Exploratory - CDC Scratch Data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy as scipy\n",
    "\n",
    "%matplotlib inline\n",
    "%config InlineBackend.print_figure_kwargs={'facecolor' : \"w\"}\n",
    "\n",
    "rawdata = pd.read_csv('https://data.cdc.gov/api/views/u6jv-9ijr/rows.csv?accessType=DOWNLOAD&bom=true&format=true%20target=')\n",
    "\n",
    "rawdata = rawdata[rawdata['Jurisdiction'] != 'United States']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Number of deaths per year up to this week, divided by cause subgroup')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "state = 'Texas'\n",
    "statedata = rawdata[rawdata['Jurisdiction'] == state]\n",
    "\n",
    "statedatatocurrentweek = statedata[statedata['Week'] <= statedata[statedata['Year'] == 2020]['Week'].max()]\n",
    "\n",
    "statedeathtable = statedatatocurrentweek.groupby(['Year', 'Cause Group']).sum().reset_index().pivot(index='Cause Group', columns='Year', values='Number of Deaths')\n",
    "\n",
    "ax = statedeathtable.plot.bar(figsize=(16,6))\n",
    "ax.set_title('Number of deaths per year up to this week, divided by cause subgroup')\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "statedatatocurrentweek = statedata[statedata['Week'] <= statedata[statedata['Year'] == 2020]['Week'].max()]\n",
    "\n",
    "pre2020averages = statedatatocurrentweek[statedatatocurrentweek['Year'] < 2020].groupby(['Year', 'Cause Group']).sum()[['Number of Deaths']].groupby(['Cause Group']).mean()\n",
    "\n",
    "pre2020averages['Number of Deaths 2020'] = statedatatocurrentweek[statedatatocurrentweek['Year'] == 2020].groupby(['Cause Group']).sum()['Number of Deaths']\n",
    "\n",
    "pre2020averages['Percent Change'] = (pre2020averages['Number of Deaths 2020'].div(pre2020averages['Number of Deaths']) - 1) * 100\n",
    "\n",
    "#pre2020averages.sort_values('Percent Change', ascending=False)[['Number of Deaths', 'Number of Deaths 2020']].plot.bar(figsize=(16,9))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Death percentage change over 2015-2019: 6.0670606811848105\n"
     ]
    }
   ],
   "source": [
    "totalNumberOfDeaths = pre2020averages[['Number of Deaths', 'Number of Deaths 2020']].sum()['Number of Deaths 2020']\n",
    "averageNumberOfDeaths = pre2020averages[['Number of Deaths', 'Number of Deaths 2020']].sum()['Number of Deaths']\n",
    "\n",
    "print('Death percentage change over 2015-2019: ' + str((totalNumberOfDeaths / averageNumberOfDeaths - 1) *100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11cf490d0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "statedatatocurrentweek = statedata[statedata['Week'] <= statedata[statedata['Year'] == 2020]['Week'].max()]\n",
    "\n",
    "pre2020averages = statedatatocurrentweek[statedatatocurrentweek['Year'] < 2020].groupby(['Year', 'Week']).sum()[['Number of Deaths']].groupby(['Week']).mean()\n",
    "\n",
    "pre2020averages['Number of Deaths 2020'] = statedatatocurrentweek[statedatatocurrentweek['Year'] == 2020].groupby(['Week']).sum()['Number of Deaths']\n",
    "\n",
    "pre2020averages['Percent Change'] = (pre2020averages['Number of Deaths 2020'].div(pre2020averages['Number of Deaths']) - 1) * 100\n",
    "\n",
    "pre2020averages[['Number of Deaths', 'Number of Deaths 2020']].plot.line(figsize=(16,9))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "certainstates = ['Texas', 'Colorado', 'New York', 'New Jersey', 'Florida', 'Colorado']\n",
    "\n",
    "gte2020 = rawdata[rawdata['Year'] == 2020].groupby(['Jurisdiction', 'Week'])[['Number of Deaths']].sum()\n",
    "maxweek = gte2020.reset_index()['Week'].max()\n",
    "lt2020 = rawdata[(rawdata['Year'] < 2020) & (rawdata['Week'] <= maxweek)].groupby(['Jurisdiction', 'Year', 'Week']).sum()[['Number of Deaths']].groupby(['Jurisdiction', 'Week']).mean()#.rename(columns={'Number of Deaths': 'Avg'})\n",
    "\n",
    "compareData = lt2020.copy().rename(columns={'Number of Deaths':'Average'})\n",
    "\n",
    "compareData['2020'] = gte2020['Number of Deaths']\n",
    "\n",
    "compareData = compareData.fillna(0)\n",
    "\n",
    "compareData['Difference'] = (compareData['2020'].div(compareData['Average']) * 100) - 100\n",
    "\n",
    "compareData = compareData.reset_index()\n",
    "#compareData = compareData[compareData['Jurisdiction'].isin(certainstates)]\n",
    "\n",
    "pivottable = compareData.pivot(index='Week', columns='Jurisdiction', values='Difference')\n",
    "\n",
    "pivottable['Week Ending'] = pd.to_datetime(rawdata[rawdata['Year'] == 2020].groupby(['Week'])['Week Ending Date'].max())\n",
    "pivottable = pivottable.reset_index().set_index('Week Ending').drop(['Week'], axis=1)\n",
    "\n",
    "states = pivottable.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "pivottable = pivottable.rolling(window=4).mean().dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, \"Who's peaking right now?\")"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "certainstates = ['Texas', 'Colorado', 'New York', 'Oklahoma', 'Mississippi', 'Louisiana']\n",
    "\n",
    "gte2020 = rawdata[rawdata['Year'] == 2020].groupby(['Jurisdiction', 'Week'])[['Number of Deaths']].sum()\n",
    "maxweek = gte2020.reset_index()['Week'].max()\n",
    "lt2020 = rawdata[(rawdata['Year'] < 2020) & (rawdata['Week'] <= maxweek)].groupby(['Jurisdiction', 'Year', 'Week']).sum()[['Number of Deaths']].groupby(['Jurisdiction', 'Week']).mean()#.rename(columns={'Number of Deaths': 'Avg'})\n",
    "\n",
    "compareData = lt2020.copy().rename(columns={'Number of Deaths':'Average'})\n",
    "#compareData['2020'] = gte2020['Number of Deaths']\n",
    "\n",
    "#pd.merge(lt2020.reset_index(), gt2020.reset_index(), left_on=['Jurisdiction', 'Week', 'Year'])\n",
    "compareData['2020'] = gte2020['Number of Deaths']\n",
    "\n",
    "compareData = compareData.fillna(0)\n",
    "\n",
    "compareData['Difference'] = (compareData['2020'].div(compareData['Average']) * 100) - 100\n",
    "\n",
    "compareData = compareData.reset_index()\n",
    "#compareData = compareData[compareData['Jurisdiction'].isin(certainstates)]\n",
    "\n",
    "pivottable = compareData[(compareData['Week'] > maxweek - 4)].reset_index()[['Jurisdiction', 'Difference']].groupby(['Jurisdiction']).mean() #.pivot(index='Jurisdiction', values='Difference')\n",
    "\n",
    "ax = pivottable.sort_values('Difference', ascending=False).plot.bar(figsize=(16,9), ylim=(-10, 30))\n",
    "ax.set_ylabel('% diff death for Past 4 Weeks 2020 vs same period 2015-2019', size=14)\n",
    "ax.set_title('Who\\'s peaking right now?', size=20)\n",
    "#ax.ylim(-50, 50)\n",
    "#ax.axhline(color='black')\n",
    "#ax.set_title('2020 Death Percentage compared to Average')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Year</th>\n",
       "      <th>Week</th>\n",
       "      <th>Number of Deaths</th>\n",
       "      <th>Average Number of Deaths in Time Period</th>\n",
       "      <th>Difference from 2015-2019 to 2020</th>\n",
       "      <th>Percent Difference from 2015-2019 to 2020</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cause Group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alzheimer disease and dementia</th>\n",
