52_Week-Covid-2020.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as mp\n",
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "#import finnhub\n",
    "from pprint import pprint\n",
    "from datetime import datetime\n",
    "from config import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[{'case': 418793,\n",
      "  'death': 32658,\n",
      "  'state': 'New York',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 180766,\n",
      "  'death': 15886,\n",
      "  'state': 'New Jersey',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 483845,\n",
      "  'death': 8885,\n",
      "  'state': 'California',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 88976,\n",
      "  'death': 6430,\n",
      "  'state': 'Michigan',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 451423,\n",
      "  'death': 6333,\n",
      "  'state': 'Florida',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 116684,\n",
      "  'death': 8580,\n",
      "  'state': 'Massachusetts',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 55197,\n",
      "  'death': 1562,\n",
      "  'state': 'Washington',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 112773,\n",
      "  'death': 3883,\n",
      "  'state': 'Louisiana',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 175124,\n",
      "  'death': 7463,\n",
      "  'state': 'Illinois',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 114888,\n",
      "  'death': 7167,\n",
      "  'state': 'Pennsylvania',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 175052,\n",
      "  'death': 3563,\n",
      "  'state': 'Georgia',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 418995,\n",
      "  'death': 6193,\n",
      "  'state': 'Texas',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 45875,\n",
      "  'death': 1822,\n",
      "  'state': 'Colorado',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 49540,\n",
      "  'death': 4425,\n",
      "  'state': 'Connecticut',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 87894,\n",
      "  'death': 3423,\n",
      "  'state': 'Ohio',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 64299,\n",
      "  'death': 2932,\n",
      "  'state': 'Indiana',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 100822,\n",
      "  'death': 1021,\n",
      "  'state': 'Tennessee',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 86285,\n",
      "  'death': 3478,\n",
      "  'state': 'Maryland',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 116088,\n",
      "  'death': 1820,\n",
      "  'state': 'North Carolina',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 51049,\n",
      "  'death': 912,\n",
      "  'state': 'Wisconsin',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 168273,\n",
      "  'death': 3454,\n",
      "  'state': 'Arizona',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 87993,\n",
      "  'death': 2125,\n",
      "  'state': 'Virginia',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 47664,\n",
      "  'death': 1271,\n",
      "  'state': 'Missouri',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 45919,\n",
      "  'death': 782,\n",
      "  'state': 'Nevada',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 83782,\n",
      "  'death': 1538,\n",
      "  'state': 'Alabama',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 55804,\n",
      "  'death': 1563,\n",
      "  'state': 'Mississippi',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 85423,\n",
      "  'death': 1551,\n",
      "  'state': 'South Carolina',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 39194,\n",
      "  'death': 292,\n",
      "  'state': 'Utah',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 52947,\n",
      "  'death': 1629,\n",
      "  'state': 'Minnesota',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 17721,\n",
      "  'death': 311,\n",
      "  'state': 'Oregon',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 34612,\n",
      "  'death': 523,\n",
      "  'state': 'Oklahoma',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 40968,\n",
      "  'death': 434,\n",
      "  'state': 'Arkansas',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 43294,\n",
      "  'death': 848,\n",
      "  'state': 'Iowa',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 11999,\n",
      "  'death': 584,\n",
      "  'state': 'Washington, D.C.',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 28727,\n",
      "  'death': 724,\n",
      "  'state': 'Kentucky',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 19673,\n",
      "  'death': 173,\n",
      "  'state': 'Idaho',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 18800,\n",
      "  'death': 1007,\n",
      "  'state': 'Rhode Island',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 26591,\n",
      "  'death': 349,\n",
      "  'state': 'Kansas',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 6513,\n",
      "  'death': 411,\n",
      "  'state': 'New Hampshire',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 3866,\n",
      "  'death': 121,\n",
      "  'state': 'Maine',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 1406,\n",
      "  'death': 56,\n",
      "  'state': 'Vermont',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 20136,\n",
      "  'death': 632,\n",
      "  'state': 'New Mexico',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 14602,\n",
      "  'death': 581,\n",
