Saude_SP.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "## ANÁLISE DOS ESTABELECIMENTOS DE SAÚDE DO MUNICÍPIO DE SÃO PAULO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import folium\n",
    "import plotly.offline as py\n",
    "import plotly.graph_objs as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Leitura do arquivo de dados\n",
    "dataset = pd.read_csv('https://tilcomunicacao.com.br/wp-content/uploads/2020/07/deinfosacadsau2014.csv', sep=',', encoding='latin-1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1467"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Número de estabelecimentos de saúde no município de São Paulo\n",
    "dataset.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a6904ca280>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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LYryc8XNB2MeLQwiU3vREfGHl5SXujiJUG+bUbt03KJE4xlmGLlKl4W09emVV/IIeT8WnlsUo6epdplYQLkVD4WOA013nyEfh95g6Ypuue3eIjHHx/rfu2vPayU3NU1y8d1eoEtvC4SseiZ3X8mj87JMb6JWJu0vLM7CPvODLcxDRUPhyvFW6TRt29mfpV75akvPFf8/a37DwgW078uIcSHtU0Tr6Vj8W/2jdQ7Hp43dRmo1Lk6M23D3d9+fIfHkEAfhhYlNnBtUzeUo0sfzlcNHEjl+dGUfFYkt+tG1HXl+xaNTD3vhjfErtA/GLPvSeDsn21PXlwMNZfo+s82tB5Owb36/+7U+JAa+Mk3iiSIqz/V6HJfTtJzfWhvNxGHWLFr+3IFG27r7Yxces1tHHAx1dhciUj5FGQYjIUcB9wGSgCdgAXK+qb6TzpiLyJeBFVd2cznap+K4goqGw4E0YatrRM8bYzy1MLPrtR4uz+lNdVPfM3Vxb0k+1fzbfJx0Jle3L9Pjoj2IXH7E4ETkRGO4gRqfPQ4iIAE8Cc1T1c8nnyoChQFoFAXwJeB34QEGISLGqxtPZme/OQURD4XFAjescfpAQts+8vrhnYy/JznqSqvEfbN+58rz9Dc6P6FSpX6vDV/049qlezyZOPzlOcT788Dt2w93TO5xkWETKgUpV/UCZi8gteIOvegJPquqdIjIKeB5YDJwBbAI+DUwHHkn+vhGYAkTxViY/B3gQ7yjv9uSvz6pqu1Pm+fFeDOffjH5RpAy+/unEq9na/2fr9y12WQ6qNG/UI5dUtlzxcrjp4ZLzmr8/9ZnE1Il5Ug4AZZ183YnA8kOfFJFzgLHAqcl9TRSRgyUyFpitqifg3Wp+iarOA5YBl6lqmao2Jl97QFU/DCwCvo93dFMGTBaRC9sLli9/kemwE5RpKFunU47ape9tOUIyeph9fFPz4m/t3J3zKxaqJHbRf9Vv4h/b9/PYJyN76XdqrjOk4WTg2W5sf07ysSL5+354xfAusF5VD67ZuhwY1c5+Do7JmAwsUNXtACLyG+BM4KlUG/qxIOwIIg0CPW9/LL7xuq+UZKwg+iUSr/9u85acXkbdp72iT8Wnbpsdu3BcLYM6+5PZtc5eKVlN2zceCvA9VX3ofU96HzGaWj0VB9pbkWx/q/2lxVcfMZInKO0IIk1H7WFK2duJVZnYV5Hqlqc21g4+zPtMnFXNWrLh2fhpC89p+v76E5t+Gf5W7KpptQw6Ktvvm0HhTr5uPtBTRK4++ISITAb2AleKSL/kc8eIdDh7WD2Q6oTxK8A0ETlSRIrx1vRY2N7O/HYE8SEgOyfcAu6GpxIlM24UxTtj3jWqB36+ZduuofH4+AxGe5+4ytZXEuGa+2MXD35Fx4+n/UPnfDd21G3PFm24e3q7K7OrqorIRcB9InIbcIDkZU688wsvJ/+37QMuxztiSOURoEpEDp6kbP0+tSLyDeAveEcTz6nq0+1l89VVjGgofAkwz3UOv/rttKK/PXVG0dSubn/drj1/u7pub5e3T0WVutU6qvrB2IV9X0hMOlkp8tWRbQfGbLh7+nrXIboqK0cQIvJN4At4TZcArlHVV1K89kvAJFXtzKzAvrsBKJ98dlFizHOTpaG5h/RJd9spjY0Lr67bm7GTkqoceEeHrvxpfLrMi08ra6bHhzO17zwzGgh+QYjIh4GxqvqwiAwG+qnqB75wEZkCnA+coqpNInIkcFiG8vrp82feKVaG/dufEgvuu6j4rHS2OzIWX/aTLdu7/Q9Ylfh2Slf+KnbOgUfi50b20acQbrgb7DpAd3SqIETkTry5H8fhDR/tAfwaaOtwcxiwQ1WbAFR1R3IfG/COFHaIyCTgHlU9K828Q9N8vTnElBo99dE6rd1ZKp1a5LiH6vqnNm0eW+zNc9Al9dp79bz4mTt/EvtUeNs/p2YrFL5YkiCVzh5BXIQ3vPlVAFXdLCKpzpS+CNwhIm8A/ws8pqrtnilNgx1BdJNAn9vmxl+95cslHReE6t7fbdqipQktTfd9Dpma7YQuhQ2GgiiI5uSZVgUQkZTTl6vqPhGZCHwE+CjwWPLMbCbYEUQGjNjO1PC7uiY6QlJfjVBNfHfHrrXjWlo6Pd6hjanZCmIx5Q4E/yMG8AcReQgYmLxWeyXtTMyZvCFkAbBARKqBGUCMf4676NXFvEFZ7NUpAbnl8XjsyhtS/+//1L79iz69b/9ZHe2rG1OzFYrgH0Go6j0icjbewI1xwB2q+ue2Xisi44CEqr6ZfKoMb3LZ3nijIJ+n6/NJ2hiIDOl3gJPOXZZ4+YVJRR+Y/Wl0c8vf/2PHrrNSbZvBqdkKQfALAiBZCG2WwiH6AQ+IyEC8o4a3gH/FG1X2CxG5HW9EV1fkzS3FQTDjpcQxL5VJU6xE/jEqsk8iEf3D5i0fuJ0+S1OzFQKnEwh3V6cGSonIxXh3gQ3BG4EleAPAcvYTPRoKH8b7x5+bDHjpZFnw0Ce9y56iuv1/Nm6OHR2LD4OcTc0WdG9tuHv6WNchuqqzRxD/BVygqtFshumAHT1kQflresrvp+mOuj4M+PHW7bVHx+In5XhqtqDz2+0M79PZ8FsdlwN04zq8SU1gwC3z4otWfFobG/ed0Gt67OK3cjw1W9D5+vu2swWxTEQew7tv/B+H+ar6RFZSta0+h+9VUIp6fVqPjJ49eS3wCe+xy3WmoFDvxL5vdbYgBgANeJNXHKRAzgoiXBNtjIbCcXzeyPlm98Cxq98dfvYUQTI1HN60Ij7/wdbZy5wzsx2kk/YBaY/qM21r7tFv54qTrz0csXLIorQmic03nbqtVkSOFZEnRWSbiGwVkcdF5Nhsh2uDr9s4nyiSWDL5mxuQYhvYlF0HXAfojs7ed/8w8AxwNN4t13/EzaIgVhAZUn3i1YuaDxtQaDdOueDr8zmdLYjBqvqwqsaSj0dwM8bcCiIDNh91+pIdg07K+yXyAqIgCmKHiFwuIsXJx+XAzmwGS8EKopv29x76Ts24y8d1a+o5k46CKIgr8Rbv2ALU4s3Ae2W2QrXDCqIb4kU9GpdOuvUAInaiN3d8XRCdvYrxLvCpLGfpDCuIblh+ys3LE8U9gzq1W74KbkGIyB3t/LGq6ncynKcjvh504tJbYz69aF+/Y/N69e2A2uI6QHd0dASxv43n+gJXAYOAXBfEuhy/XyDsLh275t3hZ5/mOkeBest1gO5otyBU9d6D/52cYu5rwEzg98C9qbbLomoH7+lrzT367lp58rWliGR9oRvTJl8XRIcnKUXkCBH5LrAKr1BOUdVbVXVb1tN9kBVEGhRJLJn0zfVaVGzLBbjRAGx2HaI72i0IEfkBsBTv5GBEVStVdXdOkrUhXBPdAuxw9f5+8/oJX17U3LPUBkO5s66iqtw/K1O1oaMjiJvwRk9+C9gsInuTj3oRcXXC8HVH7+srtUNPW7r9yJNtMJRbb7sO0F0dnYPIxyXQqoGzXIfIZw29B78XDX1xrA2Gcm616wDdlY8F0BE7D9GOeFHJgSWTvrEfb05Q49YS1wG6ywoiYJZPuHlZorhnyHUOA3R9cua84ceCWI03WY05xNujL/jrvv7DbaRkfnivoqrc14OkwIcFEa6J1uOts2Fa2V36oTXvjDj3VNc5zD/4/uMF+LAgkgLxl58p3mCo6wbYYKi84vuPF+DfgviT6wD5IjkYap0WFbuY4cuktsh1gEzwa0E8i8/n+suU10+4alFzz9JJrnOY99mBN8DQ93xZEOGa6C7gb65zuFY79NSl248ss8FQ+efFiqryhOsQmeDLgkj6o+sALnmDoa6wwVD56XnXATLFzwXxtOsArthgqLyWAP7HdYhM8W1BhGuibwJrXedwYfmEm5faYKi8tayiqjwwNxT6tiCSnnEdINfWjTr/r/v6D/+I6xwmpbmuA2SSFYSP7Ck9Lrph5Hk2GCp/JYDfug6RSX4viL9TIPNDtJT03b3i5K/1t8FQee2liqpyX08QcyhfF0S4JpqgAE5WKpJ4ZfLtb9tgqLz3qOsAmebrgkj6iesA2fb6+CsXNfccaIOh8tt+crjafa74viDCNdHlBGTce1u2DJ28bPvgCTYYKv89UVFV3tYs8L7m+4JIetB1gGxo6H3kxjWhGcfZYChfuN91gGwISkHMBVzMsp018aKSA0sn3V6PyOGus5gO/bWiqny56xDZEIiCCNdEm4CHXOfIpFcn3LQ0Xtwz7DqH6ZQfug6QLYEoiKQHgEbXITJh3ajpf63vP8IGQ/nD2wT4SlpgCiJcE90O/MJ1ju7aM2BMdMPIT0x2ncN02v1BuXOzLYEpiKR7gJjrEF3VUtJ394qy6/sj0st1FtMpW4Ffug6RTYEqiHBN9B28dUN9xwZD+dJ3g3hps7VAFUTSd4EW1yHStXr8zL/aYChfWU/AToy3JXAFEa6JrgXuc50jHVuHTFy2bfApdlLSX+6oqCr33Q+idAWuIJK+DWx0HaIzGnsduXF1eOZxiAT1/0UQVROwuzZTCeQ3Zbgmuh+40XWOjiSkpGnJpG/stcFQvnNbkK9ctBbIggAI10TnAn92naM9yyfcuCRe0mu86xwmLc9UVJU/5zpErgS2IJKuBZpdh2jL+pGfXFw/YKSdd/CXBuBrrkPkUqALInnC8r9d5zjUngGja9aP+qRdsfCfuyqqyje4DpFLgS6IpO8A77kOcVBLSZ89K8pu6GuDoXxnJXCv6xC5FviCCNdEG4AbXOcAUNAlk25/U4uKh7vOYtISA75cUVXu21G6XRX4ggAI10QfJw8muF0dnrmwqdfhdp+F/9wZ1Nu5O1IQBZE0A+/OOye2Dpm4bNuQiWe6en/TZfOBu12HcKVgCiJcE90DXIKDW8KTg6HG2GAo39kBfLFQxjy0paC+YcM10deAa3L5nq0GQx2Ry/c1GXFl0KaxT1dBFQRAuCb6KDA7V++3fMINNhjKn35UUVVe0AtEQwEWRNINwMvZfpP1Iz+xuH7AKBsM5T//C9zkOkQ+KMiCCNdEW4BL8Sb8yIq6AaPXrh81fWK29m+yZi1waSFe0mxLQRYEQLgmugn4LFmYgaqlpHfdq2XX90akd6b3bbJqF3B+RVX5HtdB8kXBFgRAuCa6EPh6JvfpDYb65htaVDIik/s1WdcCXFJRVf6W6yD5pKALAiBcE/0h8B+Z2t+a8JdsMJT/KHBVRVX5AtdB8k3BFwRAuCb6Lbyp6rpl6+CJy7cOmWSDofxnVkVVeeAW3s0EK4ikcE303/Fu7OqSxl6DNq0eP3O0DYbynesrqsp/6jpEvrJv5lbCNdE7gLvS3c4bDHV7nQ2G8p1vVFSVB3JNzUyxgjhEuCZ6J96clp326oTrX7HBUL5zZ0VVecHeY9FZVhBtCNdEK+lkSawfed7ivQNG23kH/0gA11ZUlad9pFiIrCBS6ExJ1PUftXb9qPNtMJR/NAGfq6gqf9B1EL+wgmhHsiS+jvdT531aSnrXvTrhBhsM5R97gfMqqsrnug7iJ1YQHQjXRH8AXADUHXwuORhqrQ2G8o1NwDQb55A+K4hOCNdEnwNOwxunz5rQjEVNvQ4/1W0q00kLgFMqqspXug7iR1YQnZScIfu0rYNP+enWoZPtDk1/uAf4eEVV+TbXQfxKVNV1Bl+ZPWu+AN/AGy9R7DiOads+YGZFVfk810H8zgqii2bPmj8N+DVwrOss5n1WAJdVVJVHXQcJAvuI0UUVVeULgROBh11nMYB32/5dwGlWDpljRxAZMHvW/E8CPwOOdp2lQK0GZhTq1PTZZEcQGZBczPUE