       "      <td>10254428</td>\n",
       "      <td>134278</td>\n",
       "      <td>525012.0</td>\n",
       "      <td>518736</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cerebrovascular diseases</th>\n",
       "      <td>9233826</td>\n",
       "      <td>120956</td>\n",
       "      <td>288994.0</td>\n",
       "      <td>286858</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chronic lower respiratory disease</th>\n",
       "      <td>9463764</td>\n",
       "      <td>123394</td>\n",
       "      <td>316850.0</td>\n",
       "      <td>310800</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Diabetes</th>\n",
       "      <td>8080102</td>\n",
       "      <td>105834</td>\n",
       "      <td>165836.0</td>\n",
       "      <td>164510</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Heart failure</th>\n",
       "      <td>7236996</td>\n",
       "      <td>93776</td>\n",
       "      <td>151938.0</td>\n",
       "      <td>151974</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hypertensive dieases</th>\n",
       "      <td>7741246</td>\n",
       "      <td>101874</td>\n",
       "      <td>174396.0</td>\n",
       "      <td>174120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Influenza and pneumonia</th>\n",
       "      <td>6514910</td>\n",
       "      <td>81206</td>\n",
       "      <td>101652.0</td>\n",
       "      <td>100274</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ischemic heart disease</th>\n",
       "      <td>10827256</td>\n",
       "      <td>141952</td>\n",
       "      <td>737920.0</td>\n",
       "      <td>733768</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Malignant neoplasms</th>\n",
       "      <td>11113670</td>\n",
       "      <td>146004</td>\n",
       "      <td>1207174.0</td>\n",
       "      <td>1203920</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other diseases of the circulatory system</th>\n",
       "      <td>9649328</td>\n",
       "      <td>126652</td>\n",
       "      <td>349340.0</td>\n",
       "      <td>346836</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Other diseases of the respiratory system</th>\n",
       "      <td>6946548</td>\n",
       "      <td>90096</td>\n",
       "      <td>121204.0</td>\n",
       "      <td>119338</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Renal failure</th>\n",
       "      <td>5752484</td>\n",
       "      <td>75028</td>\n",
       "      <td>88960.0</td>\n",
       "      <td>88476</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Residual (all other natural causes)</th>\n",
       "      <td>11262928</td>\n",
       "      <td>148094</td>\n",
       "      <td>666254.0</td>\n",
       "      <td>655886</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sepsis</th>\n",
       "      <td>5252268</td>\n",
       "      <td>67650</td>\n",
       "      <td>71830.0</td>\n",
       "      <td>70406</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              Year    Week  Number of Deaths  \\\n",
       "Cause Group                                                                    \n",
       "Alzheimer disease and dementia            10254428  134278          525012.0   \n",
       "Cerebrovascular diseases                   9233826  120956          288994.0   \n",
       "Chronic lower respiratory disease          9463764  123394          316850.0   \n",
       "Diabetes                                   8080102  105834          165836.0   \n",
       "Heart failure                              7236996   93776          151938.0   \n",
       "Hypertensive dieases                       7741246  101874          174396.0   \n",
       "Influenza and pneumonia                    6514910   81206          101652.0   \n",
       "Ischemic heart disease                    10827256  141952          737920.0   \n",
       "Malignant neoplasms                       11113670  146004         1207174.0   \n",
       "Other diseases of the circulatory system   9649328  126652          349340.0   \n",
       "Other diseases of the respiratory system   6946548   90096          121204.0   \n",
       "Renal failure                              5752484   75028           88960.0   \n",
       "Residual (all other natural causes)       11262928  148094          666254.0   \n",
       "Sepsis                                     5252268   67650           71830.0   \n",
       "\n",
       "                                          Average Number of Deaths in Time Period  \\\n",
       "Cause Group                                                                         \n",
       "Alzheimer disease and dementia                                             518736   \n",
       "Cerebrovascular diseases                                                   286858   \n",
       "Chronic lower respiratory disease                                          310800   \n",
       "Diabetes                                                                   164510   \n",
       "Heart failure                                                              151974   \n",
       "Hypertensive dieases                                                       174120   \n",
       "Influenza and pneumonia                                                    100274   \n",
       "Ischemic heart disease                                                     733768   \n",
       "Malignant neoplasms                                                       1203920   \n",
       "Other diseases of the circulatory system                                   346836   \n",
       "Other diseases of the respiratory system                                   119338   \n",
       "Renal failure                                                               88476   \n",
       "Residual (all other natural causes)                                        655886   \n",
       "Sepsis                                                                      70406   \n",
       "\n",
       "                                          Difference from 2015-2019 to 2020  \\\n",
       "Cause Group                                                                   \n",
       "Alzheimer disease and dementia                                          0.0   \n",
       "Cerebrovascular diseases                                                0.0   \n",
       "Chronic lower respiratory disease                                       0.0   \n",
       "Diabetes                                                                0.0   \n",
       "Heart failure                                                           0.0   \n",
       "Hypertensive dieases                                                    0.0   \n",
       "Influenza and pneumonia                                                 0.0   \n",
       "Ischemic heart disease                                                  0.0   \n",
       "Malignant neoplasms                                                     0.0   \n",
       "Other diseases of the circulatory system                                0.0   \n",
       "Other diseases of the respiratory system                                0.0   \n",
