{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Epidemiologická situace obcí\n",
    "\n",
    "https://onemocneni-aktualne.mzcr.cz/api/v2/covid-19/obce.csv\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pathlib import Path\n",
    "import seaborn as sns\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>den</th>\n",
       "      <th>datum</th>\n",
       "      <th>kraj_nuts_kod</th>\n",
       "      <th>kraj_nazev</th>\n",
       "      <th>okres_lau_kod</th>\n",
       "      <th>okres_nazev</th>\n",
       "      <th>orp_kod</th>\n",
       "      <th>orp_nazev</th>\n",
       "      <th>obec_kod</th>\n",
       "      <th>obec_nazev</th>\n",
       "      <th>nove_pripady</th>\n",
       "      <th>aktivni_pripady</th>\n",
       "      <th>nove_pripady_65</th>\n",
       "      <th>nove_pripady_7_dni</th>\n",
       "      <th>nove_pripady_14_dni</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>neděle</td>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>CZ010</td>\n",
       "      <td>Hlavní město Praha</td>\n",
       "      <td>CZ0100</td>\n",
       "      <td>Praha</td>\n",
       "      <td>0</td>\n",
       "      <td>Praha</td>\n",
       "      <td>554782</td>\n",
       "      <td>Praha</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>neděle</td>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>CZ020</td>\n",
       "      <td>Středočeský kraj</td>\n",
       "      <td>CZ020B</td>\n",
       "      <td>Příbram</td>\n",
       "      <td>2020</td>\n",
       "      <td>Příbram</td>\n",
       "      <td>564214</td>\n",
       "      <td>Počaply</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>neděle</td>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>CZ020</td>\n",
       "      <td>Středočeský kraj</td>\n",
       "      <td>CZ020B</td>\n",
       "      <td>Příbram</td>\n",
       "      <td>2020</td>\n",
       "      <td>Příbram</td>\n",
       "      <td>564249</td>\n",
       "      <td>Chrást (Příbram)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>neděle</td>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>CZ020</td>\n",
       "      <td>Středočeský kraj</td>\n",
       "      <td>CZ0204</td>\n",
       "      <td>Kolín</td>\n",
       "      <td>2006</td>\n",
       "      <td>Český Brod</td>\n",
       "      <td>564800</td>\n",
       "      <td>Hradešín</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>neděle</td>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>CZ020</td>\n",
       "      <td>Středočeský kraj</td>\n",
       "      <td>CZ0204</td>\n",
       "      <td>Kolín</td>\n",
       "      <td>2006</td>\n",
       "      <td>Český Brod</td>\n",
       "      <td>564826</td>\n",
       "      <td>Vrátkov</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2428875</td>\n",
       "      <td>úterý</td>\n",
       "      <td>2021-03-23</td>\n",
       "      <td>CZ080</td>\n",
       "      <td>Moravskoslezský kraj</td>\n",
       "      <td>CZ0801</td>\n",
       "      <td>Bruntál</td>\n",
       "      <td>8020</td>\n",
       "      <td>Rýmařov</td>\n",
       "      <td>597791</td>\n",
       "      <td>Ryžoviště</td>\n",
       "      <td>0</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2428876</td>\n",
       "      <td>úterý</td>\n",
       "      <td>2021-03-23</td>\n",
       "      <td>CZ080</td>\n",
       "      <td>Moravskoslezský kraj</td>\n",
       "      <td>CZ0801</td>\n",
       "      <td>Bruntál</td>\n",
       "      <td>8003</td>\n",
       "      <td>Bruntál</td>\n",
       "      <td>597741</td>\n",
       "      <td>Roudno</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2428877</td>\n",
       "      <td>úterý</td>\n",
       "      <td>2021-03-23</td>\n",
       "      <td>CZ080</td>\n",
       "      <td>Moravskoslezský kraj</td>\n",
       "      <td>CZ0801</td>\n",
       "      <td>Bruntál</td>\n",
       "      <td>8003</td>\n",
       "      <td>Bruntál</td>\n",
       "      <td>597546</td>\n",
       "      <td>Leskovec nad Moravicí</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2428878</td>\n",
       "      <td>úterý</td>\n",
       "      <td>2021-03-23</td>\n",
       "      <td>CZ080</td>\n",
       "      <td>Moravskoslezský kraj</td>\n",
       "      <td>CZ0804</td>\n",
       "      <td>Nový Jičín</td>\n",
       "      <td>8015</td>\n",
       "      <td>Nový Jičín</td>\n",
       "      <td>599905</td>\n",
       "      <td>Starý Jičín</td>\n",
       "      <td>0</td>\n",
       "      <td>27</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2428879</td>\n",
       "      <td>úterý</td>\n",
       "      <td>2021-03-23</td>\n",
       "      <td>CZ099</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CZ099Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9999</td>\n",
       "      <td>NaN</td>\n",
       "      <td>999999</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>420</td>\n",
       "      <td>0</td>\n",
       "      <td>236</td>\n",
       "      <td>552</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2428880 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            den       datum kraj_nuts_kod            kraj_nazev okres_lau_kod  \\\n",
       "0        neděle  2020-03-01         CZ010    Hlavní město Praha        CZ0100   \n",
       "1        neděle  2020-03-01         CZ020      Středočeský kraj        CZ020B   \n",
       "2        neděle  2020-03-01         CZ020      Středočeský kraj        CZ020B   \n",
