microproject-covid-data-from-github.ipynb

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    "<h1 style=\"text-align: center\">\n",
    "<div style=\"color: #DD3403; font-size: 60%\">Data Science DISCOVERY MicroProject</div>\n",
    "<span style=\"\">MicroProject: Exploring COVID-19 Data from GitHub</span>\n",
    "<div style=\"font-size: 60%;\"><a href=\"https://discovery.cs.illinois.edu/microproject/covid-data-from-github/\">https://discovery.cs.illinois.edu/microproject/covid-data-from-github/</a></div>\n",
    "</h1>\n",
    "\n",
    "<hr style=\"color: #DD3403;\">"
   ]
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    "## Data Source: COVID-19 Case Data from Johns Hopkins University, via GitHub\n",
    "\n",
    "Since before COVID-19 was detected in the United States, the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University has provided daily updates of COVID-19 case data as clean, structured CSV files on GitHub as a free public service to the world.\n",
    "\n",
    "You can view their COVID-19 GitHub repository here: [https://github.com/CSSEGISandData/COVID-19](https://github.com/CSSEGISandData/COVID-19).  You can find their daily reports by navigating into their repository:\n",
    "\n",
    "- Click **csse_covid_19_data** to navigate into the `csse_covid_19_data` folder,\n",
    "- Navigate into `csse_covid_19_daily_reports`,\n",
    "- Find the CSV data for **Jan. 3, 2022** *(it'll be near the top, be careful to get the correct year)*\n",
    "- Click the **Raw** button to above the file contents to navigate to the raw CSV version of the file (without the GitHub interface)\n",
    "- Use the URL of the **raw data as your dataset** for this MicroProject.\n",
    "\n",
    "Use panda's `read_csv` function to read the dataset you found and create a DataFrame called `df`:"
   ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Admin2</th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Country_Region</th>\n",
       "      <th>Last_Update</th>\n",
       "      <th>Lat</th>\n",
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       "      <th>Confirmed</th>\n",
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       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>Combined_Key</th>\n",
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       "      <th>Case_Fatality_Ratio</th>\n",
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       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>33.93911</td>\n",
       "      <td>67.709953</td>\n",
       "      <td>158183</td>\n",
       "      <td>7364</td>\n",
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       "      <td>Afghanistan</td>\n",
       "      <td>406.344057</td>\n",
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       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Albania</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>41.15330</td>\n",
       "      <td>20.168300</td>\n",
       "      <td>210885</td>\n",
       "      <td>3220</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Albania</td>\n",
       "      <td>7327.993606</td>\n",
       "      <td>1.526899</td>\n",
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       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>28.03390</td>\n",
       "      <td>1.659600</td>\n",
       "      <td>219532</td>\n",
       "      <td>6298</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>500.631194</td>\n",
       "      <td>2.868830</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>42.50630</td>\n",
       "      <td>1.521800</td>\n",
       "      <td>24502</td>\n",
       "      <td>140</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>31711.641752</td>\n",
       "      <td>0.571382</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Angola</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-11.20270</td>\n",
       "      <td>17.873900</td>\n",
       "      <td>83764</td>\n",
       "      <td>1775</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Angola</td>\n",
       "      <td>254.863132</td>\n",
       "      <td>2.119049</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",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>4011</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Ukraine</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Unknown, Ukraine</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4012</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Nauru</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-0.52280</td>\n",
       "      <td>166.931500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Nauru</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>4013</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Niue</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-19.05440</td>\n",
       "      <td>-169.867200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Niue, New Zealand</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>4014</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Tuvalu</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-7.10950</td>\n",
       "      <td>177.649300</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Tuvalu</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "    <tr>\n",
       "      <th>4015</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Pitcairn Islands</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-24.37680</td>\n",
       "      <td>-128.324200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Pitcairn Islands, United Kingdom</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
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       "  </tbody>\n",
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       "<p>4016 rows × 14 columns</p>\n",
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       "      FIPS Admin2    Province_State  Country_Region          Last_Update  \\\n",
       "0      NaN    NaN               NaN     Afghanistan  2022-01-04 04:22:17   \n",
       "1      NaN    NaN               NaN         Albania  2022-01-04 04:22:17   \n",
       "2      NaN    NaN               NaN         Algeria  2022-01-04 04:22:17   \n",
       "3      NaN    NaN               NaN         Andorra  2022-01-04 04:22:17   \n",
       "4      NaN    NaN               NaN          Angola  2022-01-04 04:22:17   \n",
       "...    ...    ...               ...             ...                  ...   \n",
       "4011   NaN    NaN           Unknown         Ukraine  2022-01-04 04:22:17   \n",
       "4012   NaN    NaN               NaN           Nauru  2022-01-04 04:22:17   \n",
       "4013   NaN    NaN              Niue     New Zealand  2022-01-04 04:22:17   \n",
       "4014   NaN    NaN               NaN          Tuvalu  2022-01-04 04:22:17   \n",
       "4015   NaN    NaN  Pitcairn Islands  United Kingdom  2022-01-04 04:22:17   \n",
       "\n",
       "           Lat       Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "0     33.93911   67.709953     158183    7364        NaN     NaN   \n",
       "1     41.15330   20.168300     210885    3220        NaN     NaN   \n",
       "2     28.03390    1.659600     219532    6298        NaN     NaN   \n",
       "3     42.50630    1.521800      24502     140        NaN     NaN   \n",
       "4    -11.20270   17.873900      83764    1775        NaN     NaN   \n",
       "...        ...         ...        ...     ...        ...     ...   \n",
       "4011       NaN         NaN          0       0        0.0     0.0   \n",
       "4012  -0.52280  166.931500          0       0        0.0     0.0   \n",
       "4013 -19.05440 -169.867200          0       0        0.0     0.0   \n",
       "4014  -7.10950  177.649300          0       0        0.0     0.0   \n",
       "4015 -24.37680 -128.324200          0       0        0.0     0.0   \n",
       "\n",
       "                          Combined_Key  Incident_Rate  Case_Fatality_Ratio  \n",
       "0                          Afghanistan     406.344057             4.655368  \n",
       "1                              Albania    7327.993606             1.526899  \n",
       "2                              Algeria     500.631194             2.868830  \n",
       "3                              Andorra   31711.641752             0.571382  \n",
       "4                               Angola     254.863132             2.119049  \n",
       "...                                ...            ...                  ...  \n",
       "4011                  Unknown, Ukraine       0.000000             0.000000  \n",
       "4012                             Nauru       0.000000             0.000000  \n",
       "4013                 Niue, New Zealand       0.000000             0.000000  \n",
       "4014                            Tuvalu       0.000000             0.000000  \n",
       "4015  Pitcairn Islands, United Kingdom       0.000000             0.000000  \n",
       "\n",
       "[4016 rows x 14 columns]"
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     },
     "execution_count": 1,
     "metadata": {},
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   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(\"https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_daily_reports/01-03-2022.csv\")\n",
    "df"
   ]
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   "source": [
    "### 🔬 Checkpoint Tests 🔬"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🎉 All Tests Passed! 🎉\n"
     ]
    }
   ],
   "source": [
    "### TEST CASE for Data Import\n",
    "tada = \"\\N{PARTY POPPER}\"\n",
    "\n",
    "assert(\"df\" in vars())\n",
    "assert(\"Country_Region\" in df)\n",
    "assert(\"People_Hospitalized\" not in df), \"Make sure you have the global daily reports, not just the US daily reports.\"\n",
    "assert(\"India\" in df[\"Country_Region\"].unique())\n",
    "assert(\"2022-01-04\" in df[\"Last_Update\"].unique()[0]), \"Make sure you have the Jan. 3, 2022 CSV file.\"\n",
    "print(f\"{tada} All Tests Passed! {tada}\")"
   ]
  },
  {
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   "source": [