       "Renal failure                                                           0.0   \n",
       "Residual (all other natural causes)                                     0.0   \n",
       "Sepsis                                                                  0.0   \n",
       "\n",
       "                                          Percent Difference from 2015-2019 to 2020  \n",
       "Cause Group                                                                          \n",
       "Alzheimer disease and dementia                                                  0.0  \n",
       "Cerebrovascular diseases                                                        0.0  \n",
       "Chronic lower respiratory disease                                               0.0  \n",
       "Diabetes                                                                        0.0  \n",
       "Heart failure                                                                   0.0  \n",
       "Hypertensive dieases                                                            0.0  \n",
       "Influenza and pneumonia                                                         0.0  \n",
       "Ischemic heart disease                                                          0.0  \n",
       "Malignant neoplasms                                                             0.0  \n",
       "Other diseases of the circulatory system                                        0.0  \n",
       "Other diseases of the respiratory system                                        0.0  \n",
       "Renal failure                                                                   0.0  \n",
       "Residual (all other natural causes)                                             0.0  \n",
       "Sepsis                                                                          0.0  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rawdata[(rawdata['Year'] == 2017)].groupby(['Cause Group']).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Year</th>\n",
       "      <th>Week</th>\n",
       "      <th>Number of Deaths</th>\n",
       "      <th>Average Number of Deaths in Time Period</th>\n",
       "      <th>Difference from 2015-2019 to 2020</th>\n",
       "      <th>Percent Difference from 2015-2019 to 2020</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>329932.000000</td>\n",
       "      <td>329932.000000</td>\n",
       "      <td>329912.000000</td>\n",
       "      <td>329932.000000</td>\n",
       "      <td>17019.000000</td>\n",
       "      <td>17019.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2017.320454</td>\n",
       "      <td>25.127602</td>\n",
       "      <td>83.763776</td>\n",
       "      <td>83.762069</td>\n",
       "      <td>3.038780</td>\n",
       "      <td>6.279811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.621167</td>\n",
       "      <td>14.990656</td>\n",
       "      <td>113.397316</td>\n",
       "      <td>110.807771</td>\n",
       "      <td>24.667337</td>\n",
       "      <td>27.349480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2015.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>-286.000000</td>\n",
       "      <td>-84.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2016.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>-4.000000</td>\n",
       "      <td>-8.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2017.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>45.000000</td>\n",
       "      <td>46.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.300000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2019.000000</td>\n",
       "      <td>38.000000</td>\n",
       "      <td>96.000000</td>\n",
       "      <td>97.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>18.150000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2020.000000</td>\n",
       "      <td>52.000000</td>\n",
       "      <td>1336.000000</td>\n",
       "      <td>1336.000000</td>\n",
       "      <td>1065.000000</td>\n",
       "      <td>531.300000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Year           Week  Number of Deaths  \\\n",
       "count  329932.000000  329932.000000     329912.000000   \n",
       "mean     2017.320454      25.127602         83.763776   \n",
       "std         1.621167      14.990656        113.397316   \n",
       "min      2015.000000       1.000000         11.000000   \n",
       "25%      2016.000000      12.000000         24.000000   \n",
       "50%      2017.000000      24.000000         45.000000   \n",
       "75%      2019.000000      38.000000         96.000000   \n",
       "max      2020.000000      52.000000       1336.000000   \n",
       "\n",
       "       Average Number of Deaths in Time Period  \\\n",
       "count                            329932.000000   \n",
       "mean                                 83.762069   \n",
       "std                                 110.807771   \n",
       "min                                  11.000000   \n",
       "25%                                  24.000000   \n",
       "50%                                  46.000000   \n",
       "75%                                  97.000000   \n",
       "max                                1336.000000   \n",
       "\n",
       "       Difference from 2015-2019 to 2020  \\\n",
       "count                       17019.000000   \n",
       "mean                            3.038780   \n",
       "std                            24.667337   \n",
       "min                          -286.000000   \n",
       "25%                            -4.000000   \n",
       "50%                             2.000000   \n",
       "75%                             9.000000   \n",
       "max                          1065.000000   \n",
       "\n",
       "       Percent Difference from 2015-2019 to 2020  \n",
       "count                               17019.000000  \n",
       "mean                                    6.279811  \n",
       "std                                    27.349480  \n",
       "min                                   -84.600000  \n",
       "25%                                    -8.800000  \n",
       "50%                                     3.300000  \n",
       "75%                                    18.150000  \n",
       "max                                   531.300000  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rawdata.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Jurisdiction</th>\n",
       "      <th>Week Ending Date</th>\n",
       "      <th>State Abbreviation</th>\n",
       "      <th>Year</th>\n",
       "      <th>Week</th>\n",
       "      <th>Cause Group</th>\n",
       "      <th>Number of Deaths</th>\n",
       "      <th>Cause Subgroup</th>\n",
       "      <th>Time Period</th>\n",
       "      <th>Suppress</th>\n",
       "      <th>Note</th>\n",
       "      <th>Average Number of Deaths in Time Period</th>\n",
       "      <th>Difference from 2015-2019 to 2020</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>2015-01-10</td>\n",
