npi_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as ptch\n",
    "\n",
    "from datetime import datetime\n",
    "from datetime import timedelta\n",
    "\n",
    "import time\n",
    "from os import listdir\n",
    "from os.path import isfile, join\n",
    "import re\n",
    "\n",
    "plt.rcParams.update(plt.rcParamsDefault)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip freeze > requirements.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pip\n",
      "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/5a/4a/39400ff9b36e719bdf8f31c99fe1fa7842a42fa77432e584f707a5080063/pip-20.2.2-py2.py3-none-any.whl (1.5MB)\n",
      "\u001b[K    100% |################################| 1.5MB 6.6MB/s ta 0:00:01\n",
      "\u001b[?25hInstalling collected packages: pip\n",
      "  Found existing installation: pip 10.0.1\n",
      "    Uninstalling pip-10.0.1:\n",
      "      Successfully uninstalled pip-10.0.1\n",
      "Successfully installed pip-20.2.2\n"
     ]
    }
   ],
   "source": [
    "!pip install --upgrade pip"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31mERROR: Could not find a version that satisfies the requirement pprint==0.1 (from versions: none)\u001b[0m\r\n",
      "\u001b[31mERROR: No matching distribution found for pprint==0.1\u001b[0m\r\n"
     ]
    }
   ],
   "source": [
    "!pip install pprint==0.1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Non-Pharmaceutical Interventions in Canada\n",
    "\n",
    "Here we show comparisons of descriptive statistics for each regional and subregional-level dataset across Canada. Download individual region CSVs from the Google Sheet and place them in `./data/`. \n",
    "\n",
    "Stats Canada data on population size by province available from: \n",
    "\n",
    "Statistics Canada. Table 17-10-0009-01 Population estimates, quarterly\"\n",
    "https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1710000901\n",
    "DOI: https://doi.org/10.25318/1710000901-eng\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "cutoff_date = datetime(2020, 9, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "stats_columns=[\n",
    "    'file',\n",
    "    'region',\n",
    "    'subregion', \n",
    "    'rows',\n",
    "    'columns',\n",
    "    'start_date.min', \n",
    "    'start_date.max', \n",
    "    'end_date.min', \n",
    "    'end_date.max', \n",
    "    'end_date.count / count', \n",
    "    'reviewer.unique', \n",
    "    'intervention_summary.unique', \n",
    "    'intervention_category.unique',\n",
    "    'target_population_category.unique',\n",
    "    'target_population_category (% not \"General\")',\n",
    "    'enforcement_category.unique',\n",
    "    'oxford_government_response_category.notna',\n",
    "    'oxford_government_response_category.unique',\n",
    "    'oxford_fiscal_measure_cad.sum',\n",
    "    'source_url.unique'\n",
    "]\n",
    "\n",
    "columns=[\n",
    "    'start_date',\n",
    "    'end_date',\n",
    "    'reviewer',\n",
    "    'country',\n",
    "    'region',\n",
    "    'subregion',\n",
    "    'intervention_summary',\n",
    "    'intervention_category',\n",
    "    'target_population_category',\n",
    "    'enforcement_category',\n",
    "    'oxford_government_response_category',\n",
    "    'oxford_closure_code',\n",
    "    'oxford_public_info_code',\n",
    "    'oxford_travel_code',\n",
    "    'oxford_geographic_target_code',\n",
    "    'oxford_fiscal_measure_cad',\n",
    "    'oxford_monetary_measure',\n",
    "    'oxford_testing_code',\n",
    "    'oxford_tracing_code',\n",
    "    'oxford_restriction_code',\n",
    "    'oxford_income_amount',\n",
    "    'oxford_income_target',\n",
    "    'oxford_debt_relief_code',\n",
    "    'source_url',\n",
    "    'source_organization',\n",
    "    'source_organization_2',\n",
    "    'source_category',\n",
    "    'source_title',\n",
    "    'source_full_text',\n",
    "    'note',\n",
    "    'end_source_url',\n",
    "    'end_source_organization',\n",
    "    'end_source_organization_2',\n",
    "    'end_source_category',\n",
    "    'end_source_title',\n",
    "    'end_source_full_text'\n",
    "]"
   ]
  },
  {
   "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>region</th>\n",
       "      <th>population_q1_2020</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Canada</td>\n",
       "      <td>37894799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Newfoundland and Labrador</td>\n",
       "      <td>521365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Prince Edward Island</td>\n",
       "      <td>158158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Nova Scotia</td>\n",
       "      <td>977457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>779993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Quebec</td>\n",
       "      <td>8537674</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ontario</td>\n",
       "      <td>14711827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Manitoba</td>\n",
       "      <td>1377517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Saskatchewan</td>\n",
       "      <td>1181666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Alberta</td>\n",
       "      <td>4413146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>British Columbia</td>\n",
       "      <td>5110917</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Yukon</td>\n",
       "      <td>41078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Northwest Territories</td>\n",
       "      <td>44904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Nunavut</td>\n",
       "      <td>39097</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       region  population_q1_2020\n",
       "0                      Canada            37894799\n",
       "1   Newfoundland and Labrador              521365\n",
       "2        Prince Edward Island              158158\n",
       "3                 Nova Scotia              977457\n",
       "4               New Brunswick              779993\n",
       "5                      Quebec             8537674\n",
       "6                     Ontario            14711827\n",
       "7                    Manitoba             1377517\n",
       "8                Saskatchewan             1181666\n",
       "9                     Alberta             4413146\n",
       "10           British Columbia             5110917\n",
       "11                      Yukon               41078\n",
       "12      Northwest Territories               44904\n",
       "13                    Nunavut               39097"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "population_df = pd.read_csv('data/statscan-population-q.csv', thousands=',')\n",
    "population_df[['Geography', 'Q1 2020']]\n",
    "population_df['region'] = population_df['Geography']\n",
    "population_df['population_q1_2020'] = pd.to_numeric(population_df['Q1 2020'])\n",
    "population_df = population_df[['region', 'population_q1_2020']]\n",
    "population_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_df = pd.read_csv('SCHEMA UPDATE - Collecting NPIs Effects - FULL.csv', error_bad_lines=False)\n",
    "full_df['start_date'] = pd.to_datetime(full_df['start_date'], format='%m/%d/%Y', errors='coerce')\n",
    "full_df['end_date'] = pd.to_datetime(full_df['end_date'], format='%m/%d/%Y', errors='coerce')\n",
    "full_df['oxford_fiscal_measure_cad'] = full_df['oxford_fiscal_measure_cad'].replace('[\\$,]', '', regex=True).astype(float)\n",
    "full_df['end_source_full_text'] = full_df['end_source_full_text'].astype(str)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_df = full_df[full_df['start_date'] <= cutoff_date]\n",
    "full_df = full_df[~full_df['start_date'].isna()]\n",
    "\n",
    "provinces_df = full_df[full_df['subregion'].isna() & full_df['region'].notna() & (full_df['region'] != \"All\")]\n",
    "\n",
    "federal_df = full_df[full_df['subregion'].isna() & (full_df['region'].isna() | (full_df['region'] == \"All\"))]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4390, 35)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2274, 35)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "provinces_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(166, 35)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "federal_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4390, 35)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "object_columns = full_df.dtypes[full_df.dtypes == 'object'].index.values\n",
    "\n",
    "# Cleans up columns\n",
    "\n",
    "full_df[object_columns] = full_df[object_columns].replace('\\n',' ', regex=True)\n",
    "full_df[object_columns] = full_df[object_columns].replace('\\r',' ', regex=True)\n",
    "full_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_df.drop(columns=['reviewer']).to_csv('npi_canada.csv')\n",
    "#provinces_df.drop(columns=['reviewer']).to_csv('npi_by_province.csv')\n",
    "#federal_df.drop(columns=['reviewer']).to_csv('npi_federal.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "check = pd.read_csv('npi_canada.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Descriptive Statistics for Paper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of interventions recorded:  4390\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of interventions recorded: \", full_df.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of oxford interventions recorded:  1855\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of oxford interventions recorded: \", full_df['oxford_government_response_category'].count())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of unique source urls:  2853\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of unique source urls: \", len(full_df['source_url'].unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of unique primary source organizations:  279\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of unique primary source organizations: \", len(full_df['source_organization'].unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "% of interventions with oxford classifications:  0.42390310786106034\n"
     ]
    }
   ],
   "source": [
    "oxford_ratio = full_df['oxford_government_response_category'].count() / full_df['intervention_category'].count()\n",
    "print(\"% of interventions with oxford classifications: \", oxford_ratio)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "C1 School Closing                            62\n",
       "C2 Workplace Closures                       290\n",
       "C3 Cancel public events                     131\n",
       "C4 Public Gathering Restrictions            100\n",
       "C5 Close public transport                    10\n",
       "C6 Stay at Home                               7\n",
       "C7 Restrictions on internal movements       200\n",
       "C8 International Travel Controls             86\n",
       "E1 Income Support                            46\n",
       "E2 Debt / Contract Relief for Households     91\n",
       "E3 Fiscal measures                          317\n",
       "E4 Support for Other Countries                4\n",
       "H1 Public Info Campaigns                    314\n",
       "H2 Testing policy                            84\n",
       "H3 Contact tracing                            8\n",
       "H4 Emergency investment in health care       92\n",
       "H5 Investment in vaccines                    13\n",
       "Name: oxford_government_response_category, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df['oxford_government_response_category'].value_counts().sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert full_df['oxford_government_response_category'].nunique() == 17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "475"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df['end_date'].count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Canada', nan], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df['country'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Northwest Territories', 'Alberta', 'All', 'Quebec',\n",
       "       'British Columbia', 'Ontario', 'Manitoba', 'New Brunswick',\n",
       "       'Nova Scotia', 'Newfoundland and Labrador', 'Yukon',\n",
       "       'Saskatchewan', nan, 'Atlantic Canada', 'Manitoba ', 'Ontario ',\n",
       "       'Nunavut', 'All except Greater Montreal', 'Prince Edward Island'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df['region'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'Calgary', 'Vancouver', 'Kelowna', 'Winnipeg', 'Montreal',\n",
       "       'Ottawa', 'Gatineau', 'Victoria', 'Edmonton', 'Toronto', 'Regina',\n",
       "       'London', 'Quebec City', \"St. John's\", 'Halifax', 'Muskoka',\n",
       "       'Kingston', 'Kitchener-Waterloo', 'Hamilton', 'Saskatoon',\n",
       "       'Windsor', 'Oshawa', 'All except Greater Montreal',\n",
       "       'Greater Montreal', 'Laval', 'Niagara'], dtype=object)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df['subregion'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of regions:  1\n",
      "Number of regions:  18\n",
      "Number of subregions:  26\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of regions: \", full_df['country'].nunique())\n",
    "print(\"Number of regions: \", full_df['region'].nunique())\n",
    "print(\"Number of subregions: \", full_df['subregion'].nunique())\n",
    "\n",
    "assert full_df['country'].nunique() == 1 # canada\n",
    "#assert full_df['region'].nunique() == 15 # 13 provinces + nan + All\n",
    "#assert full_df['subregion'].nunique() == 21"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Declaration of emergency (or similar)                           60\n",
       "Recreational / Entertainment Facility Closure or Restriction    50\n",
       "Emergency economic funding                                      50\n",
       "Public Announcement                                             35\n",
       "Non-essential workplace closure                                 33\n",
