COVID-19-daily-us.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data from [The COVID Tracking project](https://covidtracking.com/)\n",
    "\n",
    "[States historical data](http://covidtracking.com/api/states/daily.csv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "mpl.style.use('fivethirtyeight')\n",
    "mpl.rcParams[\"figure.figsize\"] = (20,10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "daily = pd.read_csv(\"~/Downloads/states-daily.csv\", parse_dates=[0])\n",
    "us_daily = daily.groupby(\"date\").sum()\n",
    "ax = us_daily[[\"negative\", \"positive\", \"hospitalized\", \"death\"]].plot(logy=True)\n",
    "ax.get_yaxis().set_major_formatter(mpl.ticker.FuncFormatter(lambda x, p: format(x, \",\")))\n",
    "ax.set_xlabel(\"Date\")\n",
    "_ = ax.set_ylabel(\"US Cases\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "us_daily_ratio = pd.DataFrame(\n",
    "    {\n",
    "        \"Tested positive\": 100 * us_daily[\"positive\"] / (us_daily[\"positive\"] + us_daily[\"negative\"]),\n",
    "        \"Hospitalized\": 100 * us_daily[\"hospitalized\"] / (us_daily[\"positive\"] + us_daily[\"negative\"]),\n",
    "        \"Died\": 100 * us_daily[\"death\"] / (us_daily[\"positive\"] + us_daily[\"negative\"])\n",
    "    })\n",
    "ax = us_daily_ratio.plot(logy=True)\n",
    "ax.get_yaxis().set_major_formatter(mpl.ticker.FuncFormatter(lambda x, p: f\"{x} %\"))\n",
    "ax.set_ylim((0.01, None))\n",
    "ax.set_xlabel(\"Date\")\n",
    "_ = ax.set_ylabel(\"Percentage (US only)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2020-03-04    0.000000\n",
       "2020-03-05    0.000000\n",
       "2020-03-06    0.000000\n",
       "2020-03-07    0.000000\n",
       "2020-03-08    0.000000\n",
       "2020-03-09    0.000000\n",
       "2020-03-10    0.000000\n",
       "2020-03-11    0.379054\n",
       "2020-03-12    0.384780\n",
       "2020-03-13    0.251046\n",
       "2020-03-14    0.250614\n",
       "2020-03-15    0.233245\n",
       "2020-03-16    0.176956\n",
       "2020-03-17    0.168770\n",
       "2020-03-18    0.151443\n",
       "2020-03-19    0.158670\n",
       "2020-03-20    0.162006\n",
       "2020-03-21    0.151865\n",
       "2020-03-22    0.176620\n",
       "2020-03-23    0.168531\n",
       "2020-03-24    0.195816\n",
       "2020-03-25    0.213507\n",
       "2020-03-26    0.223939\n",
       "2020-03-27    0.244149\n",
       "Name: Died, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_daily_ratio[\"Died\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>positive</th>\n",
       "      <th>negative</th>\n",
       "      <th>pending</th>\n",
       "      <th>hospitalized</th>\n",
       "      <th>death</th>\n",
       "      <th>total</th>\n",
       "      <th>totalTestResults</th>\n",
       "      <th>fips</th>\n",
       "      <th>deathIncrease</th>\n",
       "      <th>hospitalizedIncrease</th>\n",
       "      <th>negativeIncrease</th>\n",
       "      <th>positiveIncrease</th>\n",
       "      <th>totalTestResultsIncrease</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-03-04</th>\n",
       "      <td>118.0</td>\n",
       "      <td>748.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>969</td>\n",
       "      <td>866</td>\n",
       "      <td>425</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-05</th>\n",
       "      <td>176.0</td>\n",
       "      <td>953.0</td>\n",
       "      <td>197.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1326</td>\n",
       "      <td>1129</td>\n",
       "      <td>728</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>154.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-06</th>\n",
       "      <td>223.0</td>\n",
       "      <td>1571.0</td>\n",
       "      <td>458.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2252</td>\n",
       "      <td>1794</td>\n",
       "      <td>1031</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>507.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>551.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-07</th>\n",
       "      <td>341.0</td>\n",
       "      <td>1809.0</td>\n",
       "      <td>602.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2752</td>\n",
       "      <td>2150</td>\n",
       "      <td>1477</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>194.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>307.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-08</th>\n",
       "      <td>417.0</td>\n",
       "      <td>2335.0</td>\n",
       "      <td>347.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3099</td>\n",
       "      <td>2752</td>\n",
       "      <td>1477</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>526.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>602.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-09</th>\n",
       "      <td>584.0</td>\n",
       "      <td>3367.0</td>\n",
       "      <td>313.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4264</td>\n",