    "<hr style=\"color: #DD3403;\">"
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   "source": [
    "## Country-Level Analysis of COVID-19\n",
    "\n",
    "The CSV file from JHU provides the **total reported cases over all time until the end of the day on Jan. 3, 2022**.  However, the data is often breaks countries into individual regions.  For example, let's check out the United States.  Create a DataFrame with all records from the dataset with data about the United States in the variable `df_us`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
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       "      <td>95</td>\n",
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       "      <td>Bibb, Alabama, US</td>\n",
       "      <td>20514.423506</td>\n",
       "      <td>2.067915</td>\n",
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       "    <tr>\n",
       "      <th>677</th>\n",
       "      <td>1009.0</td>\n",
       "      <td>Blount</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>33.982109</td>\n",
       "      <td>-86.567906</td>\n",
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       "      <td>Blount, Alabama, US</td>\n",
       "      <td>19658.976931</td>\n",
       "      <td>1.741731</td>\n",
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       "      <td>Teton</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>43.935225</td>\n",
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       "      <td>Teton, Wyoming, US</td>\n",
       "      <td>26734.572110</td>\n",
       "      <td>0.223179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3948</th>\n",
       "      <td>56041.0</td>\n",
       "      <td>Uinta</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>41.287818</td>\n",
       "      <td>-110.547578</td>\n",
       "      <td>4173</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Uinta, Wyoming, US</td>\n",
       "      <td>20631.859982</td>\n",
       "      <td>0.742871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3949</th>\n",
       "      <td>90056.0</td>\n",
       "      <td>Unassigned</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unassigned, Wyoming, US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3950</th>\n",
       "      <td>56043.0</td>\n",
       "      <td>Washakie</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>43.904516</td>\n",
       "      <td>-107.680187</td>\n",
       "      <td>1886</td>\n",
       "      <td>37</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Washakie, Wyoming, US</td>\n",
       "      <td>24163.997438</td>\n",
       "      <td>1.961824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3951</th>\n",
       "      <td>56045.0</td>\n",
       "      <td>Weston</td>\n",
       "      <td>Wyoming</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>43.839612</td>\n",
       "      <td>-104.567488</td>\n",
       "      <td>1257</td>\n",
       "      <td>14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Weston, Wyoming, US</td>\n",
       "      <td>18146.383716</td>\n",
       "      <td>1.113763</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3279 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         FIPS      Admin2 Province_State Country_Region          Last_Update  \\\n",
       "673    1001.0     Autauga        Alabama             US  2022-01-04 04:22:17   \n",
       "674    1003.0     Baldwin        Alabama             US  2022-01-04 04:22:17   \n",
       "675    1005.0     Barbour        Alabama             US  2022-01-04 04:22:17   \n",
       "676    1007.0        Bibb        Alabama             US  2022-01-04 04:22:17   \n",
       "677    1009.0      Blount        Alabama             US  2022-01-04 04:22:17   \n",
       "...       ...         ...            ...            ...                  ...   \n",
       "3947  56039.0       Teton        Wyoming             US  2022-01-04 04:22:17   \n",
       "3948  56041.0       Uinta        Wyoming             US  2022-01-04 04:22:17   \n",
       "3949  90056.0  Unassigned        Wyoming             US  2022-01-04 04:22:17   \n",
       "3950  56043.0    Washakie        Wyoming             US  2022-01-04 04:22:17   \n",
       "3951  56045.0      Weston        Wyoming             US  2022-01-04 04:22:17   \n",
       "\n",
       "            Lat       Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "673   32.539527  -86.644082      11256     160        NaN     NaN   \n",
       "674   30.727750  -87.722071      40549     593        NaN     NaN   \n",
       "675   31.868263  -85.387129       3961      81        NaN     NaN   \n",
       "676   32.996421  -87.125115       4594      95        NaN     NaN   \n",
       "677   33.982109  -86.567906      11368     198        NaN     NaN   \n",
       "...         ...         ...        ...     ...        ...     ...   \n",
       "3947  43.935225 -110.589080       6273      14        NaN     NaN   \n",
       "3948  41.287818 -110.547578       4173      31        NaN     NaN   \n",
       "3949        NaN         NaN          0       0        NaN     NaN   \n",
       "3950  43.904516 -107.680187       1886      37        NaN     NaN   \n",
       "3951  43.839612 -104.567488       1257      14        NaN     NaN   \n",
       "\n",
       "                 Combined_Key  Incident_Rate  Case_Fatality_Ratio  \n",
       "673      Autauga, Alabama, US   20147.129893             1.421464  \n",
       "674      Baldwin, Alabama, US   18164.347725             1.462428  \n",
       "675      Barbour, Alabama, US   16045.531880             2.044938  \n",
       "676         Bibb, Alabama, US   20514.423506             2.067915  \n",
       "677       Blount, Alabama, US   19658.976931             1.741731  \n",
       "...                       ...            ...                  ...  \n",
       "3947       Teton, Wyoming, US   26734.572110             0.223179  \n",
       "3948       Uinta, Wyoming, US   20631.859982             0.742871  \n",
       "3949  Unassigned, Wyoming, US            NaN                  NaN  \n",
       "3950    Washakie, Wyoming, US   24163.997438             1.961824  \n",
       "3951      Weston, Wyoming, US   18146.383716             1.113763  \n",
       "\n",
       "[3279 rows x 14 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_us = df[df[\"Country_Region\"]==\"US\"]\n",
    "df_us"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analysis of COVID-19 in the United States\n",
    "\n",
    "Create a new DataFrame, `df_us_sorted`, that sorts the DataFrame based on the number of confirmed cases of COVID-19 in the United States, where the **first row contains the location with the highest number of confirmed cases**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Admin2</th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Country_Region</th>\n",
       "      <th>Last_Update</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long_</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>Combined_Key</th>\n",
       "      <th>Incident_Rate</th>\n",
       "      <th>Case_Fatality_Ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
       "      <td>6037.0</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>34.308284</td>\n",
       "      <td>-118.228241</td>\n",
       "      <td>1757522</td>\n",
       "      <td>27647</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Los Angeles, California, US</td>\n",
       "      <td>17506.756328</td>\n",
       "      <td>1.573067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>781</th>\n",
       "      <td>4013.0</td>\n",
       "      <td>Maricopa</td>\n",
       "      <td>Arizona</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>33.348359</td>\n",
       "      <td>-112.491815</td>\n",
       "      <td>887308</td>\n",
       "      <td>13737</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Maricopa, Arizona, US</td>\n",
       "      <td>19782.075857</td>\n",
       "      <td>1.548166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1305</th>\n",
       "      <td>17031.0</td>\n",
       "      <td>Cook</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>41.841448</td>\n",
       "      <td>-87.816588</td>\n",
       "      <td>862761</td>\n",
       "      <td>12055</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Cook, Illinois, US</td>\n",
       "      <td>16751.882876</td>\n",
       "      <td>1.397258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1050</th>\n",
       "      <td>12086.0</td>\n",
       "      <td>Miami-Dade</td>\n",
       "      <td>Florida</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>25.611236</td>\n",
       "      <td>-80.551706</td>\n",
       "      <td>854670</td>\n",
       "      <td>6472</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Miami-Dade, Florida, US</td>\n",
       "      <td>31457.080392</td>\n",
       "      <td>0.757251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3440</th>\n",
       "      <td>48201.0</td>\n",
       "      <td>Harris</td>\n",
       "      <td>Texas</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>29.858649</td>\n",
       "      <td>-95.393395</td>\n",
       "      <td>759902</td>\n",
       "      <td>9766</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Harris, Texas, US</td>\n",
       "      <td>14660.987732</td>\n",
       "      <td>1.413273</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2848</th>\n",
       "      <td>90039.0</td>\n",
       "      <td>Unassigned</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unassigned, Ohio, US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>725</th>\n",
       "      <td>80001.0</td>\n",
       "      <td>Out of AL</td>\n",
       "      <td>Alabama</td>\n",
       "      <td>US</td>\n",
       "      <td>2020-12-21 13:27:30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Out of AL, Alabama, US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2763</th>\n",
       "      <td>90038.0</td>\n",
       "      <td>Unassigned</td>\n",