       "Public park restriction or closure                              28\n",
       "Administrative flexibility                                      26\n",
       "Government building closure                                     20\n",
       "School closure                                                  18\n",
       "Public event/ meeting cancellation or postponement              15\n",
       "Travel Restriction (Internal)                                   14\n",
       "Improve testing capacity                                        12\n",
       "Public park restrictions or closures                             9\n",
       "Restaurant visiting restrictions or closures                     9\n",
       "Self-isolation                                                   8\n",
       "Travel Restriction (External)                                    8\n",
       "Social Service provider restrictions                             7\n",
       "Healthcare facility restrictions                                 7\n",
       "Public event size restriction (<=10)                             7\n",
       "Public event size restriction (<=5)                              6\n",
       "Emergency healthcare funding                                     6\n",
       "Social Distancing Announcement                                   6\n",
       "Public transit route reduction                                   5\n",
       "Retail closure                                                   5\n",
       "Court closure                                                    5\n",
       "Employment Protections                                           5\n",
       "Public event size restriction (<=50)                             4\n",
       "Emergency social services funding                                4\n",
       "Public event size restriction (<=250)                            2\n",
       "Health workforce task-shifting                                   2\n",
       "Public event size restriction (<=25)                             2\n",
       "Correctional facility restrictions                               1\n",
       "Tourism site restrictions                                        1\n",
       "Government-monitored quarantine                                  1\n",
       "Emergency research funding                                       1\n",
       "Technology                                                       1\n",
       "Creation of command center                                       1\n",
       "Public event size restriction (<=2)                              1\n",
       "Name: intervention_category, dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ed = full_df[~full_df['end_date'].isna()]\n",
    "ed['intervention_category'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# NPIs before Key Dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of interventions recorded before may 11:  135\n",
      "Number of interventions recorded before may 11 (%):  0.030751708428246014\n"
     ]
    }
   ],
   "source": [
    "full_11_df = full_df[full_df['start_date'] < '2020-03-11']\n",
    "print(\"Number of interventions recorded before may 11: \", full_11_df.shape[0])\n",
    "print(\"Number of interventions recorded before may 11 (%): \", full_11_df.shape[0] / full_df.shape[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0da0c25d30>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_11_df.groupby(by='intervention_category')['start_date'].count().plot.bar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of interventions recorded before Jan 25:  9\n",
      "Number of interventions recorded before Jan 25 (%):  0.002050113895216401\n"
     ]
    }
   ],
   "source": [
    "full_1_df = full_df[full_df['start_date'] < '2020-01-25'] # first case\n",
    "print(\"Number of interventions recorded before Jan 25: \", full_1_df.shape[0])\n",
    "print(\"Number of interventions recorded before Jan 25 (%): \", full_1_df.shape[0] / full_df.shape[0])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.002050113895216401"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "9 / full_df.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Public Announcement', 'Public Reassurance', 'Symptom screening',\n",
       "       'Improve testing capacity', 'Self-reported screening'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_1_df['intervention_category'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## NPI: Enforcement Categories\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(full_df['enforcement_category'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "enforcement_category\n",
       "Not Applicable         1\n",
       "Arrest                 8\n",
       "Legal Action          51\n",
       "Fines                108\n",
       "Refusal of Entry     199\n",
       "Not Applicable      3938\n",
       "dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df.groupby(by='enforcement_category').count().max(axis=1).sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'count')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 216x216 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_df.groupby(by=\"enforcement_category\").count().max(axis=1).sort_values(ascending=False).plot.barh(log=True, figsize=(3,3))\n",
    "plt.xlabel('count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Target Population Categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "19"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(full_df['target_population_category'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'count')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x504 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_df.groupby(by=\"target_population_category\").count().max(axis=1).sort_values(ascending=False).plot.barh(log=True, figsize=(5,7))\n",
    "plt.xlabel('count')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## NPI: Intervention Categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Unique interventions:  62\n"
     ]
    },
    {
     "ename": "AssertionError",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAssertionError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-38-e490e610dd84>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mn_interventions_unique\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfull_df\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'intervention_category'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munique\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Unique interventions: '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mn_interventions_unique\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0;32massert\u001b[0m \u001b[0mn_interventions_unique\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m61\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;31mAssertionError\u001b[0m: "
     ]
    }
   ],
   "source": [
    "n_interventions_unique = len(full_df['intervention_category'].unique())\n",
    "print('Unique interventions: ', n_interventions_unique)\n",
    "assert n_interventions_unique == 61"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets show examples of the top 15 interventions by count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "intervention_counts = pd.DataFrame(full_df.groupby(by='intervention_category').count().max(axis=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>0_x</th>\n",
       "      <th>0_y</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>intervention_category</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Public Announcement</th>\n",
       "      <td>820</td>\n",
       "      <td>Reminder of rules during COVID-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>General case announcement</th>\n",
       "      <td>631</td>\n",
       "      <td>Fifth confirmed case in Waterloo region</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emergency economic funding</th>\n",
       "      <td>305</td>\n",
       "      <td>Injection of $17M into economy target small and medium sized businesses</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emergency social services funding</th>\n",
       "      <td>199</td>\n",
       "      <td>Opening of additional drop-in centre and new shelter for homeless</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Social Distancing Announcement</th>\n",
       "      <td>187</td>\n",
       "      <td>Patrolling by police officer brigades to reincorce physical distancing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Administrative flexibility</th>\n",
       "      <td>156</td>\n",
       "      <td>Oshawa’s Building Services goes fully digital</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Recreational / Entertainment Facility Closure or Restriction</th>\n",
       "      <td>147</td>\n",
       "      <td>Closure of Espace Pour La Vie museums</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Public event/ meeting cancellation or postponement</th>\n",
       "      <td>124</td>\n",
       "      <td>Annual Canada Day Cellebration for Seniors cancelled</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Non-essential workplace closure</th>\n",
       "      <td>104</td>\n",
       "      <td>Personal service setting closed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Self-isolation</th>\n",
       "      <td>102</td>\n",
       "      <td>Recommendation that all travellers returning to PEI monitor symptoms and voluntarily self-islote</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Declaration of emergency (or similar)</th>\n",
       "      <td>98</td>\n",
       "      <td>Declaration of State of Emergency</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Public park restriction or closure</th>\n",
       "      <td>94</td>\n",
       "      <td>Announcement that public parks will remain open but public facilities will be closed to ensure social distancing practices are enforced.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Healthcare facility restrictions</th>\n",
       "      <td>91</td>\n",
       "      <td>Visitors arriving at Manitoba health system facilities including HSC Winnipeg hospital will be screened for COVID-19. Visitor restrictions. Healthcare rescheduling.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emergency healthcare funding</th>\n",
       "      <td>85</td>\n",
       "      <td>Quebec provides 133 million dollars to residences for seniors and vulnerable people</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Improve testing capacity</th>\n",
       "      <td>83</td>\n",
       "      <td>Testing for anyone working at Sunnyside with symptoms or who had direct contact with someone with COVID-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Public Reassurance</th>\n",
       "      <td>65</td>\n",
       "      <td>Local hospitals have virtual town hall to answer public's questions around COVID-19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Travel Restriction (Internal)</th>\n",
       "      <td>64</td>\n",
       "      <td>Visits to incarcerated individuals in federal correctional institutes suspended</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                              0_x  \\\n",
       "intervention_category                                               \n",
       "Public Announcement                                           820   \n",
       "General case announcement                                     631   \n",
       "Emergency economic funding                                    305   \n",
       "Emergency social services funding                             199   \n",
       "Social Distancing Announcement                                187   \n",
       "Administrative flexibility                                    156   \n",
       "Recreational / Entertainment Facility Closure or Restriction  147   \n",
       "Public event/ meeting cancellation or postponement            124   \n",
       "Non-essential workplace closure                               104   \n",
       "Self-isolation                                                102   \n",
       "Declaration of emergency (or similar)                         98    \n",
       "Public park restriction or closure                            94    \n",
       "Healthcare facility restrictions                              91    \n",
       "Emergency healthcare funding                                  85    \n",
       "Improve testing capacity                                      83    \n",
       "Public Reassurance                                            65    \n",
       "Travel Restriction (Internal)                                 64    \n",
       "\n",
       "                                                                                                                                                                                                                               0_y  \n",
       "intervention_category                                                                                                                                                                                                               \n",
       "Public Announcement                                           Reminder of rules during COVID-19                                                                                                                                     \n",
       "General case announcement                                     Fifth confirmed case in Waterloo region                                                                                                                               \n",
       "Emergency economic funding                                    Injection of $17M into economy target small and medium sized businesses                                                                                               \n",
       "Emergency social services funding                             Opening of additional drop-in centre and new shelter for homeless                                                                                                     \n",