      "  'state': 'Delaware',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 16061,\n",
      "  'death': 211,\n",
      "  'state': 'Puerto Rico',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 1865,\n",
      "  'death': 26,\n",
      "  'state': 'Hawaii',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 3676,\n",
      "  'death': 54,\n",
      "  'state': 'Montana',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 25350,\n",
      "  'death': 325,\n",
      "  'state': 'Nebraska',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 8927,\n",
      "  'death': 453,\n",
      "  'state': 'Navajo Nation',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 6277,\n",
      "  'death': 111,\n",
      "  'state': 'West Virginia',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 6227,\n",
      "  'death': 102,\n",
      "  'state': 'North Dakota',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 2798,\n",
      "  'death': 22,\n",
      "  'state': 'Alaska',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 2628,\n",
      "  'death': 26,\n",
      "  'state': 'Wyoming',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 8639,\n",
      "  'death': 129,\n",
      "  'state': 'South Dakota',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 103,\n",
      "  'death': 3,\n",
      "  'state': 'Grand Princess',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 351, 'death': 5, 'state': 'Guam', 'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 49,\n",
      "  'death': 0,\n",
      "  'state': 'Diamond Princess',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 385,\n",
      "  'death': 8,\n",
      "  'state': 'US Virgin Islands',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 4,\n",
      "  'death': 0,\n",
      "  'state': 'Wuhan Evacuee',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 31,\n",
      "  'death': 2,\n",
      "  'state': 'Northern Mariana Islands',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 37824,\n",
      "  'death': 58,\n",
      "  'state': 'US Military',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 11692,\n",
      "  'death': 104,\n",
      "  'state': 'Federal Bureau of Prisons',\n",
      "  'updated': '2020-07-29 22:01:15'},\n",
      " {'case': 38022,\n",
      "  'death': 2071,\n",
      "  'state': 'Veteran Affair',\n",
      "  'updated': '2020-07-29 22:01:15'}]\n"
     ]
    }
   ],
   "source": [
    "states = []\n",
    "cases = []\n",
    "deaths = []\n",
    "\n",
    "\n",
    "r = requests.get(f'https://finnhub.io/api/v1/covid19/us?token={Api_key}').json()\n",
    "for i in range(len(r)):\n",
    "    result=r[i]\n",
    "    states.append(result['state'])\n",
    "    cases.append(result['case'])\n",
    "    deaths.append(result['death'])\n",
    "\n",
    "pprint(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>States</th>\n",
       "      <th>Cases</th>\n",
       "      <th>Deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>New York</td>\n",
       "      <td>418793</td>\n",
       "      <td>32658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>New Jersey</td>\n",
       "      <td>180766</td>\n",
       "      <td>15886</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>California</td>\n",
       "      <td>483845</td>\n",
       "      <td>8885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Michigan</td>\n",
       "      <td>88976</td>\n",
       "      <td>6430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Florida</td>\n",
       "      <td>451423</td>\n",
       "      <td>6333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Wuhan Evacuee</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Northern Mariana Islands</td>\n",
       "      <td>31</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>US Military</td>\n",
       "      <td>37824</td>\n",
       "      <td>58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>Federal Bureau of Prisons</td>\n",
       "      <td>11692</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>Veteran Affair</td>\n",
       "      <td>38022</td>\n",
       "      <td>2071</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>62 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       States   Cases  Deaths\n",
       "0                    New York  418793   32658\n",
       "1                  New Jersey  180766   15886\n",
       "2                  California  483845    8885\n",
       "3                    Michigan   88976    6430\n",
       "4                     Florida  451423    6333\n",
       "..                        ...     ...     ...\n",
       "57              Wuhan Evacuee       4       0\n",
       "58   Northern Mariana Islands      31       2\n",
       "59                US Military   37824      58\n",
       "60  Federal Bureau of Prisons   11692     104\n",
       "61             Veteran Affair   38022    2071\n",
       "\n",
       "[62 rows x 3 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_dict = {\n",
    "    \"States\" : states,\n",
    "    \"Cases\" : cases,\n",
    "    \"Deaths\" : deaths\n",
    "}\n",
    "\n",
    "covid_df = pd.DataFrame(state_dict)\n",
    "\n",
    "#dow_high_df['Dow 52 Week High Date'] = pd.to_datetime(dow_high_df['Dow 52 Week High Date'])\n",
    "\n",
    "covid_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,3))\n",
    "x_axis = covid_df['States']\n",
    "y_axis = covid_df['Cases']\n",
    "\n",
    "plt.bar(x_axis, y_axis, color='r', align=\"center\",)\n",