       "      <td>AL</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>Alzheimer disease and dementia</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>103</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>2015-01-10</td>\n",
       "      <td>AL</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>Alzheimer disease and dementia</td>\n",
       "      <td>120.0</td>\n",
       "      <td>Alzheimer disease and dementia</td>\n",
       "      <td>2015-2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>2016-01-09</td>\n",
       "      <td>AL</td>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
       "      <td>Alzheimer disease and dementia</td>\n",
       "      <td>76.0</td>\n",
       "      <td>Alzheimer disease and dementia</td>\n",
       "      <td>2015-2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>AL</td>\n",
       "      <td>2016</td>\n",
       "      <td>1</td>\n",
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       "      <td>76.0</td>\n",
       "      <td>Alzheimer disease and dementia</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unweighted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alabama</td>\n",
       "      <td>2017-01-07</td>\n",
       "      <td>AL</td>\n",
       "      <td>2017</td>\n",
       "      <td>1</td>\n",
       "      <td>Alzheimer disease and dementia</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Alzheimer disease and dementia</td>\n",
       "      <td>2015-2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>103</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>338047</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>2017-12-30</td>\n",
       "      <td>WI</td>\n",
       "      <td>2017</td>\n",
       "      <td>52</td>\n",
       "      <td>Other diseases of the respiratory system</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Respiratory diseases</td>\n",
       "      <td>2015-2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unweighted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338048</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>2018-12-29</td>\n",
       "      <td>WI</td>\n",
       "      <td>2018</td>\n",
       "      <td>52</td>\n",
       "      <td>Other diseases of the respiratory system</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Respiratory diseases</td>\n",
       "      <td>2015-2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Predicted (weighted)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338049</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>2018-12-29</td>\n",
       "      <td>WI</td>\n",
       "      <td>2018</td>\n",
       "      <td>52</td>\n",
       "      <td>Other diseases of the respiratory system</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Respiratory diseases</td>\n",
       "      <td>2015-2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unweighted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338050</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>2019-12-28</td>\n",
       "      <td>WI</td>\n",
       "      <td>2019</td>\n",
       "      <td>52</td>\n",
       "      <td>Other diseases of the respiratory system</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Respiratory diseases</td>\n",
       "      <td>2015-2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Predicted (weighted)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>338051</th>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>2019-12-28</td>\n",
       "      <td>WI</td>\n",
       "      <td>2019</td>\n",
       "      <td>52</td>\n",
       "      <td>Other diseases of the respiratory system</td>\n",
       "      <td>23.0</td>\n",
       "      <td>Respiratory diseases</td>\n",
       "      <td>2015-2019</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unweighted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>329932 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Jurisdiction Week Ending Date State Abbreviation  Year  Week  \\\n",
       "0           Alabama       2015-01-10                 AL  2015     1   \n",
       "1           Alabama       2015-01-10                 AL  2015     1   \n",
       "2           Alabama       2016-01-09                 AL  2016     1   \n",
       "3           Alabama       2016-01-09                 AL  2016     1   \n",
       "4           Alabama       2017-01-07                 AL  2017     1   \n",
       "...             ...              ...                ...   ...   ...   \n",
       "338047    Wisconsin       2017-12-30                 WI  2017    52   \n",
       "338048    Wisconsin       2018-12-29                 WI  2018    52   \n",
       "338049    Wisconsin       2018-12-29                 WI  2018    52   \n",
       "338050    Wisconsin       2019-12-28                 WI  2019    52   \n",
       "338051    Wisconsin       2019-12-28                 WI  2019    52   \n",
       "\n",
       "                                     Cause Group  Number of Deaths  \\\n",
       "0                 Alzheimer disease and dementia             120.0   \n",
       "1                 Alzheimer disease and dementia             120.0   \n",
       "2                 Alzheimer disease and dementia              76.0   \n",
       "3                 Alzheimer disease and dementia              76.0   \n",
       "4                 Alzheimer disease and dementia              96.0   \n",
       "...                                          ...               ...   \n",
       "338047  Other diseases of the respiratory system              20.0   \n",
       "338048  Other diseases of the respiratory system              27.0   \n",
       "338049  Other diseases of the respiratory system              27.0   \n",
       "338050  Other diseases of the respiratory system              23.0   \n",
       "338051  Other diseases of the respiratory system              23.0   \n",
       "\n",
       "                        Cause Subgroup Time Period Suppress Note  \\\n",
       "0       Alzheimer disease and dementia   2015-2019      NaN  NaN   \n",
       "1       Alzheimer disease and dementia   2015-2019      NaN  NaN   \n",
       "2       Alzheimer disease and dementia   2015-2019      NaN  NaN   \n",
       "3       Alzheimer disease and dementia   2015-2019      NaN  NaN   \n",
       "4       Alzheimer disease and dementia   2015-2019      NaN  NaN   \n",
       "...                                ...         ...      ...  ...   \n",
       "338047            Respiratory diseases   2015-2019      NaN  NaN   \n",
       "338048            Respiratory diseases   2015-2019      NaN  NaN   \n",
       "338049            Respiratory diseases   2015-2019      NaN  NaN   \n",
       "338050            Respiratory diseases   2015-2019      NaN  NaN   \n",
       "338051            Respiratory diseases   2015-2019      NaN  NaN   \n",
       "\n",
       "        Average Number of Deaths in Time Period  \\\n",
       "0                                           103   \n",
       "1                                           103   \n",
       "2                                           103   \n",
       "3                                           103   \n",