       "Social Distancing Announcement                                Patrolling by police officer brigades to reincorce physical distancing                                                                                                \n",
       "Administrative flexibility                                    Oshawa’s Building Services goes fully digital                                                                                                                         \n",
       "Recreational / Entertainment Facility Closure or Restriction  Closure of Espace Pour La Vie museums                                                                                                                                 \n",
       "Public event/ meeting cancellation or postponement            Annual Canada Day Cellebration for Seniors cancelled                                                                                                                  \n",
       "Non-essential workplace closure                               Personal service setting closed                                                                                                                                       \n",
       "Self-isolation                                                Recommendation that all travellers returning to PEI monitor symptoms and voluntarily self-islote                                                                      \n",
       "Declaration of emergency (or similar)                         Declaration of State of Emergency                                                                                                                                     \n",
       "Public park restriction or closure                            Announcement that public parks will remain open but public facilities will be closed to ensure social distancing practices are enforced.                              \n",
       "Healthcare facility restrictions                              Visitors arriving at Manitoba health system facilities including HSC Winnipeg hospital will be screened for COVID-19. Visitor restrictions. Healthcare rescheduling.  \n",
       "Emergency healthcare funding                                  Quebec provides 133 million dollars to residences for seniors and vulnerable people                                                                                   \n",
       "Improve testing capacity                                      Testing for anyone working at Sunnyside with symptoms or who had direct contact with someone with COVID-19                                                            \n",
       "Public Reassurance                                            Local hospitals have virtual town hall to answer public's questions around COVID-19                                                                                   \n",
       "Travel Restriction (Internal)                                 Visits to incarcerated individuals in federal correctional institutes suspended                                                                                       "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_colwidth', -1)\n",
    "\n",
    "examples = pd.DataFrame(full_df.groupby(by='intervention_category').apply(lambda x: x.sample(1, random_state=3)['intervention_summary'].values[0]))\n",
    "\n",
    "intervention_counts.merge(examples, left_index=True, right_index=True).sort_values(by='0_x', ascending=False)[0:17]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "intervention_category\n",
       "Public Announcement                                             655\n",
       "General case announcement                                       596\n",
       "Administrative flexibility                                      130\n",
       "Emergency social services funding                               85 \n",
       "Recreational / Entertainment Facility Closure or Restriction    82 \n",
       "Declaration of emergency (or similar)                           80 \n",
       "Social Distancing Announcement                                  78 \n",
       "Healthcare facility restrictions                                67 \n",
       "Public Reassurance                                              50 \n",
       "Public park restriction or closure                              49 \n",
       "Health workforce task-shifting                                  47 \n",
       "Face Mask Recommendation                                        45 \n",
       "Social Service provider restrictions                            39 \n",
       "Improve testing capacity                                        37 \n",
       "Education or Work from Home                                     33 \n",
       "Employment Protections                                          33 \n",
       "Increased sanitation measures                                   32 \n",
       "Technology                                                      29 \n",
       "Creation of command center                                      27 \n",
       "First case announcement                                         26 \n",
       "Government building closure                                     24 \n",
       "Public event/ meeting cancellation or postponement              24 \n",
       "Manufacturing repurposing                                       23 \n",
       "Self-isolation                                                  20 \n",
       "Restaurant visiting restrictions or closures                    18 \n",
       "Public park restrictions or closures                            17 \n",
       "First death announcement                                        16 \n",
       "Correctional facility restrictions                              14 \n",
       "Emergency healthcare funding                                    13 \n",
       "Travel Restriction (Internal)                                   13 \n",
       "Public transit route reduction                                  12 \n",
       "Emergency economic funding                                      12 \n",
       "Symptom screening                                               11 \n",
       "Government-sponsored isolation facility                         11 \n",
       "Court closure                                                   8  \n",
       "Virtual Care Billing Enabled                                    7  \n",
       "Non-essential workplace closure                                 7  \n",
       "Travel Restriction (External)                                   6  \n",
       "Tourism site restrictions                                       5  \n",
       "Retail closure                                                  5  \n",
       "Emergency research funding                                      4  \n",
       "Case Definition Change                                          4  \n",
       "Testing Definition Change                                       4  \n",
       "School closure                                                  4  \n",
       "Self-Assessment Tool Released                                   4  \n",
       "Public event size restriction (<=50)                            3  \n",
       "Disclosed Case Reporting Change                                 3  \n",
       "Public event size restriction (<=10)                            2  \n",
       "Temperature screening                                           2  \n",
       "Border closure                                                  2  \n",
       "Electoral poll cancelation                                      1  \n",
       "Self-reported screening                                         1  \n",
       "Public event size restriction (<=5)                             1  \n",
       "Public event size restriction (<=250)                           1  \n",
       "Public event size restriction (<=25)                            1  \n",
       "First multiple case announcement                                1  \n",
       "Government-monitored lockdown                                   1  \n",
       "dtype: int64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df[full_df['oxford_government_response_category'].isna()].groupby(by='intervention_category').count().max(axis=1).sort_values(ascending=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'count')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x1008 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "full_df.groupby(by=\"intervention_category\").count().max(axis=1).sort_values(ascending=False).plot.barh(log=True, figsize=(8,14))\n",
    "plt.xlabel('count')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sources\n",
    "\n",
    "Looking at unique source urls, organizations, and source types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(279,)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = full_df['source_organization'].unique()\n",
    "a.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = full_df['source_organization_2'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "405"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_sources = list(set(a) | set(b))\n",
    "len(all_sources)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## NPI: Fiscal Measures\n",
    "\n",
    "Show investments by province or subregion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#fig, ax = plt.subplots(figsize=(12,10))\n",
    "\n",
    "dates = pd.date_range(start='03-01-2020', end='05-20-2020', name='dates').to_series() #mm-dd-yyyy\n",
    "gb = provinces_df[provinces_df['oxford_fiscal_measure_cad'].notna()][['start_date', 'region', 'oxford_fiscal_measure_cad']].groupby(by='region')\n",
    "provinces_fiscal = pd.DataFrame(dates)\n",
    "\n",
    "for g_name, g_df in gb:\n",
    "    all_dates_df = g_df.join(dates, on='start_date', how='right')\n",
    "    all_dates_df['oxford_fiscal_measure_cad'] = all_dates_df['oxford_fiscal_measure_cad'].fillna(0)\n",
    "    all_dates_df = all_dates_df.sort_values(by='start_date', ascending=True)\n",
    "    all_dates_df['cumulative'] = all_dates_df['oxford_fiscal_measure_cad'].cumsum(axis=0)\n",
    "    all_dates_df.set_index('start_date')\n",
    "    all_dates_df = all_dates_df.groupby(by='start_date').sum()\n",
    "\n",
    "    provinces_fiscal[g_name] = all_dates_df['cumulative']\n",
    "\n",
    "#plt.yscale('log')\n",
    "#plt.title('')\n",
    "#plt.ylabel('Fiscal Interventions ($)')\n",
    "#plt.xlabel('Date')\n",
    "\n",
    "#provinces_fiscal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING: Not Correct Yet\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0da085f5c0>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"WARNING: Not Correct Yet\")\n",
    "provinces_fiscal.drop(['dates'], axis=1).plot.area()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,10))\n",
    "\n",
    "dates = pd.date_range(start='03-01-2020', end='05-20-2020', name='dates').to_series() #mm-dd-yyyy\n",
    "gb = provinces_df[provinces_df['oxford_fiscal_measure_cad'].notna()][['start_date', 'region', 'oxford_fiscal_measure_cad']].groupby(by='region')\n",
    "\n",
    "for g_name, g_df in gb:\n",
    "    all_dates_df = g_df.join(dates, on='start_date', how='right')\n",
    "    all_dates_df['oxford_fiscal_measure_cad'] = all_dates_df['oxford_fiscal_measure_cad'].fillna(0)\n",
    "    all_dates_df = all_dates_df.sort_values(by='start_date', ascending=True)\n",
    "    all_dates_df['oxford_fiscal_measure_cad_cumsum'] = all_dates_df['oxford_fiscal_measure_cad'].cumsum(axis=0)\n",
    "    #print(all_dates_df)\n",
    "    all_dates_df.plot(x='start_date', y='oxford_fiscal_measure_cad_cumsum', label=g_name, ax=ax)\n",
    "\n",
    "plt.yscale('log')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f0d83d06630>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_df.groupby(by=['region']).count().max(axis=1).plot.barh()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "region\n",
       "British Columbia              2020-03-25\n",
       "Newfoundland and Labrador     2020-03-26\n",
       "Nunavut                       2020-03-27\n",
       "Quebec                        2020-04-02\n",
       "Alberta                       2020-04-03\n",
       "Northwest Territories         2020-04-06\n",
       "New Brunswick                 2020-04-09\n",
       "Prince Edward Island          2020-04-09\n",
       "Saskatchewan                  2020-04-13\n",
       "Ontario                       2020-04-15\n",
       "Nova Scotia                   2020-04-23\n",
       "Yukon                         2020-04-28\n",
       "Manitoba                      2020-04-30\n",
       "Manitoba                      2020-04-30\n",
       "All                           2020-05-06\n",
       "All except Greater Montreal   2020-06-01\n",
       "Atlantic Canada               2020-06-23\n",
       "Ontario                       2020-08-14\n",
       "Name: start_date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df.groupby(by=['region'])['start_date'].quantile(0.5).sort_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Temporal Distribution of Events"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2020-04-09 00:00:00')"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df['start_date'].quantile(0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2020-04-09 00:00:00')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "provinces_df['start_date'].quantile(0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2020-04-09 00:00:00')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df['start_date'].quantile(0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "region\n",
       "Alberta                       2020-03-05\n",
       "All except Greater Montreal   2020-06-01\n",
       "Atlantic Canada               2020-06-23\n",
       "British Columbia              2020-01-20\n",
       "Manitoba                      2020-01-28\n",
