Folium Maps.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import folium\n",
    "from folium import plugins\n",
    "import ipywidgets\n",
    "import geocoder\n",
    "import geopy\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from vega_datasets import data as vds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_confirmed = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv')\n",
    "df_deaths = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Deaths.csv')\n",
    "df_recovered = pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Recovered.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "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>Province/State</th>\n",
       "      <th>Country/Region</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>1/22/20</th>\n",
       "      <th>1/23/20</th>\n",
       "      <th>1/24/20</th>\n",
       "      <th>1/25/20</th>\n",
       "      <th>1/26/20</th>\n",
       "      <th>1/27/20</th>\n",
       "      <th>...</th>\n",
       "      <th>3/8/20</th>\n",
       "      <th>3/9/20</th>\n",
       "      <th>3/10/20</th>\n",
       "      <th>3/11/20</th>\n",
       "      <th>3/12/20</th>\n",
       "      <th>3/13/20</th>\n",
       "      <th>3/14/20</th>\n",
       "      <th>3/15/20</th>\n",
       "      <th>3/16/20</th>\n",
       "      <th>3/17/20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Thailand</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>101.0000</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>...</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>53</td>\n",
       "      <td>59</td>\n",
       "      <td>70</td>\n",
       "      <td>75</td>\n",
       "      <td>82</td>\n",
       "      <td>114</td>\n",
       "      <td>147</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Japan</td>\n",
       "      <td>36.0000</td>\n",
       "      <td>138.0000</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>502</td>\n",
       "      <td>511</td>\n",
       "      <td>581</td>\n",
       "      <td>639</td>\n",
       "      <td>639</td>\n",
       "      <td>701</td>\n",
       "      <td>773</td>\n",
       "      <td>839</td>\n",
       "      <td>825</td>\n",
       "      <td>878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>1.2833</td>\n",
       "      <td>103.8333</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>...</td>\n",
       "      <td>150</td>\n",
       "      <td>150</td>\n",
       "      <td>160</td>\n",
       "      <td>178</td>\n",
       "      <td>178</td>\n",
       "      <td>200</td>\n",
       "      <td>212</td>\n",
       "      <td>226</td>\n",
       "      <td>243</td>\n",
       "      <td>266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Nepal</td>\n",
       "      <td>28.1667</td>\n",
       "      <td>84.2500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Malaysia</td>\n",
       "      <td>2.5000</td>\n",
       "      <td>112.5000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>99</td>\n",
       "      <td>117</td>\n",
       "      <td>129</td>\n",
       "      <td>149</td>\n",
       "      <td>149</td>\n",
       "      <td>197</td>\n",
       "      <td>238</td>\n",
       "      <td>428</td>\n",
       "      <td>566</td>\n",
       "      <td>673</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 60 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Province/State Country/Region      Lat      Long  1/22/20  1/23/20  1/24/20  \\\n",
       "0            NaN       Thailand  15.0000  101.0000        2        3        5   \n",
       "1            NaN          Japan  36.0000  138.0000        2        1        2   \n",
       "2            NaN      Singapore   1.2833  103.8333        0        1        3   \n",
       "3            NaN          Nepal  28.1667   84.2500        0        0        0   \n",
       "4            NaN       Malaysia   2.5000  112.5000        0        0        0   \n",
       "\n",
       "   1/25/20  1/26/20  1/27/20  ...  3/8/20  3/9/20  3/10/20  3/11/20  3/12/20  \\\n",
       "0        7        8        8  ...      50      50       53       59       70   \n",
       "1        2        4        4  ...     502     511      581      639      639   \n",
       "2        3        4        5  ...     150     150      160      178      178   \n",
       "3        1        1        1  ...       1       1        1        1        1   \n",
       "4        3        4        4  ...      99     117      129      149      149   \n",
       "\n",
       "   3/13/20  3/14/20  3/15/20  3/16/20  3/17/20  \n",
       "0       75       82      114      147      177  \n",
       "1      701      773      839      825      878  \n",
       "2      200      212      226      243      266  \n",
