{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import urllib.request \n",
    "import time \n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Beginning file download \n"
     ]
    }
   ],
   "source": [
    "url1 = 'https://covid.ourworldindata.org/data/ecdc/total_cases.csv' #Uniform Resource Locator (URL)\n",
    "filename1 = 'data/total_cases.csv'\n",
    "print('Beginning file download ')\n",
    "urllib.request.urlretrieve(url1, filename1)\n",
    "time.sleep(.300) #delay for time 0.3 second"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Beginning file download \n"
     ]
    }
   ],
   "source": [
    "url2 = 'https://covid.ourworldindata.org/data/ecdc/total_deaths.csv'\n",
    "filename2 = 'data/total_deaths.csv'\n",
    "print('Beginning file download ')\n",
    "urllib.request.urlretrieve(url2, filename2)\n",
    "time.sleep(.300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    </tr>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>44</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>2020-01-04</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>2020-09-27</td>\n",
       "      <td>32920813</td>\n",
       "      <td>39227.0</td>\n",
       "      <td>13153.0</td>\n",
       "      <td>50914.0</td>\n",
       "      <td>1836.0</td>\n",
       "      <td>4590.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>702471.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1317.0</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>54953.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>71940.0</td>\n",
       "      <td>1069.0</td>\n",
       "      <td>766.0</td>\n",
       "      <td>2033.0</td>\n",
       "      <td>14612.0</td>\n",
       "      <td>7803.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>2020-09-28</td>\n",
       "      <td>33202820</td>\n",
       "      <td>39227.0</td>\n",
       "      <td>13259.0</td>\n",
       "      <td>51067.0</td>\n",
       "      <td>1836.0</td>\n",
       "      <td>4672.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>711312.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1317.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>55593.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>72691.0</td>\n",
       "      <td>1074.0</td>\n",
       "      <td>766.0</td>\n",
       "      <td>2034.0</td>\n",
       "      <td>14641.0</td>\n",
       "      <td>7812.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>2020-09-29</td>\n",
       "      <td>33436665</td>\n",
       "      <td>39239.0</td>\n",
       "      <td>13391.0</td>\n",
       "      <td>51213.0</td>\n",
       "      <td>1966.0</td>\n",
       "      <td>4797.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>723119.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1318.0</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>56068.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>73528.0</td>\n",
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       "      <td>766.0</td>\n",
       "      <td>2035.0</td>\n",
       "      <td>14660.0</td>\n",
       "      <td>7816.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>2020-09-30</td>\n",
       "      <td>33725618</td>\n",
       "      <td>39254.0</td>\n",
       "      <td>13518.0</td>\n",
       "      <td>51368.0</td>\n",
       "      <td>1966.0</td>\n",
       "      <td>4905.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>736596.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1318.0</td>\n",
       "      <td>2033.0</td>\n",
       "      <td>56519.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>74363.0</td>\n",
       "      <td>1094.0</td>\n",
       "      <td>766.0</td>\n",
       "      <td>2035.0</td>\n",
       "      <td>14715.0</td>\n",
       "      <td>7837.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>2020-10-01</td>\n",
       "      <td>34029923</td>\n",
       "      <td>39268.0</td>\n",
       "      <td>13649.0</td>\n",
       "      <td>51530.0</td>\n",
       "      <td>2050.0</td>\n",
       "      <td>5013.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>750988.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1318.0</td>\n",
       "      <td>2046.0</td>\n",
       "      <td>56997.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>75122.0</td>\n",
       "      <td>1094.0</td>\n",
       "      <td>766.0</td>\n",
       "      <td>2035.0</td>\n",
       "      <td>14759.0</td>\n",
       "      <td>7838.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 212 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           date     World  Afghanistan  Albania  Algeria  Andorra  Angola  \\\n",
       "0    2019-12-31        27          0.0      NaN      0.0      NaN     NaN   \n",
       "1    2020-01-01        27          0.0      NaN      0.0      NaN     NaN   \n",
       "2    2020-01-02        27          0.0      NaN      0.0      NaN     NaN   \n",
       "3    2020-01-03        44          0.0      NaN      0.0      NaN     NaN   \n",
       "4    2020-01-04        44          0.0      NaN      0.0      NaN     NaN   \n",