4FeusxSYGPB9YKKVQ3bYEUSGzZ41/6PAfcBJrrME3J/x7sRc4zpIkFlBZMHsWfOLgC/jzTEx2HGcoHkLuKmiqtz5SmmFwAoii2bPml8K/DtwHdDDcRy/2wv8J/DDiqryZtdhCoUVRA7MnjV/JHArcCXQ03Ecv6kHHgDuragq3+U6TKGxgsih2bPmHw3cjLe6Vx/HcfLdbuBB4P6KqvKdrsMUKisIB2bPmj8Yb/Geq4EjHcfJN+uAnwAPVVSV17sOU+isIByaPWt+T+Bi4F+Bs9ymcSoG/AmoAl6sqCq3b8o8YQWRJ2bPmj8OryiuoHCOKt8h/JoAAAK8SURBVN7BG4n684qq8k2uw5gPsoLIM7NnzS8BpgGXABcCw9wmyri3gMeBeRVV5cu6sgMR2aeq/boaQETKgKNV9bmu7qNQWEHkseR4iil4H0OmA+PcJuqSBLASeA6vFF7r7g4zUBBfAiap6le7myXorCB8ZPas+UfhHV1MwztnEXYaqG0HC2FB8rGooqq8rr0N0tVWQYjIccBsvIFpDcDVqlojIpcCdwJxvFnBPo53FNMbb6ap7+Gd/3gAiAAlQKWqPp3JzH5lBeFjs2fNHwJMxrurNJJ8hIDDchShAe9GqVVAdfLXVzNdCIdKURAvAbNU9U0ROQ34nqqWi0g1cJ6qbhKRgaq659AjCBH5T2CNqv5aRAYCS4AJqro/m1+HH1hBBEzyHMbxwFhgODAC7y7TocBRwEC8n569ko9DJ72JAY14//gbgT14P2k3Jn89+FgHvF1RVf6BCX2z7dCCEJF+wHaSUwIm9VTVsIhUAccBfwCeUNWdbRTEMry/i4MrvR8BnKuqBX/buBVEgZs9a34PvH8cAjRWVJW3OI7UoTYKYgCwVlXbPKGbPKKYDswEyvAmIW5dEMuBL6jq2ra2L2RWEMZ3UnzE+DvwQ1WdKyICnKSqr4nIcar6dvI1K/BK4jjgU6o6I/n8fwIDgGtVVUVkgqquyOkXlaesIIzviEgC2Nzqqf8GnsQbgTkM78a436vqXSLyBN7HLQFeAq4HDgdeSL7ue8AzeLfon5F83QZVPT83X01+s4IwxqRkM0oZY1KygjDGpGQFYYxJyQrCGJOSFYQxJiUrCGNMSlYQxpiUrCCMMSlZQRhjUrKCMMakZAVhjEnJCsIYk5IVhDEmJSsIY0xKVhDGmJSsIIwxKVlBGGNSsoIwxqRkBWGMSckKwhiTkhWEMSYlKwhjTEpWEMaYlKwgjDEpWUEYY1L6fyJFPZkNJ3NZAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Divisão dos estabelecimentos de saúde por região\n",
    "dataset.groupby('REGIAO5').size().sort_values().plot(kind='pie')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.describe of REGIAO5\n",
       "Centro     79\n",
       "Oeste     128\n",
       "Norte     280\n",
       "Sul       459\n",
       "Leste     521\n",
       "dtype: int64>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.groupby('REGIAO5').size().sort_values().describe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1a69257fca0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Temos vários estabelecimentos que não possuem leitos, a seguir apresentamos a divisão desses por região\n",
    "dataset.query('LEITOS == 0').groupby('REGIAO5').size().plot(kind='bar')"
   ]
  }
 ],
 "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": "3.8.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}