       "3        1        1        1        1        1  \n",
       "4      197      238      428      566      673  \n",
       "\n",
       "[5 rows x 60 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_confirmed.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1.2 Tidying the data\n",
    "# Using melt() command in pandas (similar to gather() in R's tidyr)\n",
    "id_list = df_confirmed.columns.to_list()[:4]\n",
    "vars_list = df_confirmed.columns.to_list()[4:]\n",
    "confirmed_tidy = pd.melt(df_confirmed, id_vars=id_list,\\\n",
    "     value_vars=vars_list, var_name='Date', value_name='Confirmed')\n",
    "deaths_tidy = pd.melt(df_deaths, id_vars=id_list,\\\n",
    "     value_vars=vars_list, var_name='Date', value_name='Deaths')\n",
    "recovered_tidy = pd.melt(df_recovered, id_vars=id_list,\\\n",
    "     value_vars=vars_list, var_name='Date', value_name='recovered')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from functools import reduce\n",
    "data_frames = [confirmed_tidy, deaths_tidy, recovered_tidy]          \n",
    "df_corona = reduce(lambda left, right: pd.merge(left, right, on =\\\n",
    "               id_list+['Date'], how='outer'), data_frames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Province/State</th>\n",
       "      <th>Country/Region</th>\n",
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       "      <td>25755</td>\n",
       "      <td>Cayman Islands</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>19.3133</td>\n",
       "      <td>-81.2546</td>\n",
       "      <td>3/17/20</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <td>25756</td>\n",
       "      <td>Reunion</td>\n",
       "      <td>France</td>\n",
       "      <td>-21.1351</td>\n",
       "      <td>55.2471</td>\n",
       "      <td>3/17/20</td>\n",
       "      <td>9</td>\n",
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       "      <td>25757</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Barbados</td>\n",
       "      <td>13.1939</td>\n",
       "      <td>-59.5432</td>\n",
       "      <td>3/17/20</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <td>25758</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Montenegro</td>\n",
       "      <td>42.5000</td>\n",
       "      <td>19.3000</td>\n",
       "      <td>3/17/20</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <td>25759</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Gambia</td>\n",
       "      <td>13.4667</td>\n",
       "      <td>-16.6000</td>\n",
       "      <td>3/17/20</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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      ],
      "text/plain": [
       "       Province/State  Country/Region      Lat     Long     Date  Confirmed  \\\n",
       "25755  Cayman Islands  United Kingdom  19.3133 -81.2546  3/17/20          1   \n",
       "25756         Reunion          France -21.1351  55.2471  3/17/20          9   \n",
       "25757             NaN        Barbados  13.1939 -59.5432  3/17/20          2   \n",
       "25758             NaN      Montenegro  42.5000  19.3000  3/17/20          2   \n",
       "25759             NaN      The Gambia  13.4667 -16.6000  3/17/20          1   \n",
       "\n",
       "       Deaths  recovered  \n",
       "25755       1          0  \n",
       "25756       0          0  \n",
       "25757       0          0  \n",
       "25758       0          0  \n",
       "25759       0          0  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_corona.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "corona_sums = df_corona.groupby(['Province/State','Country/Region', 'Lat', 'Long'])['Confirmed'].sum().reset_index()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Province/State</th>\n",
       "      <th>Country/Region</th>\n",
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       "      <th>Confirmed</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <td>267</td>\n",
       "      <td>Spotsylvania, VA</td>\n",
       "      <td>US</td>\n",
       "      <td>38.2042</td>\n",
       "      <td>-77.6078</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>268</td>\n",
       "      <td>St Martin</td>\n",
       "      <td>France</td>\n",
       "      <td>18.0708</td>\n",
       "      <td>-63.0501</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>269</td>\n",
       "      <td>St. Joseph, IN</td>\n",
       "      <td>US</td>\n",
       "      <td>41.6228</td>\n",
       "      <td>-86.3377</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>270</td>\n",
       "      <td>St. Louis County, MO</td>\n",
       "      <td>US</td>\n",
       "      <td>38.6103</td>\n",
       "      <td>-90.4125</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>271</td>\n",