    "\n",
    "\n",
    "tick_locations = [value for value in x_axis] \n",
    "plt.xticks(tick_locations,states,rotation = 'vertical')\n",
    "\n",
    "\n",
    "plt.xlim(-0.75, len(x_axis)-0.25)\n",
    "\n",
    "plt.ylim(0, max(y_axis)+5000)\n",
    "\n",
    "plt.title(\"Number of Reported COVID-19 Cases\")\n",
    "plt.xlabel(\"Locations\")\n",
    "plt.ylabel(\"Number of Cases\")\n",
    "plt.savefig('Figures/Number of Reported COVID-19 Cases')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2160x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "multi_plot = covid_df.plot(kind='bar',figsize=(30,7))\n",
    "multi_plot.set_xticklabels(covid_df['States'],rotation=45)\n",
    "\n",
    "plt.title(\"Cases of COVID-19 Reported YTD\")\n",
    "plt.xlabel(\"State\")\n",
    "plt.ylabel(\"Number of Cases\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>fips</th>\n",
       "      <th>cases</th>\n",
       "      <th>deaths</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>349985.000000</td>\n",
       "      <td>353568.000000</td>\n",
       "      <td>353568.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>30894.289915</td>\n",
       "      <td>555.445561</td>\n",
       "      <td>27.939729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>16119.490698</td>\n",
       "      <td>4362.965552</td>\n",
       "      <td>366.432188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1001.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>18133.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>29147.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>46053.000000</td>\n",
       "      <td>169.000000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>78030.000000</td>\n",
       "      <td>226388.000000</td>\n",
       "      <td>22882.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                fips          cases         deaths\n",
       "count  349985.000000  353568.000000  353568.000000\n",
       "mean    30894.289915     555.445561      27.939729\n",
       "std     16119.490698    4362.965552     366.432188\n",
       "min      1001.000000       0.000000       0.000000\n",
       "25%     18133.000000       7.000000       0.000000\n",
       "50%     29147.000000      35.000000       1.000000\n",
       "75%     46053.000000     169.000000       5.000000\n",
       "max     78030.000000  226388.000000   22882.000000"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Daily_State_Count = pd.read_csv('Resources/us_counties_covid19_daily.csv')\n",
    "\n",
    "Daily_State_Count.head()\n",
    "\n",
    "Daily_State_Count.describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>fips</th>\n",
       "      <th>cases</th>\n",
       "      <th>deaths</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-21</th>\n",
       "      <td>53061.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-22</th>\n",
       "      <td>53061.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-23</th>\n",
       "      <td>53061.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-24</th>\n",
       "      <td>70092.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-25</th>\n",
       "      <td>76151.0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               fips  cases  deaths\n",
       "date                              \n",
       "2020-01-21  53061.0      1       0\n",
       "2020-01-22  53061.0      1       0\n",
       "2020-01-23  53061.0      1       0\n",
       "2020-01-24  70092.0      2       0\n",
       "2020-01-25  76151.0      3       0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_df1 = Daily_State_Count.groupby(\"date\").sum()\n",
    "\n",
    "grouped_df1.head()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>fips</th>\n",
       "      <th>cases</th>\n",
       "      <th>deaths</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-03-01</th>\n",
       "      <td>526283.0</td>\n",
       "      <td>88</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-02</th>\n",
       "      <td>662647.0</td>\n",
       "      <td>104</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-03</th>\n",
       "      <td>705843.0</td>\n",
       "      <td>125</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-04</th>\n",
       "      <td>877129.0</td>\n",
       "      <td>161</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-05</th>\n",
       "      <td>1149865.0</td>\n",
       "      <td>228</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-06</th>\n",
       "      <td>1881392.0</td>\n",
       "      <td>311</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-07</th>\n",
       "      <td>2400681.0</td>\n",
       "      <td>428</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-08</th>\n",
       "      <td>2958807.0</td>\n",
       "      <td>547</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-09</th>\n",
       "      <td>3445851.0</td>\n",
       "      <td>748</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-10</th>\n",
       "      <td>4435704.0</td>\n",
       "      <td>1018</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-11</th>\n",
       "      <td>5672288.0</td>\n",
       "      <td>1263</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-12</th>\n",
       "      <td>7210959.0</td>\n",
       "      <td>1668</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-13</th>\n",
       "      <td>8899033.0</td>\n",
       "      <td>2224</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-14</th>\n",