       "New Brunswick                 2020-03-01\n",
       "Newfoundland and Labrador     2020-03-06\n",
       "Northwest Territories         2020-03-10\n",
       "Nova Scotia                   2020-02-28\n",
       "Nunavut                       2020-01-07\n",
       "Ontario                       2020-01-22\n",
       "Prince Edward Island          2020-02-28\n",
       "Quebec                        2020-03-11\n",
       "Saskatchewan                  2020-02-13\n",
       "Yukon                         2020-03-07\n",
       "Name: start_date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "earliest_dates = provinces_df.groupby(by='region')['start_date'].min()\n",
    "earliest_dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert earliest_dates.min() > datetime(2020, 1, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "region\n",
       "Alberta                       2020-06-05\n",
       "All except Greater Montreal   2020-06-01\n",
       "Atlantic Canada               2020-06-23\n",
       "British Columbia              2020-05-15\n",
       "Manitoba                      2020-08-08\n",
       "New Brunswick                 2020-06-01\n",
       "Newfoundland and Labrador     2020-04-26\n",
       "Northwest Territories         2020-06-29\n",
       "Nova Scotia                   2020-07-20\n",
       "Nunavut                       2020-07-10\n",
       "Ontario                       2020-08-12\n",
       "Prince Edward Island          2020-07-05\n",
       "Quebec                        2020-07-18\n",
       "Saskatchewan                  2020-07-13\n",
       "Yukon                         2020-08-26\n",
       "Name: start_date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latest_dates = provinces_df.groupby(by='region')['start_date'].max()\n",
    "latest_dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert latest_dates.min() <= cutoff_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "region\n",
       "Alberta                       2020-06-05\n",
       "All except Greater Montreal   2020-06-01\n",
       "Atlantic Canada               2020-06-23\n",
       "British Columbia              2020-05-15\n",
       "Manitoba                      2020-08-08\n",
       "New Brunswick                 2020-06-01\n",
       "Newfoundland and Labrador     2020-04-26\n",
       "Northwest Territories         2020-06-29\n",
       "Nova Scotia                   2020-07-20\n",
       "Nunavut                       2020-07-10\n",
       "Ontario                       2020-08-12\n",
       "Prince Edward Island          2020-07-05\n",
       "Quebec                        2020-07-18\n",
       "Saskatchewan                  2020-07-13\n",
       "Name: start_date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latest_dates[latest_dates < cutoff_date - timedelta(7)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "subregion\n",
       "All except Greater Montreal   2020-05-04\n",
       "Calgary                       2020-03-10\n",
       "Edmonton                      2020-03-14\n",
       "Gatineau                      2020-03-13\n",
       "Greater Montreal              2020-05-14\n",
       "Halifax                       2020-03-16\n",
       "Hamilton                      2020-03-11\n",
       "Kelowna                       2020-03-07\n",
       "Kingston                      2020-05-08\n",
       "Kitchener-Waterloo            2020-03-05\n",
       "Laval                         2020-05-21\n",
       "London                        2020-03-12\n",
       "Montreal                      2020-02-28\n",
       "Muskoka                       2020-05-08\n",
       "Niagara                       2020-03-13\n",
       "Oshawa                        2020-03-13\n",
       "Ottawa                        2020-03-11\n",
       "Quebec City                   2020-03-13\n",
       "Regina                        2020-03-16\n",
       "Saskatoon                     2020-03-12\n",
       "St. John's                    2020-03-13\n",
       "Toronto                       2020-01-07\n",
       "Vancouver                     2020-03-09\n",
       "Victoria                      2020-03-11\n",
       "Windsor                       2020-02-28\n",
       "Winnipeg                      2020-03-12\n",
       "Name: start_date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cma_earliest_dates = full_df.dropna(subset=['subregion']).groupby(by='subregion')['start_date'].min()\n",
    "cma_earliest_dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert cma_earliest_dates.min() > datetime(2020, 1, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "subregion\n",
       "All except Greater Montreal   2020-05-04\n",
       "Calgary                       2020-06-03\n",
       "Edmonton                      2020-06-15\n",
       "Gatineau                      2020-04-30\n",
       "Greater Montreal              2020-06-01\n",
       "Halifax                       2020-07-31\n",
       "Hamilton                      2020-06-22\n",
       "Kelowna                       2020-06-13\n",
       "Kingston                      2020-05-08\n",
       "Kitchener-Waterloo            2020-07-06\n",
       "Laval                         2020-05-21\n",
       "London                        2020-08-20\n",
       "Montreal                      2020-06-26\n",
       "Muskoka                       2020-05-08\n",
       "Niagara                       2020-08-28\n",
       "Oshawa                        2020-07-08\n",
       "Ottawa                        2020-07-06\n",
       "Quebec City                   2020-05-19\n",
       "Regina                        2020-08-13\n",
       "Saskatoon                     2020-06-08\n",
       "St. John's                    2020-07-06\n",
       "Toronto                       2020-08-31\n",
       "Vancouver                     2020-06-26\n",
       "Victoria                      2020-06-19\n",
       "Windsor                       2020-07-02\n",
       "Winnipeg                      2020-05-15\n",
       "Name: start_date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cma_latest_dates = full_df.dropna(subset=['subregion']).groupby(by='subregion')['start_date'].max()\n",
    "cma_latest_dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert cma_latest_dates.min() <= cutoff_date"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "subregion\n",
       "All except Greater Montreal   2020-05-04\n",
       "Calgary                       2020-06-03\n",
       "Edmonton                      2020-06-15\n",
       "Gatineau                      2020-04-30\n",
       "Greater Montreal              2020-06-01\n",
       "Halifax                       2020-07-31\n",
       "Hamilton                      2020-06-22\n",
       "Kelowna                       2020-06-13\n",
       "Kingston                      2020-05-08\n",
       "Kitchener-Waterloo            2020-07-06\n",
       "Laval                         2020-05-21\n",
       "London                        2020-08-20\n",
       "Montreal                      2020-06-26\n",
       "Muskoka                       2020-05-08\n",
       "Oshawa                        2020-07-08\n",
       "Ottawa                        2020-07-06\n",
       "Quebec City                   2020-05-19\n",
       "Regina                        2020-08-13\n",
       "Saskatoon                     2020-06-08\n",
       "St. John's                    2020-07-06\n",
       "Vancouver                     2020-06-26\n",
       "Victoria                      2020-06-19\n",
       "Windsor                       2020-07-02\n",
       "Winnipeg                      2020-05-15\n",
       "Name: start_date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cma_latest_dates[cma_latest_dates < cutoff_date - timedelta(7)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DatetimeIndex(['2020-01-31', '2020-02-29', '2020-03-31', '2020-04-30',\n",
      "               '2020-05-31', '2020-06-30', '2020-07-31', '2020-08-31'],\n",
      "              dtype='datetime64[ns]', freq='M')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.dates as mdates\n",
    "import matplotlib as mpl\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10,4))\n",
    "\n",
    "xticks = pd.date_range(start='01-01-2020', end=cutoff_date, freq='M')\n",
    "#subset = full_df[full_df['start_date'] < pd.to_datetime('04-01-2020')]\n",
    "ts = full_df.groupby(by=['start_date'])['intervention_category'].count()\n",
    "\n",
    "cmap = mpl.cm.get_cmap('viridis')\n",
    "plt.bar(ts.index, ts.values, color=cmap(0))\n",
    "\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Intervention Count')\n",
    "\n",
    "locator = mdates.MonthLocator()\n",
    "locator.MAXTICKS = 10000\n",
    "\n",
    "plt.gca().xaxis.set_major_locator(locator)\n",
    "month_format = mdates.DateFormatter('%d %b')\n",
    "plt.gca().xaxis.set_major_formatter(month_format)\n",
    "plt.xticks(rotation=90, ha='right')\n",
    "\n",
    "print(xticks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "DatetimeIndex(['2019-12-31', '2020-01-31', '2020-02-29', '2020-03-31',\n",
      "               '2020-04-30', '2020-05-31', '2020-06-30', '2020-07-31',\n",
      "               '2020-08-31'],\n",
      "              dtype='datetime64[ns]', freq='M')\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.dates as mdates\n",
    "import matplotlib as mpl\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(16, 4))\n",
    "\n",
    "xticks = pd.date_range(start='12-01-2019', end=cutoff_date, freq='M')\n",
    "#subset = full_df[full_df['start_date'] < pd.to_datetime('04-01-2020')]\n",
    "\n",
    "\n",
    "cmap = mpl.cm.get_cmap('magma')\n",
    "\n",
    "\n",
    "ts = full_df.groupby(by=['start_date'])['intervention_category'].count()\n",
    "plt.bar(ts.index, ts.values, color=cmap(0.8), label='All')\n",
    "\n",
    "ts = provinces_df.groupby(by=['start_date'])['intervention_category'].count()\n",
    "plt.bar(ts.index, ts.values, color=cmap(0.5), label='Provincial')\n",
    "\n",
    "ts = federal_df.groupby(by=['start_date'])['intervention_category'].count()\n",
    "plt.bar(ts.index, ts.values, color=cmap(0.1), label='Federal')\n",
    "\n",
    "\n",
    "\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Intervention Count')\n",
    "plt.gca().xaxis.set_major_locator(mdates.MonthLocator())\n",
    "month_format = mdates.DateFormatter('%d %b')\n",
    "plt.gca().xaxis.set_major_formatter(month_format)\n",
    "print(xticks)\n",
    "plt.legend()\n",
    "\n",
    "#ts = full_df.subtract(provinces_df).groupby(by=['start_date'])['intervention_category'].count()\n",
    "#cmap = mpl.cm.get_cmap('viridis')\n",
    "#plt.bar(ts.index, ts.values, color=cmap(.5), alpha=0.4)\n",
    "plt.savefig('doc/img/fig2.png', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Geographical Distribution of Interventions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "names = full_df['region']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14]),\n",
       " <a list of 15 Text xticklabel objects>)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.ticker as ticker\n",
    "provinces_df.dropna(subset=['region']).groupby(by=['region'])['intervention_category'].nunique().plot.bar(figsize=(10,4), cmap='viridis')\n",
    "plt.ylabel('Number of unique intervention categories recorded')\n",
    "\n",
    "#@ticker.FuncFormatter\n",
    "#def major_formatter(x, pos):\n",
    "#    return str(x).replace('(', '').replace('(', '')\n",
    "#plt.gca().xaxis.set_major_formatter(major_formatter)\n",
    "plt.xticks(rotation=45, ha='right')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,\n",
       "        17, 18, 19, 20, 21, 22, 23, 24, 25]),\n",
       " <a list of 26 Text xticklabel objects>)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.ticker as ticker\n",
    "subregions = full_df.dropna(subset=['subregion']).groupby(by=['subregion'])['intervention_category'].nunique()\n",
    "\n",
    "subregions.plot.bar(figsize=(10,4), cmap='viridis')\n",
    "plt.ylabel('Number of unique intervention categories recorded')\n",
    "\n",
    "#@ticker.FuncFormatter\n",
    "#def major_formatter(x, pos):\n",
    "#    return str(x).replace('(', '').replace('(', '')\n",
    "#plt.gca().xaxis.set_major_formatter(major_formatter)\n",
    "plt.xticks(rotation=45, ha='right')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'Number of unique Oxford interventions recorded')"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_df.fillna('Province').groupby(by=['region', 'subregion'])['oxford_government_response_category'].nunique().plot.barh()\n",
    "plt.xlabel('Number of unique Oxford interventions recorded')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'Unique Intervention Categories Recorded')"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "provinces_df.groupby(by='region')['intervention_category'].nunique().plot.barh()\n",
    "plt.ylabel('Unique Intervention Categories Recorded')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'Number of unique interventions recorded')"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_df[full_df['subregion'].isna()].groupby(by=['region'])['intervention_category'].nunique().plot.barh()\n",