       "      <td>Stanislaus, CA</td>\n",
       "      <td>US</td>\n",
       "      <td>37.5091</td>\n",
       "      <td>-120.9876</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>272</td>\n",
       "      <td>Stark, OH</td>\n",
       "      <td>US</td>\n",
       "      <td>40.8685</td>\n",
       "      <td>-81.2519</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>273</td>\n",
       "      <td>Suffolk County, MA</td>\n",
       "      <td>US</td>\n",
       "      <td>42.3601</td>\n",
       "      <td>-71.0589</td>\n",
       "      <td>56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>274</td>\n",
       "      <td>Suffolk County, NY</td>\n",
       "      <td>US</td>\n",
       "      <td>40.9849</td>\n",
       "      <td>-72.6151</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>275</td>\n",
       "      <td>Sullivan, TN</td>\n",
       "      <td>US</td>\n",
       "      <td>36.4933</td>\n",
       "      <td>-82.3452</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>276</td>\n",
       "      <td>Summit County, CO</td>\n",
       "      <td>US</td>\n",
       "      <td>39.5912</td>\n",
       "      <td>-106.0640</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>277</td>\n",
       "      <td>Summit, UT</td>\n",
       "      <td>US</td>\n",
       "      <td>40.8298</td>\n",
       "      <td>-110.9984</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>278</td>\n",
       "      <td>Tarrant, TX</td>\n",
       "      <td>US</td>\n",
       "      <td>32.7732</td>\n",
       "      <td>-97.3517</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>279</td>\n",
       "      <td>Tasmania</td>\n",
       "      <td>Australia</td>\n",
       "      <td>-41.4545</td>\n",
       "      <td>145.9707</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>280</td>\n",
       "      <td>Tennessee</td>\n",
       "      <td>US</td>\n",
       "      <td>35.7478</td>\n",
       "      <td>-86.6923</td>\n",
       "      <td>257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>281</td>\n",
       "      <td>Texas</td>\n",
       "      <td>US</td>\n",
       "      <td>31.0545</td>\n",
       "      <td>-97.5635</td>\n",
       "      <td>428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>282</td>\n",
       "      <td>Thurston, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>46.8646</td>\n",
       "      <td>-122.7696</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>283</td>\n",
       "      <td>Tianjin</td>\n",
       "      <td>China</td>\n",
       "      <td>39.3054</td>\n",
       "      <td>117.3230</td>\n",
       "      <td>5640</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>284</td>\n",
       "      <td>Tibet</td>\n",
       "      <td>China</td>\n",
       "      <td>31.6927</td>\n",
       "      <td>88.0924</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>285</td>\n",
       "      <td>Tulsa County, OK</td>\n",
       "      <td>US</td>\n",
       "      <td>36.1593</td>\n",
       "      <td>-95.9410</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>286</td>\n",
       "      <td>Ulster County, NY</td>\n",
       "      <td>US</td>\n",
       "      <td>41.8586</td>\n",
       "      <td>-74.3118</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>287</td>\n",
       "      <td>Umatilla, OR</td>\n",
       "      <td>US</td>\n",
       "      <td>45.7750</td>\n",
       "      <td>-118.7606</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>288</td>\n",
       "      <td>Union, NJ</td>\n",
       "      <td>US</td>\n",
       "      <td>40.6976</td>\n",
       "      <td>-74.2632</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>289</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>55.3781</td>\n",
       "      <td>-3.4360</td>\n",
       "      <td>9399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>290</td>\n",
       "      <td>Utah</td>\n",
       "      <td>US</td>\n",
       "      <td>40.1500</td>\n",
       "      <td>-111.8624</td>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>291</td>\n",
       "      <td>Ventura, CA</td>\n",
       "      <td>US</td>\n",
       "      <td>34.3705</td>\n",
       "      <td>-119.1391</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>292</td>\n",
       "      <td>Vermont</td>\n",
       "      <td>US</td>\n",
       "      <td>44.0459</td>\n",
       "      <td>-72.7107</td>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>293</td>\n",
       "      <td>Victoria</td>\n",
       "      <td>Australia</td>\n",
       "      <td>-37.8136</td>\n",
       "      <td>144.9631</td>\n",
       "      <td>587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>294</td>\n",
       "      <td>Virgin Islands</td>\n",