       "      <td>North Dakota</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unassigned, North Dakota, US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1287</th>\n",
       "      <td>90016.0</td>\n",
       "      <td>Unassigned</td>\n",
       "      <td>Idaho</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unassigned, Idaho, US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1920</th>\n",
       "      <td>90024.0</td>\n",
       "      <td>Unassigned</td>\n",
       "      <td>Maryland</td>\n",
       "      <td>US</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>203</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unassigned, Maryland, US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>39.494163</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3279 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         FIPS       Admin2 Province_State Country_Region          Last_Update  \\\n",
       "885    6037.0  Los Angeles     California             US  2022-01-04 04:22:17   \n",
       "781    4013.0     Maricopa        Arizona             US  2022-01-04 04:22:17   \n",
       "1305  17031.0         Cook       Illinois             US  2022-01-04 04:22:17   \n",
       "1050  12086.0   Miami-Dade        Florida             US  2022-01-04 04:22:17   \n",
       "3440  48201.0       Harris          Texas             US  2022-01-04 04:22:17   \n",
       "...       ...          ...            ...            ...                  ...   \n",
       "2848  90039.0   Unassigned           Ohio             US  2022-01-04 04:22:17   \n",
       "725   80001.0    Out of AL        Alabama             US  2020-12-21 13:27:30   \n",
       "2763  90038.0   Unassigned   North Dakota             US  2022-01-04 04:22:17   \n",
       "1287  90016.0   Unassigned          Idaho             US  2022-01-04 04:22:17   \n",
       "1920  90024.0   Unassigned       Maryland             US  2022-01-04 04:22:17   \n",
       "\n",
       "            Lat       Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "885   34.308284 -118.228241    1757522   27647        NaN     NaN   \n",
       "781   33.348359 -112.491815     887308   13737        NaN     NaN   \n",
       "1305  41.841448  -87.816588     862761   12055        NaN     NaN   \n",
       "1050  25.611236  -80.551706     854670    6472        NaN     NaN   \n",
       "3440  29.858649  -95.393395     759902    9766        NaN     NaN   \n",
       "...         ...         ...        ...     ...        ...     ...   \n",
       "2848        NaN         NaN          0       5        NaN     NaN   \n",
       "725         NaN         NaN          0       0        NaN     NaN   \n",
       "2763        NaN         NaN          0      45        NaN     NaN   \n",
       "1287        NaN         NaN          0       0        NaN     NaN   \n",
       "1920        NaN         NaN          0     203        NaN     NaN   \n",
       "\n",
       "                      Combined_Key  Incident_Rate  Case_Fatality_Ratio  \n",
       "885    Los Angeles, California, US   17506.756328             1.573067  \n",
       "781          Maricopa, Arizona, US   19782.075857             1.548166  \n",
       "1305            Cook, Illinois, US   16751.882876             1.397258  \n",
       "1050       Miami-Dade, Florida, US   31457.080392             0.757251  \n",
       "3440             Harris, Texas, US   14660.987732             1.413273  \n",
       "...                            ...            ...                  ...  \n",
       "2848          Unassigned, Ohio, US            NaN                  NaN  \n",
       "725         Out of AL, Alabama, US            NaN                  NaN  \n",
       "2763  Unassigned, North Dakota, US            NaN                  NaN  \n",
       "1287         Unassigned, Idaho, US            NaN                  NaN  \n",
       "1920      Unassigned, Maryland, US            NaN            39.494163  \n",
       "\n",
       "[3279 rows x 14 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_us_sorted = df_us.sort_values(\"Confirmed\",ascending=False)\n",
    "df_us_sorted"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a DataFrame for Country Level Analysis\n",
    "\n",
    "Create a new DataFrame, `df_countries`, that aggregates the data within each country together to get a DataFrame that contains one row for each country:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Country_Region</th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Admin2</th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Last_Update</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long_</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>Combined_Key</th>\n",
       "      <th>Incident_Rate</th>\n",
       "      <th>Case_Fatality_Ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>33.939110</td>\n",
       "      <td>67.709953</td>\n",
       "      <td>158183</td>\n",
       "      <td>7364</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>406.344057</td>\n",
       "      <td>4.655368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>41.153300</td>\n",
       "      <td>20.168300</td>\n",
       "      <td>210885</td>\n",
       "      <td>3220</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Albania</td>\n",
       "      <td>7327.993606</td>\n",
       "      <td>1.526899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>28.033900</td>\n",
       "      <td>1.659600</td>\n",
       "      <td>219532</td>\n",
       "      <td>6298</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>500.631194</td>\n",
       "      <td>2.868830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>42.506300</td>\n",
       "      <td>1.521800</td>\n",
       "      <td>24502</td>\n",
       "      <td>140</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>31711.641752</td>\n",
       "      <td>0.571382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Angola</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-11.202700</td>\n",
       "      <td>17.873900</td>\n",
       "      <td>83764</td>\n",
       "      <td>1775</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Angola</td>\n",
       "      <td>254.863132</td>\n",
       "      <td>2.119049</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>West Bank and Gaza</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>31.952200</td>\n",
       "      <td>35.233200</td>\n",
       "      <td>469748</td>\n",
       "      <td>4919</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>West Bank and Gaza</td>\n",
       "      <td>9208.188472</td>\n",
       "      <td>1.047157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>Winter Olympics 2022</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>39.904200</td>\n",
       "      <td>116.407400</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Winter Olympics 2022</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>15.552727</td>\n",
       "      <td>48.516388</td>\n",
       "      <td>10138</td>\n",
       "      <td>1984</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>33.990515</td>\n",
       "      <td>19.569935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-13.133897</td>\n",
       "      <td>27.849332</td>\n",
       "      <td>261221</td>\n",
       "      <td>3753</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>1420.918327</td>\n",
       "      <td>1.436715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-19.015438</td>\n",
       "      <td>29.154857</td>\n",
       "      <td>216087</td>\n",
       "      <td>5047</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>1453.865716</td>\n",
       "      <td>2.335633</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>201 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country_Region  FIPS Admin2 Province_State          Last_Update  \\\n",
       "0             Afghanistan   0.0      0              0  2022-01-04 04:22:17   \n",
       "1                 Albania   0.0      0              0  2022-01-04 04:22:17   \n",
       "2                 Algeria   0.0      0              0  2022-01-04 04:22:17   \n",
       "3                 Andorra   0.0      0              0  2022-01-04 04:22:17   \n",
       "4                  Angola   0.0      0              0  2022-01-04 04:22:17   \n",
       "..                    ...   ...    ...            ...                  ...   \n",
       "196    West Bank and Gaza   0.0      0              0  2022-01-04 04:22:17   \n",
       "197  Winter Olympics 2022   0.0      0              0  2022-01-04 04:22:17   \n",
       "198                 Yemen   0.0      0              0  2022-01-04 04:22:17   \n",
       "199                Zambia   0.0      0              0  2022-01-04 04:22:17   \n",
       "200              Zimbabwe   0.0      0              0  2022-01-04 04:22:17   \n",
       "\n",
       "           Lat       Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "0    33.939110   67.709953     158183    7364        0.0     0.0   \n",
       "1    41.153300   20.168300     210885    3220        0.0     0.0   \n",
       "2    28.033900    1.659600     219532    6298        0.0     0.0   \n",
       "3    42.506300    1.521800      24502     140        0.0     0.0   \n",
       "4   -11.202700   17.873900      83764    1775        0.0     0.0   \n",
       "..         ...         ...        ...     ...        ...     ...   \n",
       "196  31.952200   35.233200     469748    4919        0.0     0.0   \n",
       "197  39.904200  116.407400          0       0        0.0     0.0   \n",
       "198  15.552727   48.516388      10138    1984        0.0     0.0   \n",
       "199 -13.133897   27.849332     261221    3753        0.0     0.0   \n",
       "200 -19.015438   29.154857     216087    5047        0.0     0.0   \n",
       "\n",
       "             Combined_Key  Incident_Rate  Case_Fatality_Ratio  \n",
       "0             Afghanistan     406.344057             4.655368  \n",
       "1                 Albania    7327.993606             1.526899  \n",