       "4                                           103   \n",
       "...                                         ...   \n",
       "338047                                       25   \n",
       "338048                                       25   \n",
       "338049                                       25   \n",
       "338050                                       25   \n",
       "338051                                       25   \n",
       "\n",
       "        Difference from 2015-2019 to 2020  \\\n",
       "0                                     NaN   \n",
       "1                                     NaN   \n",
       "2                                     NaN   \n",
       "3                                     NaN   \n",
       "4                                     NaN   \n",
       "...                                   ...   \n",
       "338047                                NaN   \n",
       "338048                                NaN   \n",
       "338049                                NaN   \n",
       "338050                                NaN   \n",
       "338051                                NaN   \n",
       "\n",
       "        Percent Difference from 2015-2019 to 2020                  Type  \n",
       "0                                             NaN  Predicted (weighted)  \n",
       "1                                             NaN            Unweighted  \n",
       "2                                             NaN  Predicted (weighted)  \n",
       "3                                             NaN            Unweighted  \n",
       "4                                             NaN  Predicted (weighted)  \n",
       "...                                           ...                   ...  \n",
       "338047                                        NaN            Unweighted  \n",
       "338048                                        NaN  Predicted (weighted)  \n",
       "338049                                        NaN            Unweighted  \n",
       "338050                                        NaN  Predicted (weighted)  \n",
       "338051                                        NaN            Unweighted  \n",
       "\n",
       "[329932 rows x 15 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rawdata[rawdata['Jurisdiction'] != 'United States']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "676"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "52*13"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Difference</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jurisdiction</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Alabama</th>\n",
       "      <td>8.202637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alaska</th>\n",
       "      <td>-22.466109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arizona</th>\n",
       "      <td>20.004098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Arkansas</th>\n",
       "      <td>6.069210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>California</th>\n",
       "      <td>-3.071860</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Colorado</th>\n",
       "      <td>-10.503510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Connecticut</th>\n",
       "      <td>-82.427749</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delaware</th>\n",
       "      <td>2.337737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>District of Columbia</th>\n",
       "      <td>-42.905524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>5.004240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>7.101919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hawaii</th>\n",
       "      <td>-23.273048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idaho</th>\n",
       "      <td>4.615091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>-6.619525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>3.445376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>5.078840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>-2.061858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>0.618342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>8.830483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maine</th>\n",
       "      <td>12.169034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>-1.657653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>-17.927857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>2.321767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>4.768298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>17.302332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>3.418763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>-12.691236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebraska</th>\n",
       "      <td>-1.018744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>-5.737138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>8.695979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>-7.324255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>2.584081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>-3.868032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York City</th>\n",
       "      <td>-15.970453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>-95.971254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Dakota</th>\n",
       "      <td>-10.987743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>-14.933756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>-13.960926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>-3.484176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>5.141717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>-49.296583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>-50.090183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>14.525112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Dakota</th>\n",
       "      <td>4.341511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>-3.696887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>10.373537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>12.197282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>0.250662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>4.149345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>3.538526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>-92.099555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>1.928119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyoming</th>\n",
       "      <td>-9.811428</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Difference\n",
       "Jurisdiction                    \n",
       "Alabama                 8.202637\n",
       "Alaska                -22.466109\n",
       "Arizona                20.004098\n",
       "Arkansas                6.069210\n",
       "California             -3.071860\n",
       "Colorado              -10.503510\n",
       "Connecticut           -82.427749\n",
       "Delaware                2.337737\n",
       "District of Columbia  -42.905524\n",
       "Florida                 5.004240\n",
       "Georgia                 7.101919\n",
       "Hawaii                -23.273048\n",
       "Idaho                   4.615091\n",