       "      <td>US</td>\n",
       "      <td>18.3358</td>\n",
       "      <td>-64.8963</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>295</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>US</td>\n",
       "      <td>37.7693</td>\n",
       "      <td>-78.1700</td>\n",
       "      <td>265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>296</td>\n",
       "      <td>Volusia County, FL</td>\n",
       "      <td>US</td>\n",
       "      <td>29.0280</td>\n",
       "      <td>-81.0755</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>297</td>\n",
       "      <td>Wake County, NC</td>\n",
       "      <td>US</td>\n",
       "      <td>35.8032</td>\n",
       "      <td>-78.5661</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>298</td>\n",
       "      <td>Washington</td>\n",
       "      <td>US</td>\n",
       "      <td>47.4009</td>\n",
       "      <td>-121.4905</td>\n",
       "      <td>4838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>299</td>\n",
       "      <td>Washington County, OR</td>\n",
       "      <td>US</td>\n",
       "      <td>45.5470</td>\n",
       "      <td>-123.1386</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>300</td>\n",
       "      <td>Washington, D.C.</td>\n",
       "      <td>US</td>\n",
       "      <td>38.9072</td>\n",
       "      <td>-77.0369</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>301</td>\n",
       "      <td>Washoe County, NV</td>\n",
       "      <td>US</td>\n",
       "      <td>40.5608</td>\n",
       "      <td>-119.6035</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>302</td>\n",
       "      <td>Wayne County, PA</td>\n",
       "      <td>US</td>\n",
       "      <td>41.6739</td>\n",
       "      <td>-75.2479</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>303</td>\n",
       "      <td>Wayne, MI</td>\n",
       "      <td>US</td>\n",
       "      <td>42.2791</td>\n",
       "      <td>-83.3362</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>304</td>\n",
       "      <td>Weber, UT</td>\n",
       "      <td>US</td>\n",
       "      <td>41.2603</td>\n",
       "      <td>-111.9522</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>305</td>\n",
       "      <td>West Virginia</td>\n",
       "      <td>US</td>\n",
       "      <td>38.4912</td>\n",
       "      <td>-80.9545</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>306</td>\n",
       "      <td>Westchester County, NY</td>\n",
       "      <td>US</td>\n",
       "      <td>41.1220</td>\n",
       "      <td>-73.7949</td>\n",
       "      <td>286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>307</td>\n",
       "      <td>Western Australia</td>\n",
       "      <td>Australia</td>\n",
       "      <td>-31.9505</td>\n",
       "      <td>115.8605</td>\n",
       "      <td>157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>308</td>\n",
       "      <td>Whatcom, WA</td>\n",
       "      <td>US</td>\n",
       "      <td>48.8787</td>\n",
       "      <td>-121.9719</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>309</td>\n",
       "      <td>Williamson County, TN</td>\n",
       "      <td>US</td>\n",
       "      <td>35.9179</td>\n",
       "      <td>-86.8622</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>310</td>\n",
       "      <td>Wisconsin</td>\n",
       "      <td>US</td>\n",
       "      <td>44.2685</td>\n",
       "      <td>-89.6165</td>\n",
       "      <td>214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>311</td>\n",
       "      <td>Worcester, MA</td>\n",
       "      <td>US</td>\n",
       "      <td>42.4097</td>\n",
       "      <td>-71.8571</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>312</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>US</td>\n",
       "      <td>42.7560</td>\n",
       "      <td>-107.3025</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>313</td>\n",
       "      <td>Xinjiang</td>\n",
       "      <td>China</td>\n",
       "      <td>41.1129</td>\n",
       "      <td>85.2401</td>\n",
       "      <td>3067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>314</td>\n",
       "      <td>Yolo County, CA</td>\n",
       "      <td>US</td>\n",
       "      <td>38.7646</td>\n",
       "      <td>-121.9018</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>315</td>\n",
       "      <td>Yunnan</td>\n",
       "      <td>China</td>\n",
       "      <td>24.9740</td>\n",
       "      <td>101.4870</td>\n",
       "      <td>7758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>316</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>China</td>\n",
       "      <td>29.1832</td>\n",
       "      <td>120.0934</td>\n",