    "plt.xlabel('Number of unique interventions recorded')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'Number of unique Oxford response measures recorded')"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zg8/BzMwWku8ZaGEREZL2AM6T9CNS4/AG0rcF9m1j0wuAKZIeBA4GDpH0MDCDdKmgveM+L+lY4HZSEuL1EfH3trbZYOV+TPDXgszMGsKphdYtOLXQzKx+Ti00MzOzmrgxYGZm1uLcGDAzM2txbgyYmZm1ODcGWoSkkHR64fExkkY2saRSHcMkbdnsOszMWpm/Wtg63gG+JOkXEfFys4spGAbMAsa1tZJTC80WHU7/+/Bxz0DrmEMaH+Do8gWSRknaq/B4Vv53WA4XulLSI5Iuy0mHSDpB0vgcNHSBknUk3V/YzwBJU/P0k5KWy9ND834HAIcAR+fgo20a9/TNzKwaNwZay7nAfpLqGdt3I+AoYD1gDWCrPP+ciNgkIgYCvYAvRMQjwBKSVs/r7ANcUW3HEfEkcD5wRkQMjogxdT0bMzPrFG4MtJCIeB24FDiijs3uj4hnIuJ9YBIwIM/fXtJ9+cx/B1ICIsBfSI0AaKcx0B4HFZmZdQ03BlrPmcDXSfHCJXPI7wVJPYAlCssWCCuStBRwHrBXRGwA/I554URXAF+W9CnSiMePlR+jsG6bHFRkZtY13BhoMRHxP9LZ+9cLs59kXnrhrsDitK30Yf6ypD7AB/cbRMS/SY2GHzF/r0DxGHsW5r8B9K35CZiZWadzY6A1nQ4sV3j8O1KK4GRgC+DNtjaOiNfyNtOAm4DxZatcAexPanSUnAicJWkCqbFQci2wh28gNDNrHgcVWbfgoCIzs/o5qMjMzMxq4saAmZlZi3NjwMzMrMW5MWBmZtbi3BgwMzNrcQ4q6gYkBfCriPhOfnwM0CciRjboeCsAvwdWJY058GREfK4D+xkO3BwRz+XHF5Kex0P17mvyG2/x8dsn1buZmXUz/91+cLNLaEnuGegeSomDy7W7Zuf4CXBLRGwYEesBx3ZwP8OBlUoPIuIbHWkImJlZY7kx0D20lTg4QNJtkqZIulXSJyT1k/RUHloYSUtLelrS4pK+mdMGJ0v6m6TeFY63IvBM6UFETCkc7/uSpubtT87zBku6N9dwtaSP5BTEocBleUChXjmpcGje5jc5d2C6pBM788UyM7P6uDHQfVRLHPw1cElEDAIuA86OiJmkUKHt8jpfAG6KiPeAq3La4IbAw8w/LHHxWL+XdLuk4yStBCBpF2A3YLO8/al5/UuB7+capgI/jogrgQnAfjmR8O2yYxyXB8IYRBr9cFDHXhYzM1tYbgx0E20kDm4B/ClP/wHYOk9fwbz0wK8wLydgoKQxOW1wP+alDRaPdRMprvh3wDrAREnLAzsBF0fEW3m9/+XGSf+IuDNvfgmwbQ1P6cuSHgQm5hrWK1+hmFr4/szXatilmZl1hBsD3UulxMFqRgM7S1qWFBB0W54/Cjgspw2eSJUEwYj4X0T8KSK+RsoeqOUDviaSVgeOAXbMvQnXV6qjmFrYo1//zjq8mZmVcWOgG6mSODiOdOYP6Ux/TF53FulD/CzguogohQP1BZ6XtHhefwGSdijdSyCpL7Am8B/gFuCgwrJl8yWJVwshQ18DSr0E1RIJlyGFIc3M31zYpeYXwczMOp2/Wtj9nA4cVnh8OHCxpO8CLwEHFZZdAfwVGFaY9yPgvrzufVT+sB4CnCNpDqnBeGFEjId0syAwQdK7wA3AD4EDgfNzI+HxQg2j8vy3SZczAIiIyZImAo8ATwNj23vSG/btzQR/5cjMrCGcWmjdglMLzczq59RCMzMzq4kbA2ZmZi2upsaApC9JekzSTEmvS3pD0uuNLs7MzMwar9YbCE8FvhgRDzeyGDMzM+t6tV4meMENATMzsw+nWnsGJki6AriGFJoDQERc1ZCqGqAzkv8kDQPejYhx+fEo0nf4r+z0guc/7nAK6X+F+ecCWwFLAKsDM/Kin3W0JkmbAV+JiKMl7QC8FRH31rmPPYBPRsRpHamhkjfemMqtt63ZWbszM+sWdtzh311ynFobA8sAbwGfKcwLoNs0BpiX/PeLiHi53o0lLUb6vv4s0kA/XWk4MA2YrzEQEYfm2gaQGiV1fRFf0mIRMafs8X2k8QcAdgBeBmpuDOR9XF1PHWZm1lw1NQYi4qD211rkFZP/jisuyB+mFwHLkQfuiYj/5DP/2cBGwLPAlsBcSfuTBvsB2FbS/wM+DnwvIq7MZ+w3RcRoSVcDr0bEwZIOBtaMiOPyPo4gndXfB3w77+/3pLS/yDU9zbz0v7eBLSqE/ixA0lrAOfk5vQl8IyIelfRH0siAQ4A78uBBnyCNMvhEfs6HAd8BvpGf7/Bc3/O5po8CL+TX6ZkK+3wUGBgRR+URBn+Tj/E+cERE3Jt7Hc7Iz/N9YJuIeLO952VmZp2v1m8TrJKjaV/MP3+TtEqji2uAmpP/CstWAbaMiC8B5wNn5BS+MXn5iqRwoC8AJ+d5Y4DS8LwrMy+EZxvgLknrkkKEtspn83NJQwMPBlaOiIE5O+DiGtL/qrkA+HZEDAF+QGoYlKwIbB4R38uP1yHlBOxfWiEi/g1cCJyWjzsOOI80GuEg0siGZ7axz5KzgVPzoBdfzvsE+C4wIj//bUmNrvkUg4pee+39Gp+2mZnVq9YbCC8mBd+slH+uzfO6lQ4k/wH8tTCufyXXRMT7EfEQsEKeNwbYRtJ6wEPAC5JWzMcZB+xIOoseL2lSfrwGaSjfNST9WtLOQIe+vimpP7A58Le8/3NJv7ficyp+uv49Ihb4MK5gM+DPefpS5jV4Ku2zZCfSkMSTSPecfERSL9IQxGdJOhxYptJrXAwq6t/fQ2KYmTVKrfcMLB8RxQ//UZKOakRBXeBM4EFqb8y013X9TmFaABHxbP5A3hm4C1iWdFY8KyLekCRST8QPyncmaUPgs8AheZuDa6xzvt0AL7dxD0H5c+qM7vlq+xCwaUS8Wzb/Z5JGA58H7pW0Y0Q81gl1mJlZnWo93XpF0v6Seuaf/YFXGllYo9ST/FdBtRS+Su4FjiI1BsaQIntL+70V2EvSxyCl/0laTdJyQI+I+BtwPLBxB45LRLxKSibcI++/R25k1Kv8uPeSGigA++fn1p5/AoeWHuSgIyStGRFTIuIXpMbZ2h2oz8zMOkGtPQMHk66rl274Gsf86XjdTT3Jf0XXAldK2o15NxBWMwb4TET8S9JTpN6BUrzwQ5KOB26W1AN4j/SB+Xauo9RIK/UcjKKQ/lfjfQNfAX4jaSTpJsU/ApNr2K7o78BfJX0p13cocJGkH5BvIKxhH4fmOg4ivd9uz/OOybHH7wNTgJvb2knfvhuw4w4OKjIzawSnFlq34NRCM7P61Zpa2GbPgKTvRcSpkn5N6hGYT0SU34hnZmZm3Ux7lwlKQxD7lMzMzOxDqs3GQERcm/+9pGvKMTMzs65W0w2Ekq5lwcsEM0k9Br+t8TvqZmZmtgiq6QZCSWcBywOX51n7kAbECdKAMV+rsM1CBwNVqeVyYH3S6HxnLMy+2jjGcGBoRByW78afFRG/7IT9jqIBwUbV9lvP8Qr5BgM7sa5ZEdGnM/a10korxYgRIzpjV2a2CBs5cmSzS/hQ6ZQbCAu2jIhNCo+vlTQ+IjaRNL3KNgsVDFSJpI8Dm0TEJztjf1Y/ST3bGZGxo/udLzTJzMy6Tq2DDvWR9InSgzxdOuMrH1mupBgMNB9Jy+d8g/H5Z6s8f6qk/kpekXRAnn+ppE+Tvou+sqRJkraRNFjSvZKm5OyEj+T175A0NE8vJ+nJPD1c0lWSbpT0mKRTCzUdJOlRSfeTYoEXIOmbud7Juf7eef4oSWdLGifpcUl75fmSdI6kGZL+CXysK/db5Vh9JN0q6cH8eu9WWLyYpMskPSzpykIdT0o6RdKDwN5t1Lu6pHvyfn9WOKYknSZpWl62T54/TNIYpZEIH6r1OZiZWeeqtTHwHeBuSbdLuoM8op6kpYG2bi6sFgx0FinwZxNgT+aF14wlfRCvTxqnvzT2fWlM/12BfxeCgi4Fvp+Dc6YCP67huQwmXebYANhH0qpKuQEn5mNvzbxgoXJXRcQmEbEh6ZsWxVEMKwUW7UEaWW894ABS6mFX7reS2cAeEbExsD1wuiTlZWsD50XEuqTLQN8ubPdKRGwcEX9uo96zgN/kkKXnC9t+ifS6b0jKKjgtv+aQRlk8MiI+VcdzMDOzTlRrhPENSpG46+RZMwo3DZ5ZZTMi4nVJpWCg4qh5OwHrzfsMYhlJfUiNjG2Bp0ixtyMkrUyKAH5T0vKlDXIDo39E3JlnXUJK0mvPrRExM+/jIWA1UszvHRHxUp5/BVDpw2lgPuPtT+oZuamw7Joc1POQUmwv+blcnrvVn5N0W5WaGrXfSgScJGlb0uh/KzMvYOnpiBibp/9I+r2V7pW4ooZ6tyI17iAFPp2Sp7cu1PuCpDuBTUgNjvsj4omKhUojgBEA/fqVtyfNzKyz1Bph3JsUOXtYREwGVpX0hRqPcSbpzHHpsuNuns/wB0fEyhExizTW/Tb55w7S0MB7UT0roJo5zHtuS5UtKwYLzaX2+yYgDQt8WD7zPbFs3wsEFi0C+61kP9LNoENykNELheOV301afFwMImqr3nqHtKwaklRMLezdu3eduzUzs1rVE2H8Lqm7HuBZ4GfVV5+nSjDQzRTG9lcOr4mIp0ln6WtFxOPA3aSAnwUCcfLZ/atK49sDfA0o9RI8SYoIhtSYaM99wHaSPippcWDvKuv1JQUALU76UG3PXaRLET1zt/j2XbzfSvoBL0bEe5K2J/WMlHxCUul3/FXS619PvWOZP/CpZEyh3uVJPRv311GzmZk1UK1nxWtGxD6S9gWIiLcK15lrUR4MdARwrqQpuYa7SJG9kD6Ye+bpMcAvqP6hdCApwKc36R6DUnDOL4G/5G7m69srLiKeV/oK4T3Aa8CkKqv+KNf3Uv63vSTBq4EdSDfH/Sfvvyv3C/BbSaVLOU8DXyR9G2QqaZyIRwrrzgAOlXRR3vdv6qz3SOBPkr5PCjkq1rsFKSgpgO9FxH8lrUONVlppJX/lyMysQWodZ2AcsCMwNiI2lrQm6Rrwpo0u0AwcVGRm1hHqrHEGcg/A+cCNpHsFLiPdKDZ8YYs0MzOz5mu3MRARIem7wDBgc9JNbEd21kBCZmZm1ly13jPwILBGRLR7/d3MzMy6l1obA5uRBg96ivRVMJE6DQY1rDIzMzPrErU2Bj7b0CrMzMysaWodgfCpRhfyYaUGpTcW9j+ANCTwDFKPzZvAQRExozP231GSxkVE1WGS87DWx0RETV8RePfZWTxzbL1jT5mZNd4qJ2/T/kqLuFoHHbKOK6U3LtfAY5TyGjYkDcv8w/IVJNUz0uJCa6shYGZmixY3BhqvEemNbVkGeDWvP1zS6JxdcGtOCbyucPxzJA3P009KOrGQZrhOnr+dUkrkJEkTJfWVdK6kXfPyq/MgRUg6WNLP8/SswnG+n/c5WVIpbKm0rIdSOmNNI1qamVnn69KzxRZ2LjBFhcjkrJTeeLdSLPRNwLrMS298innpjZeSRvH7vwr7X1PSJNJIgL1JN3yWbAwMioj/SRrWTp0v50Glvk0aBvob+d9DI2JsDpOaTRoZchtgNCnoqJRAuA3w5+IOJe0C7AZslkeuXLaweDHgMmBaRPy8vJhiUNHKy6xQvtjMzDqJewa6QES8TvowP6Js0U7AOfmDfDQLpjduSxoSeINiemOFQ5QuE6wJHEXqiSi5JedD1OKq/O8DwIA8PRb4laQjSCmRc3J920hajzRs8Qs5I6EUNV3+HC+OiLfya1Gs5bdUaQjkdT8IKlq2d/8an4KZmdXLjYGu01XpjaNJjYiSYuOhmOYI1RMdP0hzjIiTST0EvYCxktaJiGdJ8cU751rHAF8GZkXEGzXUWDIO2F5SeR1mZtaF3BjoIo1Kb6xga+DfVZY9BawnaUlJ/Ul5E22StGZETI2IU4DxQClc6F5SL0SpMXAMlRsrtwAH5TApyi4T/B64gRQq5UtWZmZN4v+Au1aj0htL9wyIFDX9jUorRcTTkv4CTAOeACbWUPNROer4fWA68I9CTZ+JiH/lwaiWpUJjICJuzI2cCZLeJX34/7Cw/FeS+gF/kLRfRLxfqYglVu7zofj6jpnZoqim1EKzZnNqoZlZ/WpNLfRlAjPEvKzjAAAeUUlEQVQzsxbnxoCZmVmLc2PAzMysxbkxYGZm1uLcGPiQkhSS/lh4vJikl4rDEXdgnzfkYZL751EK21t/2MIcz8zMuoa/Wvjh9SYwUFKviHgb+DTw7MLsMCI+Bx8kJX4bOG8ha6zZC4//i9P3+UJXHc7MrGbfuaL7n/O4Z+DD7Qbg83l6X+Dy0gJJm0q6J4cPjZO0dp4/XNJVkm6U9FgxTyGHGS0HnEwe20DSaTlQ6TRJ03Ig0T6FGpaRdL2kGZLOl9Qj7+s3kiZImi7pxEa/EGZmVp0bAx9ufwa+kof7HUQayKjkEWCbiNgIOAE4qbBsMLAPsAGwj6RVy/Z7LPPyEL4LfClvsyEpi+C0nFUAsClplMX1gDXzugDH5e++DgK2kzSoM56wmZnVz42BD7GImEIKHNqX1EtQ1A/4q6RpwBnA+oVlt0bEzIiYTQoiWq2dQ20NXB4RcyPiBeBOYJO87P6IeDwi5pJ6JrbO878s6UHSKIjrkxoL85E0IvceTHjznXdre9JmZlY3NwY+/EYDv6RwiSD7KXB7RAwEvsj8oUXvFKY/CC3qoPIhLkPS6qQsgx0jYhBwPQuGJs2XWrj0kkssRAlmZtYWNwY+/C4CToyIqWXz+zHvhsLhde7zDaBv4fEY0uWEnpKWJ6Um3p+XbSpp9XyvwD6kfIVlSDc4zpS0ArBLncc3M7NO5G8TfMhFxDPA2RUWnQpcIul40pl5Pft8RdLYfInhH8D3gC2AyaSegO9FxH8lrUNKOjwH+CRwO3B1RLwvaSLpvoWngbHtHXOFNT75obhj18xsUeSgIusWHFRkZlY/BxWZmZlZTdwYMDMza3FuDJiZmbU4NwbMzMxanBsDZmZmLc5fLewkkuYCUwGRBuo5LCLGVVl3XERsmQN/toyIP+X5Q4EDIuKIKtsNA46JiHYTeyQdA3wDmA28B/w6Ii5tY/078r4X+pZ9SbMiok+F+T8B7oqIf9a7zxefeoNzD7ltYUszsxZ26Pk7NLuERZYbA53n7YgYDCDps8AvgO2KK0haLCLmRMSWedYA4KvAnwDyB3FnfBgfQkop3DQiXpe0DLDHwu53YUXECc2uwczMFuTLBI2xDPAqpLN5SWMkjSaN84+kWXm9k4Ftcvrf0Xnd6/I62+X5k3KyYGnEvz6SrpT0iKTLJKnC8X8I/F9EvA4QEa9HxCV5vzvm/U2VdJGkJcs3LtSHpL0kjcrTo3La4L2SHs/1XiTp4dI6he3OyImEt+ZRCUvb75WnT5A0PicdXlDleZiZWRdwY6Dz9Mof3I8AF5LG/i/ZGDgyIj5Vts2xwJic/ndG2bJjgENzb8M2wNt5/kbAUaRgnzWArYob5V6AvhHxeHmBOb1wFLBPRGxA6hn6vzqf50dIow0eTco9KIUcbSBpcF5naWBCRKxPCi36cYX9nBMRm+RshF5Au5c+zMysMdwY6Dxv5w/1dYCdgUsLZ7v3R8QTde5vLPArSUcA/SNiTmFfz0TE+8Ak0qWGWq0NPBERj+bHl5ByBOpxbaRhK6cCL0TE1FzL9EIt7wNX5Ok/Mi+psGh7SfdJmgrswPypicD8qYWzZr9WZ5lmZlYrNwYaICLuAZYDls+z3uzAPk4m3QDYCxibx/mHdhIF86WBWZLWqPeYxd0UpsvTBEvHf7+slvfLa6myv1IPxXnAXrmH4ncVjjNfamGfpfrXUb6ZmdXDjYEGyB/cPYFX2lm1PP2vuI8181n3KaSwn3UqrVfFL4Bz8yUDJPWRdAAwAxgg6ZN5va+RuvHLvSBp3Zw02JEbD3sAe+Xpr5KSCotKH/wvS+pTWNfMzJrA3yboPL0kTcrTAg6MiLnt3Bc3BZgraTLpWv7EwrKjJG1POuOeTkoH3KLGWn4D9AHGS3qP9NXC0yNitqSDgL9KWozUyDi/wvbHAtcBL5G+3bDA1wTb8SYpuvh44EVSdPEHIuI1Sb8DpgH/zXW06WOr9fXXgszMGsSphdYtOLXQzKx+Ti00MzOzmrgxYGZm1uLcGDAzM2txbgyYmZm1ODcGzMzMWpy/WtggknYHrgbWjYhH8rwBzJ9SOIwaUwirHOOHEXFS4fG4QghSLdsfAHyPNCjQHOCyiPhlR2qp8XgjgVkdOcbsadN5eJ11O78oYN1HHm7Ifs3Mugv3DDTOvqTBdvYtzBtAGoSns/yw+KDOhsAupIyDz+RRADcHZnZibWZm1k24MdAAeVS9rYGvA18pLJovpbBsm00l3ZMTBcdJWjvPHy7pKkk3SnpM0ql5/snMC0e6LM8rpg1+PycTTs7rlvsBqVfiOYCIeCcifpe3/WZOFJws6W+Seuf5oySdnet7vJBA2CenEz6Yj7lboY7jJD0q6W5SNgJtHcPMzLqeGwONsRtwYw4EekXSkDy/rZTCR4BtImIj4ATgpMKywaRR/DYA9pG0akQcy7xwpP2KO8pn/bsBm0XEhsCpFWocCDxQpf6rcqLghsDDpEZNyYqkhs4XSI0bgNnAHhGxMbA9cLqSIaTG0GDgc8AmNR6j9Dw+CCr639w55YvNzKyT+J6BxtgXOCtP/zk/rvbBW9IPuETSWqRr+IsXlt0aETMBJD0ErAY83ca+dgIujoi3ACLif3XWP1DSz4D+pKGIbyosuyanFD4kaYU8T8BJkrYlDZ+8MrACKXr56lIdkkbXeAxy3RcAFwAMXKqXh8o0M2sQNwY6maRlSZG8G0gKUmBRSPpuO5v+FLg9IvbINxreUVjWZlJhB00HhgC3VVg2Ctg9IiZLGg4Mq1JLKXhhP1JC45CIeE/Sk1RIIazjGGZm1oV8maDz7QX8ISJWi4gBEbEq8ATpLLlqSiGpZ+DZPD28xmO9J2nxCvNvAQ4qXOtftsI6vwBOk/TxvM4Skr6Rl/UFns/73q/CtpVqfzE3BLYn9VwA3AXsLqmXpL7AFwvb1HsMMzNrEPcMdL59gVPK5v0tzz+C6imFp5IuExwPXF/jsS4Apkh6sHjfQETcKGkwMEHSu8ANLPjNgxtyN/8/laIVA7goL/4RcB8ptfA+qjdgSi4DrpU0lZRy+Eg+xoOSrgAmk9ILi+mEdR1jqYHrs66DiszMGsKphdYtOLXQzKx+Ti00MzOzmrgxYGZm1uLcGDAzM2txbgyYmZm1uC79NkEb4T3XRcTAhQ3u6Wy5nncjYlyV5TsDPwGWIY3CNwP4bkT8pxOOPRhYKSJuWMj9BCmAaP/8eDHgeeC+jrzOkvoDX42I8xamrrJ93kH6vVe9Q3D6K9PZ4JINOuuQ85l64NSG7NfMrLvo6p6BSuE9i7JhQMXwH0kDgV8DB0bEOhExmPQVuwEV1u1Io6s0hG/NqhznTdJof73y408zbzyDjugPfLuO45uZ2SKuyxoDbYT31LJtT0mn5WCbKZK+lefvkQNyJGnFHIjz8bz+LyVNy+sfntcfIulOSQ9IuknSinn+HZLOyqE/05RCgwYAhwBH5/nblJX1feCkiPgg/zYiRkfEXYV9nilpAnCkpOVzIM/4/LNVXm+BgCJJS5B6HPbJx95H0tKSLpJ0f153t7z9cEmjJd0G3FrlJbwB+Hye3he4vPDaLivpmvw63StpUJ4/Mh/vDqVQoiPyJicDa+a6TpM0TNKYPNTwQ3nb/XOdkyT9VlLPPP83SlkD0yWdWMdbwMzMGqgrz+Q+CO+R9IqkIRHR3nj9JV8HZkbEJpKWBMZKujkirpa0J3AosDPw44j4r6T/I52hD46IOfkDb3HSmfxuEfGSpH2AnwMH52P0jojBSuPrX5QvW5wPzIqIX1aoaX2g0vyiJUrf75T0J+CMiLhb0idIY/Gvy7yAojmSdiI1MPaUdAIwNCIOy9ufBNwWEQfnrvr7Jf0zH2djYFAbGQR/Bk6QdB0wiDS4UKlxcyIwMSJ2l7QDcCmpVwJgHVLwUF9ghqTfkMKWBuaekNKllI3zvCckrUsKVdoqj0h4HmmEwUuB4yLif7lxcKukQRExpZ3X0MzMGqwrGwMdCe8p+QwwSDkylzT87VqkYX4PB6YB90ZE6Yx3J+D8iJgDKagnd+sPBG6RBCkz4PnCMS7P694laZn8gVsTSR8lnZX3Bi4oNB6uKKy2E7BePjbAMrm3pK2AovLXYFdJx+THSwGfyNO3tBVGFBFTck/HvqRegqKtgT3zerdJ+qikZfKy6yPiHeAdSS+SwocquT8insjTO5IyD8bn59qLNPogwJcljSC971YE1gOqNgbyuiMAFv9otZfFzMwWVpc0BtTx8J4PdgEcHhELJNsBq5CS8laQ1CMn6lXbx/SI2KLK8vKhGNsbmnE66Yx4ckS8AgzOH9R9Cuu8WZjuAWweEbPnK0o6h+oBReX17xkRM8q236zsONWMJvVkDAM+WsP6UHtAUvH4Ai6JiB+U1bk6cAywSUS8KmkU7YQZFVMLe63u1EIzs0bpqnsG2grvqcVNwP/lrn4kfSpfQ1+M1OW9L/Aw8P/y+rcA38rLS42RGcDykrbI8xaXtH7hGPvk+VuTLknMpO1goVOB43K3eEnvNp7DzaReDPJxSl3x1QKKyo99E3C48um2pI3aOFYlFwEnRkT5rfNjyEFBucv/5Yh4vY39tPWaQOoh2UvSx/I+l5W0GukbF28CM5UyEXaps34zM2uQrrpM0FZ4T/n8Si4k3QPwYP4wfAnYHfgOMCZfh59M6pq+Pq//KVKIz3vA7yLinHyZ4WxJ/UjP/UzSGT7AbEkTSd30pfsIrgWuzDfrHR4RY0oFRcRUSUcCl+Zu9ZeB/wA/rvIcjgDOlTQlH/su0g2K1QKKbgeOlTSJlDD401zvFEk9SI2pmr8aGBHPAGdXWDQSuCjX9RZwYDv7eUXSWEnTgH+U1UxEPJSfy825zveAQyPi3vz6PgI8DYyttXaA9T+6PhMOdDaBmVkjOKiI2r7nbs3loCIzs/rJQUVmZmZWCw8SA0TEsGbXYGZm1izuGTAzM2txbgyYmZm1ODcGzMzMWpzvGbCGU1lapTqSVPncRBjZr9GlmlmzjZzZ7ApaknsGrCt0t7RKM7OW4saANZQWIq3SzMy6hhsD1mgfpFUCr0gaUuuGkkbkyOMJL73lwbHMzBrFjQFrtH1JKZUwL62yJhFxQUQMjYihy/dW+xuYmVmH+AZCa5hqaZXAuU0tzMzM5uOeAWukammVqza5LjMzK3DPgDVStbTKH9S9p5U2gpEOKjIzawQ3BqxhImL7CvPOphClHBF3AHd0XVVmZlbOlwnMzMxanBsDZmZmLc6NATMzsxbnxoCZmVmLc2PAkLS7pJC0Tn48QNK0PD1c0jkLuf+jJPXujFrNzKzz+dsEBvMHCf24M3csqSdwFPBH4K2O7mfqszMZcOz1nVaXmXXckyd/vtklWCdzz0CLqzFIaFVJd0h6TNKPC9vuL+l+SZMk/TZ/8CNplqTTJU0GjgNWAm6XdHte/pucOTBd0okNfYJmZtYuNwasliChTYE9gUHA3pKGSloX2AfYKiIGA3OB/fL6SwP3RcSGEfET4Dlg+8K4A8dFxNC8v+0kDWrYszMzs3b5MoHtC5yVp0tBQuX3CNwSEa8ASLqK1JMwBxgCjJcE0At4Ma8/lzTSYDVfljSC9P5bEVgPmFK+Ul5nBEDPZZav93mZmVmN3BhoYXUECZXnBwcg4JKIqDS08OyImFvlmKsDxwCbRMSrkkYBS1VaNyIuAC4AWHLFtZxhbGbWIL5M0NpqDRL6tKRlJfUCdgfGArcCe0n6GKSGhaTVqhznDaBvnl4GeBOYKWkFYJfOfUpmZlYv9wy0tlqDhO7P81cB/hgREwAkHQ/cLKkH8B5wKPBUheNcANwo6bmI2F7SROAR4GlSw6JdG6zcjwm+g9nMrCEU4d5XW/QNHTo0JkxwaqGZWT0kPZBv2G6TLxOYmZm1ODcGzMzMWpwvE1i3IOkNYEaz6+iA5YCXm11EnbpjzdA96+6ONYPr7koLW/NqEdHud7N9A6F1FzNque61qJE0obvV3R1rhu5Zd3esGVx3V+qqmn2ZwMzMrMW5MWBmZtbi3Biw7uKCZhfQQd2x7u5YM3TPurtjzeC6u1KX1OwbCM3MzFqcewbMzMxanBsDtsiTtLOkGZL+JenYZtfTHkmrSrpd0kOSpks6stk11UNST0kTJV3X7FpqIam/pCslPSLpYUlbNLumWkg6Or8/pkm6XFLFwK5mk3SRpBclTSvMW1bSLZIey/9+pJk1lqtS82n5PTJF0tWS+jezxkoq1V1Y9h1JIWm5RhzbjQFbpEnqSUpR3IUUdbyvpPWaW1W75gDfiYj1gM2BQ7tBzUVHAg83u4g6nAXcGBHrABvSDWqXtDJwBDA0IgaSEkO/0tyqqhoF7Fw271jg1ohYixRatqg10kexYM23AAMjYhDwKAtmsCwKRrFg3UhaFfgM8J9GHdiNAVvUbQr8KyIej4h3gT8DuzW5pjZFxPMR8WCefoP04bRyc6uqjaRVgM8DFza7llpI6gdsC/weICLejYjXmltVzRYDeklaDOgNPNfkeiqKiLuA/5XN3g24JE9fQkozXWRUqjkibo6IOfnhvaTgtUVKldca4AzgeywYJ99p3BiwRd3KpHTDkmfoJh+sAJIGABsB9zW3kpqdSfpP5/1mF1Kj1YGXgIvzpY0LJS3d7KLaExHPAr8knek9D8yMiJubW1VdVoiI5/P0f4EVmllMBxwM/KPZRdRC0m7AsxExuZHHcWPArEEk9SFFPx8VEa83u572SPoC8GJEPNDsWuqwGLAx8JuI2Ah4k0Wvy3oB+Rr7bqTGzErA0pL2b25VHRPpK2nd5mtpko4jXcq7rNm1tEdSb+CHwAmNPpYbA7aoexZYtfB4lTxvkSZpcVJD4LKIuKrZ9dRoK2BXSU+SLsfsIOmPzS2pXc8Az0REqeflSlLjYFG3E/BERLwUEe8BVwFbNrmmerwgaUWA/O+LTa6nJpKGA18A9ovu8b36NUkNxsn573IV4EFJH+/sA7kxYIu68cBaklaXtATpJqvRTa6pTZJEuob9cET8qtn11CoifhARq0TEANLrfFtELNJnqxHxX+BpSWvnWTsCDzWxpFr9B9hcUu/8ftmRbnDjY8Fo4MA8fSDw9ybWUhNJO5Muge0aEW81u55aRMTUiPhYRAzIf5fPABvn932ncmPAFmn5hp/DgJtI/1n+JSKmN7eqdm0FfI10Zj0p/3yu2UV9iB0OXCZpCjAYOKnJ9bQr92RcCTwITCX9X7xIjo4n6XLgHmBtSc9I+jpwMvBpSY+RejlObmaN5arUfA7QF7gl/02e39QiK6hSd9ccu3v0lJiZmVmjuGfAzMysxbkxYGZm1uLcGDAzM2txbgyYmZm1ODcGzMzMWpwbA2btyElhpxceHyNpZCfte5SkvTpjX+0cZ++c6Hd7J+xr165Ij5Q0IqfMPSLpfklb17DNQj/PrvqdWPckaaSkY+rcZlaj6uksbgyYte8d4EuNig7tqBxwU6uvA9+MiO0X9rgRMToiGvq98jw08reArXMa4SHAn2oYea2u51nna7jQ29n8OvN1zAmnnaqVfs9uDJi1bw5pQJijyxeUn0WWzgAkDZN0p6S/S3pc0smS9stnuFMlrVnYzU6SJkh6NH8IIqlnzl8fn/PXv1XY7xhJo6kw0p6kffP+p0k6Jc87Adga+L2k08rWHybpusLjc/KQrUh6UtKJkh7M+1wnzx8u6Zw8vbqke/Lyn5U9/2r7HZJfmwck3VQa1rbM94HvRsTLADkF8hJSHHQ/STNKow5KulzSN8ufp6SlJF2ca5soaftC/aMl3QbcquScvM9/Ah+rUA+S7pB0pqQJwJGSlpf0t/w7Gi9pq7zedpo32NRESX3z63GXpOvzcc6X1KPa76z0XpL0c0mTJd0raYU8f++87mRJd7X1fimrf4BSL8uo/F67TNJOksZKekzSpnm9pSVdlN+rE5WCckrbj8nvhwclbZnnr5if26Rc1zal+gvH3kvSqDw9Kj//+4BT2zje+nnepPyc1qrwnGZJOl3SZGCLau8tSZ+U9M/8mj0oac38ez8t1zxV0j6F9+58f2OSjsuv2d3A2oXjrynpxny8MZr3N7K6Cn8Xld5Pi5yI8I9//NPGDzALWAZ4EugHHAOMzMtGAXsV183/DgNeA1YEliTlKZyYlx0JnFnY/kZSw3wt0nCjSwEjgOPzOksCE0hjlA8jhfGsXqHOlUjD3C5PCvC5Ddg9L7sDGFphm2HAdYXH5wDD8/STwOF5+tvAhXl6OHBOnh4NHJCnDy17/gvsF1gcGAcsn+fvA1xUoa7/Af3K5u0GXJWnP00aqe0rwI2FdT54nsB3SvsG1smvzVK5jmeAZfOyL5Gy7nvm1/C14u+0bN/nFR7/idRzAfAJ0vDTANcCW+XpPvl3MQyYDayRj3MLsFc7v7MAvpinTy28H6YCK+fp/vnfiu+XsvoHkBq2G5Debw8AFwHKr+01eb2TgP1L+wceBZYmxSwvleevBUwovM7H5emeQN/i30Ke3gsYVXjPXwf0bOd4vyZlCAAsAfSq8DsJ4Mt5uup7i5QaukeeXio/lz0Lv/cV8u9hRcr+xoAh+TXvTfp/4F/AMXnZrcBaeXoz0hDeUOXvYlH+aZkuELOFERGvS7oUOAJ4u8bNxkeOeZX0b6AUUTsVKHZj/yUi3gcek/Q46YPrM8Agzet16Ef6D/hd4P6IeKLC8TYB7oiIl/IxLwO2Ba6psd5KSiFLD5A+NMttRfpPFeAPwCkV1ilaGxhIGhIW0n/Ez7e5RQURcYukvYFzgQ2rrLY16QOFiHhE0lPAp/KyWyKilBu/LXB5RMwFnlPqMajmisL0TsB6+XkALKOUVDkW+FV+/a+KiGfyOvdHxOPwwbCzWwPvUf139i7pQxPS6//pPD0WGCXpL8z7/VR7v5S/T56IiKn5WNOBWyMiJE0lNRZK+9pV866LL0Vq7DwHnCNpMDCXea/leOAipXCuayJiUhuvX8lf8+vd1vHuAY6TtEp+HR+rsJ+5pEAwqPLektSX1Hi6GiAiZufnvzXzfu8vSLqT9Df0OvP/jW0DXB05zyD3GJRSSbcE/lp4DyyZ/63376Lp3Bgwq92ZpLHkLy7Mm0O+3Ja7fZcoLHunMP1+4fH7zP+3Vz4meJDO1g6PiJuKCyQNI521dJYP6s+WKlteqnku1f+/qDSmebX9CpgeEVu0U9dDpDOy4gfzEGA6fPBarwu8BXyEdKZfj46+hsXtegCblz5cCk6WdD3wOWCspM/m+ZV+z215L/KpJYXXPyIOkbQZ8HngAUlDqPJ+qaCW96SAPSNiRnFDpZtmXyA1vnqQejqIiLskbZvrGSXpVxFxadnzK39fFV/HiscDHs6XEj4P3CDpWxFR3lCbXWhUVHxv5cZAvWp5f/QAXouIwVWWd6ux/n3PgFmN8pnkX0g3qZU8SfqQAtiV1FVZr70l9VC6j2ANYAYpmOn/8tkWkj4lael29nM/sJ2k5ZRuptoXuLOdbZ4ind0uKak/KT2vHmNJXfUA+9Ww3xnA8pK2gBT1LGn9Cvs9FThF0kfzeoNJ3fvn5eVHk4KrvgpcXHqdyowp1STpU6SzzfIPHIC7gH2UrruvyPy9Nm25mRSSRKFGJK0ZKW3uFNJZ8zp5lU3zteQepC7su+nA7yzv/76IOAF4iRTx3ZH3SzU3AYcrn+5K2ijP7wc8n3uxvkY680bSasALEfE74ELmRUi/IGnd/Hz3qPd4ktYAHo+Is0mpiIPaqbvieysi3gCekbR7nr+kpN6k90fp9748qUfm/gr7vQvYXVKv3LD4IqTeQuCJ3ENFvgeh1EtV7e9ikeXGgFl9TgeK3yr4Hek/88nAFnTsjPM/pP+E/gEcks80LySdHT8oaRrwW9rpycuXJI4FbgcmAw9ERJvRshHxNKmBMy3/O7HO2o8k3dQ3FVi5vf1GxLuk68en5NdsEqmrtbyu0aTr2eMkPUJ6nfePiOeVbhz8BvCdiBhD+s/6+Aq1nQf0yLVdQboX4p0K610NPEZ6vS8ldU/X4ghgqNLNbQ+RvvEAcJTSTWlTSJcB/pHnjyfdO/Ewqfv+6o78zoDT8o1p00jXyCfTgfdLG35KatROyZcSfprnnwccmH9v6zDvvT4MmCxpIqmRc1aefyzpMsc42r4UVO14XwamSZpE6v6/tK2i23lvfQ04Iv9OxgH/v707OEEgBqIA+vduARZlBx5tQezJCrxZhGAn3mcPWW/rTdiFee8cyJAQ+EwCOWbs+ytj/Z5JbrXyNXCNx6v3ZdwjYx+/zkkuy3zvjLcXyY9zsWd+LQT+ZpqmT1Udtq5jb5brnWtVnbauBdboDABAczoDANCczgAANCcMAEBzwgAANCcMAEBzwgAANCcMAEBzMxMSuW9adbLQAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_df[full_df['subregion'].isna()].groupby(by=['region'])['oxford_government_response_category'].nunique().plot.barh()\n",