       "..          ...       ...          ...      ...      ...      ...     ...   \n",
       "271  2020-09-27  32920813      39227.0  13153.0  50914.0   1836.0  4590.0   \n",
       "272  2020-09-28  33202820      39227.0  13259.0  51067.0   1836.0  4672.0   \n",
       "273  2020-09-29  33436665      39239.0  13391.0  51213.0   1966.0  4797.0   \n",
       "274  2020-09-30  33725618      39254.0  13518.0  51368.0   1966.0  4905.0   \n",
       "275  2020-10-01  34029923      39268.0  13649.0  51530.0   2050.0  5013.0   \n",
       "\n",
       "     Anguilla  Antigua and Barbuda  Argentina  ...  \\\n",
       "0         NaN                  NaN        NaN  ...   \n",
       "1         NaN                  NaN        NaN  ...   \n",
       "2         NaN                  NaN        NaN  ...   \n",
       "3         NaN                  NaN        NaN  ...   \n",
       "4         NaN                  NaN        NaN  ...   \n",
       "..        ...                  ...        ...  ...   \n",
       "271       3.0                101.0   702471.0  ...   \n",
       "272       3.0                101.0   711312.0  ...   \n",
       "273       3.0                101.0   723119.0  ...   \n",
       "274       3.0                101.0   736596.0  ...   \n",
       "275       3.0                101.0   750988.0  ...   \n",
       "\n",
       "     United States Virgin Islands  Uruguay  Uzbekistan  Vatican  Venezuela  \\\n",
       "0                             NaN      NaN         NaN      NaN        NaN   \n",
       "1                             NaN      NaN         NaN      NaN        NaN   \n",
       "2                             NaN      NaN         NaN      NaN        NaN   \n",
       "3                             NaN      NaN         NaN      NaN        NaN   \n",
       "4                             NaN      NaN         NaN      NaN        NaN   \n",
       "..                            ...      ...         ...      ...        ...   \n",
       "271                        1317.0   1998.0     54953.0     12.0    71940.0   \n",
       "272                        1317.0   2008.0     55593.0     12.0    72691.0   \n",
       "273                        1318.0   2010.0     56068.0     12.0    73528.0   \n",
       "274                        1318.0   2033.0     56519.0     12.0    74363.0   \n",
       "275                        1318.0   2046.0     56997.0     12.0    75122.0   \n",
       "\n",
       "     Vietnam  Western Sahara   Yemen   Zambia  Zimbabwe  \n",
       "0        0.0             NaN     NaN      NaN       NaN  \n",
       "1        0.0             NaN     NaN      NaN       NaN  \n",
       "2        0.0             NaN     NaN      NaN       NaN  \n",
       "3        0.0             NaN     NaN      NaN       NaN  \n",
       "4        0.0             NaN     NaN      NaN       NaN  \n",
       "..       ...             ...     ...      ...       ...  \n",
       "271   1069.0           766.0  2033.0  14612.0    7803.0  \n",
       "272   1074.0           766.0  2034.0  14641.0    7812.0  \n",
       "273   1077.0           766.0  2035.0  14660.0    7816.0  \n",
       "274   1094.0           766.0  2035.0  14715.0    7837.0  \n",
       "275   1094.0           766.0  2035.0  14759.0    7838.0  \n",
       "\n",
       "[276 rows x 212 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1 = pd.read_csv(filename1)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>2020-09-27</td>\n",
       "      <td>995163</td>\n",
       "      <td>1453.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>1711.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15543.0</td>\n",
       "      <td>...</td>\n",
       "      <td>19.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>454.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>588.0</td>\n",
       "      <td>332.0</td>\n",
       "      <td>227.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
       "      <td>2020-09-28</td>\n",
       "      <td>998983</td>\n",
       "      <td>1453.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>1714.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15749.0</td>\n",
       "      <td>...</td>\n",
       "      <td>19.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>460.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>606.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>588.0</td>\n",
       "      <td>332.0</td>\n",
       "      <td>227.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>2020-09-29</td>\n",
       "      <td>1002903</td>\n",
       "      <td>1456.0</td>\n",
       "      <td>380.0</td>\n",
       "      <td>1719.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16113.0</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>463.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>614.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>588.0</td>\n",
       "      <td>332.0</td>\n",
       "      <td>228.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>274</th>\n",
       "      <td>2020-09-30</td>\n",
       "      <td>1009109</td>\n",