       "Illinois               -6.619525\n",
       "Indiana                 3.445376\n",
       "Iowa                    5.078840\n",
       "Kansas                 -2.061858\n",
       "Kentucky                0.618342\n",
       "Louisiana               8.830483\n",
       "Maine                  12.169034\n",
       "Maryland               -1.657653\n",
       "Massachusetts         -17.927857\n",
       "Michigan                2.321767\n",
       "Minnesota               4.768298\n",
       "Mississippi            17.302332\n",
       "Missouri                3.418763\n",
       "Montana               -12.691236\n",
       "Nebraska               -1.018744\n",
       "Nevada                 -5.737138\n",
       "New Hampshire           8.695979\n",
       "New Jersey             -7.324255\n",
       "New Mexico              2.584081\n",
       "New York               -3.868032\n",
       "New York City         -15.970453\n",
       "North Carolina        -95.971254\n",
       "North Dakota          -10.987743\n",
       "Ohio                  -14.933756\n",
       "Oklahoma              -13.960926\n",
       "Oregon                 -3.484176\n",
       "Pennsylvania            5.141717\n",
       "Puerto Rico           -49.296583\n",
       "Rhode Island          -50.090183\n",
       "South Carolina         14.525112\n",
       "South Dakota            4.341511\n",
       "Tennessee              -3.696887\n",
       "Texas                  10.373537\n",
       "Utah                   12.197282\n",
       "Vermont                 0.250662\n",
       "Virginia                4.149345\n",
       "Washington              3.538526\n",
       "West Virginia         -92.099555\n",
       "Wisconsin               1.928119\n",
       "Wyoming                -9.811428"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pivottable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "states = ['New York', 'New York City', 'Texas']\n",
    "statedata = rawdata[rawdata['Jurisdiction'].isin(states)]\n",
    "early = statedata[statedata['Year'] < 2020]\n",
    "\n",
    "early = early.groupby(['Jurisdiction', 'Week']).sum()\n",
    "early['Number of Deaths'] = early['Number of Deaths'] / 5\n",
    "early = early[['Number of Deaths']]\n",
    "early = early.reset_index().pivot(index='Week', columns='Jurisdiction', values='Number of Deaths')\n",
    "early['New York All'] = early['New York'] + early['New York City']\n",
    "ax = early[['New York All', 'Texas']].plot.line()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Week')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "late = statedata[statedata['Year'] == 2020]\n",
    "late = late.groupby(['Jurisdiction', 'Week']).sum()\n",
    "late = late[['Number of Deaths']]\n",
    "late = late.reset_index().pivot(index='Week', columns='Jurisdiction', values='Number of Deaths')\n",
    "late['Week Ending'] = pd.to_datetime(statedata[statedata['Year'] == 2020].groupby(['Week'])['Week Ending Date'].max())\n",
    "late = late.reset_index().set_index(['Week Ending'])\n",
    "late['New York All'] = late['New York'] + late['New York City']\n",
    "ax = late[['New York All', 'Texas']].plot.line()\n",
    "ax.set_title('Weekly Death Count', size=18)\n",
    "ax.set_ylabel('Deaths', size=14)\n",
    "ax.set_xlabel('Week', size=14)\n",
    "\n",
    "\n",
    "#late"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "ename": "AttributeError",
     "evalue": "'Index' object has no attribute 'strftime'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-34-79da38c18f6a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m     16\u001b[0m             \u001b[0mlinecolor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'white'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m             cmap=\"Reds\")\n\u001b[0;32m---> 18\u001b[0;31m \u001b[0mx_dates\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf_norm_col_2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrftime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'%Y-%m-%d'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msort_values\u001b[0m\u001b[0;34m(\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[0m\u001b[1;32m     19\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     20\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_xticklabels\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mx_dates\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrotation\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m45\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mha\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'right'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mAttributeError\u001b[0m: 'Index' object has no attribute 'strftime'"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "fig, ax = plt.subplots(figsize=(15,20))  \n",
    "\n",
    "pvt2 = pivottable.copy().T\n",
    "pvt2['New York'] = pvt2['New York'] + pvt2['New York City']\n",
    "pvt2 = pvt2.drop(['New York City'], axis=1).T\n",
    "\n",
    "df_norm_col=(pvt2-pvt2.mean())/pvt2.std()\n",
    "df_norm_col_2 = df_norm_col.reindex(df_norm_col.idxmax().sort_values().index, axis=1)\n",
    "\n",
    "sns.heatmap(df_norm_col_2.transpose(), \n",
    "            xticklabels=True, \n",
    "            yticklabels=True, \n",
    "            ax=ax, cbar=False, \n",
    "            linewidths=2, \n",
    "            linecolor='white', \n",
    "            cmap=\"Reds\")\n",
    "x_dates = df_norm_col_2.index.strftime('%Y-%m-%d').sort_values().unique()\n",
    "\n",
    "ax.set_xticklabels(labels=x_dates, rotation=45, ha='right')\n",
    "ax.set_ylabel('')\n",
    "ax.set_xlabel('')\n",
    "ax.set_title('Normalized Excess Deaths, 2020 vs 2015-2019', size=30, pad=20)\n",
    "\n",
    "plt.annotate('Reported deaths per week in 2020 vs the same time period\\'s average in 2015-2019, and sorted by peak. Source: CDC', (0,0), (100, -70), xycoords='axes fraction', textcoords='offset points', va='top')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "us_state_abbrev = {\n",
    "    'Alabama': 'AL',\n",
    "    'Alaska': 'AK',\n",
    "    'American Samoa': 'AS',\n",
    "    'Arizona': 'AZ',\n",
    "    'Arkansas': 'AR',\n",
    "    'California': 'CA',\n",
    "    'Colorado': 'CO',\n",
    "    'Connecticut': 'CT',\n",
    "    'Delaware': 'DE',\n",
    "    'District of Columbia': 'DC',\n",
    "    'Florida': 'FL',\n",
    "    'Georgia': 'GA',\n",
    "    'Guam': 'GU',\n",
    "    'Hawaii': 'HI',\n",
    "    'Idaho': 'ID',\n",
    "    'Illinois': 'IL',\n",
    "    'Indiana': 'IN',\n",
    "    'Iowa': 'IA',\n",
    "    'Kansas': 'KS',\n",
    "    'Kentucky': 'KY',\n",
    "    'Louisiana': 'LA',\n",
    "    'Maine': 'ME',\n",
    "    'Maryland': 'MD',\n",
    "    'Massachusetts': 'MA',\n",
    "    'Michigan': 'MI',\n",
    "    'Minnesota': 'MN',\n",
    "    'Mississippi': 'MS',\n",
    "    'Missouri': 'MO',\n",
    "    'Montana': 'MT',\n",
    "    'Nebraska': 'NE',\n",
    "    'Nevada': 'NV',\n",
    "    'New Hampshire': 'NH',\n",
    "    'New Jersey': 'NJ',\n",
    "    'New Mexico': 'NM',\n",
    "    'New York': 'NY',\n",
    "    'North Carolina': 'NC',\n",