    "plt.xlabel('Number of unique Oxford response measures recorded')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,0,'Oxford Fiscal Measure (CAD) recorded')"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1474i6VjgblJmxpsj4m8t7bPJqj0Z61f2zMwawlkLbaHgrIVmZvVz1kIzMzOriYMBMzOzJudgwMzMrMk5GDAzM2tyDgaahKSQdHrh89GSTuzEJpXaMVjSNp3dDjOzZuZgoHl8AHxJ0oqd3ZAygwEHA2ZmncjBQPOYSZof4KjyDZKGS9q78Pmd/O/gnFzor5Iel3RlznSIpBMkjcmJhi5Usr6khwv19JE0KS8/VwpEJA3M9fYBDgGOyomPtm/c6ZuZWTUOBprLOcB+kuqZ23cz4EhgQ2BtYNu8/uyIGBQRGwNdgd0j4nFgSUlr5TL7AtdWqzgingPOB86IiP4RMaquszEzs3bhYKCJRMRbwOXAEXXs9nBEvBgRHwPjgT55/RBJD+U7/51IGRAB/kwKAqCVYKA1xURF06ZNa2s1ZmbWCgcDzef3wDdJ6YVLZpL/FiQtBixZ2DZPsiJJSwPnAntHxCbARcxJTnQt8BVJ65FmPH6q/BiFsi0qJirq3bt3rednZmZ1cjDQZCLif6S7928WVj/HnOyFXwSWoGWli/lrkroDs8cbRMTTpKDhp8zdK1A8xpcL698GetR8AmZm1u4cDDSn04HiWwUXkbIITgC2Bt5taeeIeDPvMxm4DRhTVuRaYH9S0FFyEnCmpLGkYKHk78BeHkBoZtZ5nKjIFgpOVGRmVj8nKjIzM7OaOBgwMzNrcg4GzMzMmpyDATMzsybnYMDMzKzJORhYCHR0xkFJK0m6SdIESVMl3dLGeoZJWqXw+WJJG7alrglvv8cn7x7PJ+8e35bdzcysBQ4GFg4dnXHw58AdEbFpRGwIHNvGeoYBs4OBiPhWRExth/aZmVk7cjCwcGgp42AfSXdJmijpTklrSOop6fk8tTCSlpH0gqQlJH07ZxucIOk6Sd0qHG9l4MXSh4iYWDjejyRNyvufktf1l/RgbsMNkpbLWRAHAlfmCYW65kyFA/M+5+W8A1MkndSeX5aZmdXHwcDCo1rGwT8Al0VEP+BK4KyImE5KKrRjLrM7cFtEfARcn7MNbgo8xtzTEheP9UdJd0s6rtTVL2k3YA9gy7z/qbn85cCPchsmAT+LiL8CY4H9ckbC98uOcVyeCKMfafbDfm37WszMbH45GFhItJBxcGvgqrz8J2C7vHwtc7IHfpU5eQI2ljQqZxvcjznZBovHuo2UrvgiYH1gnKTewC7ApRHxXi73vxyc9IqIe/LulwE71HBKX5H0KDAut2GesQTFrIUfT3+zhirNzKwtHAwsXCplHKxmBLCrpOVJCYLuyuuHA4flbIMnUSWDYET8LyKuioivk3IP1HKBr4mktYCjgZ1zb8LNldpRzFq4WM9e7XV4MzMr42BgIVIl4+D9pDt/SHf6o3LZd0gX8TOBmyKilByoB/CKpCVy+XlI2qk0lkBSD6Av8G/gDuDAwrbl8yOJNwpJhr4OlHoJqmUkXJaUDGm6pJWA3Wr+EszMrN0t3tkNsLqdDhxW+Hw4cKmkY4BpwIGFbdcCfwEGF9b9FHgol32IyhfrAcDZkmaSAsaLI2IMpMGCwFhJHwK3AD8BvgGcn4OEZwptGJ7Xv096nAFAREyQNA54HHgBGN3aSW/aoxtjh/RvrZiZmbWBsxbaQsFZC83M6ueshWZmZlYTBwNmZmZNrqZgQNKXJD0labqktyS9LemtRjfOzMzMGq/WAYSnAl+IiMca2RgzMzPreLU+JvivAwEzM7NFU63BwFhJ10oamh8ZfEnSlxrasnbWHpn/JA2WtE3h8/A8B39DlWf/K6w/J8/7P1XS+3l5/Py0SdKWks7IyztJ2qoNdeyVX3VsN2+/Pak9qzMzs4JaHxMsC7wHfKawLoDr271FjVPK/PfriHit3p0lLU56X/8d0kQ/HWkYMBl4ubgyIg7NbetDmliorhfxJS0eETPLPj9Emn8AYCfgNeDBOuu8oZ52mJlZ56opGIiIA1svtcArZv47rrghX0wvAVYkT9wTEf+WNByYAWwGvARsA8yStD9psh+AHST9H/BJ4IcR8VdJ55ASA42QdAPwRkQcJOkgoG9EHJfrOAJYknTx/V6u74+kbH+R2/QCc7L/vQ9sXSHpzzwkrQucnc/pXeBbEfGkpCtIMwMOAEbmyYPWIM0y+Gw+58OAHwDfyuc7LLfvldymFYD/5u/pxQp1PglsHBFH5hkGz8vH+Bg4IiIelLQTcEY+z4+B7SPi3dbOy8zM2l+tbxOsllPTvpp/rpO0WqMb1wA1Z/4rbFsN2CYivgScD5yRs/CNyttXJiUH2h04Ja8bBZSm512VOUl4tgfulbQBKYnQtvlufhZpauD+wKoRsXHOHXBpDdn/qrkQ+F5EDAB+TAoMSlYGtoqIH+bP65PyBOxfKhARTwMXA6fl494PnEuajbAfaWbD37dQZ8lZwKl50ouv5DoBjgEOzue/AynomksxUdGbb35c42mbmVm9ah0zcCkp8c0q+efved1CpQ2Z/wD+UpjXv5IbI+LjiJgKrJTXjQK2l7QhMBX4r6SV83HuB3Ym3UWPkTQ+f16bNJXv2pL+IGlXoE2vb0rqBWwFXJfrP4f0eyueU/Hq+reImOdiXMGWwDV5+XLmBDyV6izZhTQl8XjgRmA5SV1JUxCfKelwYNlK33ExUVGvXp4Sw8ysUWodM9A7IooX/+GSjmxEgzrA74FHqT2Yaa3r+oPCsgAi4qV8Qd4VuBdYnnRX/E5EvC1JpJ6IH5dXJmlT4LPAIXmfg2ps51zVAK+1MIag/Jzao3u+Wh0CtoiID8vW/1LSCODzwIOSdo6Ip9qhHWZmVqdab7del7S/pC75Z3/g9UY2rFHqyfxXQbUsfJU8CBxJCgZGkVL2luq9E9hb0icgZf+TtKakFYHFIuI64Hhg8zYcl4h4g5SZcK9c/2I5yKhX+XEfJAUoAPvnc2vNP4FDSx9yoiMk9Y2IiRHxa1Jw9qk2tM/MzNpBrcHAQaSLwH9Ig8j2Zu7seAub00kD60oOJ6XmnUhKwfv9Kvv9Hdgrv763fZUyJaOAxSPiX6SL3fLMSS88lXSxvz0f8w7SM/dVSQPwxgNXkJ71w5zsf+NzF3stvgocImkCMIU0pqFefwO+ImlcfqXyUODg3OZ9SYMxW3MosK2kiZKmAt/O64+WNDnX9Q5we0uV9OixSRuab2ZmtXDWQlsoOGuhmVn9as1a2OKYAUk/jIhTJf2B9ArYXCKifCCemZmZLWRaG0BYmoLYt2RmZmaLqBaDgYj4e/73so5pjpmZmXW0ml4tlPR35n1MMJ3UY3BBje+om5mZ2QKo1rcJniGN+L4o/7xFeu1svfx5Hu2RGKhKvVfnkem1jGRv6zGGSTo7L58o6eh2qrchiY2q1VvP8ST1kTS5ndv1TnvV9fLLL7deyMzM2qTWSYe2iYhBhc9/lzQmIgZJmlJln/lKDFSJpE8CgyJinfaoz+onqUsrMzK2td65kiaZmVnHqbVnoLukNUof8nL3/LF8ZrmSYmKguUjqnfMbjMk/2+b1kyT1UvK6pAPy+sslfZr0Lvqqpff8JfWX9GDuKbhB0nK5/EhJA/PyipKey8vDJF0v6VZJT0k6tdCmAyU9KelhYNtKJyTp27m9E3L7u+X1wyWdJel+Sc+U7sbzeZwt6QlJ/wQ+0ZH1VjlWd0l3Sno0f997FDYvLulKSY9J+muhHc9J+o2kR4F9WmjvWpIeyPX+snBMSTpNaV6BSZL2zesHSxqlNBPh1FrPwczM2letwcAPgPsk3S1pJHlGPUnLAC0NLqyWGOhMUsKfQcCXmZO8ZjTpQrwR6dFEaWKf0pz+XwSeLiQKuhz4UU6cMwn4WQ3n0p80Yc4mwL6SVlfKG3BSPvZ2zEksVO76iBgUEZuS3rQozmJYKWHRXqSZ9TYEDiBlPezIeiuZAewVEZsDQ4DTJSlv+xRwbkRsQHoU9L3Cfq9HxOYRcU0L7T0TOC8nWXqlsO+XSN/7pqRcBafl7xzSLIvfj4j16jgHMzNrR7WmML5FKSXu+nnVE4VBg7+vshsR8ZakUmKgYra9XYAN51yDWFZSd1KQsQPwPCnt7cGSViWlAH5XUu/SDjnA6BUR9+RVl5Ey6bXmzoiYnuuYCqxJmo1wZERMy+uvJY2HKLdxvuPtReoZua2w7cacqGeqUtpe8rlcnbvVX5Z0V5U2NareSgScLGkHUurgVZmTYOmFiBidl68g/d5+mz9fW0N7tyUFd5ASPv0mL29XaO9/Jd0DDCIFHA9HxLMVGyodDBwM0LNneTxpZmbtpdYUxt1IKWcPi4gJwOqSap3e9vekO8dlyo67Vb7D7x8Rq0bEO6S57rfPPyOBaaSpj6vlCqhmJnPObemybcXEQrOofdwEpGmBD8t3vieV1T1PwqIFoN5K9gN6AwNyIqP/Fo5X/sZI8XMxEVFL7a13SsuqSZKKWQu7detWZ7VmZlarelIYf0jqrgd4Cfhl9eJzVEkMdDspHwAwJ3lNRLxAuktfNyKeAe4jJfiZJyFOvrt/Q3NyBHwdKPUSPEdKEQwpmGjNQ8COklaQtASwT5VyPUgJgJYgXVRbcy/pUUSX3C0+pIPrraQn8GpEfCRpCKlnpGQNSaXf8ddI33897R3N3AmfSkYV2tub1LPxcB1tNjOzBqo1GOgbEacCHwFExHvUd5danhjoCGCg5iSvOaSw7SHgybw8itSNXe2i9A3S8+eJpGfSP8/rfwt8V9K4suNWFBGvACcCD5AuaI9VKfrT3L7RwOOt1QvcADxFGhx3ea6/I+sFuEDSi/nnAeBK0nc/iTTeoHi8J4BDJT0GLEd6VFNPe7+f959E+r0V2zsRmADcBfwwIv5Tw3nOtsoqq9RT3MzM6lBToiJJ9wM7A6MjYnNJfUnPgLdodAPNwImKzMzaQu2RqChXJOB84FbSWIErSQPFhs1vI83MzKzztRoMRERIOgYYDGxFejzw/faaSMjMzMw6V60j6R8F1o6ImxvZGDMzM+t4tQYDW5ImD3qe9CqYSJ0G/RrWMjMzM+sQtQYDn21oK8zMzKzT1PRqYUQ8X+mn0Y1bFKhB2RsL9fWR9L5SvoYJOY/Bp9qr/vlo1/2tbJ+dP6IWH77UbgkQzcysTK3zDFjblbI3tjrfwXwo5WvYlDQt80/KC0iqZ6bF+RYR9eRLMDOzTuRgoPEakb2xJcsCb+TywySNyLkL7sxZAm8qHP9sScPy8nOSTtKcbIbr5/U75l6H8ZLGSeoh6RxJX8zbb5B0SV4+SNKv8vI7heP8KNc5QVIp2VJp22JK2RlrmtHSzMzaX4feLTaxc4CJKqRMzkrZG+9TSgt9G7ABc7I3Ps+c7I2Xk6aD/m6F+vtKGk+aJrgbacBnyeZAv4j4n6TBrbTztTyp1PdI00B/K/97aESMzsmkZpBmhtweGEGaabCUgXB74JpihZJ2A/YAtoyI9yQtX9i8OGlGxMkR8avyxhQTFa267Erlm83MrJ24Z6ADRMRbpIv5EWWbdgHOzhfyEcybvXEH0pTAmxSzN1Y4ROkxQV/gSFJPRMkdOT9ELa7P/z4C9MnLo4HfSTqClCVyZm7f9pI2JE2J/N+cI6GUarr8HC/NU1hT1pYLqBII5LKzExUt361XjadgZmb1cjDQcToqe+MIUhBRUgweitkcoXpGx9nZHCPiFFIPQVdgtKT1I+IlUvriXXNbRwFfAd6JiLdraGPJ/cAQSeXtMDOzDuRgoIM0KntjBdsBT1fZ9jywoaSlJPUi5ZtokaS+ETEpIn4DjAHWz5seJPVClIKBo6kcrNwBHJjTYFP2mOCPwC3Anzt6gKOZmc3hYKBjNSp7Y9/Sq4XAyaQ7+XnkIOPPwOT877ga2nykpMk5M+RHwD8KbVo8Iv5FmqFyeSoEAxFxK6m3Ymx+HHJ02fbf5Xb8SVLVv8clV+1eQ1PNzKwtaspaaNbZnLXQzKx+tWYtdM+AmZlZk3MwYGZm1uQcDJiZmTU5BwNmZmZNzsHAIionSLqi8HlxSdOK0xG3oc5b8jTJvfIsha2VHzw/xzMzs47hd7sXXe8CG0vqGhHvA58GXpqfCiPic5AyJQLfA86dzzbW7L/P/IvT99291XI/uNaxh5lZvdwzsGi7Bfh8Xh4KXF3aIGkLSQ/k5EOz0x7x5MM0AAAc/0lEQVTn5EbXS7pV0lPFfAo5mdGKwCnMmdvgtJxQ6bQ8H8EkSfsW2rCspJslPSHp/NJcApLOkzRW0hRJJzX6izAzs+ocDCzargG+mqf77UeayKjkcWD7iNgMOIE0WVFJf2BfYBNgX0mrl9V7LHPyIRwDfCnvsykpF8FpOVcBwBakWRY3BPrmsgDH5Xdf+wE7SurXHidsZmb1czCwCIuIiaSEQ0NJvQRFPYG/SJoMnAFsVNh2Z0RMj4gZpEREa7ZyqO2AqyNiVkT8F7gHGJS3PRwRz0TELFLPxHZ5/VckPUqafXAjUrAwF0kH596Dse9+8GFtJ21mZnVzMLDoGwH8lsIjguwXwN0RsTHwBeZOWvRBYXl20qI2Kp/iMiStRZqWeOeI6AfczLxJk+bKWrjMUkvORxPMzKwlDgYWfZcAJ0XEpLL1PZkzoHBYnXW+DfQofB5FepzQRVJvUtbEh/O2LSStlccK7EvKr7AsaYDjdEkrAbvVeXwzM2tHfptgERcRLwJnVdh0KnCZpONJd+b11Pm6pNH5EcM/gB8CWwMTSD0BP4yI/0han5Tp8GxgHeBu4IaI+FjSONK4hReA0a0dc6W11/GbAmZmDeJERbZQcKIiM7P6OVGRmZmZ1cTBgJmZWZNzMGBmZtbkHAyYmZk1OQcDZmZmTc6vFrYTSbOASYBIE/UcFhH3Vyl7f0RskxP+bBMRV+X1A4EDIuKIKvsNBo6OiFYz9kg6GvgWMAP4CPhDRFzeQvmRue75HrIv6Z2I6F5h/c+BeyPin/XW+erzb3POIXfNb9NadOj5OzW0fjOzBZWDgfbzfkT0B5D0WeDXwI7FApIWj4iZEbFNXtUH+BpwFUC+ELfHxfgQUpbCLSLiLUnLAnvNb73zKyJO6Ow2mJnZvPyYoDGWBd6AdDcvaZSkEaR5/pH0Ti53CrB9zv53VC57Uy6zY14/PmcWLM34113SXyU9LulKSapw/J8A342ItwAi4q2IuCzXu3Oub5KkSyQtVb5zoX1I2lvS8Lw8PGcbfFDSM7m9l0h6rFSmsN8ZOSPhnXlWwtL+e+flEySNyZkOL6xyHmZm1gEcDLSfrvnC/ThwMWnu/5LNge9HxHpl+xwLjMrZ/84o23Y0cGjubdgeeD+v3ww4kpTYZ21g2+JOuRegR0Q8U97AnL1wOLBvRGxC6hn6bp3nuRxptsGjSHkPSkmONpHUP5dZBhgbERuRkhb9rEI9Z0fEoJwboSvQ6qMPMzNrDAcD7ef9fFFfH9gVuLxwt/twRDxbZ32jgd9JOgLoFREzC3W9GBEfA+NJjxpq9Sng2Yh4Mn++jJRHoB5/jzRt5STgvxExKbdlSqEtHwPX5uUrmJOpsGiIpIckTQJ2Yu6sicDcWQvfmfFmnc00M7NaORhogIh4AFgR6J1XvduGOk4hDQDsCozO8/xDKxkF86OBdyStXe8xi9UUlsuzCZaO/3FZWz4ub0uV+ko9FOcCe+ceiosqHGeurIXdl+5VR/PNzKweDgYaIF+4uwCvt1K0PPtfsY6++a77N6RkP+tXKlfFr4Fz8iMDJHWXdADwBNBH0jq53NdJ3fjl/itpg5xpsC0DDxcD9s7LXyNlKiwqXfhfk9S9UNbMzDqB3yZoP10ljc/LAr4REbNaGRc3EZglaQLpWf64wrYjJQ0h3XFPIWUH3LrGtpwHdAfGSPqI9Grh6RExQ9KBwF8kLU4KMs6vsP+xwE3ANNLbDfO8JtiKd0mpi48HXiWlLp4tIt6UdBEwGfhPbkeLPrFmD7/6Z2bWIM5aaAsFZy00M6ufsxaamZlZTRwMmJmZNTkHA2ZmZk3OwYCZmVmTczBgZmbW5BwMNIikPSVFYbIgJPWR9LXC59m5CNp4jJ+Ufa6YJbGF/Q/IuQEm5XwFR7e1LTUe78RGH8PMzOrnYKBxhpIm2xlaWNeHNAlPe5krGChkQ2yVpN1IOQ4+k2cB3AqY3o5tMzOzhYSDgQbIs+ptB3wT+Gph01xZCsv22ULSA/kO/X5Jn8rrh0m6XtKtkp6SdGpefwpzkiNdmdcVsw3+KN/xT8hly/0YODoiXgaIiA8i4qK877dzRsEJkq6T1C2vHy7prNy+ZwoZCLvn7ISP5mPuUWjHcZKelHQfKTcCLR3DzMw6noOBxtgDuDUnBHpd0oC8vqUshY8D20fEZsAJwMmFbf1Js/htAuwrafWIOJY5yZH2K1aU7/r3ALaMiE2BUyu0cWPgkSrtvz5nFNwUeIwU1JSsTAp0dicFNwAzgL0iYnNgCHC6kgGkYKg/8DlgUI3HKJ3H7ERF06ZNq9JUMzObX56OuDGGAmfm5Wvy52oX3pKewGWS1iUl9lmisO3OiJgOIGkqsCbwQgt17QJcGhHvAUTE/+ps/8aSfgn0Ik1FfFth2405S+FUSSvldQJOlrQDafrkVYGVSKmXbyi1Q9KIGo9BbveFwIWQZiCs8xzMzKxGDgbamaTlSSl5N5EUpIRFIemYVnb9BXB3ROwlqQ8wsrCtxUyFbTQFGADcVWHbcGDPiJggaRgwuEpbSokX9iNlaBwQER9Jeo4KWQjrOIaZmXUgPyZof3sDf4qINSOiT0SsDjxLukuumqWQ1DPwUl4eVuOxPpK0RIX1dwAHFp71L1+hzK+B0yR9MpdZUtK38rYewCu57v0q7Fup7a/mQGAIqecC4F5gT0ldJfUAvlDYp95jmJlZgzgYaH9DgRvK1l2X18/OUlg+gJD0XP/XksZR+53/hcDE0gDCkoi4FRgBjM2ZFOd5nS8ibgHOBv4paQrwKLBs3vxT4CFgNGksQ2uuBAZKmgQcUNonIh4FrgUmkLIuFrMT1nsMMzNrEGcttIWCsxaamdXPWQvNzMysJg4GzMzMmpyDATMzsybnYMDMzKzJdWgw0ELynsl5eb4S97S33J6q8/1L2lXSw5Iez9MCXytpjXY6dn9Jn2uHekLSFYXPi0ua1tbvWVIvSd+b33aV1TlSUqsDXMzMrDE6umegUvKeBdlgoGIwIGlj4A/ANyJi/YjoT3rFrk+Fsm2ZJKg0hW/NqhznXdJsf13z508zZz6DtugFVAwG2nieZmbWyTosGGgheU8t+3aRdFpObDNR0nfy+r1yghxJWjknxPlkLv9bpfS8EyUdnssPkHSPpEck3SZp5bx+pKQz8939ZKWkQX2AQ4Cj8vrty5r1I+DkiHistCIiRkTEvYU6fy9pLPB9Sb1zQp4x+WfbXG6eBEWSlgR+TspDMF7SvpKWkXRJ7okYp5wMSCmR0QhJdwF3VvkKbwE+n5eHAlcXvtvlJd2Yv6cHJfXL60/MxxuplJToiLzLKUDf3K7Tcu/JKKWphqfmfffP7Rwv6QJJXfL685RyDUyRdFIdfwJmZtZAHXknNzt5j6TXJQ2IiNbm6y/5JjA9IgZJWgoYLen2iLhB0peBQ4FdgZ9FxH8kfZd0h94/ImbmC94SpDv5PSJimqR9gV8BB+VjdIuI/krz618SERtLOh94JyJ+W6FNGwGV1hctWXq/U9JVwBkRcV9+lHAbsAFzEhTNlLQLKcD4sqQTgIERcVje/2Tgrog4SFIv4GFJ/8zH2Rzo10IOgmuAE/KjgX7AJaQZEQFOAsZFxJ6SdgIuJ/VKAKxPSjzUA3hC0nmkZEsb554QJA3Ox984Ip6VtAEpqdK2eUbCc0kzDF4OHBcR/8vBwZ2S+kXExFa+QzMza7CODAbakryn5DNAP+WUuaTpb9clTfN7ODAZeDAiSne8uwDnR8RMSIl6crf+xsAdkiDlDHilcIyrc9l7JS2bL7g1kbQC6a68G3BhIXi4tlBsF2DDfGyAZXNvSUsJisq/gy9KKs0muDRQGp9wR0vJiCJiYu7pGErqJSjaDvhyLneXpBUklWYivDkiPgA+kPQqKflQJQ9HxLN5eWdSzoMx+Vy7Aq/mbV+RdDDp725lYEPSrIwV5bIHA6yxRrsMxTAzswo6JBhQ25P3zK4CODwi5slsB6xGypS3kqTFcka9anVMiYitq2wvn4qxtakZp5DuiCdExOtA/3yh7l4o825heTFgq4iYMVejpLOpnqCovP1fjognyvbfsuw41Ywg9WQMBlaooTzUniCpeHwBl0XEj8vauRZpWuRBEfGGpOG0kszIWQvNzDpGR40ZaCl5Ty1uA76bu/qRtF5+hr44qct7KPAY8H+5/B3Ad/L2UjDyBNBb0tZ53RKSNiocY9+8fjvSI4nptJxY6FTguNwtXtKthXO4ndSLQT5OqSu+WoKi8mPfBhyufLstabMWjlXJJcBJETGpbP0ocqKg3OX/WkS81UI9LX0nkHpI9pb0iVzn8pLWJOU9eBeYrpT6eLc6229mZg3SUcFAS8l7anExaXDao0qvIV5Aukv9CTAqIu4jBQLfyhfni4F/k5L4TAC+FhEfkoKS3+R145n7TYEZSkmCzieNUQD4O7CXKgwgzBfV7wOXS3pC0mjSGICrqpzDEaRkPhMlTSUNToTqCYruJj1WGJ/HN/yC9AhholJioV/U+N2V2vtiRJxVYdOJwABJE0mDA7/RSj2vk8ZsTJZ0WoXtU4HjgdtznXcAK0fEBGAcaYzEVaQERWZmtgBwoiLSyH/g6IhwJpwFlBMVmZnVT05UZGZmZrXwJDFARAzu7DaYmZl1FvcMmJmZNTkHA2ZmZk3OwYCZmVmT85gBazhJe5JeLd0gIh7PkyvdlKd8Hkx6k2P3Fit5eRyc2LPRTTUzW7CcOL1DDuOeAesIC1u2SjOzpuJgwBpK85Gt0szMOoaDAWu02dkqgdclDah1R0kH55THY6e958mxzMwaxcGANdpQUpZKmJOtsiYRcWFEDIyIgb27qfUdzMysTTyA0BqmWrZK4JxObZiZmc3FPQPWSNWyVa7eye0yM7MC9wxYIw0FflO27jrgx3XXtMpmcKITFZmZNYKDAWuYiBhSYd1ZwFmFzyOBkR3XKjMzK+fHBGZmZk3OwYCZmVmTczBgZmbW5BwMmJmZNTkHA4akPSWFpPXz5z6SJuflYZLOns/6j5TUrT3aamZm7c9vExjMnUjoZ+1ZsaQuwJHAFcB7ba1n0kvT6XPszXXt89wpn2/r4czMmop7BppcjYmEVpc0UtJTkn5W2Hd/SQ9LGi/pgnzhR9I7kk6XNAE4DlgFuFvS3Xn7eTnnwBRJJzX0BM3MrFUOBqyWREJbAF8G+gH7SBooaQNgX2DbiOgPzAL2y+WXAR6KiE0j4ufAy8CQwrwDx0XEwFzfjpL6NezszMysVX5MYEOBM/NyKZFQ+RiBOyLidQBJ15N6EmYCA4AxkgC6Aq/m8rNIMw1W8xVJB5P+/lYGNgQmlhfKZQ4G6LJs73rPy8zMauRgoInVkUioPH9wAAIui4hKUwvPiIhZVY65FnA0MCgi3pA0HFi6UtmIuBC4EGCpldd1DmMzswbxY4LmVmsioU9LWl5SV2BPYDRwJ7C3pE9ACiwkrVnlOG8DPfLyssC7wHRJKwG7te8pmZlZvdwz0NxqTST0cF6/GnBFRIwFkHQ8cLukxYCPgEOB5ysc50LgVkkvR8QQSeOAx4EXSIFFqzZZtSdj/XaAmVlDKMK9r7bgGzhwYIwd66yFZmb1kPRIHrDdIj8mMDMza3IOBszMzJqcHxPYQkHS28ATnd2OdrAi8FpnN2I++RwWHIvCeSwK5wAL7nmsGRGtvpvtAYS2sHiiludeCzpJYxf28/A5LDgWhfNYFM4BFv7z8GMCMzOzJudgwMzMrMk5GLCFxYWd3YB2siich89hwbEonMeicA6wkJ+HBxCamZk1OfcMmJmZNTkHA7ZAkbSrpCck/UvSsRW2LyXp2rz9IUl9Or6VLavhHP5P0lRJEyXd2UJOh07V2nkUyn1ZUkha4EZS13IOkr6Sfx9TJF3V0W2sRQ1/U2tIulvSuPx39bnOaGc1ki6R9KqkyVW2S9JZ+fwmStq8o9tYixrOY7/c/kmS7pe0aUe3sc0iwj/+WSB+SFkTnwbWBpYEJgAblpX5HnB+Xv4qcG1nt7sN5zAE6JaXv7ugnUOt55HL9QDuBR4EBnZ2u9vwu1gXGAcslz9/orPb3cbzuBD4bl7eEHius9td1r4dgM2ByVW2fw74Bykb6lbAQ53d5jaexzaFv6XdFtTzqPTjngFbkGwB/CsinomID4FrgD3KyuwBXJaX/wrsLEkd2MbWtHoOEXF3RLyXPz5ISgC1oKnldwHwC1Kyqxkd2bga1XIO3wbOiYg3ACLi1Q5uYy1qOY8gZQQF6Am83IHta1VE3Av8r4UiewCXR/Ig0EvSyh3Tutq1dh4RcX/pb4kF97/tihwM2IJkVVImw5IX87qKZSJiJjAdWKFDWlebWs6h6JukO6IFTavnkbtyV4+ImzuyYXWo5XexHrCepNGSHpS0a4e1rna1nMeJwP6SXgRuAQ7vmKa1m3r/u1kYLKj/bVfkGQjNOomk/YGBwI6d3ZZ65bTVvwOGdXJT5tfipEcFg0l3cfdK2iQi3uzUVtVvKDA8Ik6XtDXwJ0kbR8THnd2wZiRpCCkY2K6z21Ir9wzYguQlYPXC59XyuoplJC1O6hJ9vUNaV5tazgFJuwDHAV+MiA86qG31aO08egAbAyMlPUd6zjtiARtEWMvv4kVgRER8FBHPAk+SgoMFSS3n8U3gzwAR8QCwNGmu/IVFTf/dLAwk9QMuBvaIiAXp/00tcjBgC5IxwLqS1pK0JGmA4IiyMiOAb+TlvYG7Io/WWUC0eg6SNgMuIAUCC+IzamjlPCJiekSsGBF9IqIP6fnoFyNibOc0t6Ja/p5uJPUKIGlF0mODZzqykTWo5Tz+DewMIGkDUjAwrUNbOX9GAAfktwq2AqZHxCud3ah6SVoDuB74ekQ82dntqYcfE9gCIyJmSjoMuI00gvqSiJgi6efA2IgYAfyR1AX6L9JAnq92XovnVeM5nAZ0B/6Sxz7+OyK+2GmNrqDG81ig1XgOtwGfkTQVmAUcs6DdzdV4Hj8ALpJ0FGkw4bAFKUiWdDUp6Foxj2v4GbAEQEScTxrn8DngX8B7wIGd09KW1XAeJ5DGMJ2b/9ueGQtJ8iLPQGhmZtbk/JjAzMysyTkYMDMza3IOBszMzJqcgwEzM7Mm52DAzMysk7SW/Kis7A6SHpU0U9LeZdtulfSmpJva0g4HA2ZmZp1nOFDrNNj/Js36WSm75mnA19vaCAcDZosISatJ+pukpyQ9LenMPElNS/ssJemfksZL2reNx+1T6a4mr38/1136WVLSF6ulE27j8YeX3yUV1r8nqUdh3e+V0i0v0LPzSfqrpLXzcndJF+Tf6SOSRkraslB2z3xO6xfWlb77cZIek/SwpGGF7bvneQoWGJLeqbP8iZKOblR7Okql5EeS+uY7/UckjSr9biPiuYiYCMwzzXRE3Am83dZ2OBgwWwTkzI3XAzdGxLqkmfS6A79qZdfNACKif0RcW+OxutTRtKdz3aWfDyNiREScUkcd8+Nf5Ax/OZ/CTnTCNLd56uxay24EdImI0kyIF5MuFutGxADShDzFYGYocF/+t+jpiNgsIjYgTc51pKTSZD43A1+Q1K292l2PRtW7CLkQODz/vo8Gzm30AR0MmC0adgJmRMSlABExCzgKOEhSN0lHSboEQNImkibnqVOvAAblu/a+knbOd5OT8rPMpfI+z0n6jaRHgX0kDZA0QdIE4NB6GippmKSz8/I+uS0TJN2b13WR9Nu8fqKkw/P6EySNyesvzAFQa64BSj0eg4HRwMxCW/bPd83j8913l7z+PEljJU2RdFKh/CmSpuZ2/Tavm6tnonSHK2lwvqsbAUxt6Xhl9gP+lsv3BbYEji8lHYqIZ0uZIiV1JyXD+SYtzMaZA4v/A47InwMYCexeXjbfcf9J0mjSbJ9dJJ2Wv/uJkr5TKPuj/LcyQdIpeV1/pQyQEyXdIGm5vH5k7pkZC3xfaXrlB/L+vyxrwzGF4xW//+MkPSnpPuBT1c53YZZ/p9uQZigdT5q6vOHpnB0MmC0aNgIeKa6IiLdIzxjXAc4E1pG0F3Ap8J2I+DfwLWBURPQn3TEPB/aNiE1I05V/t1Dl6xGxeURck+s4PCI2baVdfTXnEcE5FbafAHw211OakvlgoA/QPyL6AVfm9WdHxKCI2BjoSoULWQVPAr3zBWkoKTgAZs/hvy+wbT7/WaQLMcBxeRrZfsCOkvpJWgHYC9got2uuC1gVmwPfj4j1Wjle0bbM+V1uBIzPwV0lewC35nnwX5c0oIW2PAqsX/g8Fti+StkNgV0iYigp0JgeEYOAQcC384V8t3z8LfPv79S87+XAj/J3NIk0ZW/JkhExMCJOJ/1Nnpf/1mbnIZD0GVKyqC2A/sAApYFzA0gBT3/S1MWDWjjXhdliwJtlPWobdMRBzWwRl+8qhwF/Au6JiNEVin0KeLaQYOUyYIfC9msBJPUCeuVnneQ6qyk+JqjUgzAaGC7p26R59wF2AS6IiJm57aXnqUMkPSRpEqknZKMWjlt0PekisiUwqrB+Z2AAMCbfge0MrJ23fSX3gozLx9kQmA7MAP4o6UukOfRb83DOhtja8YpWpvYkQ8UA5xrmfVRQVN6T8iqwSpWyIyLi/bz8GVISofHAQ6S599cl/Z4ujYj3IP2eJPUk/W3ck/et+DeUbQtcnZeLf0OfyT/jmBPArEsKXG6IiPdyoLvA58doi3xuz0raB9IjQEmtBd3zzc9tzBYNU0lZHGeTtCywBum5OaT/ob5D9QtAa95tc+uqiIhDlAbDfR54pNqdraSlSc9NB0bEC5JOJGXmq8W1pDvtyyLi48LTBeV1Py471lqk57SDIuINScOBpXPCoC1IF/G9gcNIQclM8o2V0riE4qDN4ndW8XgVvF84tynAppK6lPcOSFo+H38TSUEKpkLSMVXq3Qx4rPB56XysSsrbfXhE3FZ2/M+2ch6t1QspqVI5Ab+OiAvKjndkG463wFPl5Ef7AedJOp6UCOkaYIKkQcANwHKkMR8nRcRGuZ5RpMCpe67nm+W/s5a4Z8Bs0XAn0E3SATB7kN/pwPCIeC/fsZ1FuktbQRVG3wNPAH0krZM/fx24p7xQRLwJvClpu7yqUld3TST1jYiHIuIE0t3w6sAdwHeUB5nli17p4vhafqZaqf0VRcTzwHHMOwjrTmBvSZ8oHUfSmsCypIvWdEkrAbvl7d2BnhFxC2k8Rulu7TnSHT+kRx1LVGlKteOVe4z0aIeIeJrUnX+SchSj9KbA5/N38KeIWDOnkl4deJYKXf+S+gC/Bf5QWL0e0Oq77aRsid+VtESuaz1Jy5B+TwcqD0KUtHxETAfekFRqQ8W/oWw0c8Y5FP+GbiONdeme6101f2f3AntK6qr0hsgXamj7Ai8ihkbEyhGxRESsFhF/zONCdo2ITSNiw4j4eS47JpdZJiJWKAUCedv2EdE7IrrmMjUHAuBgwGyRkAeE7UUa3PcU6Vn5DOAnucgZwDn5EcA3gVNKF6VCHTNII9X/krviPwbOr3LIA4FzctdxLQP5qjktDyCbDNwPTCCNnv83MFFpgOLXcgByEenidRswpp6DRMQF+cJaXDcVOB64XdJE0sVt5YiYQOqifpz0PnfpkUoP4KZc9j7SgDxyu3bMbd2aKj0o1Y5XoejNpDvFkm8BKwH/yt/TcFIX/1DSXWLRdcx5VNBX+dVC4M/AWaUBptmQfKzWXEzqeXo0H/8CYPGIuJXUVT82/x2UXvP7Bun3OpH0fL/aK4zfBw7Nf2urllZGxO2k7/2BvO2vQI+IeJTUyzMB+Ad1/g1Yy5zC2MxsASKpK3A3aaBhtYGD83uMlYCrImLnRtRvCx8HA2ZmC5j8PP6x/MZHI+ofBHwUEeMbUb8tfBwMmJmZNTmPGTAzM2tyDgbMzMyanIMBMzOzJudgwMzMrMk5GDAzM2ty/w+NrxcyWMv4aAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "full_df[full_df['subregion'].isna()].groupby(by=['region'])['oxford_fiscal_measure_cad'].sum().plot.barh()\n",
    "plt.xlabel('Oxford Fiscal Measure (CAD) recorded')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "region\n",
       "Alberta                        5.035300e+09\n",
       "All                            1.290604e+11\n",
       "All except Greater Montreal    0.000000e+00\n",
       "Atlantic Canada                1.600000e+07\n",
       "British Columbia               9.875500e+09\n",
       "Manitoba                       3.927377e+09\n",
       "New Brunswick                  1.845016e+08\n",
       "Newfoundland and Labrador      3.205000e+08\n",
       "Northwest Territories          1.829650e+08\n",
       "Nova Scotia                    1.023160e+09\n",
       "Nunavut                        5.712000e+07\n",
       "Ontario                        1.745075e+10\n",
       "Prince Edward Island           1.852250e+08\n",
       "Quebec                         3.533900e+09\n",
       "Saskatchewan                   2.496275e+09\n",
       "Yukon                          2.770000e+07\n",
       "Name: oxford_fiscal_measure_cad, dtype: float64"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_df[full_df['subregion'].isna()].groupby(by=['region'])['oxford_fiscal_measure_cad'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'$ / person')"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(provinces_df.groupby(by='region')['oxford_fiscal_measure_cad'].sum())\n",
    "df['region'] = df.index\n",
    "df = df.merge(population_df, on='region', how='left')\n",
    "df['fiscal_measure_cad_popnorm'] = df['oxford_fiscal_measure_cad'] /  df['population_q1_2020']\n",
    "df = df.sort_values(by='fiscal_measure_cad_popnorm', ascending=False)\n",
    "df.plot.bar(x='region', y='fiscal_measure_cad_popnorm')\n",
    "plt.ylabel(\"$ / person\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'fiscal measures (CAD)')"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "provinces_df.groupby(by='region')['oxford_fiscal_measure_cad'].sum().sort_values(ascending=False).plot.bar()\n",
    "plt.ylabel('fiscal measures (CAD)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparing Provincial and Municipal Interventions of the Same Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "NaTType does not support toordinal",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-83-e5c5f5536bbd>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     29\u001b[0m \u001b[0mrec_ont_date\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrec_ont\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'start_date'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     30\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 31\u001b[0;31m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxvline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrec_ont_date\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'First provincial public event cancellation'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0.25\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlinewidth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     32\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxvline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msoc_ont_date\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'First provincial social distancing announcement'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcmap\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m0.65\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlinewidth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     33\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/pyplot.py\u001b[0m in \u001b[0;36maxvline\u001b[0;34m(x, ymin, ymax, hold, **kwargs)\u001b[0m\n\u001b[1;32m   2728\u001b[0m                       mplDeprecation)\n\u001b[1;32m   2729\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2730\u001b[0;31m         \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maxvline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mymin\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mymin\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mymax\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mymax\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2731\u001b[0m     \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2732\u001b[0m         \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_hold\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mwashold\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/axes/_axes.py\u001b[0m in \u001b[0;36maxvline\u001b[0;34m(self, x, ymin, ymax, **kwargs)\u001b[0m\n\u001b[1;32m    784\u001b[0m         \u001b[0;31m# non-unitized bounds\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    785\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_process_unit_info\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mxdata\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 786\u001b[0;31m         \u001b[0mxx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconvert_xunits\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    787\u001b[0m         \u001b[0mscalex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mxx\u001b[0m \u001b[0;34m<\u001b[0m \u001b[0mxmin\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mxx\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0mxmax\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    788\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/artist.py\u001b[0m in \u001b[0;36mconvert_xunits\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m    189\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0max\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxaxis\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    190\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 191\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxaxis\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconvert_units\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    192\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    193\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mconvert_yunits\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/axis.py\u001b[0m in \u001b[0;36mconvert_units\u001b[0;34m(self, x)\u001b[0m\n\u001b[1;32m   1524\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1525\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1526\u001b[0;31m         \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconverter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconvert\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munits\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1527\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mret\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1528\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/plotting/_converter.py\u001b[0m in \u001b[0;36mconvert\u001b[0;34m(values, unit, axis)\u001b[0m\n\u001b[1;32m    278\u001b[0m                       for v in values]\n\u001b[1;32m    279\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 280\u001b[0;31m             \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDatetimeConverter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_convert_1d\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0munit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    281\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    282\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/plotting/_converter.py\u001b[0m in \u001b[0;36m_convert_1d\u001b[0;34m(values, unit, axis)\u001b[0m\n\u001b[1;32m    290\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    291\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mdatetime\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpydt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 292\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0m_dt_to_float_ordinal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    293\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdatetime64\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    294\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0m_dt_to_float_ordinal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTimestamp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/plotting/_converter.py\u001b[0m in \u001b[0;36m_dt_to_float_ordinal\u001b[0;34m(dt)\u001b[0m\n\u001b[1;32m    263\u001b[0m         \u001b[0mbase\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdates\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mepoch2num\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masi8\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0;36m1.0E9\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    264\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 265\u001b[0;31m         \u001b[0mbase\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdates\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdate2num\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    266\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mbase\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    267\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/dates.py\u001b[0m in \u001b[0;36mdate2num\u001b[0;34m(d)\u001b[0m\n\u001b[1;32m    445\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0m_dt64_to_ordinalf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    446\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mcbook\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0miterable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 447\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_to_ordinalf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    448\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    449\u001b[0m         \u001b[0md\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0md\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/matplotlib/dates.py\u001b[0m in \u001b[0;36m_to_ordinalf\u001b[0;34m(dt)\u001b[0m\n\u001b[1;32m    253\u001b[0m         \u001b[0mtzi\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mUTC\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    254\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 255\u001b[0;31m     \u001b[0mbase\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfloat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtoordinal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    256\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    257\u001b[0m     \u001b[0;31m# If it's sufficiently datetime-like, it will have a `date()` method\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/tslib.pyx\u001b[0m in \u001b[0;36mpandas._libs.tslib._make_error_func.f\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mValueError\u001b[0m: NaTType does not support toordinal"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.dates import MO\n",