       "2                 Algeria     500.631194             2.868830  \n",
       "3                 Andorra   31711.641752             0.571382  \n",
       "4                  Angola     254.863132             2.119049  \n",
       "..                    ...            ...                  ...  \n",
       "196    West Bank and Gaza    9208.188472             1.047157  \n",
       "197  Winter Olympics 2022       0.000000             0.000000  \n",
       "198                 Yemen      33.990515            19.569935  \n",
       "199                Zambia    1420.918327             1.436715  \n",
       "200              Zimbabwe    1453.865716             2.335633  \n",
       "\n",
       "[201 rows x 14 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_countries = df.groupby(\"Country_Region\").agg(\"sum\").reset_index()\n",
    "df_countries"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Performing Country-Level Analysis"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a DataFrame called `df_most_cases` that contains the country which has had the most confirmed cases of COVID-19:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Country_Region</th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Admin2</th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Last_Update</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long_</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>Combined_Key</th>\n",
       "      <th>Incident_Rate</th>\n",
       "      <th>Case_Fatality_Ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>US</td>\n",
       "      <td>105902623.0</td>\n",
       "      <td>AutaugaBaldwinBarbourBibbBlountBullockButlerCa...</td>\n",
       "      <td>AlabamaAlabamaAlabamaAlabamaAlabamaAlabamaAlab...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>121693.134039</td>\n",
       "      <td>-293352.619164</td>\n",
       "      <td>56438999</td>\n",
       "      <td>828234</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Autauga, Alabama, USBaldwin, Alabama, USBarbou...</td>\n",
       "      <td>5.576002e+07</td>\n",
       "      <td>7600.185927</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Country_Region         FIPS  \\\n",
       "186             US  105902623.0   \n",
       "\n",
       "                                                Admin2  \\\n",
       "186  AutaugaBaldwinBarbourBibbBlountBullockButlerCa...   \n",
       "\n",
       "                                        Province_State  \\\n",
       "186  AlabamaAlabamaAlabamaAlabamaAlabamaAlabamaAlab...   \n",
       "\n",
       "                                           Last_Update            Lat  \\\n",
       "186  2022-01-04 04:22:172022-01-04 04:22:172022-01-...  121693.134039   \n",
       "\n",
       "             Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "186 -293352.619164   56438999  828234        0.0     0.0   \n",
       "\n",
       "                                          Combined_Key  Incident_Rate  \\\n",
       "186  Autauga, Alabama, USBaldwin, Alabama, USBarbou...   5.576002e+07   \n",
       "\n",
       "     Case_Fatality_Ratio  \n",
       "186          7600.185927  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_most_cases = df_countries.nlargest(1,\"Confirmed\")\n",
    "df_most_cases"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 🔬 Checkpoint Tests 🔬"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🎉 All Tests Passed! 🎉\n"
     ]
    }
   ],
   "source": [
    "### TEST CASE for Data Analysis\n",
    "tada = \"\\N{PARTY POPPER}\"\n",
    "\n",
    "assert(\"df_us\" in vars())\n",
    "assert(\"Province_State\" in df_us)\n",
    "\n",
    "assert(\"df_us_sorted\" in vars())\n",
    "assert(df_us_sorted.iloc[:,-7].values[2] <= df_us_sorted.iloc[:,-7].values[1])\n",
    "assert(df_us_sorted.iloc[:,-7].values[10] <= df_us_sorted.iloc[:,-7].values[9])\n",
    "assert(df_us_sorted[\"Confirmed\"].values[0]) == max(df_us[\"Confirmed\"])\n",
    "\n",
    "assert(\"df_countries\" in vars())\n",
    "assert(df_countries[\"Confirmed\"].sum() == df[\"Confirmed\"].cumsum().values[len(df) - 1])\n",
    "\n",
    "assert(\"df_most_cases\" in vars())\n",
    "assert(len(df_most_cases) == 1)\n",
    "assert(len(df_most_cases.iloc[0][\"Country_Region\"]) == 2)\n",
    "\n",
    "print(f\"{tada} All Tests Passed! {tada}\")\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr style=\"color: #DD3403;\">"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Checking for the Pareto principle\n",
    "\n",
    "The Pareto principle states that *\"for many outcomes, roughly 80% of consequences come from 20% of causes (the \"vital few\")\"* ([See more on Wikipedia: Pareto principle](https://en.wikipedia.org/wiki/Pareto_principle)).  This is also known as the \"80-20 rule\" and appears often in Data Science.\n",
    "\n",
    "In terms of COVID-19 cases, the application of the Pareto principle would be that **80% of confirmed cases comes from just 20% of countries**.  Is this true?\n",
    "\n",
    "To test this, we need to find total number of cases across all countries.  Compute the total number of confirmed cases in the variable `confirmed_total` (this should be a number, not a DataFrame):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "293190148"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confirmed_total = df_countries[\"Confirmed\"].sum()\n",
    "confirmed_total"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using a bit of math, 80% of the total number of confirmed cases would be:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "234552118.4"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confirmed_80pct = confirmed_total * 0.8\n",
    "confirmed_80pct"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Finding the Cumulative Sum of Cases\n",
    "\n",
    "DataFrames provides the function \"cumulative sum\" function, or `df.cumsum(...)`, that allows us to calculate the sum of every row up until and including the current row.\n",
    "\n",
    "Read the DISCOVERY guide to learn the syntax on \"What is the Cumulative Sum of a pandas DataFrame?\" to find out more on using the cumulative sum function:\n",
    "- [Guide: \"What is the Cumulative Sum of a pandas DataFrame?\"](https://discovery.cs.illinois.edu/guides/DataFrame-Fundamentals/Cumulative-Sum-in-pandas/)\n",
    "\n",
    "Before finding the cumulative sum, we need to have a sorted DataFrame of all countries in ascending order.  Use `df_countries` to create a DataFrame sorted by confirmed cases in the variable `df_countries_sorted`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Country_Region</th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Admin2</th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Last_Update</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long_</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>Combined_Key</th>\n",
       "      <th>Incident_Rate</th>\n",
       "      <th>Case_Fatality_Ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>US</td>\n",
       "      <td>105902623.0</td>\n",
       "      <td>AutaugaBaldwinBarbourBibbBlountBullockButlerCa...</td>\n",
       "      <td>AlabamaAlabamaAlabamaAlabamaAlabamaAlabamaAlab...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>121693.134039</td>\n",
       "      <td>-293352.619164</td>\n",
       "      <td>56438999</td>\n",
       "      <td>828234</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Autauga, Alabama, USBaldwin, Alabama, USBarbou...</td>\n",
       "      <td>5.576002e+07</td>\n",
       "      <td>7600.185927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>India</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Andaman and Nicobar IslandsAndhra PradeshAruna...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>831.177882</td>\n",
       "      <td>2945.020567</td>\n",
       "      <td>34960261</td>\n",
       "      <td>482017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Andaman and Nicobar Islands, IndiaAndhra Prade...</td>\n",
       "      <td>1.537603e+05</td>\n",
       "      <td>46.956740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AcreAlagoasAmapaAmazonasBahiaCearaDistrito Fed...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>-342.077100</td>\n",
       "      <td>-1308.973300</td>\n",
       "      <td>22309081</td>\n",
       "      <td>619473</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Acre, BrazilAlagoas, BrazilAmapa, BrazilAmazon...</td>\n",
       "      <td>3.272539e+05</td>\n",
       "      <td>66.658983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AnguillaBermudaBritish Virgin IslandsCayman Is...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>496.754894</td>\n",
       "      <td>-642.546956</td>\n",
       "      <td>13498751</td>\n",
       "      <td>178396</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Anguilla, United KingdomBermuda, United Kingdo...</td>\n",
       "      <td>1.993084e+05</td>\n",
       "      <td>11.388305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>France</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>French GuianaFrench PolynesiaGuadeloupeMartini...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>77.169695</td>\n",
       "      <td>-416.763414</td>\n",
       "      <td>10422830</td>\n",
       "      <td>125200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>French Guiana, FranceFrench Polynesia, FranceG...</td>\n",
       "      <td>1.306596e+05</td>\n",
       "      <td>13.176218</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>Tonga</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-21.179000</td>\n",
       "      <td>-175.198200</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Tonga</td>\n",
       "      <td>9.461006e-01</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Korea, North</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>40.339900</td>\n",
       "      <td>127.510100</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Korea, North</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>Nauru</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-0.522800</td>\n",