       "      <td>53797</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Province/State  Country/Region      Lat      Long  Confirmed\n",
       "267        Spotsylvania, VA              US  38.2042  -77.6078          0\n",
       "268               St Martin          France  18.0708  -63.0501         18\n",
       "269          St. Joseph, IN              US  41.6228  -86.3377          0\n",
       "270    St. Louis County, MO              US  38.6103  -90.4125          2\n",
       "271          Stanislaus, CA              US  37.5091 -120.9876          0\n",
       "272               Stark, OH              US  40.8685  -81.2519          0\n",
       "273      Suffolk County, MA              US  42.3601  -71.0589         56\n",
       "274      Suffolk County, NY              US  40.9849  -72.6151          2\n",
       "275            Sullivan, TN              US  36.4933  -82.3452          0\n",
       "276       Summit County, CO              US  39.5912 -106.0640          4\n",
       "277              Summit, UT              US  40.8298 -110.9984          0\n",
       "278             Tarrant, TX              US  32.7732  -97.3517          0\n",
       "279                Tasmania       Australia -41.4545  145.9707         48\n",
       "280               Tennessee              US  35.7478  -86.6923        257\n",
       "281                   Texas              US  31.0545  -97.5635        428\n",
       "282            Thurston, WA              US  46.8646 -122.7696          0\n",
       "283                 Tianjin           China  39.3054  117.3230       5640\n",
       "284                   Tibet           China  31.6927   88.0924         48\n",
       "285        Tulsa County, OK              US  36.1593  -95.9410          3\n",
       "286       Ulster County, NY              US  41.8586  -74.3118          2\n",
       "287            Umatilla, OR              US  45.7750 -118.7606          8\n",
       "288               Union, NJ              US  40.6976  -74.2632          0\n",
       "289          United Kingdom  United Kingdom  55.3781   -3.4360       9399\n",
       "290                    Utah              US  40.1500 -111.8624        147\n",
       "291             Ventura, CA              US  34.3705 -119.1391          0\n",
       "292                 Vermont              US  44.0459  -72.7107         43\n",
       "293                Victoria       Australia -37.8136  144.9631        587\n",
       "294          Virgin Islands              US  18.3358  -64.8963          5\n",
       "295                Virginia              US  37.7693  -78.1700        265\n",
       "296      Volusia County, FL              US  29.0280  -81.0755          2\n",
       "297         Wake County, NC              US  35.8032  -78.5661          7\n",
       "298              Washington              US  47.4009 -121.4905       4838\n",
       "299   Washington County, OR              US  45.5470 -123.1386         31\n",
       "300        Washington, D.C.              US  38.9072  -77.0369          4\n",
       "301       Washoe County, NV              US  40.5608 -119.6035          6\n",
       "302        Wayne County, PA              US  41.6739  -75.2479          4\n",
       "303               Wayne, MI              US  42.2791  -83.3362          0\n",
       "304               Weber, UT              US  41.2603 -111.9522          0\n",
       "305           West Virginia              US  38.4912  -80.9545          1\n",
       "306  Westchester County, NY              US  41.1220  -73.7949        286\n",
       "307       Western Australia       Australia -31.9505  115.8605        157\n",
       "308             Whatcom, WA              US  48.8787 -121.9719          0\n",
       "309   Williamson County, TN              US  35.9179  -86.8622          5\n",
       "310               Wisconsin              US  44.2685  -89.6165        214\n",
       "311           Worcester, MA              US  42.4097  -71.8571          0\n",
       "312                 Wyoming              US  42.7560 -107.3025         21\n",
       "313                Xinjiang           China  41.1129   85.2401       3067\n",
       "314         Yolo County, CA              US  38.7646 -121.9018          4\n",
       "315                  Yunnan           China  24.9740  101.4870       7758\n",
       "316                Zhejiang           China  29.1832  120.0934      53797"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corona_sums.tail(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "corona_sums = df_corona.groupby(['Province/State', 'Lat','Long'],\\\n",
    "                     as_index=False).agg({'Confirmed':'sum'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "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>Province/State</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long</th>\n",
