{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d95bdf66-7851-4197-932b-cd30a96a0909",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import sqlite3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e3fc1758",
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = sqlite3.connect(\"stats-political/corona_israel_ver_00178.db\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "0d2ac208",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_sql_query(\"SELECT * from corona_israel_00178 where corona_result = 'Positive'\", conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "72fefe00-184e-4032-b323-f15058f6d8b3",
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>test_date</th>\n",
       "      <th>cough</th>\n",
       "      <th>fever</th>\n",
       "      <th>sore_throat</th>\n",
       "      <th>shortness_of_breath</th>\n",
       "      <th>head_ache</th>\n",
       "      <th>corona_result</th>\n",
       "      <th>age_60_and_above</th>\n",
       "      <th>gender</th>\n",
       "      <th>test_indication</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Positive</td>\n",
       "      <td>No</td>\n",
       "      <td>female</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Positive</td>\n",
       "      <td>No</td>\n",
       "      <td>female</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Positive</td>\n",
       "      <td>No</td>\n",
       "      <td>female</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Positive</td>\n",
       "      <td>No</td>\n",
       "      <td>male</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Positive</td>\n",
       "      <td>No</td>\n",
       "      <td>female</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    test_date cough fever sore_throat shortness_of_breath head_ache  \\\n",
       "0  2021-09-05     0     0           0                   0         0   \n",
       "1  2021-09-05     0     0           0                   0         0   \n",
       "2  2021-09-05     0     0           0                   0         0   \n",
       "3  2021-09-05     0     0           0                   0         0   \n",
       "4  2021-09-05     0     0           0                   0         0   \n",
       "\n",
       "  corona_result age_60_and_above  gender test_indication  \n",
       "0      Positive               No  female           Other  \n",
       "1      Positive               No  female           Other  \n",
       "2      Positive               No  female           Other  \n",
       "3      Positive               No    male           Other  \n",
       "4      Positive               No  female           Other  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "da10c3c0-0fb1-4c62-a5a5-4c2db98444f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>test_date</th>\n",
       "      <th>cough</th>\n",
       "      <th>fever</th>\n",
       "      <th>sore_throat</th>\n",
       "      <th>shortness_of_breath</th>\n",
       "      <th>head_ache</th>\n",
       "      <th>corona_result</th>\n",
       "      <th>age_60_and_above</th>\n",
       "      <th>gender</th>\n",
       "      <th>test_indication</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Positive</td>\n",
       "      <td>No</td>\n",
       "      <td>male</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>283</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
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       "      <td>No</td>\n",
       "      <td>male</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>289</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Positive</td>\n",
       "      <td>No</td>\n",
       "      <td>female</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Positive</td>\n",
       "      <td>No</td>\n",
       "      <td>male</td>\n",
       "      <td>Contact with confirmed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>316</th>\n",
       "      <td>2021-09-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Positive</td>\n",
       "      <td>Yes</td>\n",
       "      <td>female</td>\n",
       "      <td>Contact with confirmed</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      test_date cough fever sore_throat shortness_of_breath head_ache  \\\n",
       "263  2021-09-05     0     0           1                   0         1   \n",
       "283  2021-09-05     0     0           0                   0         1   \n",
       "289  2021-09-05     0     0           1                   0         1   \n",
       "315  2021-09-05     0     0           0                   0         1   \n",
       "316  2021-09-05     1     0           0                   0         1   \n",
       "\n",
       "    corona_result age_60_and_above  gender         test_indication  \n",
       "263      Positive               No    male                   Other  \n",
       "283      Positive               No    male                   Other  \n",
       "289      Positive               No  female                   Other  \n",
       "315      Positive               No    male  Contact with confirmed  \n",
       "316      Positive              Yes  female  Contact with confirmed  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['head_ache'] != '0'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "410b60a9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "test_date              488972\n",
       "cough                  488972\n",
       "fever                  488972\n",
       "sore_throat            488972\n",
       "shortness_of_breath    488972\n",
       "head_ache              488972\n",
       "corona_result          488972\n",
       "age_60_and_above       488972\n",
       "gender                 488972\n",
       "test_indication        488972\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "60ef9fb6",
   "metadata": {},
   "outputs": [],
   "source": [
    "df['test_date'] = pd.to_datetime(df['test_date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "82cc20be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['test_date', 'cough', 'fever', 'sore_throat', 'shortness_of_breath',\n",
       "       'head_ache', 'corona_result', 'age_60_and_above', 'gender',\n",
       "       'test_indication'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2f578127",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df.groupby(df['test_date'].dt.date).count()['corona_result']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c8b1bccb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "test_date\n",
       "2020-03-11    42\n",
       "2020-03-12    38\n",
       "2020-03-13    36\n",
       "2020-03-14    47\n",
       "2020-03-15    61\n",
       "Name: corona_result, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9c731980",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AxesSubplot(0.125,0.125;0.775x0.755)\n"
     ]
    },
    {
     "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": [
    "ax = df1.plot()\n",
    "print(ax)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f17fd8ab",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}