       "      <td>166.931500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Nauru</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>Winter Olympics 2022</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>39.904200</td>\n",
       "      <td>116.407400</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Winter Olympics 2022</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>Tuvalu</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-7.109500</td>\n",
       "      <td>177.649300</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Tuvalu</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>201 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country_Region         FIPS  \\\n",
       "186                    US  105902623.0   \n",
       "80                  India          0.0   \n",
       "24                 Brazil          0.0   \n",
       "190        United Kingdom          0.0   \n",
       "63                 France          0.0   \n",
       "..                    ...          ...   \n",
       "181                 Tonga          0.0   \n",
       "93           Korea, North          0.0   \n",
       "126                 Nauru          0.0   \n",
       "197  Winter Olympics 2022          0.0   \n",
       "185                Tuvalu          0.0   \n",
       "\n",
       "                                                Admin2  \\\n",
       "186  AutaugaBaldwinBarbourBibbBlountBullockButlerCa...   \n",
       "80                                                   0   \n",
       "24                                                   0   \n",
       "190                                                  0   \n",
       "63                                                   0   \n",
       "..                                                 ...   \n",
       "181                                                  0   \n",
       "93                                                   0   \n",
       "126                                                  0   \n",
       "197                                                  0   \n",
       "185                                                  0   \n",
       "\n",
       "                                        Province_State  \\\n",
       "186  AlabamaAlabamaAlabamaAlabamaAlabamaAlabamaAlab...   \n",
       "80   Andaman and Nicobar IslandsAndhra PradeshAruna...   \n",
       "24   AcreAlagoasAmapaAmazonasBahiaCearaDistrito Fed...   \n",
       "190  AnguillaBermudaBritish Virgin IslandsCayman Is...   \n",
       "63   French GuianaFrench PolynesiaGuadeloupeMartini...   \n",
       "..                                                 ...   \n",
       "181                                                  0   \n",
       "93                                                   0   \n",
       "126                                                  0   \n",
       "197                                                  0   \n",
       "185                                                  0   \n",
       "\n",
       "                                           Last_Update            Lat  \\\n",
       "186  2022-01-04 04:22:172022-01-04 04:22:172022-01-...  121693.134039   \n",
       "80   2022-01-04 04:22:172022-01-04 04:22:172022-01-...     831.177882   \n",
       "24   2022-01-04 04:22:172022-01-04 04:22:172022-01-...    -342.077100   \n",
       "190  2022-01-04 04:22:172022-01-04 04:22:172022-01-...     496.754894   \n",
       "63   2022-01-04 04:22:172022-01-04 04:22:172022-01-...      77.169695   \n",
       "..                                                 ...            ...   \n",
       "181                                2022-01-04 04:22:17     -21.179000   \n",
       "93                                 2022-01-04 04:22:17      40.339900   \n",
       "126                                2022-01-04 04:22:17      -0.522800   \n",
       "197                                2022-01-04 04:22:17      39.904200   \n",
       "185                                2022-01-04 04:22:17      -7.109500   \n",
       "\n",
       "             Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "186 -293352.619164   56438999  828234        0.0     0.0   \n",
       "80     2945.020567   34960261  482017        0.0     0.0   \n",
       "24    -1308.973300   22309081  619473        0.0     0.0   \n",
       "190    -642.546956   13498751  178396        0.0     0.0   \n",
       "63     -416.763414   10422830  125200        0.0     0.0   \n",
       "..             ...        ...     ...        ...     ...   \n",
       "181    -175.198200          1       0        0.0     0.0   \n",
       "93      127.510100          0       0        0.0     0.0   \n",
       "126     166.931500          0       0        0.0     0.0   \n",
       "197     116.407400          0       0        0.0     0.0   \n",
       "185     177.649300          0       0        0.0     0.0   \n",
       "\n",
       "                                          Combined_Key  Incident_Rate  \\\n",
       "186  Autauga, Alabama, USBaldwin, Alabama, USBarbou...   5.576002e+07   \n",
       "80   Andaman and Nicobar Islands, IndiaAndhra Prade...   1.537603e+05   \n",
       "24   Acre, BrazilAlagoas, BrazilAmapa, BrazilAmazon...   3.272539e+05   \n",
       "190  Anguilla, United KingdomBermuda, United Kingdo...   1.993084e+05   \n",
       "63   French Guiana, FranceFrench Polynesia, FranceG...   1.306596e+05   \n",
       "..                                                 ...            ...   \n",
       "181                                              Tonga   9.461006e-01   \n",
       "93                                        Korea, North   0.000000e+00   \n",
       "126                                              Nauru   0.000000e+00   \n",
       "197                               Winter Olympics 2022   0.000000e+00   \n",
       "185                                             Tuvalu   0.000000e+00   \n",
       "\n",
       "     Case_Fatality_Ratio  \n",
       "186          7600.185927  \n",
       "80             46.956740  \n",
       "24             66.658983  \n",
       "190            11.388305  \n",
       "63             13.176218  \n",
       "..                   ...  \n",
       "181             0.000000  \n",
       "93              0.000000  \n",
       "126             0.000000  \n",
       "197             0.000000  \n",
       "185             0.000000  \n",
       "\n",
       "[201 rows x 14 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_countries_sorted = df_countries.sort_values(\"Confirmed\",ascending=False)\n",
    "df_countries_sorted"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using `df_countries_sorted`, create a new column called `Cumulative Confirmed` that contains the cumulative sum of the Confirmed cases:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country_Region</th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Admin2</th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Last_Update</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long_</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>Combined_Key</th>\n",
       "      <th>Incident_Rate</th>\n",
       "      <th>Case_Fatality_Ratio</th>\n",
       "      <th>Cumulative Confirmed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>US</td>\n",
       "      <td>105902623.0</td>\n",
       "      <td>AutaugaBaldwinBarbourBibbBlountBullockButlerCa...</td>\n",
       "      <td>AlabamaAlabamaAlabamaAlabamaAlabamaAlabamaAlab...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>121693.134039</td>\n",
       "      <td>-293352.619164</td>\n",
       "      <td>56438999</td>\n",
       "      <td>828234</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Autauga, Alabama, USBaldwin, Alabama, USBarbou...</td>\n",
       "      <td>5.576002e+07</td>\n",
       "      <td>7600.185927</td>\n",
       "      <td>56438999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>India</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Andaman and Nicobar IslandsAndhra PradeshAruna...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>831.177882</td>\n",
       "      <td>2945.020567</td>\n",
       "      <td>34960261</td>\n",
       "      <td>482017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Andaman and Nicobar Islands, IndiaAndhra Prade...</td>\n",
       "      <td>1.537603e+05</td>\n",
       "      <td>46.956740</td>\n",
       "      <td>91399260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AcreAlagoasAmapaAmazonasBahiaCearaDistrito Fed...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>-342.077100</td>\n",
       "      <td>-1308.973300</td>\n",
       "      <td>22309081</td>\n",
       "      <td>619473</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Acre, BrazilAlagoas, BrazilAmapa, BrazilAmazon...</td>\n",
       "      <td>3.272539e+05</td>\n",
       "      <td>66.658983</td>\n",
       "      <td>113708341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AnguillaBermudaBritish Virgin IslandsCayman Is...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>496.754894</td>\n",
       "      <td>-642.546956</td>\n",
       "      <td>13498751</td>\n",
       "      <td>178396</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Anguilla, United KingdomBermuda, United Kingdo...</td>\n",
       "      <td>1.993084e+05</td>\n",
       "      <td>11.388305</td>\n",
       "      <td>127207092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>France</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>French GuianaFrench PolynesiaGuadeloupeMartini...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>77.169695</td>\n",
       "      <td>-416.763414</td>\n",
       "      <td>10422830</td>\n",
       "      <td>125200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>French Guiana, FranceFrench Polynesia, FranceG...</td>\n",
       "      <td>1.306596e+05</td>\n",
       "      <td>13.176218</td>\n",
       "      <td>137629922</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>Tonga</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-21.179000</td>\n",