       "      <th>Confirmed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Adams, IN</td>\n",
       "      <td>39.8522</td>\n",
       "      <td>-77.2865</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>32.3182</td>\n",
       "      <td>-86.9023</td>\n",
       "      <td>91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Alachua, FL</td>\n",
       "      <td>29.7938</td>\n",
       "      <td>-82.4944</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Alameda County, CA</td>\n",
       "      <td>37.6017</td>\n",
       "      <td>-121.7195</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>61.3707</td>\n",
       "      <td>-152.4044</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Alberta</td>\n",
       "      <td>53.9333</td>\n",
       "      <td>-116.5765</td>\n",
       "      <td>286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>31.8257</td>\n",
       "      <td>117.2264</td>\n",
       "      <td>41707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Anoka, MN</td>\n",
       "      <td>45.3293</td>\n",
       "      <td>-93.2197</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Arapahoe, CO</td>\n",
       "      <td>39.6203</td>\n",
       "      <td>-104.3326</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>33.7298</td>\n",
       "      <td>-111.4312</td>\n",
       "      <td>96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>Arkansas</td>\n",
       "      <td>34.9697</td>\n",
       "      <td>-92.3731</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>Arlington, VA</td>\n",
       "      <td>38.8816</td>\n",
       "      <td>-77.0910</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>Australian Capital Territory</td>\n",
       "      <td>-35.4735</td>\n",
       "      <td>149.0124</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>Beadle, SD</td>\n",
       "      <td>44.4797</td>\n",
       "      <td>-98.2213</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>Beijing</td>\n",
       "      <td>40.1824</td>\n",
       "      <td>116.4142</td>\n",
       "      <td>17987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>Bennington County, VT</td>\n",
       "      <td>43.0279</td>\n",
       "      <td>-73.1350</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>Bergen County, NJ</td>\n",
       "      <td>40.9263</td>\n",
       "      <td>-74.0770</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>17</td>\n",
       "      <td>Berkshire County, MA</td>\n",
       "      <td>42.3118</td>\n",
       "      <td>-73.1822</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>18</td>\n",
       "      <td>Bernalillo, NM</td>\n",
       "      <td>35.0178</td>\n",
       "      <td>-106.6291</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>19</td>\n",
       "      <td>Bon Homme, SD</td>\n",
       "      <td>42.9815</td>\n",
       "      <td>-97.8722</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>20</td>\n",
       "      <td>Boone, IN</td>\n",
       "      <td>40.0106</td>\n",
       "      <td>-86.4997</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>21</td>\n",
       "      <td>British Columbia</td>\n",
       "      <td>49.2827</td>\n",
       "      <td>-123.1207</td>\n",
       "      <td>807</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>22</td>\n",
       "      <td>Broward County, FL</td>\n",
       "      <td>26.1901</td>\n",
       "      <td>-80.3659</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>23</td>\n",
       "      <td>Bucks, PA</td>\n",
       "      <td>40.4108</td>\n",
       "      <td>-75.2479</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>24</td>\n",
       "      <td>Burlington, NJ</td>\n",
       "      <td>40.0712</td>\n",
       "      <td>-74.8649</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>25</td>\n",
       "      <td>Calaveras, CA</td>\n",
       "      <td>38.1960</td>\n",
       "      <td>-120.6805</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>26</td>\n",
       "      <td>California</td>\n",
       "      <td>36.1162</td>\n",
       "      <td>-119.6816</td>\n",
       "      <td>2845</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>27</td>\n",
       "      <td>Camden, NC</td>\n",
       "      <td>34.2465</td>\n",
       "      <td>-80.6070</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>28</td>\n",
       "      <td>Camden, NJ</td>\n",
       "      <td>39.9259</td>\n",
       "      <td>-75.1196</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>29</td>\n",
       "      <td>Carver County, MN</td>\n",
       "      <td>44.8254</td>\n",
       "      <td>-93.7842</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>30</td>\n",