    "    'North Dakota': 'ND',\n",
    "    'Northern Mariana Islands':'MP',\n",
    "    'Ohio': 'OH',\n",
    "    'Oklahoma': 'OK',\n",
    "    'Oregon': 'OR',\n",
    "    'Pennsylvania': 'PA',\n",
    "    'Puerto Rico': 'PR',\n",
    "    'Rhode Island': 'RI',\n",
    "    'South Carolina': 'SC',\n",
    "    'South Dakota': 'SD',\n",
    "    'Tennessee': 'TN',\n",
    "    'Texas': 'TX',\n",
    "    'Utah': 'UT',\n",
    "    'Vermont': 'VT',\n",
    "    'Virgin Islands': 'VI',\n",
    "    'Virginia': 'VA',\n",
    "    'Washington': 'WA',\n",
    "    'West Virginia': 'WV',\n",
    "    'Wisconsin': 'WI',\n",
    "    'Wyoming': 'WY'\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "from chart_studio.plotly import image as PlotlyImage\n",
    "from PIL import Image as PILImage\n",
    "import io\n",
    "import chart_studio\n",
    "\n",
    "chart_studio.tools.set_credentials_file(username='hellodmo', api_key='TR6NU9TpOnIYl8bdfYgg')\n",
    "\n",
    "pivottable2 = pivottable.copy()\n",
    "\n",
    "pivottable2 = pivottable2.rename(columns=us_state_abbrev)\n",
    "\n",
    "\n",
    "sortedvalues = np.sort(pivottable2.values.flatten().flatten())\n",
    "mx = max(sortedvalues)\n",
    "rg = max(sortedvalues) - min(sortedvalues)\n",
    "mn = min(sortedvalues)\n",
    "pivottable3 = (pivottable2 - mn).div(rg)\n",
    "pivottable3 = pivottable3.resample(rule='8H').asfreq().interpolate()\n",
    "\n",
    "bins = pd.qcut(sortedvalues, q=8, retbins=True)[1]\n",
    "bins = (bins - bins.min()) / (bins.max() - bins.min())\n",
    "\n",
    "colorscale = list(zip(bins, getattr(px.colors.sequential, 'Reds')))\n",
    "\n",
    "images = []\n",
    "\n",
    "for i in np.arange(0, pivottable3.shape[0]):\n",
    "    \n",
    "    data = pivottable3.iloc[i]\n",
    "    fig = go.Figure(\n",
    "        data=go.Choropleth(\n",
    "            locations=data.index,\n",
    "            z = data,\n",
    "            locationmode = 'USA-states',\n",
    "            colorscale = colorscale,\n",
    "            showscale=False,\n",
    "            zmin=0,\n",
    "            zmax=1\n",
    "        )\n",
    "    )\n",
    "\n",
    "\n",
    "    fig.update_layout(\n",
    "        title= {\n",
    "            \"text\":'Daily Excess Deaths ' + data.name.strftime('%-m-%-d-%Y'),\n",
    "            'xanchor': 'center',\n",
    "            'x':0.5\n",
    "        },\n",
    "        font=dict(\n",
    "            size=18\n",
    "        ),\n",
    "        geo_scope='usa', # limite map scope to USA\n",
    "        annotations=[\n",
    "           go.layout.Annotation(\n",
    "                showarrow=False,\n",
    "                text='Source: CDC Excess Deaths (https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm)',\n",
    "                xanchor='center',\n",
    "                x=.5,\n",
    "                yanchor='bottom',\n",
    "                y=-0.2,\n",
    "                font=dict(\n",
    "                    size=12\n",
    "                )\n",
    "        ),\n",
    "        go.layout.Annotation(\n",
    "                showarrow=False,\n",
    "                text='Darker colors indicate a higher death rate for 2020 when compared to the same time period in 2015-2019',\n",
    "                xanchor='center',\n",
    "                x=0.5,\n",
    "                yanchor='bottom',\n",
    "                y=-0.15,\n",
    "                font=dict(\n",
    "                    size=12\n",
    "                ))]\n",
    "    )\n",
    "\n",
    "\n",
    "    img_bytes = fig.to_image(format='png')\n",
    "    image = PILImage.open(io.BytesIO(img_bytes))\n",
    "    image.save(\"gifdata/\"+str(data.name).replace(':', '-')+\".png\")\n",
    "    \n",
    "    images.append(image)\n",
    "    if i == pivottable3.shape[0] - 1:\n",
    "        for i in np.arange(0,40):\n",
    "            images.append(image)\n",
    "    \n",
    "images[0].save('gifdata/covid19-case.gif',\n",
    "               save_all=True, append_images=images[1:], optimize=True, duration=75, loop=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![SegmentLocal](gifdata/covid19-case.gif \"segment\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {},
   "outputs": [
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   ],
   "source": [
    "import plotly.express as px\n",
    "import plotly.graph_objects as go\n",
    "from chart_studio.plotly import image as PlotlyImage\n",
    "from PIL import Image as PILImage\n",
    "import io\n",
    "import chart_studio\n",
    "\n",
    "chart_studio.tools.set_credentials_file(username='hellodmo', api_key='TR6NU9TpOnIYl8bdfYgg')\n",
    "\n",
    "pivottable2 = pivottable.copy()\n",
    "\n",
    "pivottable2 = pivottable2.rename(columns=us_state_abbrev)\n",
    "\n",
    "\n",
    "sortedvalues = np.sort(pivottable2.values.flatten().flatten())\n",
    "mx = max(sortedvalues)\n",
    "rg = max(sortedvalues) - min(sortedvalues)\n",
    "mn = min(sortedvalues)\n",
    "pivottable3 = (pivottable2 - mn).div(rg)\n",
    "pivottable3 = pivottable3.resample(rule='8H').asfreq().interpolate()\n",
    "\n",
    "bins = pd.qcut(sortedvalues, q=8, retbins=True)[1]\n",
    "bins = (bins - bins.min()) / (bins.max() - bins.min())\n",
    "\n",
    "colorscale = list(zip(bins, getattr(px.colors.sequential, 'Reds')))\n",
    "\n",
    "images = []\n",
    "\n",
    "i = 20\n",
    "data = pivottable3.iloc[i]\n",
    "fig = go.Figure(\n",
    "    data=go.Choropleth(\n",
    "        locations=data.index,\n",
    "        z = data,\n",
    "        locationmode = 'USA-states',\n",
    "        colorscale = colorscale,\n",
    "        showscale=False,\n",
    "        zmin=0,\n",
    "        zmax=1, \n",
    "        text=\"blah\"\n",
    "    )\n",
    ")\n",
    "\n",
    "fig.update_layout(\n",
    "    title= {\n",
    "        \"text\":'Daily Excess Deaths ' + data.name.strftime('%-m-%-d-%Y'),\n",
    "        'xanchor': 'center',\n",
    "        'x':0.5\n",
    "    },\n",
    "    font=dict(\n",
    "        size=18\n",
    "    ),\n",
    "    geo_scope='usa', # limite map scope to USA\n",
    "    annotations=[\n",
    "       go.layout.Annotation(\n",
    "            showarrow=False,\n",
    "            text='Source: CDC Excess Deaths (https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm)',\n",
    "            xanchor='center',\n",
    "            x=.5,\n",
    "            yanchor='bottom',\n",
    "            y=-0.2,\n",
    "            font=dict(\n",
    "                size=12\n",
    "            )\n",
    "    ),\n",
    "    go.layout.Annotation(\n",
    "            showarrow=False,\n",
    "            text='Darker colors indicate a higher death rate for 2020 when compared to the same time period in 2015-2019',\n",
    "            xanchor='center',\n",
    "            x=0.5,\n",
    "            yanchor='bottom',\n",
    "            y=-0.15,\n",
    "            font=dict(\n",
    "                size=12\n",
    "            ))]\n",
    ")\n",
    "\n",
    "\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
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       "      <th>California</th>\n",