       "      <td>-175.198200</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Tonga</td>\n",
       "      <td>9.461006e-01</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>293190148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Korea, North</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>40.339900</td>\n",
       "      <td>127.510100</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Korea, North</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>293190148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>Nauru</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-0.522800</td>\n",
       "      <td>166.931500</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Nauru</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>293190148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>Winter Olympics 2022</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>39.904200</td>\n",
       "      <td>116.407400</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Winter Olympics 2022</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>293190148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>Tuvalu</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-7.109500</td>\n",
       "      <td>177.649300</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Tuvalu</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>293190148</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>201 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Country_Region         FIPS  \\\n",
       "186                    US  105902623.0   \n",
       "80                  India          0.0   \n",
       "24                 Brazil          0.0   \n",
       "190        United Kingdom          0.0   \n",
       "63                 France          0.0   \n",
       "..                    ...          ...   \n",
       "181                 Tonga          0.0   \n",
       "93           Korea, North          0.0   \n",
       "126                 Nauru          0.0   \n",
       "197  Winter Olympics 2022          0.0   \n",
       "185                Tuvalu          0.0   \n",
       "\n",
       "                                                Admin2  \\\n",
       "186  AutaugaBaldwinBarbourBibbBlountBullockButlerCa...   \n",
       "80                                                   0   \n",
       "24                                                   0   \n",
       "190                                                  0   \n",
       "63                                                   0   \n",
       "..                                                 ...   \n",
       "181                                                  0   \n",
       "93                                                   0   \n",
       "126                                                  0   \n",
       "197                                                  0   \n",
       "185                                                  0   \n",
       "\n",
       "                                        Province_State  \\\n",
       "186  AlabamaAlabamaAlabamaAlabamaAlabamaAlabamaAlab...   \n",
       "80   Andaman and Nicobar IslandsAndhra PradeshAruna...   \n",
       "24   AcreAlagoasAmapaAmazonasBahiaCearaDistrito Fed...   \n",
       "190  AnguillaBermudaBritish Virgin IslandsCayman Is...   \n",
       "63   French GuianaFrench PolynesiaGuadeloupeMartini...   \n",
       "..                                                 ...   \n",
       "181                                                  0   \n",
       "93                                                   0   \n",
       "126                                                  0   \n",
       "197                                                  0   \n",
       "185                                                  0   \n",
       "\n",
       "                                           Last_Update            Lat  \\\n",
       "186  2022-01-04 04:22:172022-01-04 04:22:172022-01-...  121693.134039   \n",
       "80   2022-01-04 04:22:172022-01-04 04:22:172022-01-...     831.177882   \n",
       "24   2022-01-04 04:22:172022-01-04 04:22:172022-01-...    -342.077100   \n",
       "190  2022-01-04 04:22:172022-01-04 04:22:172022-01-...     496.754894   \n",
       "63   2022-01-04 04:22:172022-01-04 04:22:172022-01-...      77.169695   \n",
       "..                                                 ...            ...   \n",
       "181                                2022-01-04 04:22:17     -21.179000   \n",
       "93                                 2022-01-04 04:22:17      40.339900   \n",
       "126                                2022-01-04 04:22:17      -0.522800   \n",
       "197                                2022-01-04 04:22:17      39.904200   \n",
       "185                                2022-01-04 04:22:17      -7.109500   \n",
       "\n",
       "             Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "186 -293352.619164   56438999  828234        0.0     0.0   \n",
       "80     2945.020567   34960261  482017        0.0     0.0   \n",
       "24    -1308.973300   22309081  619473        0.0     0.0   \n",
       "190    -642.546956   13498751  178396        0.0     0.0   \n",
       "63     -416.763414   10422830  125200        0.0     0.0   \n",
       "..             ...        ...     ...        ...     ...   \n",
       "181    -175.198200          1       0        0.0     0.0   \n",
       "93      127.510100          0       0        0.0     0.0   \n",
       "126     166.931500          0       0        0.0     0.0   \n",
       "197     116.407400          0       0        0.0     0.0   \n",
       "185     177.649300          0       0        0.0     0.0   \n",
       "\n",
       "                                          Combined_Key  Incident_Rate  \\\n",
       "186  Autauga, Alabama, USBaldwin, Alabama, USBarbou...   5.576002e+07   \n",
       "80   Andaman and Nicobar Islands, IndiaAndhra Prade...   1.537603e+05   \n",
       "24   Acre, BrazilAlagoas, BrazilAmapa, BrazilAmazon...   3.272539e+05   \n",
       "190  Anguilla, United KingdomBermuda, United Kingdo...   1.993084e+05   \n",
       "63   French Guiana, FranceFrench Polynesia, FranceG...   1.306596e+05   \n",
       "..                                                 ...            ...   \n",
       "181                                              Tonga   9.461006e-01   \n",
       "93                                        Korea, North   0.000000e+00   \n",
       "126                                              Nauru   0.000000e+00   \n",
       "197                               Winter Olympics 2022   0.000000e+00   \n",
       "185                                             Tuvalu   0.000000e+00   \n",
       "\n",
       "     Case_Fatality_Ratio  Cumulative Confirmed  \n",
       "186          7600.185927              56438999  \n",
       "80             46.956740              91399260  \n",
       "24             66.658983             113708341  \n",
       "190            11.388305             127207092  \n",
       "63             13.176218             137629922  \n",
       "..                   ...                   ...  \n",
       "181             0.000000             293190148  \n",
       "93              0.000000             293190148  \n",
       "126             0.000000             293190148  \n",
       "197             0.000000             293190148  \n",
       "185             0.000000             293190148  \n",
       "\n",
       "[201 rows x 15 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_countries_sorted[\"Cumulative Confirmed\"] = df_countries_sorted[\"Confirmed\"].cumsum()\n",
    "df_countries_sorted"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, create a DataFrame called `df_80pct` with all the countries up to the country that, cumulatively, account for 80% of the global cases (remember, that's the cases you stored in `confirmed_80pct`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Country_Region</th>\n",
       "      <th>FIPS</th>\n",
       "      <th>Admin2</th>\n",
       "      <th>Province_State</th>\n",
       "      <th>Last_Update</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Long_</th>\n",
       "      <th>Confirmed</th>\n",
       "      <th>Deaths</th>\n",
       "      <th>Recovered</th>\n",
       "      <th>Active</th>\n",
       "      <th>Combined_Key</th>\n",
       "      <th>Incident_Rate</th>\n",
       "      <th>Case_Fatality_Ratio</th>\n",
       "      <th>Cumulative Confirmed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>US</td>\n",
       "      <td>105902623.0</td>\n",
       "      <td>AutaugaBaldwinBarbourBibbBlountBullockButlerCa...</td>\n",
       "      <td>AlabamaAlabamaAlabamaAlabamaAlabamaAlabamaAlab...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>121693.134039</td>\n",
       "      <td>-293352.619164</td>\n",
       "      <td>56438999</td>\n",
       "      <td>828234</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Autauga, Alabama, USBaldwin, Alabama, USBarbou...</td>\n",
       "      <td>5.576002e+07</td>\n",
       "      <td>7600.185927</td>\n",
       "      <td>56438999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>India</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Andaman and Nicobar IslandsAndhra PradeshAruna...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>831.177882</td>\n",
       "      <td>2945.020567</td>\n",
       "      <td>34960261</td>\n",
       "      <td>482017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Andaman and Nicobar Islands, IndiaAndhra Prade...</td>\n",
       "      <td>1.537603e+05</td>\n",
       "      <td>46.956740</td>\n",
       "      <td>91399260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Brazil</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AcreAlagoasAmapaAmazonasBahiaCearaDistrito Fed...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>-342.077100</td>\n",
       "      <td>-1308.973300</td>\n",
       "      <td>22309081</td>\n",
