],\n", + " 'medians': [,\n", + " ,\n", + " ,\n", + " ],\n", + " 'fliers': [,\n", + " ,\n", + " ,\n", + " ],\n", + " 'means': []}" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.boxplot([tmp_sp, tmp_rj, tmp_mg, tmp_es])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\Bru\\AppData\\Local\\Temp\\ipykernel_10192\\3969472040.py:5: MatplotlibDeprecationWarning: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11.\n", + " ax1.boxplot([tmp_sp, tmp_rj, tmp_mg, tmp_es], labels=['SP','RJ','MG','ES'])\n" + ] + }, + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax1 = plt.subplot(2, 2, 1)\n", + "ax1.set_ylabel('Temperatura em (°C)')\n", + "ax1.set_xlabel('Estado')\n", + "ax1.set_title('Temperatura por estado por hora')\n", + "ax1.boxplot([tmp_sp, tmp_rj, tmp_mg, tmp_es], labels=['SP','RJ','MG','ES'])\n", + "ax1.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\Bru\\AppData\\Local\\Temp\\ipykernel_10192\\2281516267.py:6: MatplotlibDeprecationWarning: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11.\n", + " ax1.boxplot([tmp_pe], labels=['PE'])\n" + ] + }, + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "tmp_pe = temperatura_hora_estado('PE')\n", + "ax1 = plt.subplot(1, 1, 1) #número de linhas, numero de colunas e posição \n", + "ax1.set_ylabel('Temperatura em (°C)')\n", + "ax1.set_xlabel('Estado')\n", + "ax1.set_title('Temperatura por estado por hora')\n", + "ax1.boxplot([tmp_pe], labels=['PE'])\n", + "ax1.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\Bru\\AppData\\Local\\Temp\\ipykernel_10192\\3155381308.py:5: MatplotlibDeprecationWarning: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11.\n", + " ax1.boxplot([tmp_sp, tmp_rj, tmp_mg, tmp_es], labels=['SP','RJ','MG','ES'])\n", + "C:\\Users\\Bru\\AppData\\Local\\Temp\\ipykernel_10192\\3155381308.py:7: MatplotlibDeprecationWarning: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11.\n", + " auxsp.boxplot(tmp_sp, labels=['SP'])\n", + "C:\\Users\\Bru\\AppData\\Local\\Temp\\ipykernel_10192\\3155381308.py:9: MatplotlibDeprecationWarning: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11.\n", + " auxrj.boxplot(tmp_rj, labels=['RJ'])\n", + "C:\\Users\\Bru\\AppData\\Local\\Temp\\ipykernel_10192\\3155381308.py:11: MatplotlibDeprecationWarning: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11.\n", + " auxmg.boxplot(tmp_mg, labels=['MG'])\n", + "C:\\Users\\Bru\\AppData\\Local\\Temp\\ipykernel_10192\\3155381308.py:13: MatplotlibDeprecationWarning: The 'labels' parameter of boxplot() has been renamed 'tick_labels' since Matplotlib 3.9; support for the old name will be dropped in 3.11.\n", + " auxes.boxplot(tmp_es, labels=['ES'])\n" + ] + }, + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax1 = plt.subplot(2, 1, 1)\n", + "ax1.set_ylabel('Temperatura em (°C)')\n", + "ax1.set_xlabel('Estado')\n", + "ax1.set_title('Temperatura por estado por hora')\n", + "ax1.boxplot([tmp_sp, tmp_rj, tmp_mg, tmp_es], labels=['SP','RJ','MG','ES'])\n", + "auxsp = plt.subplot(2,4,5)\n", + "auxsp.boxplot(tmp_sp, labels=['SP'])\n", + "auxrj = plt.subplot(2,4,6)\n", + "auxrj.boxplot(tmp_rj, labels=['RJ'])\n", + "auxmg = plt.subplot(2,4,7)\n", + "auxmg.boxplot(tmp_mg, labels=['MG'])\n", + "auxes = plt.subplot(2,4,8)\n", + "auxes.boxplot(tmp_es, labels=['ES'])\n", + "ax1.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([9., 4., 2., 3., 6.]),\n", + " array([18.91604478, 20.68405226, 22.45205975, 24.22006723, 25.98807472,\n", + " 27.7560822 ]),\n", + " )" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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edfmgKxXvKenDm3369IlLLrkk1q9f37Ktubk51q9fH5MnTy7lqQCAM1DJb4Xcdtttce2118aECRPic5/7XCxdujQOHToUc+fO7Yj5AIBupOSw+PrXvx7/+te/4o477oj9+/fHZz/72Vi3bt1xH+gkT0VFRdx5553HvaVE57IuXZN16ZqsS9fUEetSVpzseyMAAO3kXiEAQBphAQCkERYAQBphAQCkERZdSF1dXUycODEqKyujuro6rr766ti1a1erfd55552oqamJwYMHx0c+8pH46le/etw/WEauk63LwYMH46abbopPfepT0a9fvxgxYkTMnz+/5b44dIz2vF7eUxRFXHHFFVFWVhZPPfXU6R20h2nvumzevDn+7//+LwYMGBBVVVVx6aWXxpEjRzph4p6hPeuyf//++Na3vhXnnntuDBgwIC6++OL4xS9+UfK5hEUXsmnTpqipqYktW7bEM888E0ePHo0ZM2bEoUOHWva59dZb41e/+lU8+eSTsWnTpti3b1/MmjWrE6c+851sXfbt2xf79u2LJUuWxM6dO+ORRx6JdevWxXe/+91OnvzM1p7Xy3uWLl3qFgKnSXvWZfPmzfGlL30pZsyYEVu3bo1t27bFjTfeGL16+ZPUUdqzLt/+9rdj165dsXbt2nj55Zdj1qxZMXv27HjppZdKO1lBl3XgwIEiIopNmzYVRVEUb731VnHWWWcVTz75ZMs+f/nLX4qIKDZv3txZY/Y471+XE1m9enXRp0+f4ujRo6dxsp6trXV56aWXio9//OPFa6+9VkREsWbNms4ZsIc60bpMmjSpuP322ztxKk60LgMGDCh+9rOftdpv0KBBxfLly0t6bnnYhb13KX3QoEEREbFjx444evRoTJ8+vWWf0aNHx4gRI9q8bT353r8ube1TVVUVvXt3+H3++J8Trcvhw4fjmmuuiQcffLDN+xnRsd6/LgcOHIgXXnghqqurY8qUKTFkyJC47LLL4vnnn+/MMXucE71epkyZEqtWrYqDBw9Gc3NzPPHEE/HOO+/E5ZdfXtJzC4suqrm5OW655ZaYOnVqjB07NiL++/5Xnz59jruJ25AhQ2L//v2dMGXPc6J1eb833ngjFi9eHN/73vdO83Q9V1vrcuutt8aUKVPiqquu6sTpeq4TrcvevXsjIuKuu+6K6667LtatWxcXX3xxTJs2LV555ZXOHLfHaOv1snr16jh69GgMHjw4KioqYt68ebFmzZq44IILSnp+/zvVRdXU1MTOnTtVfBdzsnVpbGyMmTNnxpgxY+Kuu+46vcP1YCdal7Vr18aGDRtKf3+YNCdal+bm5oiImDdvXss9psaPHx/r16+Phx9+OOrq6jpl1p6krf+OLVy4MN5666343e9+F+ecc0489dRTMXv27Hjuuedi3Lhx7T9Byps1pKqpqSmGDRtW7N27t9X29evXFxFRvPnmm622jxgxorj//vtP44Q9U1vr8p7GxsZi8uTJxbRp04ojR46c5ul6rrbW5eabby7KysqK8vLylkdEFL169Souu+yyzhm2B2lrXfbu3VtERPHzn/+81fbZs2cX11xzzekcsUdqa1327NlTRESxc+fOVtunTZtWzJs3r6RzeCukCymKIm688cZYs2ZNbNiwIUaNGtXq95dcckmcddZZrW5bv2vXrnj11Vfdtr4DnWxdIv57pWLGjBnRp0+fWLt2bfTt27cTJu1ZTrYuCxYsiD//+c/xxz/+seUREfHAAw/EihUrOmHinuFk6zJy5MgYOnTocV913L17d5x//vmnc9Qe5WTrcvjw4YiI476ZU15e3nKVqZST0UVcf/31xcCBA4uNGzcWr732Wsvj8OHDLft8//vfL0aMGFFs2LCh2L59ezF58uRi8uTJnTj1me9k69LQ0FBMmjSpGDduXLFnz55W+/znP//p5OnPXO15vbxf+FZIh2vPujzwwANFVVVV8eSTTxavvPJKcfvttxd9+/Yt9uzZ04mTn9lOti7vvvtuccEFFxSf//znixdeeKHYs2dPsWTJkqKsrKx4+umnSzqXsOhCIuKEjxUrVrTsc+TIkeKGG24ozj777KJ///7FV77yleK1117rvKF7gJOty+9///s29/nb3/7WqbOfydrzejnRMcKiY7V3Xerq6ophw4YV/fv3LyZPnlw899xznTNwD9Geddm9e3cxa9asorq6uujfv39x0UUXHff10/Zw23QAII3PWAAAaYQFAJBGWAAAaYQFAJBGWAAAaYQFAJBGWAAAaYQFAJBGWAAAaYQFAJBGWAAAaYQFAJDm/wHiLDtxN3iOygAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist(temperatura_hora, bins = 5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([21.76363983, 21.12282735, 20.66582569, 20.17065379, 19.83814623,\n", + " 19.58221154, 19.3924642 , 18.97025316, 18.91604478, 18.94470284,\n", + " 19.69269057, 21.46132578, 23.34516672, 24.8295846 , 25.90661213,\n", + " 27.02503264, 27.43821084, 27.7560822 , 27.62720268, 27.10855763,\n", + " 26.24793618, 24.63620448, 23.05617037, 22.34205607])" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "temperatura_hora" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([ 2., 13., 49., 126., 215., 239., 198., 110., 38., 10.]),\n", + " array([ 65.44546034, 71.9104344 , 78.37540845, 84.8403825 ,\n", + " 91.30535655, 97.7703306 , 104.23530466, 110.70027871,\n", + " 117.16525276, 123.63022681, 130.09520086]),\n", + " )" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#dados_randomicos = \n", + "np.random.normal(100,10, 1000) #media (pico da curva normal), escala(cada intervalo de x), quantidade de dados\n", + "plt.hist(dados_randomicos)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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kvPzAhx9W1U2aP79mgghIr3tQkJRcPvWUdO6ry8sDpk+XbvfpI71fbIlaDSxdKt3es8f4HDbJyVVz8Pzzn3VP1dAU+nmHcnON/87YubPl+5hR87BDMclGX3On+uWl9PSqXyITJhgfHbRypXT55bvvpGb7Rx4BBg6U5p84fFj6y1etlv46rn49vnrNp+Limo/n5yc1iVevi6S3b5/0eH36SP9OnJD+7dtXtc3330sJzKBBVROoVdezpzTpYJ8+UouFvrbUsmVVtaU2bpRqZd3qgQekGJ96SvrC27lTSvC8vKQk4auvpH4azz0nFX809hpXLzSof33btq27lWfZMmm0SFYWEBUl/UU9YIDUyTM5WRqK36WL1KpRXFz3OZsyRRpO/skn0nMUBKkQpYNDVT0nvZkzpda41FTpvD73nDRa5fRpqSVu1SqpZhEgPZ+VK6VLlfrJEfUx6Ec1Xb9etSwkRHqP3MrXF/jsM6mWUGamNH+SvvbXtWtSAlJQID1OYWHV+6W+164xvvhCeh+sWydNKiiKUm2xH36Q1v/f/9Vu2QKk13DrVmlywl27pPeTvrZURob0+l25InU+/+GHmiOO6nv/A1Xvb1PU9dpXf52+/166tGPs/Dz2WNWxxo+XOvU+8wwQFye936rXlvr6aym5e+MN4NVXa8ah/2xWb/1LSanqv1PX75Q33pA+VwcPSn9g7Nkjve/VaikRXblSSqL0rXsNfd7JCsg9RTK1XtWnajf2z1hZhOqSk0Vx4kSpPpSTk1RLqk8fUfy//6tdw0kUa5YDuPXfsGHSNtWnyL/1n37K/+qlDG79d2uZAf1z1B9/40ZRjIoSRR8fKebOnUXxueeMx3urS5dE8YUXRLFXL+m5OjlJJRAmThTFbduM71Pfa9y5c/2Pd/WqKM6aJYphYdKU+S4uohgaKopPPy2Kf/4pTc/f0DkrLZXqUAUFSfWvfHxE8d57q8o83Or6damURKdO0vb+/qI4ebL0eKJY+/FCQqr2re+91FApgcOHRfGRR0QxIEAUHR2lmlm33y6Kb7whillZNcsVNOa1M6b6e+v8eVG8eFGqgxYUJL2+np5SWYYtWxo+VlmZVDbinnukcgVKpSj6+krvrRUrpPpot6rv/d9QSYuGNOY9dutrWP2fMRcuiGJCgijedpsotmkjvf+Cg6UaYMeOGd+nvs9mQ79TSktFcf58UezfX3o8pVJ6P0yYIP2uMfa7oTFlRUgerApOZEHVqyTv2CF3NCSn5cur+szoK5ITkWWwzw0RERHZFSY3REREZFeY3BAREZFd4WgpIjOrPirF2MiQukZskH3Sj1gzNrquOSOUiKhu7FBMZGYZGTWnzb8VO5O2LvpO5cbMmdP4ArBE1HhMboiIiMiutMrLUjqdDlevXoWrqyuEphbAISIiIlmIoojCwkIEBARAoai723CrTG6uXr2KjvVVSCMiIiKrdenSJQQGBta5vlUmN66urgCkF8fNzc1sx9Vqtfj5558RGRkJpVJptuNS0/A8WAeeB+vBc2EdeB6ar6CgAB07djR8j9elVSY3+ktRbm5uZk9u1Go13Nzc+MaVEc+DdeB5sB48F9aB58F8GupSYnXz3MybNw8DBgyAq6srfH19MX78eJw5c6bGNpmZmXj88cfh7++PNm3a4I477kBSUpJMERMREZE1sbrkZufOnZgxYwb279+PlJQUaLVaREZGolhfxhbAlClTcObMGfzwww/4/fff8eCDD2LixIk4evSojJETERGRNbC6y1JbtmypcX/58uXw9fXFkSNHMHToUADA3r17sWTJEoSHhwMAXn/9dXz00Uc4cuQIbr/99haPmYiIiKyH1bXc3Co/Px8A4OXlZVg2aNAgfPfdd8jJyYFOp8O3336L0tJSDB8+XKYoiYiIyFpYXctNdTqdDrNmzcLgwYPRq1cvw/LVq1dj0qRJ8Pb2hqOjI9RqNdavX4/Q0FCjxykrK0NZWZnhfkFBAQCpc5dWqzVbvPpjmfOY1HQ8D9aB58F68FxYB56H5mvsa2fVMxRPnz4dP/30E/bs2VNjPHtcXBwOHjyIt99+G+3atcP333+Pjz76CLt370bv3r1rHWfu3Ll46623ai1ftWoV1Gq1RZ8DERERmYdGo8HkyZORn59f72hnq01uZs6ciQ0bNmDXrl0IqlaoJy0tDaGhoTh58iR69uxpWD5y5EiEhobi008/rXUsYy03HTt2RFZWltmHgqekpGDUqFEc5icjngfrwPNgPaz1XIiiiOySbBSVF6GtU1t4q7ztetZ4az0PtqSgoADt2rVrMLmxustSoigiLi4O69evx44dO2okNoCUtQGoNe2yg4MDdDqd0WM6OzvD2dm51nKlUmmRN5iljktNw/NgHXgerIe1nIu80jysOLYCiw8uRlpummF5iGcI4sLjENsvFh4uHvIFaGHWch5sUWNfN6vrUDxjxgysXLkSq1atgqurKzIzM5GZmYmSkhIAQPfu3REaGopnn30WBw8eRFpaGj744AOkpKRg/Pjx8gZPRET1Sk5NRuCHgUhITkB6bnqNdem56UhITkDgh4FITk2WKUKyB1aX3CxZsgT5+fkYPnw42rdvb/j33XffAZCyts2bN8PHxwdjx45Fnz59kJiYiBUrVuC+++6TOXoiIqpLcmoyoldFo0RbAvGvn+r0y0q0JYheFc0Eh0xmlZelGhIWFsYZiYmIbEheaR5iVsdAFEXoYLwLgZ4OOihEBWJWx+Dy7Mt2fYmKLMPqWm6IiMj+rDi2AhqtpsHERk8HHTRaDRKPJzZqe1EUkaXJQkZeBrI0WY36Q5nsF5MbIiKyKFEUsfjgYpP2XXRgUb2JSl5pHhbuX4iwxWHwme+DoIVB8Jnvg7DFYVi4fyHySvNMjJpsGZMbIiKyqOySbKTlptXqY9MQESLSctOQU5JjdD07J1NdmNwQEZFFFZUXNWv/wvLCWi0w7JxM9bG6DsVERGRf2jq1bdb+2kotvN/zRk+fnhjeZTgGBAzA3zf9nZ2TqU5MboiIyKK8Vd4I8QxBem56ky5NCRAQ7BmM36//Dp2ow+83fsfvN35v8uNX75wcHxHf5P3J9vCyFBERWUSlrhIAIAgC4sLjTDpGfEQ8HBQOuDPgTiiE5n1lNdQ5mewHkxsiImqUxg63rtRVYsmhJbjtk9uQW5ILAIjtFwu1Ug1FI792FIICaqUaU/pOwbju43Do6UPIeSkHXz/4tWmxN9A5mewLkxsiIqpXU4ZbH712FIO+HITnNj+Hs9ln8crWVwAAHi4eSJqYBEEQGkxwFFBAgIB1k9bV6CPj7uKOQR0HNeu5FJYXNmt/sg3sc0NERHVKTk1GzOoYaLSaWuv0w61f2/YaEickYteFXVh8cDF0YlUn3/LKcuhEHRSCAlGhUdg0eVON41XvgyNAqgiuUqqwbtI6RIZE1nrM5nZOdnVybdb+ZBuY3BARkVH64daiWHuoNVCVmGi0GsSsjqmxrke7HlgSvQTDugyrsTwqNAqXZ19G4vFELDqwqEZV8GDPYMRHxCO2byzcXdyNxtTczsleKq9G70O2i8kNERHV0pRaUNWTDBcHF8wZPgezB86Gk4OT0e09XDwQHxGPuPA45JTkoLC8EK5OrvBSeUEQhHofS985OSE5ocnPKT4ivsHjk31gnxsiIqqlqbWg9F4a/BJevvvlOhOb6gRBgLfaG108usBb7d3oxKOpnZP1RgWPatL2ZLuY3BARUQ2m1oISIODr37+2+HDrpnRO1hMhYsJ3E3Ct8JpFYyPrwOSGiIhqsFQtKHPSd05WKVUQ/vqpTr9MrVTDr40fAOBM9hmMSByBzKJMi8dH8mJyQ0RENZijFlRL0HdOXjB6AYI9g2usC/YMxoLRC3B19lUceOoAunh0AQCczjqNe1bcwwTHzrFDMRER1WBLw60b0znZ3cUd22O3Y/jy4biQfwGns05jxIoR+PXJX+Gp8myxWKnlsOWGiIhq0A+3vvVST0MECAjxDJFluHVDnZO7eHTBjqk70Mm9EwBgSKchdQ43J9vH5IaIiGrp3q57k/vcANY93LqLRxfsiN2B14a8hiX3L2l2rSqyXjyzRERkUFRehIlrJ2LTuU1N2q96LShrFuQZhH+P+HetxIYFNe0LkxsiIgIApOakYuD/BmLtn2sNywSYXgvKVhzLPIYRiSNws/imYVlji4SSdWKHYiIiAgA8t+k5nLxxEgDg5uyGrx/8GkqFslm1oKzd0WtHcW/ivcgtzcW9ifdi/aT12Hh2IxYfXFyjNESIZwjiwuMQ2y/WJhO41oYtN0REBAD43wP/g28bX3Rv1x0HnzqI+7ve36jh1ldmX7HJxAYAXJ1doVaqAQC/3/gdXf/bFQnJCUjPTa+xnb5IaOCHgUhOTZYjVGoCttwQEdkx/eWV62XXkaXJgr+bf50dfju6d8TPj/2MIM8guDm7GZY3pxaUtQv1CsX22O246393Iackp0ZF8+r0LVYl2hJEr4rGpsmbEBUa1ZKhUhOw5YaIyA7lleZh4f6FCFschoAFAXj21LMIWBCAsMVhWLh/IY5eO4qH1jyEgrKCGvv19e9bI7GpztRaUNbOp40PSrWljdpWBx1EUUTM6hjkleZZNjAyGVtuiIjsTHJqco1+MtXpL6/oWyIqdBVImpjUqodFrzi2AiUVJY3eXgcdNFoNEo8nIj4i3oKRkala77uZiMgOJacmI3pVNEq0JRD/+qnu1mWHrx5GliarpcO0GqYWCQWARQcWcRSVlWJyQ0RkJ/JK8xCzOgaiKEIH431HbpVbkgsnBycLR2a9bKFIKDUdkxsiIjux4tgKaLSaRic2AAyXV1orWykSSk3D5IaIyA7w8oppbKlIKDUekxsiIjvAyyumscUiodQwJjdERHaAl1dMIwgC4sLjTNrXmouEtnZMboiI7AAvr5gutl8s1Ep1gzW09GylSGhrxuSGiMgO8PKK6TxcPJA0MQmC0HCRUD1bLRLaWjC5ISKyA7y80jxRoVHYNHkTVEoVhL9+6tLXry9GBY9qweioqZjcEBHZCf3llca23vDySk31Fgn1CIaniycA4GjmUSSdSpIjRGokJjdERHZCf3mlMRRQQIDAyyu30BcJPRd3DlkvZuH8P84j68UspMan4stxXxq2S0hOaHYnbrIcJjdERHaks0fnGsPBb23F0V9yUSlV2PzoZkSGRLZ0iDbBWJHQcd3GYUzoGADA5YLL+Peuf8scJdWFyQ0RkR35YO8HhtsPdH2g9uUVz2AsGL0AV2ZfYWLTRIIgYNGYRYZyFR/u+xCns07LHBUZw6rgRER24lrhNSSekEopuDm7IXFCItyc3XC94Dp+SP4BD0Q9AD83v1bfebg5Qr1C8dKgl/Dv3f+GVqdF3E9x+Pmxn/maWhm23BAR2YlFBxahvLIcADD9zulwd3E3XF7xc/YzXF6h5nllyCvo7N4ZAFBaUYqCsgKZI6JbseWGiMgOFJQVYMnhJQAAJwcnxEfEyxyR/VIr1VgSvQRZmiw81ucxJoxWiMkNEZEdWHpkKfLL8gEAj/d5HAGuATJHZN/GhI2ROwSqBy9LERHZuPLKcny0/yPD/RcGvSBjNETyY3JDRGTjNp/bjCuFVwAA47qNQ/d23WWOqPXZdn4bntv0HESxaVXZyTKY3BAR2bhx3cZhe+x2jAkdgxcHvSh3OK3O88nP497Ee7Hk8BKsO7VO7nAITG6IiGyeIAgY3mU4Nj+6GYM7DZY7nFbn7k53G24nJCeguLxYxmgIYHJDRETULOO7j0dUSBQA4FLBJfxn939kjoiY3BAR2aji8mL28bACgiBg8ZjFhpmL39/7Ps5mn5U5qtaNyQ0RkY16fP3jGPzlYKw/tR46USd3OK1amHcYXhgojVLTz1zMxFM+TG6IiGzQmawz+P7099h3eR9m/jQT2kqt3CG1eq8OeRWd3DsBAH5O+xnrT6+XOaLWi8kNEZEN+mDfB4bq37MiZsHZ0VnmiKiNUxt8FFU13xA7F8uHyQ0RkY3JLMrEiuMrAEgFMp/p/4zMEZHehO4TDJ2LL+ZfxNu73wYAiKKILE0WrpddR5Ymi5esLIzJDRGRjaleIPPv/f8Odxd3mSMiPUEQsGjMIigVSowMHolx3cdh4f6FCFschoAFAXj21LMIWBCAsMVhWLh/IfJK8+QO2S6xthQRkQ0pLCvEJ4c+AQAoFUr8465/yBwR3aqrd1ccffYoLuVfwogVI6DRamptk56bjoTkBLy27TUkTUxCVGiUDJHaL7bcEBHZkKW/sUCmLbhccBn3f3M/SrQlEP/6qU6/rERbguhV0UhOTZYpUvvE5IaIyEawQKZtyCvNQ8zqGIiiCB3qH6Kvgw6iKCJmdQwvUZkRkxsiIhvx7clvcbngMgDggW4PoIdPD5kjImNWHFsBjVbTYGKjp4MOGq0GiccTLRxZ68HkhojIRvRo1wP3d70fAPDSoJdkjoaMEUURiw8uNmnfRQcWcRSVmbBDMRGRjRjQYQB+fORHpOakItQrVO5wyIjskmyk5aY1eT8RItJy05BTkgNvtbcFImtd2HJDRGRjmNhYr6LyombtX1heaKZIWjcmN0RERGbS1qlts/Z3dXI1UyStG5MbIiIr9/q217HmjzWo1FXKHQo1wFvljRDPEAgQmrSfAAEhniHwUnlZKLLWhckNEZEVO5t9Fm/vfhsT107EPSvukTscaoAgCIgLjzNp3/iIeAhC05IiMo7JDRGRFftgb1WBzOiwaJmjocaI7RcLtVINRSO/YhWCAmqlGlP6TrFwZK2H1SU38+bNw4ABA+Dq6gpfX1+MHz8eZ86cqbXdvn37MGLECLRp0wZubm4YOnQoSkpKZIiYiMh89AUWM/Iy8MeNP7D82HIAUl+MZ+98Vt7gqFE8XDyQNDEJgiA0mOAooIAAAesmrYOHi0fLBNgKWF1ys3PnTsyYMQP79+9HSkoKtFotIiMjUVxcVTZ+3759GD16NCIjI3Hw4EEcOnQIM2fOhEJhdU+HiKhR8krzDAUWfeb7IGhhEHot6YVynVQgM7ZvLL/8bEhUaBQ2Td4ElVIF4a+fWwkQoFKqsPnRzYgMiZQhSvtldfPcbNmypcb95cuXw9fXF0eOHMHQoUMBAAkJCYiPj8fLL79s2K5bt24tGicRkbkkpyYjZnWM0QKLel8e+xL3d72fBRZtSFRoFC7PvozE44lYdGBRjflvQjxDEB8Rj9i+sazqbgFW39SRny8ViPPyknqQ37hxAwcOHICvry8GDRoEPz8/DBs2DHv27JEzTCIikySnJiN6VXSdBRb1SrWlLLBogzxcPBAfEY9zcedwbdY1fNbjM1ybdQ3n4s4hPiKeiY2FWF3LTXU6nQ6zZs3C4MGD0atXLwBAeno6AGDu3Ll4//330a9fPyQmJuLee+/FyZMnERYWVus4ZWVlKCsrM9wvKCgAAGi1Wmi1WrPFqz+WOY9JTcfzYB14HhrW1AKLClGBmNUxOB93vkmXqHgurIOb0g1+zn5wU7qhoqJC7nBsUmPfw4JoxYUspk+fjp9++gl79uxBYGAgAGDv3r0YPHgwXnnlFbz99tuGbfv06YPo6GjMmzev1nHmzp2Lt956q9byVatWQa1WW+4JEBHV48ebP+LLK1/W2VpjjAAB0zpMw/0+91swMmoJFWIFSipL4OrIifsaS6PRYPLkycjPz4ebm1ud21lty83MmTOxceNG7Nq1y5DYAED79u0BALfddluN7Xv06IGLFy8aPdYrr7yC2bNnG+4XFBSgY8eOiIyMrPfFaSqtVouUlBSMGjUKSqXSbMelpuF5sA48D/UTRRGzl8xueEMjthVvw8dTPm70nCg8F9ZBfx56D+yNuXvmYuO5jXiw+4NYct8SuUOzGforLw2xuuRGFEXExcVh/fr12LFjB4KCgmqs79KlCwICAmoNDz979izGjBlj9JjOzs5wdnautVypVFrkg26p41LT8DxYB54H47I0WUjPS2/yfiJEpOelo7CisMkFFnkurIN3W2+sPbUWJRUl+OHsD/hs7GdwUDjIHZZNaOz71+o6FM+YMQMrV67EqlWr4OrqiszMTGRmZhrmsBEEAS+++CIWLVqEtWvXIjU1FW+88QZOnz6NadOmyRw9EVHjsMBi66VWqjEmTPpj/KbmJn699KvMEdkfq2u5WbJEap4bPnx4jeXLli3D1KlTAQCzZs1CaWkpEhISkJOTg759+yIlJQUhISEtHC0RkWlYYLF1e7D7g1h3ah0AYN2pdRjaeajMEdkXq0tuGtu/+eWXX64xzw0RkS3RF1hMz01vcofiYM9gFli0cdFdo6FUKKHVabH+9Hp8FPUR60qZkdVdliIiag1YYLF183DxwL3B9wIALuZfxG/XfpM5IvvC5IaISCYssNi6Pdj9QcNt/SUqMg8mN0REMtEXWDRSdqgWFli0P+O6jzPUnFp3msmNOTG5ISKSUVRoFIZ3GV7nen3RRRZYtD++bXwxpPMQAMDprNM4dfOUzBHZDyY3REQySs9Nx86MnQCkIcJBHjXn9gr2DMaC0QtwZfYVJjZ2SH9pKtAtEBfzjU9ES01ndaOliIhak/d+fQ+VYiUA4OXBL+P1oa8jpyQHheWFcHVyhZfKi52H7dgjvR/BoI6DcGfAnTzPZsTkhohIJlcLr2LZsWUApHlrZobPhCAI8FZ7N3n2YbJNvm184dvGV+4w7A4vSxERyeSDvR+gvLIcAPDcgOfgqfKUOSIi+8DkhohIBhqtBl8c/QIA4OLogoS7EmSOiKxBTkmO3CHYBV6WIiKSgVqpxtFnj+K9X99DW6e28GvrJ3dIJKOVJ1ZiyeElOHD5AC7Pvgz/tv5yh2TTmNwQEckk2DMYn97/qdxhkBU4k3UGey/tBQBsOL0Bz975rMwR2TZeliIiIpLZhB4TDLc5oV/zMbkhImpBZRVlKKsokzsMsjK3+9+Ozu6dAQDbzm9DbkmuzBHZNiY3REQt6PMjnyNkUQgW7F+A4vJiucMhKyEIAh7sIU3oV6GrwMazG2WOyLYxuSEiaiHlleV4b+97uFJ4BQnJCUjLTZM7JLIi+uQGANafXi9jJLaPyQ0RUQtZeWIlLhdcBgCM7ToWffz6yBwRWZOBgQPh10YaNbcldQtb9pqByQ0RUQuo1FXinT3vGO6/OuRVGaMha+SgcMD47uMBACUVJUhOS5Y3IBvG5IaIqAWs/XMtzuWcAwCMCBqBuwLvkjkiskbVL02tO8VRU6ZickNEZGGiKOLtPW8b7r96N1ttyLjhXYbDw8UDCkGBovIiucOxWZzEj4jIwjad24QT108AACI6RGBE0AiZIyJr5eTghO8nfY/bfG6DTxsfucOxWUxuiIgsSBRF/Gf3fwz3Xx3yKgRBkDEisnbDugyTOwSbx8tSREQWtCNjB/Zf3g8A6O3bG/d3vV/miIjsH5MbIiIL6urdFfHh8VA5qvDK3a9AIfDXLjWeTtShsKxQ7jBsDj9lREQW1MGtAxaOWYiMWRl4qOdDcodDNuJa4TVM3zgdHT7sgDe2vyF3ODaHyQ0RUQvwbeMLRwW7OVLjqJQq/O/o/5BZlIl1p9ZBFEW5Q7IpTG6IiIisjIeLB+4NvhcAcKngEo5cOyJzRLaFyQ0RkQXE/xSPd/e8i4KyArlDIRs1ofsEw21O6Nc0TG6IiMzsXPY5fHzoY7y89WUMWDoAOlEnd0hkg8Z1GwcB0rQBSaeSeGmqCZjcEBGZ2bu/vmtIaKb2ncoRUmQSv7Z+uLvT3QCAs9lncSrrlMwR2Q5+4oiIzOhS/iUkHk8EALg7u+O5Ac/JHBHZMtaaMg2TGyKiZhBFEVmaLGTkZSBLk4X5v86HVqcFAMwMnwl3F3eZIyRbxn43puG4RCIiE+SV5mHFsRVYfHAx0nLTDMv1fSRUjirMumuWTNGRvejs0Rn92/fHkWtHcDTzKM7nnkeQZ5DcYVk9ttwQETVRcmoyAj8MREJyAtJz02usEyF1+qzQVeDIVQ7fpebTX5ryUfvgXM45maOxDWy5ISJqguTUZESvioYoioZExphKXSWiV0Vj0+RNiAqNasEIyd5M6TsFd3e6G4M7DoaDwkHucGwCW26IiBoprzQPMatjIIoidKh/eLcOOoiiiJjVMcgrzWuZAMkuBboFYmjnoUxsmoDJDRFRI604tgIarabBxEZPBx00Wo1h9BQRtQwmN0REjSCKIhYfXGzSvosOLOIEbGQ2xeXFcodg9ZjcEBE1QnZJNtJy0+rtZ2OMCBFpuWnIKcmxUGTUWnx78luM+moUfOb78FJnA5jcEBE1QlF5UbP2LywvNFMk1FodvHIQv6T/gpKKEnzz+zeGuZXYKlibRZMbUafD+eRkSz4EEVGLaOvUtln7uzq