       "      <td>3951</td>\n",
       "      <td>1477</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1032.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>1199.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-10</th>\n",
       "      <td>778.0</td>\n",
       "      <td>3807.0</td>\n",
       "      <td>469.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5054</td>\n",
       "      <td>4585</td>\n",
       "      <td>1477</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>440.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>634.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-11</th>\n",
       "      <td>1053.0</td>\n",
       "      <td>6070.0</td>\n",
       "      <td>563.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>7686</td>\n",
       "      <td>7123</td>\n",
       "      <td>1477</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2263.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>2538.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-12</th>\n",
       "      <td>1315.0</td>\n",
       "      <td>8041.0</td>\n",
       "      <td>673.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>10029</td>\n",
       "      <td>9356</td>\n",
       "      <td>1477</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>262.0</td>\n",
       "      <td>2233.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-13</th>\n",
       "      <td>1922.0</td>\n",
       "      <td>13613.0</td>\n",
       "      <td>1130.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>16665</td>\n",
       "      <td>15535</td>\n",
       "      <td>1477</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5572.0</td>\n",
       "      <td>607.0</td>\n",
       "      <td>6179.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-14</th>\n",
       "      <td>2450.0</td>\n",
       "      <td>17102.0</td>\n",
       "      <td>1236.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>20788</td>\n",
       "      <td>19552</td>\n",
       "      <td>1477</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3489.0</td>\n",
       "      <td>528.0</td>\n",
       "      <td>4017.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-15</th>\n",
       "      <td>3173.0</td>\n",
       "      <td>22551.0</td>\n",
       "      <td>2242.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>27966</td>\n",
       "      <td>25724</td>\n",
       "      <td>1477</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5449.0</td>\n",
       "      <td>723.0</td>\n",
       "      <td>6172.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-16</th>\n",
       "      <td>4019.0</td>\n",
       "      <td>36104.0</td>\n",
       "      <td>1691.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>41814</td>\n",
       "      <td>40123</td>\n",
       "      <td>1822</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13521.0</td>\n",
       "      <td>837.0</td>\n",
       "      <td>14358.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-17</th>\n",
       "      <td>5723.0</td>\n",
       "      <td>47604.0</td>\n",
       "      <td>1687.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>55014</td>\n",
       "      <td>53327</td>\n",
       "      <td>1822</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11500.0</td>\n",
       "      <td>1704.0</td>\n",
       "      <td>13204.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-18</th>\n",
       "      <td>7730.0</td>\n",
       "      <td>66225.0</td>\n",
       "      <td>2538.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>76493</td>\n",
       "      <td>73955</td>\n",
       "      <td>1822</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18621.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>20628.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-19</th>\n",
       "      <td>11719.0</td>\n",
       "      <td>89119.0</td>\n",
       "      <td>3025.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>103863</td>\n",
       "      <td>100838</td>\n",
       "      <td>1822</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22894.0</td>\n",
       "      <td>3989.0</td>\n",
       "      <td>26883.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-20</th>\n",
       "      <td>17033.0</td>\n",
       "      <td>118147.0</td>\n",
       "      <td>3336.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>138516</td>\n",
       "      <td>135180</td>\n",
       "      <td>1822</td>\n",
       "      <td>59.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29028.0</td>\n",
       "      <td>5314.0</td>\n",
       "      <td>34342.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-21</th>\n",
       "      <td>23197.0</td>\n",
       "      <td>155909.0</td>\n",
       "      <td>3477.0</td>\n",
       "      <td>1964.0</td>\n",
       "      <td>272.0</td>\n",
       "      <td>182583</td>\n",
       "      <td>179106</td>\n",
       "      <td>1822</td>\n",
       "      <td>53.0</td>\n",