       "      <td>1458.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>1726.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>179.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16519.0</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>468.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>621.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>588.0</td>\n",
       "      <td>332.0</td>\n",
       "      <td>228.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>275</th>\n",
       "      <td>2020-10-01</td>\n",
       "      <td>1015043</td>\n",
       "      <td>1458.0</td>\n",
       "      <td>387.0</td>\n",
       "      <td>1734.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16937.0</td>\n",
       "      <td>...</td>\n",
       "      <td>20.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>628.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>588.0</td>\n",
       "      <td>332.0</td>\n",
       "      <td>228.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>276 rows × 212 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           date    World  Afghanistan  Albania  Algeria  Andorra  Angola  \\\n",
       "0    2019-12-31        0          0.0      NaN      0.0      NaN     NaN   \n",
       "1    2020-01-01        0          0.0      NaN      0.0      NaN     NaN   \n",
       "2    2020-01-02        0          0.0      NaN      0.0      NaN     NaN   \n",
       "3    2020-01-03        0          0.0      NaN      0.0      NaN     NaN   \n",
       "4    2020-01-04        0          0.0      NaN      0.0      NaN     NaN   \n",
       "..          ...      ...          ...      ...      ...      ...     ...   \n",
       "271  2020-09-27   995163       1453.0    375.0   1711.0     53.0   167.0   \n",
       "272  2020-09-28   998983       1453.0    377.0   1714.0     53.0   171.0   \n",
       "273  2020-09-29  1002903       1456.0    380.0   1719.0     53.0   176.0   \n",
       "274  2020-09-30  1009109       1458.0    384.0   1726.0     53.0   179.0   \n",
       "275  2020-10-01  1015043       1458.0    387.0   1734.0     53.0   182.0   \n",
       "\n",
       "     Anguilla  Antigua and Barbuda  Argentina  ...  \\\n",
       "0         NaN                  NaN        NaN  ...   \n",
       "1         NaN                  NaN        NaN  ...   \n",
       "2         NaN                  NaN        NaN  ...   \n",
       "3         NaN                  NaN        NaN  ...   \n",
       "4         NaN                  NaN        NaN  ...   \n",
       "..        ...                  ...        ...  ...   \n",
       "271       0.0                  3.0    15543.0  ...   \n",
       "272       0.0                  3.0    15749.0  ...   \n",
       "273       0.0                  3.0    16113.0  ...   \n",
       "274       0.0                  3.0    16519.0  ...   \n",
       "275       0.0                  3.0    16937.0  ...   \n",
       "\n",
       "     United States Virgin Islands  Uruguay  Uzbekistan  Vatican  Venezuela  \\\n",
       "0                             NaN      NaN         NaN      NaN        NaN   \n",
       "1                             NaN      NaN         NaN      NaN        NaN   \n",
       "2                             NaN      NaN         NaN      NaN        NaN   \n",
       "3                             NaN      NaN         NaN      NaN        NaN   \n",
       "4                             NaN      NaN         NaN      NaN        NaN   \n",
       "..                            ...      ...         ...      ...        ...   \n",
       "271                          19.0     47.0       454.0      0.0      600.0   \n",
       "272                          19.0     47.0       460.0      0.0      606.0   \n",
       "273                          20.0     47.0       463.0      0.0      614.0   \n",
       "274                          20.0     48.0       468.0      0.0      621.0   \n",
       "275                          20.0     48.0       471.0      0.0      628.0   \n",
       "\n",
       "     Vietnam  Western Sahara  Yemen  Zambia  Zimbabwe  \n",
       "0        0.0             NaN    NaN     NaN       NaN  \n",
       "1        0.0             NaN    NaN     NaN       NaN  \n",
       "2        0.0             NaN    NaN     NaN       NaN  \n",
       "3        0.0             NaN    NaN     NaN       NaN  \n",
       "4        0.0             NaN    NaN     NaN       NaN  \n",
       "..       ...             ...    ...     ...       ...  \n",
       "271     35.0             1.0  588.0   332.0     227.0  \n",
       "272     35.0             1.0  588.0   332.0     227.0  \n",
       "273     35.0             1.0  588.0   332.0     228.0  \n",
       "274     35.0             1.0  588.0   332.0     228.0  \n",
       "275     35.0             1.0  588.0   332.0     228.0  \n",
       "\n",
       "[276 rows x 212 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2 = pd.read_csv(filename2)\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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