       "      <td>619473</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Acre, BrazilAlagoas, BrazilAmapa, BrazilAmazon...</td>\n",
       "      <td>3.272539e+05</td>\n",
       "      <td>66.658983</td>\n",
       "      <td>113708341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AnguillaBermudaBritish Virgin IslandsCayman Is...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>496.754894</td>\n",
       "      <td>-642.546956</td>\n",
       "      <td>13498751</td>\n",
       "      <td>178396</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Anguilla, United KingdomBermuda, United Kingdo...</td>\n",
       "      <td>1.993084e+05</td>\n",
       "      <td>11.388305</td>\n",
       "      <td>127207092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>France</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>French GuianaFrench PolynesiaGuadeloupeMartini...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>77.169695</td>\n",
       "      <td>-416.763414</td>\n",
       "      <td>10422830</td>\n",
       "      <td>125200</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>French Guiana, FranceFrench Polynesia, FranceG...</td>\n",
       "      <td>1.306596e+05</td>\n",
       "      <td>13.176218</td>\n",
       "      <td>137629922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Russia</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Adygea RepublicAltai KraiAltai RepublicAmur Ob...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>4527.343882</td>\n",
       "      <td>5156.031399</td>\n",
       "      <td>10374292</td>\n",
       "      <td>305096</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Adygea Republic, RussiaAltai Krai, RussiaAltai...</td>\n",
       "      <td>5.899722e+05</td>\n",
       "      <td>250.391796</td>\n",
       "      <td>148004214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>Turkey</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>38.963700</td>\n",
       "      <td>35.243300</td>\n",
       "      <td>9597670</td>\n",
       "      <td>82795</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Turkey</td>\n",
       "      <td>1.138220e+04</td>\n",
       "      <td>0.862480</td>\n",
       "      <td>157601884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Germany</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Baden-WurttembergBayernBerlinBrandenburgBremen...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>825.149500</td>\n",
       "      <td>164.446100</td>\n",
       "      <td>7129500</td>\n",
       "      <td>111602</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Baden-Wurttemberg, GermanyBayern, GermanyBerli...</td>\n",
       "      <td>1.400206e+05</td>\n",
       "      <td>25.414232</td>\n",
       "      <td>164731384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>Spain</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AndalusiaAragonAsturiasBalearesC. ValencianaCa...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>755.510158</td>\n",
       "      <td>-69.972552</td>\n",
       "      <td>6667511</td>\n",
       "      <td>89573</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Andalusia, SpainAragon, SpainAsturias, SpainBa...</td>\n",
       "      <td>2.679851e+05</td>\n",
       "      <td>24.964501</td>\n",
       "      <td>171398895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>Italy</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AbruzzoBasilicataCalabriaCampaniaEmilia-Romagn...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>903.972147</td>\n",
       "      <td>256.745065</td>\n",
       "      <td>6396110</td>\n",
       "      <td>137786</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Abruzzo, ItalyBasilicata, ItalyCalabria, Italy...</td>\n",
       "      <td>2.178439e+05</td>\n",
       "      <td>44.653120</td>\n",
       "      <td>177795005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Iran</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>32.427908</td>\n",
       "      <td>53.688046</td>\n",
       "      <td>6198590</td>\n",
       "      <td>131702</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Iran</td>\n",
       "      <td>7.379893e+03</td>\n",
       "      <td>2.124709</td>\n",
       "      <td>183993595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-38.416100</td>\n",
       "      <td>-63.616700</td>\n",
       "      <td>5739326</td>\n",
       "      <td>117245</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>1.269881e+04</td>\n",
       "      <td>2.042836</td>\n",
       "      <td>189732921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Colombia</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AmazonasAntioquiaAraucaAtlanticoBolivarBoyacaC...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>176.521600</td>\n",
       "      <td>-2448.296300</td>\n",
       "      <td>5191021</td>\n",
       "      <td>130061</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Amazonas, ColombiaAntioquia, ColombiaArauca, C...</td>\n",
       "      <td>2.688351e+05</td>\n",
       "      <td>91.245576</td>\n",
       "      <td>194923942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>Indonesia</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-0.789300</td>\n",
       "      <td>113.921300</td>\n",
       "      <td>4263433</td>\n",
       "      <td>144102</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Indonesia</td>\n",
       "      <td>1.558707e+03</td>\n",
       "      <td>3.379952</td>\n",
       "      <td>199187375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Poland</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>51.919400</td>\n",
       "      <td>19.145100</td>\n",
       "      <td>4133851</td>\n",
       "      <td>97601</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Poland</td>\n",
       "      <td>1.092265e+04</td>\n",
       "      <td>2.361019</td>\n",
       "      <td>203321226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>Mexico</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AguascalientesBaja CaliforniaBaja California S...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>695.047500</td>\n",
       "      <td>-3216.873200</td>\n",
       "      <td>3993464</td>\n",
       "      <td>299581</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Aguascalientes, MexicoBaja California, MexicoB...</td>\n",
       "      <td>1.019636e+05</td>\n",
       "      <td>267.131987</td>\n",
       "      <td>207314690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>Ukraine</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>Cherkasy OblastChernihiv OblastChernivtsi Obla...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>1318.826600</td>\n",
       "      <td>831.094400</td>\n",
       "      <td>3856359</td>\n",
       "      <td>102558</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Cherkasy Oblast, UkraineChernihiv Oblast, Ukra...</td>\n",
       "      <td>2.427613e+05</td>\n",
       "      <td>74.057612</td>\n",
       "      <td>211171049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>South Africa</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>-30.559500</td>\n",
       "      <td>22.937500</td>\n",
       "      <td>3475512</td>\n",
       "      <td>91312</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>South Africa</td>\n",
       "      <td>5.860038e+03</td>\n",
       "      <td>2.627296</td>\n",
       "      <td>214646561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>Netherlands</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>ArubaBonaire, Sint Eustatius and SabaCuracaoDr...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>682.008776</td>\n",
       "      <td>-203.678156</td>\n",
       "      <td>3234143</td>\n",
       "      <td>21439</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Aruba, NetherlandsBonaire, Sint Eustatius and ...</td>\n",
       "      <td>2.675149e+05</td>\n",
       "      <td>11.288161</td>\n",
       "      <td>217880704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>Philippines</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>12.879721</td>\n",
       "      <td>121.774017</td>\n",
       "      <td>2855819</td>\n",
       "      <td>51586</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Philippines</td>\n",
       "      <td>2.606124e+03</td>\n",
       "      <td>1.806347</td>\n",
       "      <td>220736523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>Malaysia</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>JohorKedahKelantanMelakaNegeri SembilanPahangP...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>66.174400</td>\n",
       "      <td>1665.209500</td>\n",
       "      <td>2767044</td>\n",
       "      <td>31560</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Johor, MalaysiaKedah, MalaysiaKelantan, Malays...</td>\n",
       "      <td>1.299151e+05</td>\n",
       "      <td>17.663864</td>\n",
       "      <td>223503567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Czechia</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>49.817500</td>\n",
       "      <td>15.473000</td>\n",
       "      <td>2483762</td>\n",
       "      <td>36255</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Czechia</td>\n",
       "      <td>2.319326e+04</td>\n",
       "      <td>1.459681</td>\n",
       "      <td>225987329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Canada</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AlbertaBritish ColumbiaDiamond PrincessGrand P...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172020-12-...</td>\n",
       "      <td>708.855600</td>\n",
       "      <td>-1202.597900</td>\n",
       "      <td>2323056</td>\n",
       "      <td>30400</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Alberta, CanadaBritish Columbia, CanadaDiamond...</td>\n",
       "      <td>5.621980e+04</td>\n",
       "      <td>11.988604</td>\n",
       "      <td>228310385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Peru</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>AmazonasAncashApurimacArequipaAyacuchoCajamarc...</td>\n",