       "      <td>1964.0</td>\n",
       "      <td>37762.0</td>\n",
       "      <td>6164.0</td>\n",
       "      <td>43926.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-22</th>\n",
       "      <td>31879.0</td>\n",
       "      <td>193463.0</td>\n",
       "      <td>2842.0</td>\n",
       "      <td>2554.0</td>\n",
       "      <td>398.0</td>\n",
       "      <td>228184</td>\n",
       "      <td>225342</td>\n",
       "      <td>1822</td>\n",
       "      <td>126.0</td>\n",
       "      <td>590.0</td>\n",
       "      <td>37554.0</td>\n",
       "      <td>8682.0</td>\n",
       "      <td>46236.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-23</th>\n",
       "      <td>42152.0</td>\n",
       "      <td>237321.0</td>\n",
       "      <td>14571.0</td>\n",
       "      <td>3325.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>294044</td>\n",
       "      <td>279473</td>\n",
       "      <td>1822</td>\n",
       "      <td>73.0</td>\n",
       "      <td>771.0</td>\n",
       "      <td>43858.0</td>\n",
       "      <td>10273.0</td>\n",
       "      <td>54131.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-24</th>\n",
       "      <td>51954.0</td>\n",
       "      <td>292758.0</td>\n",
       "      <td>14433.0</td>\n",
       "      <td>4468.0</td>\n",
       "      <td>675.0</td>\n",
       "      <td>359145</td>\n",
       "      <td>344712</td>\n",
       "      <td>1822</td>\n",
       "      <td>204.0</td>\n",
       "      <td>1143.0</td>\n",
       "      <td>55437.0</td>\n",
       "      <td>9802.0</td>\n",
       "      <td>65239.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-25</th>\n",
       "      <td>63928.0</td>\n",
       "      <td>357604.0</td>\n",
       "      <td>51235.0</td>\n",
       "      <td>6136.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>472767</td>\n",
       "      <td>421532</td>\n",
       "      <td>1822</td>\n",
       "      <td>225.0</td>\n",
       "      <td>1668.0</td>\n",
       "      <td>64846.0</td>\n",
       "      <td>11974.0</td>\n",
       "      <td>76820.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-26</th>\n",
       "      <td>80735.0</td>\n",
       "      <td>438603.0</td>\n",
       "      <td>60251.0</td>\n",
       "      <td>10131.0</td>\n",
       "      <td>1163.0</td>\n",
       "      <td>579589</td>\n",
       "      <td>519338</td>\n",
       "      <td>1822</td>\n",
       "      <td>264.0</td>\n",
       "      <td>3996.0</td>\n",
       "      <td>80999.0</td>\n",
       "      <td>16807.0</td>\n",
       "      <td>97806.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-27</th>\n",
       "      <td>99447.0</td>\n",
       "      <td>527220.0</td>\n",
       "      <td>60094.0</td>\n",
       "      <td>13717.0</td>\n",
       "      <td>1530.0</td>\n",
       "      <td>686761</td>\n",
       "      <td>626667</td>\n",
       "      <td>1822</td>\n",
       "      <td>367.0</td>\n",
       "      <td>3652.0</td>\n",
       "      <td>88617.0</td>\n",
       "      <td>18712.0</td>\n",
       "      <td>107329.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            positive  negative  pending  hospitalized   death   total  \\\n",
       "date                                                                    \n",
       "2020-03-04     118.0     748.0    103.0           0.0     0.0     969   \n",
       "2020-03-05     176.0     953.0    197.0           0.0     0.0    1326   \n",
       "2020-03-06     223.0    1571.0    458.0           0.0     0.0    2252   \n",
       "2020-03-07     341.0    1809.0    602.0           0.0     0.0    2752   \n",
       "2020-03-08     417.0    2335.0    347.0           0.0     0.0    3099   \n",
       "2020-03-09     584.0    3367.0    313.0           0.0     0.0    4264   \n",
       "2020-03-10     778.0    3807.0    469.0           0.0     0.0    5054   \n",
       "2020-03-11    1053.0    6070.0    563.0           0.0    27.0    7686   \n",
       "2020-03-12    1315.0    8041.0    673.0           0.0    36.0   10029   \n",
       "2020-03-13    1922.0   13613.0   1130.0           0.0    39.0   16665   \n",
       "2020-03-14    2450.0   17102.0   1236.0           0.0    49.0   20788   \n",
       "2020-03-15    3173.0   22551.0   2242.0           0.0    60.0   27966   \n",
       "2020-03-16    4019.0   36104.0   1691.0           0.0    71.0   41814   \n",
       "2020-03-17    5723.0   47604.0   1687.0           0.0    90.0   55014   \n",
       "2020-03-18    7730.0   66225.0   2538.0           0.0   112.0   76493   \n",
       "2020-03-19   11719.0   89119.0   3025.0           0.0   160.0  103863   \n",
       "2020-03-20   17033.0  118147.0   3336.0           0.0   219.0  138516   \n",
       "2020-03-21   23197.0  155909.0   3477.0        1964.0   272.0  182583   \n",
       "2020-03-22   31879.0  193463.0   2842.0        2554.0   398.0  228184   \n",
       "2020-03-23   42152.0  237321.0  14571.0        3325.0   471.0  294044   \n",