       "      <td>Cayman Islands</td>\n",
       "      <td>19.3133</td>\n",
       "      <td>-81.2546</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>31</td>\n",
       "      <td>Channel Islands</td>\n",
       "      <td>49.3723</td>\n",
       "      <td>-2.3644</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>32</td>\n",
       "      <td>Charles Mix, SD</td>\n",
       "      <td>43.0985</td>\n",
       "      <td>-98.3965</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>33</td>\n",
       "      <td>Charleston County, SC</td>\n",
       "      <td>32.7957</td>\n",
       "      <td>-79.7848</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>34</td>\n",
       "      <td>Charlotte County, FL</td>\n",
       "      <td>26.8946</td>\n",
       "      <td>-81.9098</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>35</td>\n",
       "      <td>Charlton, GA</td>\n",
       "      <td>30.7917</td>\n",
       "      <td>-82.0843</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>36</td>\n",
       "      <td>Chatham County, NC</td>\n",
       "      <td>35.7211</td>\n",
       "      <td>-79.1781</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>37</td>\n",
       "      <td>Cherokee County, GA</td>\n",
       "      <td>34.2515</td>\n",
       "      <td>-84.4803</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>38</td>\n",
       "      <td>Chongqing</td>\n",
       "      <td>30.0572</td>\n",
       "      <td>107.8740</td>\n",
       "      <td>25201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>39</td>\n",
       "      <td>Clark County, NV</td>\n",
       "      <td>36.0796</td>\n",
       "      <td>-115.0940</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>40</td>\n",
       "      <td>Clark County, WA</td>\n",
       "      <td>45.7466</td>\n",
       "      <td>-122.5194</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>41</td>\n",
       "      <td>Cobb County, GA</td>\n",
       "      <td>33.8999</td>\n",
       "      <td>-84.5641</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>42</td>\n",
       "      <td>Collier, FL</td>\n",
       "      <td>26.0700</td>\n",
       "      <td>-81.4279</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>43</td>\n",
       "      <td>Collin County, TX</td>\n",
       "      <td>33.1795</td>\n",
       "      <td>-96.4930</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>44</td>\n",
       "      <td>Colorado</td>\n",
       "      <td>39.0598</td>\n",
       "      <td>-105.3111</td>\n",
       "      <td>695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>45</td>\n",
       "      <td>Connecticut</td>\n",
       "      <td>41.5978</td>\n",
       "      <td>-72.7554</td>\n",
       "      <td>165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>46</td>\n",
       "      <td>Contra Costa County, CA</td>\n",
       "      <td>37.8534</td>\n",
       "      <td>-121.9018</td>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>47</td>\n",
       "      <td>Cook County, IL</td>\n",
       "      <td>41.7377</td>\n",
       "      <td>-87.6976</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>48</td>\n",
       "      <td>Curacao</td>\n",
       "      <td>12.1696</td>\n",
       "      <td>-68.9900</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>49</td>\n",
       "      <td>Cuyahoga, OH</td>\n",
       "      <td>41.4339</td>\n",
       "      <td>-81.6758</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>50</td>\n",
       "      <td>Dallas, TX</td>\n",
       "      <td>32.7767</td>\n",
       "      <td>-96.7970</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>51</td>\n",
       "      <td>Dane, WI</td>\n",
       "      <td>43.0186</td>\n",
       "      <td>-89.5498</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>52</td>\n",
       "      <td>Davidson County, TN</td>\n",
       "      <td>36.1343</td>\n",
       "      <td>-86.8220</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>53</td>\n",
       "      <td>Davis County, UT</td>\n",
       "      <td>40.9629</td>\n",
       "      <td>-112.0953</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>54</td>\n",
       "      <td>Davison, SD</td>\n",
       "      <td>43.7242</td>\n",
       "      <td>-98.2213</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Province/State      Lat      Long  Confirmed\n",
       "0                      Adams, IN  39.8522  -77.2865          0\n",
       "1                        Alabama  32.3182  -86.9023         91\n",
       "2                    Alachua, FL  29.7938  -82.4944          0\n",
       "3             Alameda County, CA  37.6017 -121.7195         10\n",
       "4                         Alaska  61.3707 -152.4044          7\n",
