canada-covid-19-data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>provincial_case_id</th>\n",
       "      <th>age</th>\n",
       "      <th>sex</th>\n",
       "      <th>health_region</th>\n",
       "      <th>province</th>\n",
       "      <th>country</th>\n",
       "      <th>date_report</th>\n",
       "      <th>report_week</th>\n",
       "      <th>travel_yn</th>\n",
       "      <th>travel_history_country</th>\n",
       "      <th>locally_acquired</th>\n",
       "      <th>case_source</th>\n",
       "      <th>additional_info</th>\n",
       "      <th>additional_source</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>case_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>50-59</td>\n",
       "      <td>Male</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Canada</td>\n",
       "      <td>25-01-2020</td>\n",
       "      <td>19-01-2020</td>\n",
       "      <td>1</td>\n",
       "      <td>China</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(1) https://news.ontario.ca/mohltc/en/2020/01/...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>50-59</td>\n",
       "      <td>Female</td>\n",
       "      <td>Toronto</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Canada</td>\n",
       "      <td>27-01-2020</td>\n",
       "      <td>26-01-2020</td>\n",
       "      <td>1</td>\n",
       "      <td>China</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(1) https://news.ontario.ca/mohltc/en/2020/01/...</td>\n",
       "      <td>Travel and Close Contact</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>40-49</td>\n",
       "      <td>Male</td>\n",
       "      <td>Vancouver Coastal</td>\n",
       "      <td>BC</td>\n",
       "      <td>Canada</td>\n",
       "      <td>28-01-2020</td>\n",
       "      <td>26-01-2020</td>\n",
       "      <td>1</td>\n",
       "      <td>China</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://news.gov.bc.ca/releases/2020HLTH0015-0...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>20-29</td>\n",
       "      <td>Female</td>\n",
       "      <td>Middlesex-London</td>\n",
       "      <td>Ontario</td>\n",
       "      <td>Canada</td>\n",
       "      <td>31-01-2020</td>\n",
       "      <td>26-01-2020</td>\n",
       "      <td>1</td>\n",
       "      <td>China</td>\n",
       "      <td>NaN</td>\n",
       "      <td>(1) https://news.ontario.ca/mohltc/en/2020/01/...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2</td>\n",
       "      <td>50-59</td>\n",
       "      <td>Female</td>\n",
       "      <td>Vancouver Coastal</td>\n",
       "      <td>BC</td>\n",
       "      <td>Canada</td>\n",
       "      <td>04-02-2020</td>\n",
       "      <td>02-02-2020</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Close Contact</td>\n",
       "      <td>https://news.gov.bc.ca/releases/2020HLTH0023-0...</td>\n",
       "      <td>The individual had close contact with family v...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         provincial_case_id    age     sex      health_region province  \\\n",
       "case_id                                                                  \n",
       "1                         1  50-59    Male            Toronto  Ontario   \n",
       "2                         2  50-59  Female            Toronto  Ontario   \n",
       "3                         1  40-49    Male  Vancouver Coastal       BC   \n",
       "4                         3  20-29  Female   Middlesex-London  Ontario   \n",
       "5                         2  50-59  Female  Vancouver Coastal       BC   \n",
       "\n",
       "        country date_report report_week travel_yn travel_history_country  \\\n",
       "case_id                                                                    \n",
       "1        Canada  25-01-2020  19-01-2020         1                  China   \n",
       "2        Canada  27-01-2020  26-01-2020         1                  China   \n",
       "3        Canada  28-01-2020  26-01-2020         1                  China   \n",
       "4        Canada  31-01-2020  26-01-2020         1                  China   \n",
       "5        Canada  04-02-2020  02-02-2020         0                    NaN   \n",
       "\n",
       "        locally_acquired                                        case_source  \\\n",
       "case_id                                                                       \n",
       "1                    NaN  (1) https://news.ontario.ca/mohltc/en/2020/01/...   \n",
       "2                    NaN  (1) https://news.ontario.ca/mohltc/en/2020/01/...   \n",
       "3                    NaN  https://news.gov.bc.ca/releases/2020HLTH0015-0...   \n",
       "4                    NaN  (1) https://news.ontario.ca/mohltc/en/2020/01/...   \n",
       "5          Close Contact  https://news.gov.bc.ca/releases/2020HLTH0023-0...   \n",
       "\n",
       "                                           additional_info additional_source  \n",
       "case_id                                                                       \n",
       "1                                                      NaN               NaN  \n",
       "2                                 Travel and Close Contact               NaN  \n",
       "3                                                      NaN               NaN  \n",
       "4                                                      NaN               NaN  \n",
       "5        The individual had close contact with family v...               NaN  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = \"https://docs.google.com/spreadsheets/d/1D6okqtBS3S2NRC7GFVHzaZ67DuTw7LX49-fqSLwJyeo/export?format=csv\"\n",
    "# url = \"/Users/kmclean/Downloads/covid-cases.csv\" # Can use to avoid downloading the data over and over again if you already have the dataset locally\n",
    "data = pd.read_csv(url, index_col=0, header=3)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "province\n",
       "Alberta           690\n",
       "BC                970\n",
       "Manitoba           96\n",
       "NL                148\n",
       "NWT                 1\n",
       "New Brunswick      68\n",
       "Nova Scotia       127\n",
       "Ontario          1706\n",
       "PEI                18\n",
       "Quebec           3430\n",
       "Repatriated        13\n",
       "Saskatchewan      176\n",
       "Yukon               5\n",
       "Name: provincial_case_id, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(['province'])['provincial_case_id'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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