       "      <td>-3.071860</td>\n",
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       "      <th>Colorado</th>\n",
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       "      <th>District of Columbia</th>\n",
       "      <td>-42.905524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Florida</th>\n",
       "      <td>5.004240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Georgia</th>\n",
       "      <td>7.101919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hawaii</th>\n",
       "      <td>-23.273048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Idaho</th>\n",
       "      <td>4.615091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Illinois</th>\n",
       "      <td>-6.619525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Indiana</th>\n",
       "      <td>3.445376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Iowa</th>\n",
       "      <td>5.078840</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kansas</th>\n",
       "      <td>-2.061858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kentucky</th>\n",
       "      <td>0.618342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Louisiana</th>\n",
       "      <td>8.830483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maine</th>\n",
       "      <td>12.169034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Maryland</th>\n",
       "      <td>-1.657653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Massachusetts</th>\n",
       "      <td>-17.927857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Michigan</th>\n",
       "      <td>2.321767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minnesota</th>\n",
       "      <td>4.768298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mississippi</th>\n",
       "      <td>17.302332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Missouri</th>\n",
       "      <td>3.418763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Montana</th>\n",
       "      <td>-12.691236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nebraska</th>\n",
       "      <td>-1.018744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nevada</th>\n",
       "      <td>-5.737138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Hampshire</th>\n",
       "      <td>8.695979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Jersey</th>\n",
       "      <td>-7.324255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New Mexico</th>\n",
       "      <td>2.584081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York</th>\n",
       "      <td>-3.868032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>New York City</th>\n",
       "      <td>-15.970453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Carolina</th>\n",
       "      <td>-95.971254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>North Dakota</th>\n",
       "      <td>-10.987743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ohio</th>\n",
       "      <td>-14.933756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>-13.960926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Oregon</th>\n",
       "      <td>-3.484176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>5.141717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Puerto Rico</th>\n",
       "      <td>-49.296583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rhode Island</th>\n",
       "      <td>-50.090183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Carolina</th>\n",
       "      <td>14.525112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>South Dakota</th>\n",
       "      <td>4.341511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tennessee</th>\n",
       "      <td>-3.696887</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Texas</th>\n",
       "      <td>10.373537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Utah</th>\n",
       "      <td>12.197282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vermont</th>\n",
       "      <td>0.250662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virginia</th>\n",
       "      <td>4.149345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Washington</th>\n",
       "      <td>3.538526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Virginia</th>\n",
       "      <td>-92.099555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wisconsin</th>\n",
       "      <td>1.928119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wyoming</th>\n",
       "      <td>-9.811428</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Difference\n",
       "Jurisdiction                    \n",
       "Alabama                 8.202637\n",
       "Alaska                -22.466109\n",
       "Arizona                20.004098\n",
       "Arkansas                6.069210\n",
       "California             -3.071860\n",
       "Colorado              -10.503510\n",
       "Connecticut           -82.427749\n",
       "Delaware                2.337737\n",
       "District of Columbia  -42.905524\n",
       "Florida                 5.004240\n",
       "Georgia                 7.101919\n",
       "Hawaii                -23.273048\n",
       "Idaho                   4.615091\n",
       "Illinois               -6.619525\n",
       "Indiana                 3.445376\n",
       "Iowa                    5.078840\n",
       "Kansas                 -2.061858\n",
       "Kentucky                0.618342\n",
       "Louisiana               8.830483\n",
       "Maine                  12.169034\n",
       "Maryland               -1.657653\n",
       "Massachusetts         -17.927857\n",
       "Michigan                2.321767\n",
       "Minnesota               4.768298\n",
       "Mississippi            17.302332\n",
       "Missouri                3.418763\n",
       "Montana               -12.691236\n",
       "Nebraska               -1.018744\n",
       "Nevada                 -5.737138\n",
       "New Hampshire           8.695979\n",
       "New Jersey             -7.324255\n",
       "New Mexico              2.584081\n",
       "New York               -3.868032\n",
       "New York City         -15.970453\n",
       "North Carolina        -95.971254\n",
       "North Dakota          -10.987743\n",
       "Ohio                  -14.933756\n",
       "Oklahoma              -13.960926\n",
       "Oregon                 -3.484176\n",
       "Pennsylvania            5.141717\n",
       "Puerto Rico           -49.296583\n",
       "Rhode Island          -50.090183\n",
       "South Carolina         14.525112\n",
       "South Dakota            4.341511\n",
       "Tennessee              -3.696887\n",
       "Texas                  10.373537\n",
       "Utah                   12.197282\n",
       "Vermont                 0.250662\n",
       "Virginia                4.149345\n",
       "Washington              3.538526\n",
       "West Virginia         -92.099555\n",
       "Wisconsin               1.928119\n",
       "Wyoming                -9.811428"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pivottable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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