       "      <td>10628898.0</td>\n",
       "      <td>2898</td>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-15</th>\n",
       "      <td>12047406.0</td>\n",
       "      <td>3600</td>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-16</th>\n",
       "      <td>13347846.0</td>\n",
       "      <td>4507</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-17</th>\n",
       "      <td>15510123.0</td>\n",
       "      <td>5906</td>\n",
       "      <td>117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-18</th>\n",
       "      <td>18326466.0</td>\n",
       "      <td>8350</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-19</th>\n",
       "      <td>21533169.0</td>\n",
       "      <td>12393</td>\n",
       "      <td>212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-20</th>\n",
       "      <td>26145621.0</td>\n",
       "      <td>18012</td>\n",
       "      <td>277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-21</th>\n",
       "      <td>29613981.0</td>\n",
       "      <td>24528</td>\n",
       "      <td>360</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-22</th>\n",
       "      <td>32696806.0</td>\n",
       "      <td>33073</td>\n",
       "      <td>458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-23</th>\n",
       "      <td>35108998.0</td>\n",
       "      <td>43505</td>\n",
       "      <td>579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-24</th>\n",
       "      <td>38516422.0</td>\n",
       "      <td>53938</td>\n",
       "      <td>785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-25</th>\n",
       "      <td>44387128.0</td>\n",
       "      <td>68572</td>\n",
       "      <td>1054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-26</th>\n",
       "      <td>48260361.0</td>\n",
       "      <td>85570</td>\n",
       "      <td>1353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-27</th>\n",
       "      <td>51843916.0</td>\n",
       "      <td>102900</td>\n",
       "      <td>1765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-28</th>\n",
       "      <td>55164663.0</td>\n",
       "      <td>123966</td>\n",
       "      <td>2292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-29</th>\n",
       "      <td>57926105.0</td>\n",
       "      <td>142486</td>\n",
       "      <td>2707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-30</th>\n",
       "      <td>60668022.0</td>\n",
       "      <td>163955</td>\n",
       "      <td>3354</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>62959111.0</td>\n",
       "      <td>188461</td>\n",
       "      <td>4289</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  fips   cases  deaths\n",
       "date                                  \n",
       "2020-03-01    526283.0      88       3\n",
       "2020-03-02    662647.0     104       6\n",
       "2020-03-03    705843.0     125      10\n",
       "2020-03-04    877129.0     161      12\n",
       "2020-03-05   1149865.0     228      12\n",
       "2020-03-06   1881392.0     311      15\n",
       "2020-03-07   2400681.0     428      19\n",
       "2020-03-08   2958807.0     547      22\n",
       "2020-03-09   3445851.0     748      26\n",
       "2020-03-10   4435704.0    1018      31\n",
       "2020-03-11   5672288.0    1263      37\n",
       "2020-03-12   7210959.0    1668      43\n",
       "2020-03-13   8899033.0    2224      50\n",
       "2020-03-14  10628898.0    2898      60\n",
       "2020-03-15  12047406.0    3600      68\n",
       "2020-03-16  13347846.0    4507      91\n",
       "2020-03-17  15510123.0    5906     117\n",
       "2020-03-18  18326466.0    8350     162\n",
       "2020-03-19  21533169.0   12393     212\n",
       "2020-03-20  26145621.0   18012     277\n",
       "2020-03-21  29613981.0   24528     360\n",
       "2020-03-22  32696806.0   33073     458\n",
       "2020-03-23  35108998.0   43505     579\n",
       "2020-03-24  38516422.0   53938     785\n",
       "2020-03-25  44387128.0   68572    1054\n",
       "2020-03-26  48260361.0   85570    1353\n",
       "2020-03-27  51843916.0  102900    1765\n",
       "2020-03-28  55164663.0  123966    2292\n",
       "2020-03-29  57926105.0  142486    2707\n",
       "2020-03-30  60668022.0  163955    3354\n",
       "2020-03-31  62959111.0  188461    4289"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date_covid = grouped_df1.loc[(grouped_df1.index>='2020-03-01')&(grouped_df1.index<='2020-03-31')]\n",
    "\n",
    "date_covid\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "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": [
    "x_axis = date_covid.index\n",
    "y_axis = date_covid['cases']\n",
    "y_axis2 = date_covid['deaths']\n",
    "\n",
    "plt.plot(x_axis,y_axis)\n",
    "plt.plot(x_axis,y_axis2)\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots()\n",
    "\n",
    "fig.suptitle('March 2020 COVID-19 Statistics')\n",
    "\n",
    "ax1.plot(x_axis,y_axis, color=\"#dd0011\",label='Cases')\n",
    "plt.xticks(rotation='vertical')\n",
    "plt.legend(loc='center left',bbox_to_anchor=(0,.85))\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(x_axis, y_axis2,label='Deaths')\n",
    "ax2.tick_params(axis='y')\n",
    "ax1.set_ylabel(\"Number of Cases\")\n",
    "ax2.set_ylabel(\"Number of Deaths\")\n",
    "plt.legend(loc='best')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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