       "2020-03-24   51954.0  292758.0  14433.0        4468.0   675.0  359145   \n",
       "2020-03-25   63928.0  357604.0  51235.0        6136.0   900.0  472767   \n",
       "2020-03-26   80735.0  438603.0  60251.0       10131.0  1163.0  579589   \n",
       "2020-03-27   99447.0  527220.0  60094.0       13717.0  1530.0  686761   \n",
       "\n",
       "            totalTestResults  fips  deathIncrease  hospitalizedIncrease  \\\n",
       "date                                                                      \n",
       "2020-03-04               866   425            0.0                   0.0   \n",
       "2020-03-05              1129   728            0.0                   0.0   \n",
       "2020-03-06              1794  1031            0.0                   0.0   \n",
       "2020-03-07              2150  1477            0.0                   0.0   \n",
       "2020-03-08              2752  1477            0.0                   0.0   \n",
       "2020-03-09              3951  1477            0.0                   0.0   \n",
       "2020-03-10              4585  1477            0.0                   0.0   \n",
       "2020-03-11              7123  1477           27.0                   0.0   \n",
       "2020-03-12              9356  1477            9.0                   0.0   \n",
       "2020-03-13             15535  1477            3.0                   0.0   \n",
       "2020-03-14             19552  1477           10.0                   0.0   \n",
       "2020-03-15             25724  1477           11.0                   0.0   \n",
       "2020-03-16             40123  1822           11.0                   0.0   \n",
       "2020-03-17             53327  1822           19.0                   0.0   \n",
       "2020-03-18             73955  1822           22.0                   0.0   \n",
       "2020-03-19            100838  1822           48.0                   0.0   \n",
       "2020-03-20            135180  1822           59.0                   0.0   \n",
       "2020-03-21            179106  1822           53.0                1964.0   \n",
       "2020-03-22            225342  1822          126.0                 590.0   \n",
       "2020-03-23            279473  1822           73.0                 771.0   \n",
       "2020-03-24            344712  1822          204.0                1143.0   \n",
       "2020-03-25            421532  1822          225.0                1668.0   \n",
       "2020-03-26            519338  1822          264.0                3996.0   \n",
       "2020-03-27            626667  1822          367.0                3652.0   \n",
       "\n",
       "            negativeIncrease  positiveIncrease  totalTestResultsIncrease  \n",
       "date                                                                      \n",
       "2020-03-04               0.0               0.0                       0.0  \n",
       "2020-03-05              99.0              55.0                     154.0  \n",
       "2020-03-06             507.0              44.0                     551.0  \n",
       "2020-03-07             194.0             113.0                     307.0  \n",
       "2020-03-08             526.0              76.0                     602.0  \n",
       "2020-03-09            1032.0             167.0                    1199.0  \n",
       "2020-03-10             440.0             195.0                     634.0  \n",
       "2020-03-11            2263.0             275.0                    2538.0  \n",
       "2020-03-12            1971.0             262.0                    2233.0  \n",
       "2020-03-13            5572.0             607.0                    6179.0  \n",
       "2020-03-14            3489.0             528.0                    4017.0  \n",
       "2020-03-15            5449.0             723.0                    6172.0  \n",
       "2020-03-16           13521.0             837.0                   14358.0  \n",
       "2020-03-17           11500.0            1704.0                   13204.0  \n",
       "2020-03-18           18621.0            2007.0                   20628.0  \n",
       "2020-03-19           22894.0            3989.0                   26883.0  \n",
       "2020-03-20           29028.0            5314.0                   34342.0  \n",
       "2020-03-21           37762.0            6164.0                   43926.0  \n",
       "2020-03-22           37554.0            8682.0                   46236.0  \n",
       "2020-03-23           43858.0           10273.0                   54131.0  \n",
       "2020-03-24           55437.0            9802.0                   65239.0  \n",
       "2020-03-25           64846.0           11974.0                   76820.0  \n",
       "2020-03-26           80999.0           16807.0                   97806.0  \n",
       "2020-03-27           88617.0           18712.0                  107329.0  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "us_daily"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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