       "5                        Alberta  53.9333 -116.5765        286\n",
       "6                          Anhui  31.8257  117.2264      41707\n",
       "7                      Anoka, MN  45.3293  -93.2197          0\n",
       "8                   Arapahoe, CO  39.6203 -104.3326          0\n",
       "9                        Arizona  33.7298 -111.4312         96\n",
       "10                      Arkansas  34.9697  -92.3731         85\n",
       "11                 Arlington, VA  38.8816  -77.0910          0\n",
       "12  Australian Capital Territory -35.4735  149.0124          7\n",
       "13                    Beadle, SD  44.4797  -98.2213          0\n",
       "14                       Beijing  40.1824  116.4142      17987\n",
       "15         Bennington County, VT  43.0279  -73.1350          2\n",
       "16             Bergen County, NJ  40.9263  -74.0770         16\n",
       "17          Berkshire County, MA  42.3118  -73.1822          2\n",
       "18                Bernalillo, NM  35.0178 -106.6291          0\n",
       "19                 Bon Homme, SD  42.9815  -97.8722          0\n",
       "20                     Boone, IN  40.0106  -86.4997          0\n",
       "21              British Columbia  49.2827 -123.1207        807\n",
       "22            Broward County, FL  26.1901  -80.3659          7\n",
       "23                     Bucks, PA  40.4108  -75.2479          0\n",
       "24                Burlington, NJ  40.0712  -74.8649          0\n",
       "25                 Calaveras, CA  38.1960 -120.6805          0\n",
       "26                    California  36.1162 -119.6816       2845\n",
       "27                    Camden, NC  34.2465  -80.6070          0\n",
       "28                    Camden, NJ  39.9259  -75.1196          0\n",
       "29             Carver County, MN  44.8254  -93.7842          1\n",
       "30                Cayman Islands  19.3133  -81.2546          5\n",
       "31               Channel Islands  49.3723   -2.3644         24\n",
       "32               Charles Mix, SD  43.0985  -98.3965          0\n",
       "33         Charleston County, SC  32.7957  -79.7848          3\n",
       "34          Charlotte County, FL  26.8946  -81.9098          1\n",
       "35                  Charlton, GA  30.7917  -82.0843          0\n",
       "36            Chatham County, NC  35.7211  -79.1781          4\n",
       "37           Cherokee County, GA  34.2515  -84.4803          1\n",
       "38                     Chongqing  30.0572  107.8740      25201\n",
       "39              Clark County, NV  36.0796 -115.0940          7\n",
       "40              Clark County, WA  45.7466 -122.5194          3\n",
       "41               Cobb County, GA  33.8999  -84.5641          5\n",
       "42                   Collier, FL  26.0700  -81.4279          0\n",
       "43             Collin County, TX  33.1795  -96.4930          1\n",
       "44                      Colorado  39.0598 -105.3111        695\n",
       "45                   Connecticut  41.5978  -72.7554        165\n",
       "46       Contra Costa County, CA  37.8534 -121.9018         26\n",
       "47               Cook County, IL  41.7377  -87.6976        112\n",
       "48                       Curacao  12.1696  -68.9900          6\n",
       "49                  Cuyahoga, OH  41.4339  -81.6758          0\n",
       "50                    Dallas, TX  32.7767  -96.7970          0\n",
       "51                      Dane, WI  43.0186  -89.5498          0\n",
       "52           Davidson County, TN  36.1343  -86.8220          2\n",
       "53              Davis County, UT  40.9629 -112.0953          3\n",
       "54                   Davison, SD  43.7242  -98.2213          0"
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     "execution_count": 102,
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   "source": [
    "import plotly_express as px\n",
    "def plot_timeseries(df):\n",
    "    fig = px.line(df, x='Date', y='Confirmed') \n",
    "\n",
    "    fig.update_layout(legend_orientation=\"h\")\n",
    "    return(fig)\n",
    "\n",
    "fig = plot_timeseries(corona_sums)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (<ipython-input-79-874fbbc20570>, line 4)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-79-874fbbc20570>\"\u001b[1;36m, line \u001b[1;32m4\u001b[0m\n\u001b[1;33m    tsmap_corona['Date'] = tsmap_corona['Date'].astype(str)\u001b[0m\n\u001b[1;37m               ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "import plotly_express as px\n",
    "# Selecting only the Confirmed cases\n",
    "tsmap_corona = df_corona[df_corona['Confirmed']\n",
    "tsmap_corona['Date'] = tsmap_corona['Date'].astype(str)"
   ]
  }
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