    "fig = matplotlib.pyplot.gcf()\n",
    "fig.set_size_inches(10, 5)\n",
    "\n",
    "ont_df = full_df[full_df['region'] == 'Ontario']\n",
    "\n",
    "cmap = mpl.cm.get_cmap('magma')\n",
    "\n",
    "soc = ont_df[ont_df['intervention_category'] == 'Social Distancing Announcement']\n",
    "#rec = ont_df[ont_df['intervention_category'] == 'Recreational / Entertainment Facility Closure']\n",
    "pem = ont_df[ont_df['intervention_category'] == 'Public event/ meeting cancellation or postponement']\n",
    "#park = ont_df[ont_df['intervention_category'] == 'Public park closure']\n",
    "\n",
    "start = datetime(2020, 3, 9)\n",
    "end = datetime(2020, 4, 1) \n",
    "drange=(start, end)\n",
    "\n",
    "pem.groupby('subregion').min()['start_date'].hist(bins=50, range=drange, color=cmap(0.35),  alpha=0.9, cumulative=True, label='Public event cancellation')\n",
    "#rec.groupby('subregion').min()['start_date'].hist(bins=30, color=cmap(0.8), alpha=0.5, cumulative=True, label='Recreational / Entertainment Facility Closure')\n",
    "soc.groupby('subregion').min()['start_date'].hist(bins=50, range=drange, color=cmap(0.6), alpha=0.6, cumulative=True, label='Social distancing announcements')\n",
    "#park.groupby('subregion').min()['start_date'].hist(color='red', alpha=0.5, label='Public park closure')\n",
    "\n",
    "a = soc[soc['subregion'].isna()]\n",
    "soc_ont = a[a['intervention_category'] == 'Social Distancing Announcement']\n",
    "soc_ont_date = soc_ont['start_date'].min()\n",
    "\n",
    "#a = rec[rec['subregion'].isna()]\n",
    "rec_ont = a[a['intervention_category'] == 'Recreational / Entertainment Facility Closure']\n",
    "rec_ont_date = rec_ont['start_date'].min()\n",
    "\n",
    "plt.axvline(x=rec_ont_date, label='First provincial public event cancellation', color=cmap(0.25), linewidth=2)\n",
    "plt.axvline(x=soc_ont_date, label='First provincial social distancing announcement', color=cmap(0.65), linewidth=2)\n",
    "\n",
    "plt.xticks(rotation=45, ha='right')\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.title('Municipality interventions over time in Ontario compared with Provincial interventions')\n",
    "\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Municipalities with intervention')\n",
    "plt.gca().xaxis.set_major_locator(mdates.WeekdayLocator(byweekday=(MO)))\n",
    "month_format = mdates.DateFormatter('%d %b')\n",
    "plt.gca().xaxis.set_major_formatter(month_format)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Heatmap of cumulative municipal top intervention categories"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Thanks to matplotlib documentation for this\n",
    "\n",
    "def heatmap(data, row_labels, col_labels, ax=None,\n",
    "            cbar_kw={}, cbarlabel=\"\", **kwargs):\n",
    "    \"\"\"\n",
    "    Create a heatmap from a numpy array and two lists of labels.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    data\n",
    "        A 2D numpy array of shape (N, M).\n",
    "    row_labels\n",
    "        A list or array of length N with the labels for the rows.\n",
    "    col_labels\n",
    "        A list or array of length M with the labels for the columns.\n",
    "    ax\n",
    "        A `matplotlib.axes.Axes` instance to which the heatmap is plotted.  If\n",
    "        not provided, use current axes or create a new one.  Optional.\n",
    "    cbar_kw\n",
    "        A dictionary with arguments to `matplotlib.Figure.colorbar`.  Optional.\n",
    "    cbarlabel\n",
    "        The label for the colorbar.  Optional.\n",
    "    **kwargs\n",
    "        All other arguments are forwarded to `imshow`.\n",
    "    \"\"\"\n",
    "\n",
    "    if not ax:\n",
    "        ax = plt.gca()\n",
    "\n",
    "    # Plot the heatmap\n",
    "    im = ax.imshow(data, **kwargs)\n",
    "\n",
    "    # Create colorbar\n",
    "    cbar = ax.figure.colorbar(im, ax=ax, **cbar_kw)\n",
    "    cbar.ax.set_ylabel(cbarlabel, rotation=-90, va=\"bottom\")\n",
    "\n",
    "    # We want to show all ticks...\n",
    "    ax.set_xticks(np.arange(data.shape[1]))\n",
    "    ax.set_yticks(np.arange(data.shape[0]))\n",
    "    # ... and label them with the respective list entries.\n",
    "    ax.set_xticklabels(col_labels)\n",
    "    ax.set_yticklabels(row_labels)\n",
    "\n",
    "    # Let the horizontal axes labeling appear on top.\n",
    "    ax.tick_params(top=True, bottom=False,\n",
    "                   labeltop=True, labelbottom=False)\n",
    "\n",
    "    # Rotate the tick labels and set their alignment.\n",
    "    plt.setp(ax.get_xticklabels(), rotation=-30, ha=\"right\",\n",
    "             rotation_mode=\"anchor\")\n",
    "\n",
    "    # Turn spines off and create white grid.\n",
    "    for edge, spine in ax.spines.items():\n",
    "        spine.set_visible(False)\n",
    "\n",
    "    ax.set_xticks(np.arange(data.shape[1]+1)-.5, minor=True)\n",
    "    ax.set_yticks(np.arange(data.shape[0]+1)-.5, minor=True)\n",
    "    ax.grid(which=\"minor\", color=\"w\", linestyle='-', linewidth=3)\n",
    "    ax.tick_params(which=\"minor\", bottom=False, left=False)\n",
    "\n",
    "    return im, cbar\n",
    "\n",
    "def annotate_heatmap(im, data=None, valfmt=\"{x:.2f}\",\n",
    "                     textcolors=[\"black\", \"white\"],\n",
    "                     threshold=None, **textkw):\n",
    "    \"\"\"\n",
    "    A function to annotate a heatmap.\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    im\n",
    "        The AxesImage to be labeled.\n",
    "    data\n",
    "        Data used to annotate.  If None, the image's data is used.  Optional.\n",
    "    valfmt\n",
    "        The format of the annotations inside the heatmap.  This should either\n",
    "        use the string format method, e.g. \"$ {x:.2f}\", or be a\n",
    "        `matplotlib.ticker.Formatter`.  Optional.\n",
    "    textcolors\n",
    "        A list or array of two color specifications.  The first is used for\n",
    "        values below a threshold, the second for those above.  Optional.\n",
    "    threshold\n",
    "        Value in data units according to which the colors from textcolors are\n",
    "        applied.  If None (the default) uses the middle of the colormap as\n",
    "        separation.  Optional.\n",
    "    **kwargs\n",
    "        All other arguments are forwarded to each call to `text` used to create\n",
    "        the text labels.\n",
    "    \"\"\"\n",
    "\n",
    "    if not isinstance(data, (list, np.ndarray)):\n",
    "        data = im.get_array()\n",
    "\n",
    "    # Normalize the threshold to the images color range.\n",
    "    if threshold is not None:\n",
    "        threshold = im.norm(threshold)\n",
    "    else:\n",
    "        threshold = im.norm(data.max())/2.\n",
    "\n",
    "    # Set default alignment to center, but allow it to be\n",
    "    # overwritten by textkw.\n",
    "    kw = dict(horizontalalignment=\"center\",\n",
    "              verticalalignment=\"center\")\n",
    "    kw.update(textkw)\n",
    "\n",
    "    # Get the formatter in case a string is supplied\n",
    "    if isinstance(valfmt, str):\n",
    "        valfmt = matplotlib.ticker.StrMethodFormatter(valfmt)\n",
    "\n",
    "    # Loop over the data and create a `Text` for each \"pixel\".\n",
    "    # Change the text's color depending on the data.\n",
    "    texts = []\n",
    "    for i in range(data.shape[0]):\n",
    "        for j in range(data.shape[1]):\n",
    "            kw.update(color=textcolors[int(im.norm(data[i, j]) > threshold)])\n",
    "            text = im.axes.text(j, i, valfmt(data[i, j], None), **kw)\n",
    "            texts.append(text)\n",
    "\n",
    "    return texts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "intervention_category\n",
       "Public Announcement                                             20\n",
       "Social Distancing Announcement                                  19\n",
       "Public event/ meeting cancellation or postponement              19\n",
       "Recreational / Entertainment Facility Closure or Restriction    19\n",
       "Public park restriction or closure                              19\n",
       "Administrative flexibility                                      18\n",
       "Government building closure                                     16\n",
       "Declaration of emergency (or similar)                           16\n",
       "Non-essential workplace closure                                 16\n",
       "Emergency economic funding                                      15\n",
       "Name: intervention_category, dtype: int64"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "top_interventions = full_df.groupby(by='subregion')['intervention_category'].value_counts() \\\n",
    "    .groupby(by='intervention_category') \\\n",
    "    .count() \\\n",
    "    .sort_values(ascending=False)[:10] \\\n",
    "    \n",
    "top_interventions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "cma_population= pd.DataFrame([['Toronto', 5429524],\n",
    "                [\"Montreal\", 3519595],\n",
    "                [\"Vancouver\", 2264823],\n",
    "                [\"Calgary\", 1237656],\n",
    "                [\"Edmonton\", 1062643],\n",
    "                [\"Ottawa\", 989657],\n",
    "                [\"Gatineau\", 989657],\n",
    "                [\"Winnipeg\", 711925],\n",
    "                [\"Quebec City\", 705103],\n",
    "                [\"Hamilton\", 693645],\n",
    "                [\"Kitchener-Waterloo\", 535154],\n",
    "                [\"London\", 383437],\n",
    "                [\"Victoria\", 335696],\n",
    "                [\"Halifax\", 316701],\n",
    "                [\"Oshawa\", 308875],\n",
    "                [\"Windsor\", 287069],\n",
    "                [\"Saskatoon\", 245181],\n",
    "                [\"Niagara\", 229246],\n",
    "                [\"Regina\", 214631],\n",
    "                [\"St. John's\", 178427],\n",
    "                [\"Kelowna\", 151957]], columns=['subregion', 'population'])\n",
    "# Population numbers from Canadian Census 2016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "filtered_df = full_df[full_df['intervention_category'].isin(top_interventions.index.values)]\n",
    "#filtered_df = filtered_df.groupby(by=['subregion', 'start_date']).nunique()['intervention_category']\n",
    "filtered_df = filtered_df.merge(cma_population, on='subregion')\n",
    "filtered_df = filtered_df.sort_values(by='population', ascending=False)\n",
    "soc_count = filtered_df.groupby(by=['subregion', 'intervention_category'], sort=False).min()['start_date']\n",
    "#soc_count = soc_count.merge(cma_population, on='subregion')\n",
    "\n",
    "xticks = pd.date_range(start='03-08-2020', end=cutoff_date, freq='W')\n",
    "\n",
    "\n",
    "col = ['subregion', *xticks.date]\n",
    "cma_df = pd.DataFrame()\n",
    "\n",
    "for subregion in soc_count.index.get_level_values(0).unique():\n",
    "    dates = soc_count.loc[[subregion]].reset_index()\n",
    "    empty_row = [subregion]\n",
    "    for week_end in xticks.values:\n",
    "        count = dates[dates['start_date'] < week_end]['intervention_category'].count()\n",
    "        empty_row.append(count)\n",
    "    cma_df = cma_df.append([empty_row])\n",
    "    \n",
    "cma_df.columns = col\n",
    "cma_df = cma_df.set_index('subregion')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#fig, (a0, a1) = plt.subplots(1, 2, gridspec_kw={'width_ratios': [5, 1]}, figsize=(10,6))\n",
    "fig, ax = plt.subplots(figsize=(10,8))\n",
    "\n",
    "nice_date = [x.strftime('%B %d') for x in cma_df.columns.values]\n",
    "\n",
    "im, cbar = heatmap(cma_df.values, cma_df.index.values, nice_date, ax=ax,\n",
    "                   cmap=\"magma_r\", cbarlabel=\"# of distinct intervention categories\")\n",
    "texts = annotate_heatmap(im, valfmt=\"{x:.0f}\")\n",
    "\n",
    "fig.tight_layout()\n",
    "plt.savefig('doc/img/fig5.png', dpi=300)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Mobility comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "ox = full_df['oxford_government_response_category'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nan"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ox[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "gb = provinces_df.groupby(by='region')\n",
    "for gb_name, g in gb:\n",
    "    for intervention in ox:\n",
    "        rows = g[g['oxford_government_response_category'] == intervention]\n",
    "        if ox[2] in rows['oxford_government_response_category']: # public events\n",
    "            print(rows['oxford_closure_code'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    C8 International Travel Controls\n",
       "1    H1 Public Info Campaigns        \n",
       "dtype: object"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g['oxford_government_response_category'].mode()"
   ]
  }
 ],
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