5mikSaq1GBY8y3H5u83MIWhgEn/k+CFschoX7F7I1p5pmDQU/9umn+GP5cmhu3ICushLQZ4+iiEqtFuX5+agsL8fzlZXmiJWISDbeKm+EeIYgPTe9SZemBAgI9gyGl8rLgtGRvUtOTcZDax4yui49Nx0JyQl4bdtrSJqYxKkH0Izk5uSKFfjlufprpji7uaHHY4+Z+hBERFZDEATEhcchITmhyfvGR8RDEAQLREWtQfW5lYzRJ9sl2hLOrfQXky9LnfjsMzg4OeFvW7ZgVkkJ/O+8E32ffRazSkrw2KFDCLjrLlRqtbjz+efNGS8RkWxi+8VCrVRD0chfnQpBAbVSjSl9p1g4MrJXnFvJNCYnN9l//onQcePQJTISjs7OCBg4EJd27ICjszP8+/fHg5s2QalW4+A775gzXiIi2Xi4eCBpYhIEQWgwwVFAAQEC1k1aBw8Xj5YJkOwO51YyjcnJTUVJCTxCQgz3Pbt1Q+65c6goKwMAuHh6IuSBB3DtwIHmR0lEZCWiQqOwafImKB2URtcLf/2olCpsfnQzIkMiWzhCshecW8l0Jic3qnbtUJqXZ7jvHhQEiCJyz541LGvj54fCy5ebFSARkbWJCo3C3Z3uNrou2DMYC0YvwJXZV5jYULNwbiXTmdyhuH1EBNI2bMDd//oXVN7eaNezJ0RRxMWtW+HTuzcA4OaJE3Bq27zhk0RE1uZm8U3syNgBAOjk1glHnjmCIm0RXJ1c4aXyYudhMgtzzK3krfY2UzS2xeTk5va4OKRu2IDlvXphTGIiuowahQ6DBmHPG2+gsrwc+RkZOP/TTwgZO9ac8RIRyW7tn2tRKUpTXDzS+xG0a9MO7dBO5qjI3nBuJdOZfFmq0z33IHLpUui0WpQXSjNvDps/HwCw+5VXcPzTT+Hi5YW7//Mf80RKRGQlvjn5jeH2I70ekTESsmf6uZUENK0lUICAEM+QVj23UrMm8ev95JPoOWUKdBUVAICAgQPx5KlTOLduHRxVKoSMHYs2/v5mCZSIyBqIoojRoaORXZINURTRx6+P3CGRneLcSqYzueXm26FDsfett6BwdISji4thuWtgIO6Ij0efp59mYkNEdkcQBLw65FWcnH4Su5/Y3aq/QMjyOLeSaUxObjIPHUJpTuvtiU1ErZsgCK22sya1HM6tZBqTkxu1vz+TGyIiIgvTz62kUqoM8ygZw7mVqpic3Ny7aBHOrV+PPa+/jpsnTqC8qAiiTmf0HxGRPdh+fjv+vPmn3GFQKxQVGoXLsy9jwegFCPYMNrrNhoc3MLH5i8kdine/9hocnJ1xYN48HJg3r+4NBQHP/9XhmIjIVomiiOmbpuNM9hn08++HfdP2wcXRpeEdiczEw8UD8RHxiAuPQ05JDgrLC/HjmR8RvyUeALAldQvuDb5X5iitg8nJTXlBAZzc3ODk5mbOeIiIrNKxzGM4k30GAODm7MbEhmSj7+/lrfbGo30exeyfZ6NCV4G1p9bivVHvsZM7mpHcPJORYcYwiIisG+e2IWvkpfLCPV3uQUp6CjLyMnA08yjuaH+H3GHJzuQ+N0RErYVO1OHbk98CABwVjvjbbX+TOSKiKtXfj2v/XCtjJNbD5JabS7t2NXrbjkOHmvowRESy23tpLy4VXAIAjAoehXZqllog6zG++3hM3zQdOlGHtX+uxX9G/KfVX5oyObn5bvjwRr94z1dWmvowRESy++Z3XpIi6+XbxhdDOw/FjowdOJdzDidvnERvv95yhyUrk5ObHpMnG01utMXFyD13Dll//IGOw4YhdPz45sRHRCSrCl0F1vy5BgDg4uiC8d3HyxsQkRF/6/E37MjYAXdnd5zLOcfkxtQdo1eurHf9mbVrsfnRRxHx6qumPgQRkey2pm/FTc1NAMD9Xe+Hq3PrrbRM1uuhng8hxCsEI4JGwMnBSe5wZGexDsXd/vY3BN13H/b985+WeggiIov79o9vDbd5SYqslW8bX4wOHc3E5i8WHS3l1b07bhw9asmHICKyqAe7P4gJ3SfAt40v7gu7T+5wiKgRTL4s1RhX9uypUTGciMjWjO02FmO7jUV5ZTn/KiabUVRehLZObeUOQzYmJze/f/ml0eWiTofywkKkb9qEq3v3ovvDDzfpuPPmzcO6detw+vRpqFQqDBo0CO+++y66detW+7FEEffddx+2bNmC9evXYzw7LxORhTCxIVvw07mf8MnhT5CSloI/nvsDIV4hcockC5OTm+Snnqp3KLgoinDr3BlD6qs7ZcTOnTsxY8YMDBgwABUVFXj11VcRGRmJP//8E23atKmx7YIFC1r9WH4iIiK932/8jo1nNwIAkk4l4aXBL8kckTxMTm4Gvvmm8cRCEODg5ATvHj0QHB0NhWPTHmLLli017i9fvhy+vr44cuQIhlabDPDYsWP44IMPcPjwYbRv396k50BEVJddF3YhpyQHY0LHwNnRWe5wiBolpkcM/u+X/wMgzVbM5KaJBs+da8Yw6pafnw8A8PLyMizTaDSYPHkyPv74Y/j7+7dIHETUurz767vYfG4z3J3dcfiZwwj1CpU7JKIGhXiFoJ9/PxzLPIZDVw/hQt4FdPboLHdYLc70GYpHjECvqVPRc8qUOrf5bdEiHP3vfzHt7FmTHkOn02HWrFkYPHgwevXqZViekJCAQYMGYdy4cY06TllZGcrKygz3CwoKAABarRZardak2IzRH8ucx6Sm43mwDrZ8HrI12fg57WcAgKuTKzq27WiTz0PPls+FPWmp8zC+63gcyzwGAFjzxxr8I/wfFn28ltTY167RyY0oioAoGm5f2rEDHYcNg6jTGd2+srwcl3bsQOGlS419iFpmzJiBkydPYs+ePYZlP/zwA7Zt24ajTRhiPm/ePLz11lu1lv/8889Qq9Umx1eXlJQUsx+Tmo7nwTrY4nlIzkpGha4CAHCny53Y8tOWBvawDbZ4LuyRpc9Du9Kq2mdf7vsSYVlhFn28lqTRaBq1nSCKf2UsDTj43nvY/corhvuiKDaqM69Pnz6YYsJcNzNnzsSGDRuwa9cuBAUFGZbPmjULixYtgkJRNUVPZWUlFAoFhgwZgh07dtQ6lrGWm44dOyIrKwtubm5Njq0uWq0WKSkpGDVqFJRKpdmOS03D82AdbPk8jFw5ErsuSsWBDzx5ALf73y5zRM1jy+fCnrTkeej7eV+cyjoFAMiIy0CAa4BFH6+lFBQUoF27dsjPz6/3+7vRLTf9ExJwbt06FF+/DgAovHgRTm5ucPbwqLWtIAhQKJVw69QJQ999t0mBi6KIuLg4rF+/Hjt27KiR2ADAyy+/jKeeeqrGst69e+Ojjz7C2LFjjR7T2dkZzs61OwQqlUqLvMEsdVxqGp4H62Br5+FKwRXsvrgbANDVuysGBA6wm1GZtnYu7FVLnIeHbnsI/9wlVQjYmLoRM8JnWPTxWkpjX7dGJzcOSiUe3b/fcP99hQL9ExIw6M03mx5dPWbMmIFVq1Zhw4YNcHV1RWZmJgDA3d0dKpUK/v7+RjsRd+rUqVYiRETUVN/98R1ESA3aj/R6xG4SG2pdYm6LMSQ3a0+ttZvkprFMLr8waft29IyNNWcsAIAlS5YgPz8fw4cPR/v27Q3/vvvuO7M/FhHRrb45+Y3hNmtJka3q7dsbYV5SX5uCsgKUV5bLHFHLMnm0VMdhwxrcRtTpkJGSgqCoqEYft5FdgJq9DxHRrc5ln8Phq4cBALf7345u7WrPjE5kCwRBwBcPfIEOrh1a5SzFzaotdezTT/HH8uXQ3LgBXWWlYTQVRBGVWi3K8/NRWV6O5ysrzRErEZFFffdHVQsxW23I1g3tPLThjeyUycnNyRUr8Mtzz9W7jbObG3o89pipD0FE1KJiesSguLwY3/3xHSb1miR3OERkIpP73Jz47DM4ODnhb1u2YFZJCfzvvBN9n30Ws0pK8NihQwi46y5UarW48/nnzRkvEZHF9PDpgXkj5yEtPg2d3DvJHQ6R2YiiiKLyIrnDaDEmJzfZf/6J0HHj0CUyEo7OzggYOBCXduyAo7Mz/Pv3x4ObNkGpVuPgO++YM14iIovjCCmyFyXaEry+7XX0+LgHHl77sNzhtBiTk5uKkhJ4hFR1UvLs1g25586h4q/J8lw8PRHywAO4duBA86MkIiKiJnN2dMbyY8txJvsMfk77Gfml+XKH1CJMTm5U7dqhNC/PcN89KAgQReRWqyPVxs8PhZcvNytAIiJLO3rtKN7d8y4u5F2QOxQis1IICsT0iAEAaHVabDy7UeaIWobJyU37iAikbdiAkuxsAEC7nj0hiiIubt1q2ObmiRNwatu2+VESEVnQl0e/xMtbX0aXhV1azS9/aj3+dtvfDLfXnlorYyQtx+TRUrfHxSF1wwYs79ULYxIT0WXUKHQYNAh73ngDleXlyM/IwPmffkJIHSURiIisQYWuAqv/XA0AcHZwbtXDZ8k+Deo4CH5t/HC9+Dq2pG5BUXkR2jrZd8ODyS03ne65B5FLl0Kn1aK8sBAAMGz+fADA7ldewfFPP4WLlxfu/s9/zBMpEZEFbD+/HTeKbwAAortGw83ZfMV0iayBg8IBD/Z4EABQWlGKzec2yxyR5TVrEr/eTz6JnlOmQFdRAQAIGDgQT546hXPr1sFRpULI2LFoY6QOFBGRtfj25LeG25y4j+xVTI8YLDm8BACw9s+1mNhzoswRWZbJyc23Q4ei0733YtCcOVA4Vh3GNTAQd8THmyU4IiJLKqsoQ9KpJACAq5MrosOiZY6IyDKGdRkGb5U3skuysencJmi0GqiVarnDshiTL0tlHjqE0pwcc8ZCRNQiRFFEliYLK46vQH6ZNDR2fPfxUClVMkdGZBmOCkdM6D4BAKDRapCcmixzRJZlcsuN2t+fyQ0R2ZS80jysOLYCiw8uRlpuWo11KkcV8krz4OHiIU9wRBYWc1sMvjj6BdRKNS4X2Pc0LSa33Ny7aBHOrV+PPa+/jpsnTqC8qAiiTmf0HxGR3JJTkxH4YSASkhOQnptea/3S35Yi8MNAu/+LllqvEUEjsG7iOtx88SbiIuLkDseiTG652f3aa3BwdsaBefNwYN68ujcUBDz/V4djIiI5JKcmI3pVNERRhAjR6DYiRJRoSxC9KhqbJm9CVGhUC0dJZFlODk6Y0GOC3GG0CJOTm/KCAji5ucHJjcMmich65ZXmIWZ1DERRhA71tyTroINCVCBmdQwuz77MS1RENsrk5OaZjAwzhkFEZBkrjq2ARqups8XmVjrooNFqkHg8EfERHPlJ9qtEWwKlgxKOimbNCmOVTO5zQ0Rk7URRxOKDi03ad9GBRRDFxiVERLZk/+X9mLR2Enzm+2Br+taGd7BBzU5uMg8fRsr06VgZEYH/de0KADiblISjn3ximNyPiEgO2SXZSMtNa3SrjZ4IEWm5acgp4YhQsj9XCq5g9R+rUawtNszzZG+aldzs+/e/8fVdd+H4Z58h89Ah5KVJQyuv7t+PbXFx+H7CBFRqtWYJlIioqYrKi5q1f2F5oZkiIbIeY8LGGCbwW396PSp09tcQYXJyk7phA35980349O6NCRs21JiVuNcTTyBg0CCc37wZJ5YuNUugRERN1dzigK5OrmaKhMh6qJVq3Bd2HwAgS5OF3Rd2yxyR+Zmc3Bz+6CO4duiAh3ftQsjYsXDx9DSsa3fbbXgoJQVunTvj5LJlZgmUiKipvFXeCPEMgQChSfsJEBDiGQIvlZeFIiOSV0yPGMPttX+ulTESyzA5ublx9ChCJ0yAk6vxv2wcXVwQ8sADyEtNNTk4IqLmEAQBceGmTVYWHxEPQWhaUkRkK6LDouHs4AwASDqVhBvFN5CRl4EsTZZddKQ3ObkRKyshKOrfXafVQsc+N0Qko9h+sVAr1VA08tedQlBArVRjSt8pFo6MSD6uzq4YETQCAHC9+Dr83vdD0MIg+Mz3QdjiMCzcvxB5pXnyBtkMJic3Xj164EJKCnSVlUbXV5aXI+Pnn+HVo4fJwRERNZeHiweSJiZBEIQGL08poIAAAesmreMEfmTXklOTse38NqPr0nPTkZCcYNPlSExObno98QSyT53CliefRFlBQY11JTk52Pz448hPT0fPxx9vdpBERM0RFRqFTZM3wUHhYHS98NePSqnC5kc3IzIksoUjJGo5+nIk2krjV1bEv3705UhsMcExeVrCftOn40JKCv786iucXrUKjmppWNmynj2Rl5aGyvJydB45Ev1mzDBbsEREpooMiYSniyduam5CgFBj7ptgz2DER8Qjtm8s3F3cZYySyLJaSzkSk5MbQRAwbt06HP3vf3H800+RfeoUACD71Cl4BAej97RpGPDii1A4GP9LiYioJf1+43fc1NwEANwXdh9WjF+BwvJCuDq5wkvlxc7D1Cq0lnIkzSooIQgC7oiLwx1xcdBqNCjLy4OTq2udI6iIiORSvWk9KiQK3mpveKu9ZYyIqGU1txxJXHiczfwRYJbaUpVaLfLPn0f++fMounYNoq7+pi4iopY2rMswzIqYhdt8bsOokFFyh0PU4lpTOZJmtdxobt7Entdfx+lvv4W2qGqacxdvb/R+8kkMnDMHSpWq2UESETVXeIdwhHcIlzsMItmYoxyJrbR2mpzcaG7exKpBg5CXlgaVtzf8hw9Hm/btUZaXh2sHD+Lge+/h4vbtmLRjBxMcIiIimbWmciQmJzd7585FXloaBrzwAga99VaNBEZXUYHdr76KQ++/j4PvvovBc+eaI1YiIiIykb4cSXpuepMuTQkQEOwZbFPlSEzuc5P2448IHDIEw957r1bLjMLREcPeew8Bd92FU19/3ewgiYiaY80fa3Ap/5LcYRDJqjWVIzE5uSnJzkbAwIH1bhMwaBCKrlwx9SGIiJrtauFVTFw7EZ0WdMLDax+WOxwiWTW5HAlssxyJyclNu169cHX//nq3uXniBLxZfoGIZJSSlmK4HeYVJmMkRPKrXo6kMQmODjqseWiNTU3gBzQjuRn67ru4tm8ftj//PMqLi2utP7JwIS5u24ZBb73VrACJiJrj5/SfDbdZVoGoqhyJSqkylB6p7tb7RzOPtmR4ZmFyh+Izq1fDu2dP/LZgAf5MTIR/eDjcOnaEVqPBtQMHkJeaCic3Nxx67z0ceu+9qh0FAQ/v3GmO2ImI6qUTdYaWG1cnV9wVeJfMERFZh6jQKFyefRmJxxOx6MAipOWmGdYFewbjvrD78N+D/4UIEW9ufxMjgkbY1OfH5OTm+KefGm6XZGfj/E8/1dqmLD8fl/fsqbHMljokEZFtO5553FByYUTQCCgdlDJHRGQ9PFw8EB8Rj7jwOOSU5NQqR+Lh4oF/7foXKsVKvLPnHXz/8Pdyh9xoJic3T58/b844iIjM7uc0XpIiaoggCEbLkbw57E1sO78N/dv3x7uj3pUpOtOYnNy4d+5szjiIiMyO/W2ITOeocMTWKVvh7OgsdyhN1qzyC3pFV6+iorS0zvUewcHmeBgiokYrLi/GnovSZfEgjyCEeIbIHBGR7bHFxAZoRnJTXlyMHQkJ+POrr1BZXl73hoKA5ysqTH0YIiKT7LywE+WV0u+myJBI9vcjMoNTN0/hvb3v4bP7P4OTg5Pc4dTJ5ORmz6uv4sQXX0DZpg38+vSBUq02Z1xERM3i4uiCUcGjsOvCLl6SIjKD1X+sxtTvp6KkogS+al+r7odjcnKTumEDPMPC8Oj+/XDx9DRnTEREzTYiaARGBI1AibYECsHkKb2I6C8hniGo0ElXYt7b+x5GhYzCyOCRMkdlnMmfeM3NmwibMIGJDRFZNZVSZbP9BoisSf+A/nj73rcN96esn4KbxTdljKhuJic3Pr17o+DCBXPGQkRERFZs9sDZhsu814quYdoP0yCKja8w3lJMTm7ueu01nE1KwvnkZHPGQ0TUbGk5aajUVcodBpHdUQgKrBi/Aj5qHwDAj2d/xMeHPpY5qtpM7nMTMnYs7pw9G+vuuw++/frBPSQEji4utTcUBNy3YkVzYiQiarRKXSXCvwiHTtQhpkcMvnjgC7lDIrIr/m39sXz8ckSvigYAvPDzCxjaeSj6+PWRObIqJic3aRs34vCHH0IURVw/ehTXjxovrCUwuSGiFnQ08yhySnIAALmluTJHQ2Sf7gu7D/+I+AcWHliIssoyPJL0CA49fQgqRxWyS7JRVF6Etk5t4a3ylmUaBpOTm1/ffBOiTofw//s/dLj7bji1bWvOuIiITFKj5EIwh4ATWcq7I9/FjowdOH79OE7dPIVZW2Zh2/ltNYpwhniGIC48DrH9YuHh4tFisZmc3OScPo3bHnsMQ+fNM2c8RETNwnpSRC3D2dEZ38R8g8ivIpFVkoUvfqt9CTg9Nx0JyQl4bdtrSJqYhKjQqBaJzeQOxSpvb7h4eze8IRFRCyksK8TeS3sBAKFeoQjyDJI5IiL7djH/Iq4VXUN5RTnEv36q0y8r0ZYgelU0klNbZhCSyclN90cewbmkJJQXFpozHiIik+28sBNanRYAL0kRWVpeaR5iVsdAFEXooKt3Wx10EEURMatjkFeaZ/HYTL4s1X/WLFzctg1f9e+PPs8+C8+wsDr73XQaMcLkAImIGouXpIhazopjK6DRamq11tRFBx00Wg0SjyciPiLeorGZnNx8GhgIQRAgiiJ2vfRSvds+X8n5JojI8vTJjYPggHuC7pE5GiL7JYoiFh9cbNK+iw4sQlx4nEVHUZmc3PScMgVglV0ishIX8i7gTPYZAMDAjgPh5uwmc0RE9iu7JLvGqKjGEiEiLTcNOSU58FZbrt+uycnNmOXLzRgGEVHzZORlIMA1AFcLr7K/DZGFFZUXNWv/wvJC60xubqXVaFCamwvXDh3MdUgiokYb1mUYLidcxp83/2zR+TSIWqO2Ts2b287VydVMkRhn8mgpABB1Ohz64AN82aMHFrm64vPOnQEAhz/6CD9MnIjCK1fMEiQRUWMIgoCevj3RwY1/ZBFZkrfKGyGeIRDQtO4pAgSEeIbAS+VlocgkJic3uooKJEVHY9dLLyH33Dk4ubkBf1UGLbx4EWfXrsW3Q4dCc9M6y6ETERGRaQRBQFx4nEn7xkfEW7wkg8nJzZGFC5GRnIxeTz6JGVlZuOMf/zCsG/LOO7hz9mzknz+PQ++/b5ZAiYjqwgrgRC0vtl8s1Eo1FI1MJRSCAmqlGlP6TrFwZM1Ibv5MTIRvv36IWroULh4eNbIwR2dnDH//fQTcdRfSfvzRLIESEdVlROIIDPrfIMzdMZeJDlEL8XDxQNLEJAiC0GCCo4ACAgSsm7SuRfrEmZzc5J47hy6R9Y9I6DBkCAouXDD1IYiIGpRfmo9fL/6KfZf34duT38JB4SB3SEStRlRoFDZN3gSVUgXhr5/q9MtUShU2P7q5xSbXNDm5cXRxQUl2dr3baK5fh6Ozs6kPQUTUoO0Z21EpSq01nJWYqOVFhUbh8uzLWDB6AYI9g2usC/YMxoLRC3Bl9pUW/XyanNz43Xkn0n74AaW5uUbXF2dmIu2HH+A/YECTjjtv3jwMGDAArq6u8PX1xfjx43HmzBnD+pycHMTFxaFbt25QqVTo1KkT4uPjkZ+fb+pTISIbVr3kQlRIy1QcJqKaPFw8EB8Rj3Nx55D1YhbO/+M8sl7Mwrm4c4iPiIe7i3uLxtPo5OaPxETcPHHCcH/Aiy9Cc/Mmvh02DGkbNxpacTRZWUjbuBHf3XMPyvLzcXt80+pH7Ny5EzNmzMD+/fuRkpICrVaLyMhIFBcXAwCuXr2Kq1ev4v3338fJkyexfPlybNmyBdOmTWvS4xCRfdAnN0qFEsO6DJM5GqLWTRAEeKu90cWjC7zV3hYfFVWXRk/i99PUqRg0dy58+vQBAHQZNQrD5s/Hrv/7P3w/bpxhuyV+fgCkuhMD33gDIdHRTQpoy5YtNe4vX74cvr6+OHLkCIYOHYpevXohKSnJsD4kJAT/+c9/8Nhjj6GiogKOjmabl5CIrFxaTpphCvjBnQY3e2IxIrIPzcoEBjz/PLqMGoXjn32GzMOHUZabCydXV/jefjt6T5uGgIEDmx2g/nKTl1fdE/7k5+fDzc2NiQ1RK5OSnmK4zZILRKTX7GzAp08fjPz4Y3PEUotOp8OsWbMwePBg9OrVy+g2WVlZ+Ne//oVnnnmmzuOUlZWhrKzMcL+goAAAoNVqodVqzRav/ljmPCY1Hc+DdWiJ8/DTuZ8Mt0d0HsFzXgd+JqwDz0PzNfa1s+qmjhkzZuDkyZPYs2eP0fUFBQWIjo7Gbbfdhrlz59Z5nHnz5uGtt96qtfznn3+GWq02V7gGKSkpDW9EFsfzYB0sdR4qxAr8kvoLAMDVwRVXf7uKTCHTIo9lL/iZsA48D6bTaDSN2k4Qxb9qJjTgfYUCYePHI3T8+CYH03NK02cjnDlzJjZs2IBdu3YhKCio1vrCwkJERUVBrVZj48aNcHFxqfNYxlpuOnbsiKysLLi5uTU5NmNEUURmQSa2bNuC0SNGw9/NX7aOVK2dVqtFSkoKRo0aBaVSKXc4rZalz8PRzKO468u7IELExNsmYuX4lWZ/DHvBz4R14HlovoKCArRr187QHaUuTWq5Sd2wAakbNjQ5mKYkN6IoIi4uDuvXr8eOHTuMJjYFBQWIioqCs7Mzfvjhh3oTGwBwdnaGs5H5dpRKZbPfYHmleVhxbAUWH1xs6NiIU0CIZwjiwuMQ2y+WFYplYo7zS81nqfMQ3jEcN1+8ia3ntyLANYDnuhH4mbAOPA+ma+zr1qTkxqdvX/j07WtSQI01Y8YMrFq1Chs2bICrqysyM6VmZnd3d6hUKhQUFCAyMhIajQYrV65EQUGBoQ+Nj48PHBxabnbS5NRkxKyOgUZbu5ksPTcdCckJeG3ba0iamISoUM6/QWRu3mpvTOw5Ue4wiMjKNCm5CR0/HoPefNNSsQAAlixZAgAYPnx4jeXLli3D1KlT8dtvv+HAgQNSPKGhNbY5f/48unTpYtH49JJTkxG9KhqiKEJE7St7+mUl2hJEr4rGpsmbmOAQERG1AKvrUNxQF6Dhw4c3uI2l5ZXmIWZ1DERRhA66erfVQQeFqEDM6hhcnn2Zl6iIiIgszOTyC63ZimMroNFqGkxs9HTQQaPVIPF4ooUjI2od3tz+Jp7+4Wms+WMNSitK5Q6HiKwMk5smEkURiw8uNmnfRQcWyd7qRGTrRFFE4vFEfHH0Czy2/jFU6irlDomIrEyjk5tBc+ag4y39YFqj7JJspOWmGe1nUx8RItJy05BTkmOhyIhah9ScVFzIvwAAuLvT3Wjj1EbmiIjI2jS6z82gOXMsGYfNKCovatb+heWF8FZ7mykaotaHVcCJqCG8LNVEzS3M5+rkaqZIiFqnn9OrkpvIENaTIqLamNw0kbfKGyGeIRDQtNmHBQgI8QyBl6ruAqBEVD9tpRbbzm8DAPi28UUfvz4yR0RE1ojJTRMJgoC48DiT9o2PiGdJBiITiKKILE0W1p9ab7g0PCp4FBQCf4URUW38zWCC2H6xUCvVUDTh5XNxdMGUvk2vsUXUmuWV5mHh/oUIWxwGn/k+mJQ0qdZ6IqJbMbkxgYeLB5ImJkEQhEYnOJ4qTwtHRWRfklOTEfhhIBKSE5Cem15r/arfVyHww0AkpybLEB0RWTMmNyaKCo3CpsmboFKqIPz1U51+mb7Z/GrhVTyx4Qk5QiWyOfryJiXaEoiou8SJvrwJExwiqo7JTTNEhUbh8uzLWDB6AYI9g2usC/YMxoLRC3D02aPwVnnDr40fXhj4gkyREtmOppY3EUURMatjeImKiAysrraUrfFw8UB8RDziwuNwveA6fkj+AQ9EPQA/Nz9D5+EfH/kRHd07ItAtUOZoiayfvrxJYyfKrF7eJD4i3sLREZEtYMuNmQiCAG+1N/yc/eCt9q4xKmpgx4FMbIgageVNiMgcmNzIQCfq8MHeD5CtyZY7FCKrwvImRGQOTG5aWH5pPsZ9Ow4vpLyAR5IeQYWuQu6QiKyGOcqbEBExuWlhBWUFOHD5AAAgJT0Fr/zyiswREVkPljchInNgctPCOrp3xNqJa+GokPpyv7/vfaz6fZXMURFZB5Y3ISJzYHIjg6Gdh2Lh6IWG+9N+mIbfrv0mY0RE1oHlTYjIHJjcyGT6ndMx7fZpAIDSilJM+G4CbhbflDkqIvk1tbyJQlBArVSzvAkRGTC5kYkgCPj4vo9xV+BdAICL+Rcxce1EaCu1AKoKBWbkZSBLk8UhrtRqNKW8iQIKCBCwbtI6eLh4tEyARGT1mNzIyNnRGUkTk+Df1h8AsCNjB+I2x9UoFBi0MAg+830QtjgMC/cv5Cys1Croy5s4OzobXa8vb6JSqrD50c2IDIls4QiJyJoxuZFZgGsA1k1cB6VCCQBY+ttSo4UC03PTkZCcwEKB1GpEhUYh4a4Eo+v05U2uzL7CxIaIamH5BSswsONAPDfgOSw6sAgA6iwSCMBQKHDT5E2ICo1q0TiJWtr2jO2G20efOQoPlQdcnVzhpfJi52EiqhNbbqxAXmkevvjtCwgQWCiQ6C9Zmizsv7wfANDTpyf6te+HLh5dapU3ISK6FZMbK6AvFNhQYqNXvVAgkb1ydnDG0rFLMaH7BEzsOVHucIjIhvCylMyaWygwLjyOf8WSXXJ1dsW0O6Zh2h3T5A6FiGwMW25kxkKBRERE5sXkRmYsFEhERGRevCwlMxYKJKpt49mNUCqUGNZlGFwcXeQOh4hsDFtuZMZCgUS1vbbtNYz+ejR85vugsIytk0TUNExuZMZCgUQ1Xcq/hBPXTwAAerTrAVdntk4SUdMwubECTS0UCEgdiqNCOIkf2Z/N5zYbbkeHRcsYCRHZKiY3VqAphQL1Hu75MLq162bhyIha3qZzmwy3o7syuSGipmNyYyX0hQJVSpWhKGB1+mVtlG3w9/5/x6qYVTJFSmQ5pRWl2Hp+KwDAr40f7mh/h8wREZEtYnJjRaJCo3B59mUsGL0AwZ7BNdZVLxS45P4ltfraHL12FDqxcTMcE1mrnRk7odFqAABjwsZAIfBXFBE1HYeCWxkPFw/ER8QjLjwOOSU5KCwvbLBQ4O4LuzHqq1F4oNsDSJyQyKGzZLNqXJJifxsiMhGTGyslCAK81d7wVnvXu11ReRFiVsegrLIMa/5cg+vF1/H9pO/hqfKssZ0oisguyUZReRHaOrWFt4rFB8m6iKJoSG4cFY4YFTxK5oiIyFaxzdfGtXVqi+Xjl0OtVAMAdl3YhcFfDsbF/IsApIrjC/cvRNjiMPjM90HQwiD4zPdB2OIwLNy/kJXFyWqczT6L9Nx0AMDdne6Gu4u7zBERka1icmMH7gu7Dztid8BH7QMAOJV1CgP/NxBLDi1B4IeBSEhOMHxp6KXnpiMhOQGBHwYiOTVZjrCJanB2dMasiFno6t2Vl6SIqFmY3NiJAR0GYN+0fQjzCgMAXC28iuc2PweNVgPxr5/q9MtKtCWIXhXNBIdk18WjCz4a/RHOzDyDhLsS5A6HiGwYkxs7EuIVgl+f/BX92/c3LGuo2rgOOoiiiJjVMbxERVbDQeEgdwhEZMOY3NgZnzY+mNRzUpP20UEHjVaDxOOJFoqKiIio5TC5sTOiKOKzI581uRAnACw6sAiiWH9LD5El7LqwC1cKrsgdBhHZCSY3dia7JBtpuWkNXo66lQgRablpyCnJsVBkRMaJooiH1z6MwI8CMeh/g5hgE1GzMbmxM0XlRc3av7C80EyREDXOscxjuFZ0DQDqnaySiKixmNzYmbZObZu1v6uTq5kiIWoczkpMRObG5MbOeKu8EeIZ0uQ+NwIEhHiGwEvlZaHIiIzbfG6z4fZ9YffJGAkR2QsmN3ZGEATEhceZtG98RDwvCVCLytJkYf/l/QCAnj490dmjs8wREZE9YHJjh2L7xUKtVEPRhNOrUqowpe8UC0ZFVNuW1C2Gzu+8JEVE5sLkxg55uHggaWISBEFodILj4eKBwjJ2JqaWxUtSRGQJTG7sVFRoFDZN3gSVUgXhr5/qhGo/gFSuYciyIbVqUBFZSoWuAltStwAA3J3dMajjIJkjIiJ7weTGjkWFRuHy7MtYMHoBgj2Da6wL9gzGgtELcGL6CYR6hQIALuRfwIPfPQidqJMjXGpl9l/ej9zSXABAZEgklA5KmSMiInvhKHcAZFkeLh6Ij4hHXHgcckpyUFheCFcn1xrzieyaugsjvxqJq4VXsWzcMigE5rxkeQIEjAweiZ0ZO9nfhojMislNKyEIArzV3vBWe9da1961PXbE7sClgku4vf3tMkRHrdHgToOR8ngKCssKWSiTiMyKyQ0BkApu+rTxqbFMJ+pwNvssurfrLlNU1Bq4OnPiSCIyL15/IKNEUcT0jdPR//P+2HZ+W611WZosZORlIEuTxVpARERkVZjckFFLf1uKz3/7HBqtBtGrovHTuZ+QV5qHhfsXImxxGHzm+yBoYRB85vsgbHEYFu5fiLzSPLnDJhtxOus0KnWVcodBRHaKyQ0ZFds3Fg90ewAAUFpRirHfjIX/+/5ISE6oNVw8PTcdCckJCPwwEMmpyXKESzakrKIM/T/vD9/3fTFryyy5wyEiO8TkhoxydnTG2ofWYmLPiQCASrESZZVlEP/6qU6/rERbguhV0UxwqF47L+yERqtBTkkO8svy5Q6HiOwQkxuqk9JBiU/u+wSOisb1O9dBB1EUEbM6hpeoqE6bzrIKOBFZFpMbqtfKEyub1DdCBx00Wg0SjydaMCqyZZtTpZILjgpHjAoeJXM0RGSPmNxQnURRxOKDi03ad9GBRRxFRbWczT6L1JxUAMDdne6Gu4u7zBERkT1ickN1yi7JRlpuWq0+Ng0RISItNw05JTkWioxsFS9JEVFLYHJDdSoqL2rW/oXlrDJONW06V5XcsAo4EVkKkxuqU1unts3a39WJM89SlcKyQuy6sAsA0MWjC3q06yFzRERkr6wuuZk3bx4GDBgAV1dX+Pr6Yvz48Thz5kyNbUpLSzFjxgx4e3ujbdu2iImJwfXr12WK2H55q7wR4hkCAUKT9w3xDIGXyssCUZGt+iX9F2h1WgDAfaH3GQq3EhGZm9UlNzt37sSMGTOwf/9+pKSkQKvVIjIyEsXFxYZtEhIS8OOPP2LNmjXYuXMnrl69igcffFDGqO2TIAiIC48zeX99x1EiQLpMGeAaAACI7sr+NkRkOVaX3GzZsgVTp05Fz5490bdvXyxfvhwXL17EkSNHAAD5+fn43//+hw8//BAjRoxA//79sWzZMuzduxf79++XOXr7E9svFmqlGoomvlXSctPQ59M+eHfPu6jQVVgoOrIlU/pOweWEyzj67FHc0+UeucMhIjtmdcnNrfLzpRlMvbykSxxHjhyBVqvFyJEjDdt0794dnTp1wr59+2SJ0Z55uHggaWISBEFoMMFRQAGFoIBfGz8AUtmGl7e+jPCl4Th67Wid+7EQZ+shCAL6+feDSqmSOxQismONm3pWJjqdDrNmzcLgwYPRq1cvAEBmZiacnJzg4eFRY1s/Pz9kZmYaPU5ZWRnKysoM9wsKCgAAWq0WWq3WbPHqj2XOY1qDEZ1HYMOkDZiUNAkarQYAagwP1/fJUSlVWB2zGoMCB2HurrlYfGgxdKIORzOPYsDSAfhg1Ad47s7nDPvllebhqxNf4ePDHyM9r6peVbBHMGbcOQOP93kcHi4eTY7XXs+DreF5sB48F9aB56H5GvvaCaIV/5k8ffp0/PTTT9izZw8CAwMBAKtWrcITTzxRI1kBgPDwcNxzzz149913ax1n7ty5eOutt2otX7VqFdRqtWWCt0NFFUXYkbsDG29uRGZ5VSLp7+SP+33uxz1e96CNQxvD8rPFZ/HfS//FxdKLECDgnbB30K1NNwDA0YKjeDfjXZTppPNoLFlyVjjj/7r8H253u70lnh5ZUEllCVQObK0houbRaDSYPHky8vPz4ebmVud2VpvczJw5Exs2bMCuXbsQFBRkWL5t2zbce++9yM3NrdF607lzZ8yaNQsJCQm1jmWs5aZjx47Iysqq98VpKq1Wi5SUFIwaNQpKpdJsx7U2oigipyQHheWFcHVyhZfKq86RL+WV5Zi/bz4Kywvxzoh3AAA/p/+Mcd+NgyiK0EFX5+MooIAgCNgwaQMigyMbHV9rOQ/WTn8ebh98O0KXhGJAwABM7TsVU/tOlTu0VoefCevA89B8BQUFaNeuXYPJjdVdlhJFEXFxcVi/fj127NhRI7EBgP79+0OpVGLr1q2IiYkBAJw5cwYXL17EwIEDjR7T2dkZzs7OtZYrlUqLvMEsdVxr4u/kD3/4N7idUqnE3HvmGu7nleZhUtKkBhMbQKpTpRAVmJQ0CZdnX27yJarWcB5swbZL26DVabH38l4M7jSY50RG/ExYB54H0zX2dbO65GbGjBlYtWoVNmzYAFdXV0M/Gnd3d6hUKri7u2PatGmYPXs2vLy84Obmhri4OAwcOBB33XWXzNFTQ1YcWwGNVtPokg7VC3HGR8RbODoyF30n8etl17H59GbDcpZcIKKWYHXJzZIlSwAAw4cPr7F82bJlmDp1KgDgo48+gkKhQExMDMrKyhAVFYVPPvmkhSOlpmpuIc648DhO/Gbl8krzsOLYCiw+uBhpuWk11rk4uOA2n9tkioyIWhOrS24a0wXIxcUFH3/8MT7++OMWiIjMRV+Is6mqF+L0VntbIDIyh+TUZMSsjjGMqLtVaWUpghYGIWliEqJCo1o4OiJqTax+nhuyHyzEab+SU5MRvSoaJdoSiH/9GFOiLUH0qmgkpya3cIRE1JowuaEWw0Kc9imvNA8xq2Ma3UlcFEXErI5BXmleywRIRK0OkxtqMaYW4hQgGApxNnTZsnpHVs523DL0ncQbSmz0qncSJyKyBCY31GKaU4gzPiIeReVF6P95f3x2+DOUV5bXWJ9XmoeF+xcibHEYAhYE4NlTzyJgQQDCFodh4f6FbCWwkOZ2EmfySUSWwOSGWlRTC3EqBAXUSjWm9J2C/x78L45mHsXfN/0doYtCseTQEpRVlCE5NRmBHwYiITkB6bnpNfZPz01HQnICAj8MZD8PC9B3Em/s0H696p3EiYjMjckNtaimFuIUIGDdpHXwcPHAqaxThnWXCi7huc3PIfCjQIz5ekydHVn1y9iR1TLYSZyIrBGTG2pxUaFR2DR5E1RKFYS/fqrTL1MpVdj86GZEhkilFxInJOLAUwdqTASXpcmCCHZklQs7iRORNWJyQ7KICo3C5dmXsWD0AgR7BtdYF+wZjAWjF+DK7CuGxEYvvEM4Nk7eiENPH0JPn55Nekx2ZDU/c3QSJyIyN6ubxI9aDw8XD8RHxCMuPK7RhTj1+rfvj9KKUggQmtzfg7Mdm4++k3hCcu2CtQ2Jj4jnOSAii2DLDclOEAR4q73RxaMLvNXejfrCa6mOrPqh5Rl5GRxaXofmdBInIrIEJjdkk5rbkbWh5Kb60HKf+T4IWhgEn/k+HFpuhIeLB9Y+tLZR89zc2kmciMgSmNyQTWpuR9ZBXw5CwpYEHL12tFZrDIeWN93Fgos17je2kzgRkSUwuSGbZGpHVr0sTRYWHFiAOz6/A30+7YP5v85Hpa6ywRpJHFpeW1pOGmYnzzbcf+aOZ5rUSZyIyNyY3JBNMnW2YwEC+vr1hZODk2HZyRsn8fXvX6OwvJA1kpqoUleJ2O9jUawtBiAlNp+N/Qzn4s7h2qxr+KzHZ7g26xrOxZ1DfEQ83F3cZY6YiFoDJjdks0ztyLpj6g5kPp+JT6M/xaCOgwAAU/pOYY0kE7y/9338eulXAFLrzAdRHwCo6iTu5+zX6E7iRETmwuSGbFZzZjv2VHni2Tufxa9P/oqzM88itm8sayQ10fHM43hj+xsApMQxcXxis/tCERGZA5MbsmmmznZcXZh3mGGIOGskNd7KEyuh1WkBAC8NegmDOw2WOSIiIgmTG7J5ps52XB1rJDXde6Pew5cPfIkhnYZg7vC5codDRGTAGYrJLlSf7fh6wXX8kPwDHoh6AH5ufo3q78EaSU0nCAKeuP0JTO03lX1qiMiqsOWG7IqpHVlZI8l0TGyIyNowuSGC6UPLgdZVI+mVX17BxrMb5Q6DiKheTG6I/sIaSfX78cyPeOfXdzD2m7FI2NL0QplERC2FyQ3RX5oztBwAyirKWiBKedwsvomnfnzKcL+nb08ZoyEiqh+TG6JqTB1anluSi36f9cMHez+wuzlvRFHE3zf9HTeKbwAA7u96P6bdPk3mqIiI6sbkhugWTR1aXqGrwCNJj+B01mm8kPICpm6YitKKUjlCt4iVJ1Zi3al1AKSO10vHLm01fYyIyDZxKDiREdWHlueU5KCwvBCuTq7wUnnV+mJXCApEdIhAcppURDPxeCLOZJ3BuknrEOAaUGNbURSRXZKNovIitHVqC2+VdZcmuJh/ETN/mmm4/9n9n8G/rb+MERERNYwtN0T10A8t7+LRpc6h5QpBgbfueQtrHloDtVINADhw5QAGLB2AQ1cOAQDySvOwcP9ChC0Og898HwQtDILPfB+ELQ7Dwv0LraL4piiKyNJkISMvA1maLFTqKvHEhidQUFYAAHi8z+OIuS1G5iiJiBrGlhsiM/nbbX9DqFcoxn07DhfzL+Jq4VUMWTYE8RHx+OTQJ9BoNbX2Sc9NR0JyAl7b9hqSJiYhKjSq0Y9nrlagvNI8rDi2AosPLkZabpphubfKG9kl2QCAQLdALBqzqMnHJiKSA5MbIjPq598Ph54+hL+t/ht2X9yNssoyzN87v87t9bWsSrQliF4VjU2TNzWY4NSVjIR4hiAuPA6x/WINI7gakpyajJjVMUYTL31iAwAzBsxo9DGJiOTGy1JEZubbxhe/TPkFU/o0fv4bHXQQRRExq2PqvUSVnJqMwA8DkZCcgPTc9Brr9K1AgR8GIjk1ucHHTE5NRvSqaJRoSyD+9VOX17e93qhjEhFZAyY3RBbg5OCE29vf3qR9dNBBo9Ug8Xii0fUNJSP6ZfpWoPqSkbzSPMSsjoEoitBB12BsjUm8iIisBZMbIgsQRRH/PfjfJteqAoBFBxbVmiunKclIY1qBVhxbAY1W06jERn/M+hIvIiJrwuSGyAKyS7KRlptW76UeY0SISMtNw2PrHsOb29/E1vStAMyTjJRVlOFa4TWcvnka7+99v8mxAcYTLyIia8MOxUQWUFRe1Kz9V51cBQDQDNRgRNAILD642KTjLDqwCHHhcRAEAYsPLsaLKS+aHJM+8copyYG32tvk4xARWRpbbogsoK1TW7Mcp4Nrh2a3AuWU5AAA3JzdzBJTYXmhWY5DRGQpbLkhsgBvlTdCPEOQnpvepKREgIDOHp2xfuJ6XC26im7e3ZrdClRYXghvtTfCvMIwrts4ODk4Yc2fa0w+nquTa7PiISKyNLbcEFmAIAiIC48zad+EuxLQr30/3Bd2H0K8QprdCqRPRu4JugffP/w9vvvbdwjxDGlyZ2cBAkI8Q+Cl8mpWPERElsbkhshCYvvFQq1UQ9HIj5lCUECtVGNK35rz4+hbgcyVjDQn8YqPiLfqWlhERACTGyKL8XDxQNLEJAiC0GCCo4ACAgSsm7Su1kzAlkhGzJV4ERFZIyY3RBYUFRqFTZM3QaVUQfjrpzr9MpVShc2PbkZkSKTR45g7GTFX4kVEZI2Y3BBZWFRoFC7PvowFoxcg2DO4xrpgz2AsGL0AV2ZfqTOxASyTjJgr8SIisjYcLUXUAjxcPBAfEY+48DjklOSgsLwQrk6u8FJ5NboPiz4ZqV7osvpILH1yolKqsG7SukYlI/rEK/F4IhYdWFSjEGewZzDiI+IR2zcW7i7uTXm6RESyYnJD1IIEQYC32tvkSfAskYyYI/EiIrImTG6IbIylkpHmJl5ERNaCyQ2RjWIyQkRkHDsUExERkV1hckNERER2hckNERER2RUmN0RERGRXmNwQERGRXWFyQ0RERHalVQ4FF0VpVteCggKzHler1UKj0aCgoABKpdKsx6bG43mwDjwP1oPnwjrwPDSf/ntb/z1el1aZ3BQWFgIAOnbsKHMkRERE1FSFhYVwd697JnZBbCj9sUM6nQ5Xr16Fq6urWaeXLygoQMeOHXHp0iW4ubmZ7bjUNDwP1oHnwXrwXFgHnofmE0URhYWFCAgIgEJRd8+aVtlyo1AoEBgYaLHju7m58Y1rBXgerAPPg/XgubAOPA/NU1+LjR47FBMREZFdYXJDREREdoXJjRk5Oztjzpw5cHZ2ljuUVo3nwTrwPFgPngvrwPPQclplh2IiIiKyX2y5ISIiIrvC5IaIiIjsCpMbIiIisitMboiIiMiuMLkxo48//hhdunSBi4sLIiIicPDgQblDalXmzp0LQRBq/OvevbvcYdm9Xbt2YezYsQgICIAgCPj+++9rrBdFEW+++Sbat28PlUqFkSNH4ty5c/IEa8caOg9Tp06t9fkYPXq0PMHasXnz5mHAgAFwdXWFr68vxo8fjzNnztTYprS0FDNmzIC3tzfatm2LmJgYXL9+XaaI7ROTGzP57rvvMHv2bMyZMwe//fYb+vbti6ioKNy4cUPu0FqVnj174tq1a4Z/e/bskTsku1dcXIy+ffvi448/Nrr+vffew6JFi/Dpp5/iwIEDaNOmDaKiolBaWtrCkdq3hs4DAIwePbrG5+Obb75pwQhbh507d2LGjBnYv38/UlJSoNVqERkZieLiYsM2CQkJ+PHHH7FmzRrs3LkTV69exYMPPihj1HZIJLMIDw8XZ8yYYbhfWVkpBgQEiPPmzZMxqtZlzpw5Yt++feUOo1UDIK5fv95wX6fTif7+/uL8+fMNy/Ly8kRnZ2fxm2++kSHC1uHW8yCKohgbGyuOGzdOlnhasxs3bogAxJ07d4qiKL3/lUqluGbNGsM2p06dEgGI+/btkytMu8OWGzMoLy/HkSNHMHLkSMMyhUKBkSNHYt++fTJG1vqcO3cOAQEBCA4OxqOPPoqLFy/KHVKrdv78eWRmZtb4bLi7uyMiIoKfDRns2LEDvr6+6NatG6ZPn47s7Gy5Q7J7+fn5AAAvLy8AwJEjR6DVamt8Jrp3745OnTrxM2FGTG7MICsrC5WVlfDz86ux3M/PD5mZmTJF1fpERERg+fLl2LJlC5YsWYLz589jyJAhKCwslDu0Vkv//udnQ36jR49GYmIitm7dinfffRc7d+7EmDFjUFlZKXdodkun02HWrFkYPHgwevXqBUD6TDg5OcHDw6PGtvxMmFerrApO9mnMmDGG23369EFERAQ6d+6M1atXY9q0aTJGRiS/hx9+2HC7d+/e6NOnD0JCQrBjxw7ce++9MkZmv2bMmIGTJ0+y758M2HJjBu3atYODg0Ot3u7Xr1+Hv7+/TFGRh4cHunbtitTUVLlDabX0739+NqxPcHAw2rVrx8+HhcycORMbN27E9u3bERgYaFju7++P8vJy5OXl1dienwnzYnJjBk5OTujfvz+2bt1qWKbT6bB161YMHDhQxshat6KiIqSlpaF9+/Zyh9JqBQUFwd/fv8Zno6CgAAcOHOBnQ2aXL19GdnY2Px9mJooiZs6cifXr12Pbtm0ICgqqsb5///5QKpU1PhNnzpzBxYsX+ZkwI16WMpPZs2cjNjYWd955J8LDw7FgwQIUFxfjiSeekDu0VuOFF17A2LFj0blzZ1y9ehVz5syBg4MDHnnkEblDs2tFRUU1/vo/f/48jh07Bi8vL3Tq1AmzZs3Cv//9b4SFhSEoKAhvvPEGAgICMH78ePmCtkP1nQcvLy+89dZbiImJgb+/P9LS0vDSSy8hNDQUUVFRMkZtf2bMmIFVq1Zhw4YNcHV1NfSjcXd3h0qlgru7O6ZNm4bZs2fDy8sLbm5uiIuLw8CBA3HXXXfJHL0dkXu4lj1ZvHix2KlTJ9HJyUkMDw8X9+/fL3dIrcqkSZPE9u3bi05OTmKHDh3ESZMmiampqXKHZfe2b98uAqj1LzY2VhRFaTj4G2+8Ifr5+YnOzs7ivffeK545c0beoO1QfedBo9GIkZGRoo+Pj6hUKsXOnTuLTz/9tJiZmSl32HbH2DkAIC5btsywTUlJifjcc8+Jnp6eolqtFidMmCBeu3ZNvqDtkCCKotjyKRURERGRZbDPDREREdkVJjdERERkV5jcEBERkV1hckNERER2hckNERER2RUmN0RERGRXmNwQERGRXWFyQ0Qt5uTy5XhfEPDT1Kn1bvfT1Kl4XxBwcvnyFomLiOwLkxsiIiKyK0xuiIiIyK4wuSEiIiK7wuSGiGyCtqQE+/71Lyzr2RMfubhgsYcHVo8cibRNm2pt+74gYN399+P455/jE39/LFCrsbFadfiz69Zh7ejR+NjXFx8qlVjs6YnvRoxA2o8/1jrWxR07sHbMGCwJCMBHLi5YGhyMX2bMQNG1axZ9vkRkOke5AyAiakhZfj6+Gz4cN44dg3fPnujzzDMoy81F6g8/YP3992PwP/+JgW+8UWOfzEOHcHHrVtz2+OMAAN/bbwcA/DpnDvb985/wCAlB90mT4KhWI/uPP5C+eTMubd+OCRs3IiQ6GoCU2KwZORKqdu0Q9uCDcHZzw/UjR3Dsk0+QkZyM2N9/h1KlatkXg4gaxOSGiFrcjWPH8OvcufWur27Xyy/jxrFj6P3UUxi1ZAkUjtKvrrz0dHw3bBh+ffNNdBoxAh0GDzbso7lxA6M+/RR9n33WsKz4+nUcePttePXogccPH4ZSrTasO/bpp/hl+nT8sWKFIbk59vHHECsrMfnXX+EREmLYNvmpp/D7//6H1PXr0WPy5Oa8FERkAUxuiKjF3Tx+HDePH2/UtpXl5fjzq6/g7OGBEYsWGRIbAPAIDsbgf/8bW6ZOxfHPP6+R3ABAt4kTa9xXKJW476uv4NqpU43EBgA63XMPACkp0hN1OgDA5d27ayQ3w95/H4P/9S+08fdv1HMgopbF5IaIWlzP2FiMqWcOm5+mTsUfK1YAAHLOnoW2uBhdoqKMXgIKHDoUAHDj6NEay108PeHi6VljmcrLC90ffhgAkHvuHLJPnUL++fPIOXUKl3fvBgCIlZWG7fv+/e9I/f57bHniCeydOxddIiPRedQodImMRNv27Zv+xImoRTC5ISKrVp6fDwBwdnc3ut61QwcAgLa4uMZyx1taZvTSNm3Cnldfxc0TJwAAgoMDvG+7DX79+yP7zz8BUTRs22XUKDy8ezcOf/ABMpKTcWLpUpxYuhQOTk7o8dhjGLFoEZzatGn2cyQi82JyQ0RWzcnNDQBQdOWK0fWlubkAAJW3d4PHyjx8GN+PGwcXDw9Efv45AgYNgmdYGBycnJB9+jT+/OqrWvt0GDQIHQYNQmV5Oa4dOICMn3/GHytW4OSXX0JQKBC1dGkznh0RWQKTGyKyal7du8NRrcbNEydQmptb61LTpe3bAQDtevdu8Finvv4aYmUlRixejB7VhoYDQPYffwAAxL9abkSdDgfnz4e2sBB3//vfcHByQuCQIQgcMgR9nn4an3fujMs7d5rjKRKRmXGeGyKyag5KJW577DGUFxZi26xZ0FVUGNblZ2Rg92uvAZD68TTE8a8+OwUXLtRYXnDpEna/8goAQKfVAgAEhQJpGzZg/9tv4/KePTW2z0tPBwC4Bweb+KyIyJLYckNEVm/Ye+/h6r59+DMxEdePHEGnESNQlpeHtB9+QFl+PgbOmYOOf3Usrk/3Rx7B4Q8/xJ7XX8f1336DR0gICi5cQNqPP0Lh6AgHJyeUZGcbth/67rtYM3Ik1tx7L0InTIB7UBCKLl/G2aQkOKpUGPzPf1ryaRORidhyQ0RWz9ndHZP37sXAN9+EWFmJE59/jvObNyNg0CDEbNmCwfXMmVOdT+/eeOiXXxA4dCgubt2Ko//9L24cO4bbHnsMU3//HR2GDEF+ejqyT50CAAQOGYKH9+xBcHQ0ru7bhyMffoiMlBSEjhuHxw4dQvvwcAs+ayIylSCK1YYGEBEREdk4ttwQERGRXWFyQ0RERHaFyQ0RERHZFSY3REREZFeY3BAREZFdYXJDREREdoXJDREREdkVJjdERERkV5jcEBERkV1hckNERER2hckNERER2RUmN0RERGRXmNwQERGRXfl/DZxRpDhmyRQAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.grid () #guias no gráfico\n", + "font1 = {'family':'serif','color':'blue','size':20}\n", + "font2 = {'family':'arial','color':'darkred','size':15}\n", + "plt.xlabel('Horas', fontdict = font2) #legenda\n", + "plt.ylabel('Temperatura', fontdict = font2) #legenda\n", + "plt.title('Temperatura por hora', fontdict = font1)\n", + "plt.plot(hora, temperatura_hora, marker = 'o', mec= 'green', color = 'green', ms = '10', linestyle = '--', linewidth= 2, ) #primeiro x e depois y, marcador para cada ponto do dado, cor de cada ponto, mudar a cor da linha, tamanho do ponto, formatar a linha, largura da linha,\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#gráfico de barra\n", + "# no de barras geralmente usamos para comparações de dados,\n", + "# distribuições de dados categóricos e tbm para mudanças ao longo do tempo...\n", + "\n", + "import matplotlib.pyplot as plt\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Precptação por hora')" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.bar(hora, preciptacao)\n", + "plt.grid () #guias no gráfico\n", + "font1 = {'family':'serif','color':'blue','size':20}\n", + "font2 = {'family':'arial','color':'darkred','size':15}\n", + "plt.xlabel('Horas', fontdict = font2) #legenda\n", + "plt.ylabel('Precptação', fontdict = font2) #legenda\n", + "plt.title('Precptação por hora', fontdict = font1)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 111, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#gráfico de disperção\n", + "plt.grid()\n", + "plt.xlabel('Velocidade do vento por segundo')\n", + "plt.ylabel('Temperatura (°C)')\n", + "plt.title('Vento pela temperatura')\n", + "plt.scatter(vento_ms, temperatura_hora)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 134, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#plt.fill_between()\n", + "ax1 = plt.subplot(2, 1, 1)\n", + "plt.fill_between(hora, temperatura_hora)\n", + "plt.grid () #guias no gráfico\n", + "font1 = {'family':'serif','color':'red','size':30}\n", + "font2 = {'family':'arial','color':'darkred','size':10}\n", + "plt.xlabel('Horas', fontdict = font2) #legenda\n", + "plt.ylabel('Temperatura', fontdict = font2) #legenda\n", + "plt.title('Temperatura por hora', fontdict = font1)\n", + "plt.plot(hora, temperatura_hora) #primeiro x e depois y\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "vento_km = vento_ms * 3.6\n", + "sensacao_termica_hora = 33 + (10 * np.sqrt(vento_km )+10.45 - vento_km) *(temperatura_hora-33)/22" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([464.68942085, 455.18599882, 438.31485336, 424.4574935 ,\n", + " 414.3597089 , 408.48442378, 404.60727978, 391.6443185 ,\n", + " 391.7108789 , 388.04146846, 414.63513475, 474.6234546 ,\n", + " 539.2487678 , 581.43123753, 614.22403658, 642.62053509,\n", + " 651.71965539, 655.98268181, 652.82273912, 635.06753535,\n", + " 603.44776709, 542.88329079, 498.45283797, 479.11741263])" + ] + }, + "execution_count": 137, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sensacao_termica_hora" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 146, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(hora, sensacao_termica_hora, label = 'Sensação')\n", + "plt.plot(hora, temperatura_hora, label = 'Temperatura')\n", + "plt.legend()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "X = temperatura_hora\n", + "Y = vento_ms\n", + "n = np.size(temperatura_hora)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "a = (n * np.sum(X*Y)-np.sum(X)*np.sum(Y))/(n*np.sum(X**2)-np.sum(X)**2)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "b = np.mean(Y) - a * np.mean(X)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "y = a*X + b" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 161, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#gráfico de disperção\n", + "plt.grid()\n", + "plt.ylabel('Velocidade do vento por segundo')\n", + "plt.xlabel('Temperatura (°C)')\n", + "plt.title('Vento pela temperatura')\n", + "plt.scatter(temperatura_hora, vento_ms)\n", + "plt.plot(temperatura_hora, y, color='r')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "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": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/Soraia/temperatura_PE.csv b/Soraia/temperatura_PE.csv new file mode 100644 index 0000000..e8d543b --- /dev/null +++ b/Soraia/temperatura_PE.csv @@ -0,0 +1,25 @@ +Hora,Temperatura +00,24.011870247148288 +01,23.51813311108465 +02,23.057124105011933 +03,22.63965290245362 +04,22.25095564370718 +05,21.9176924933623 +06,21.626344476744187 +07,21.3683531987351 +08,21.15036674816626 +09,21.400477354756084 +10,22.6949143525907 +11,24.272506253126565 +12,25.7527190622598 +13,27.07737767220903 +14,28.145632271600228 +15,29.008849138746925 +16,29.561143291235403 +17,29.731862320930677 +18,29.50587300009937 +19,28.804562101077746 +20,27.614909879078255 +21,26.262876760153613 +22,25.295987763266268 +23,24.58622448979592