       "3        neděle  2020-03-01         CZ020      Středočeský kraj        CZ0204   \n",
       "4        neděle  2020-03-01         CZ020      Středočeský kraj        CZ0204   \n",
       "...         ...         ...           ...                   ...           ...   \n",
       "2428875   úterý  2021-03-23         CZ080  Moravskoslezský kraj        CZ0801   \n",
       "2428876   úterý  2021-03-23         CZ080  Moravskoslezský kraj        CZ0801   \n",
       "2428877   úterý  2021-03-23         CZ080  Moravskoslezský kraj        CZ0801   \n",
       "2428878   úterý  2021-03-23         CZ080  Moravskoslezský kraj        CZ0804   \n",
       "2428879   úterý  2021-03-23         CZ099                   NaN        CZ099Y   \n",
       "\n",
       "        okres_nazev  orp_kod   orp_nazev  obec_kod             obec_nazev  \\\n",
       "0             Praha        0       Praha    554782                  Praha   \n",
       "1           Příbram     2020     Příbram    564214                Počaply   \n",
       "2           Příbram     2020     Příbram    564249       Chrást (Příbram)   \n",
       "3             Kolín     2006  Český Brod    564800               Hradešín   \n",
       "4             Kolín     2006  Český Brod    564826                Vrátkov   \n",
       "...             ...      ...         ...       ...                    ...   \n",
       "2428875     Bruntál     8020     Rýmařov    597791              Ryžoviště   \n",
       "2428876     Bruntál     8003     Bruntál    597741                 Roudno   \n",
       "2428877     Bruntál     8003     Bruntál    597546  Leskovec nad Moravicí   \n",
       "2428878  Nový Jičín     8015  Nový Jičín    599905            Starý Jičín   \n",
       "2428879         NaN     9999         NaN    999999                    NaN   \n",
       "\n",
       "         nove_pripady  aktivni_pripady  nove_pripady_65  nove_pripady_7_dni  \\\n",
       "0                   2                2                1                   2   \n",
       "1                   0                0                0                   0   \n",
       "2                   0                0                0                   0   \n",
       "3                   0                0                0                   0   \n",
       "4                   0                0                0                   0   \n",
       "...               ...              ...              ...                 ...   \n",
       "2428875             0                7                0                   3   \n",
       "2428876             0                1                0                   1   \n",
       "2428877             0                9                0                   5   \n",
       "2428878             0               27                0                   6   \n",
       "2428879             0              420                0                 236   \n",
       "\n",
       "         nove_pripady_14_dni  \n",
       "0                          2  \n",
       "1                          0  \n",
       "2                          0  \n",
       "3                          0  \n",
       "4                          0  \n",
       "...                      ...  \n",
       "2428875                    5  \n",
       "2428876                    1  \n",
       "2428877                    9  \n",
       "2428878                   20  \n",
       "2428879                  552  \n",
       "\n",
       "[2428880 rows x 15 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(Path(\"~/Downloads/obce.csv\"))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "obce = [\"Strážov\", \"Chudenice\", \"Čachrov\"]\n",
    "\n",
    "df[\"datum\"] = pd.to_datetime(df.datum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='datum', ylabel='nove_pripady_14_dni'>"
      ]
     },
     "execution_count": 48,
     "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": [
    "sns.lineplot(data=df[df.obec_nazev.isin(obce)],hue=\"obec_nazev\", x='datum', y=\"nove_pripady_14_dni\")\n",
    "# sns.lineplot(data=df[df.obec_nazev == \"Chudenice\"], x='datum', y=\"nove_pripady_14_dni\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sns.ecdfplot(data=df[df.obec_nazev.isin([\"Strážov\", \"Chudenice\", \"Čachrov\"])],hue=\"obec_nazev\", x='datum', y=\"nove_pripady_14_dni\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.10.0'"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sns.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Celkový počet nakažených za 2021"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Jirik\\Miniconda3\\envs\\lisa3qt5\\lib\\site-packages\\ipykernel_launcher.py:1: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "dfsel = df[df.obec_nazev.isin(obce)][df.datum < pd.to_datetime(\"2021-01-01\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>nove_pripady</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>obec_nazev</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>Chudenice</td>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Strážov</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>Čachrov</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            nove_pripady\n",
       "obec_nazev              \n",
       "Chudenice             33\n",
       "Strážov               84\n",
       "Čachrov               25"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "pd.pivot_table(data=dfsel, index=\"obec_nazev\",values=[\"nove_pripady\"], aggfunc=np.sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.7"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}