       "      <td>2022-01-04 04:22:172022-01-04 04:22:172022-01-...</td>\n",
       "      <td>-265.933101</td>\n",
       "      <td>-1881.943595</td>\n",
       "      <td>2304674</td>\n",
       "      <td>202818</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Amazonas, PeruAncash, PeruApurimac, PeruArequi...</td>\n",
       "      <td>1.640096e+05</td>\n",
       "      <td>205.400435</td>\n",
       "      <td>230615059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>Thailand</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2022-01-04 04:22:17</td>\n",
       "      <td>15.870032</td>\n",
       "      <td>100.992541</td>\n",
       "      <td>2232485</td>\n",
       "      <td>21738</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Thailand</td>\n",
       "      <td>3.198404e+03</td>\n",
       "      <td>0.973713</td>\n",
       "      <td>232847544</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Country_Region         FIPS  \\\n",
       "186              US  105902623.0   \n",
       "80            India          0.0   \n",
       "24           Brazil          0.0   \n",
       "190  United Kingdom          0.0   \n",
       "63           France          0.0   \n",
       "147          Russia          0.0   \n",
       "184          Turkey          0.0   \n",
       "67          Germany          0.0   \n",
       "167           Spain          0.0   \n",
       "86            Italy          0.0   \n",
       "82             Iran          0.0   \n",
       "7         Argentina          0.0   \n",
       "38         Colombia          0.0   \n",
       "81        Indonesia          0.0   \n",
       "143          Poland          0.0   \n",
       "117          Mexico          0.0   \n",
       "188         Ukraine          0.0   \n",
       "165    South Africa          0.0   \n",
       "128     Netherlands          0.0   \n",
       "142     Philippines          0.0   \n",
       "110        Malaysia          0.0   \n",
       "47          Czechia          0.0   \n",
       "33           Canada          0.0   \n",
       "141            Peru          0.0   \n",
       "178        Thailand          0.0   \n",
       "\n",
       "                                                Admin2  \\\n",
       "186  AutaugaBaldwinBarbourBibbBlountBullockButlerCa...   \n",
       "80                                                   0   \n",
       "24                                                   0   \n",
       "190                                                  0   \n",
       "63                                                   0   \n",
       "147                                                  0   \n",
       "184                                                  0   \n",
       "67                                                   0   \n",
       "167                                                  0   \n",
       "86                                                   0   \n",
       "82                                                   0   \n",
       "7                                                    0   \n",
       "38                                                   0   \n",
       "81                                                   0   \n",
       "143                                                  0   \n",
       "117                                                  0   \n",
       "188                                                  0   \n",
       "165                                                  0   \n",
       "128                                                  0   \n",
       "142                                                  0   \n",
       "110                                                  0   \n",
       "47                                                   0   \n",
       "33                                                   0   \n",
       "141                                                  0   \n",
       "178                                                  0   \n",
       "\n",
       "                                        Province_State  \\\n",
       "186  AlabamaAlabamaAlabamaAlabamaAlabamaAlabamaAlab...   \n",
       "80   Andaman and Nicobar IslandsAndhra PradeshAruna...   \n",
       "24   AcreAlagoasAmapaAmazonasBahiaCearaDistrito Fed...   \n",
       "190  AnguillaBermudaBritish Virgin IslandsCayman Is...   \n",
       "63   French GuianaFrench PolynesiaGuadeloupeMartini...   \n",
       "147  Adygea RepublicAltai KraiAltai RepublicAmur Ob...   \n",
       "184                                                  0   \n",
       "67   Baden-WurttembergBayernBerlinBrandenburgBremen...   \n",
       "167  AndalusiaAragonAsturiasBalearesC. ValencianaCa...   \n",
       "86   AbruzzoBasilicataCalabriaCampaniaEmilia-Romagn...   \n",
       "82                                                   0   \n",
       "7                                                    0   \n",
       "38   AmazonasAntioquiaAraucaAtlanticoBolivarBoyacaC...   \n",
       "81                                                   0   \n",
       "143                                                  0   \n",
       "117  AguascalientesBaja CaliforniaBaja California S...   \n",
       "188  Cherkasy OblastChernihiv OblastChernivtsi Obla...   \n",
       "165                                                  0   \n",
       "128  ArubaBonaire, Sint Eustatius and SabaCuracaoDr...   \n",
       "142                                                  0   \n",
       "110  JohorKedahKelantanMelakaNegeri SembilanPahangP...   \n",
       "47                                                   0   \n",
       "33   AlbertaBritish ColumbiaDiamond PrincessGrand P...   \n",
       "141  AmazonasAncashApurimacArequipaAyacuchoCajamarc...   \n",
       "178                                                  0   \n",
       "\n",
       "                                           Last_Update            Lat  \\\n",
       "186  2022-01-04 04:22:172022-01-04 04:22:172022-01-...  121693.134039   \n",
       "80   2022-01-04 04:22:172022-01-04 04:22:172022-01-...     831.177882   \n",
       "24   2022-01-04 04:22:172022-01-04 04:22:172022-01-...    -342.077100   \n",
       "190  2022-01-04 04:22:172022-01-04 04:22:172022-01-...     496.754894   \n",
       "63   2022-01-04 04:22:172022-01-04 04:22:172022-01-...      77.169695   \n",
       "147  2022-01-04 04:22:172022-01-04 04:22:172022-01-...    4527.343882   \n",
       "184                                2022-01-04 04:22:17      38.963700   \n",
       "67   2022-01-04 04:22:172022-01-04 04:22:172022-01-...     825.149500   \n",
       "167  2022-01-04 04:22:172022-01-04 04:22:172022-01-...     755.510158   \n",
       "86   2022-01-04 04:22:172022-01-04 04:22:172022-01-...     903.972147   \n",
       "82                                 2022-01-04 04:22:17      32.427908   \n",
       "7                                  2022-01-04 04:22:17     -38.416100   \n",
       "38   2022-01-04 04:22:172022-01-04 04:22:172022-01-...     176.521600   \n",
       "81                                 2022-01-04 04:22:17      -0.789300   \n",
       "143                                2022-01-04 04:22:17      51.919400   \n",
       "117  2022-01-04 04:22:172022-01-04 04:22:172022-01-...     695.047500   \n",
       "188  2022-01-04 04:22:172022-01-04 04:22:172022-01-...    1318.826600   \n",
       "165                                2022-01-04 04:22:17     -30.559500   \n",
       "128  2022-01-04 04:22:172022-01-04 04:22:172022-01-...     682.008776   \n",
       "142                                2022-01-04 04:22:17      12.879721   \n",
       "110  2022-01-04 04:22:172022-01-04 04:22:172022-01-...      66.174400   \n",
       "47                                 2022-01-04 04:22:17      49.817500   \n",
       "33   2022-01-04 04:22:172022-01-04 04:22:172020-12-...     708.855600   \n",
       "141  2022-01-04 04:22:172022-01-04 04:22:172022-01-...    -265.933101   \n",
       "178                                2022-01-04 04:22:17      15.870032   \n",
       "\n",
       "             Long_  Confirmed  Deaths  Recovered  Active  \\\n",
       "186 -293352.619164   56438999  828234        0.0     0.0   \n",
       "80     2945.020567   34960261  482017        0.0     0.0   \n",
       "24    -1308.973300   22309081  619473        0.0     0.0   \n",
       "190    -642.546956   13498751  178396        0.0     0.0   \n",
       "63     -416.763414   10422830  125200        0.0     0.0   \n",
       "147    5156.031399   10374292  305096        0.0     0.0   \n",
       "184      35.243300    9597670   82795        0.0     0.0   \n",
       "67      164.446100    7129500  111602        0.0     0.0   \n",
       "167     -69.972552    6667511   89573        0.0     0.0   \n",
       "86      256.745065    6396110  137786        0.0     0.0   \n",
       "82       53.688046    6198590  131702        0.0     0.0   \n",
       "7       -63.616700    5739326  117245        0.0     0.0   \n",
       "38    -2448.296300    5191021  130061        0.0     0.0   \n",
       "81      113.921300    4263433  144102        0.0     0.0   \n",
       "143      19.145100    4133851   97601        0.0     0.0   \n",
       "117   -3216.873200    3993464  299581        0.0     0.0   \n",
       "188     831.094400    3856359  102558        0.0     0.0   \n",
       "165      22.937500    3475512   91312        0.0     0.0   \n",
       "128    -203.678156    3234143   21439        0.0     0.0   \n",
       "142     121.774017    2855819   51586        0.0     0.0   \n",
       "110    1665.209500    2767044   31560        0.0     0.0   \n",
       "47       15.473000    2483762   36255        0.0     0.0   \n",
       "33    -1202.597900    2323056   30400        0.0     0.0   \n",
       "141   -1881.943595    2304674  202818        0.0     0.0   \n",
       "178     100.992541    2232485   21738        0.0     0.0   \n",
       "\n",
       "                                          Combined_Key  Incident_Rate  \\\n",
       "186  Autauga, Alabama, USBaldwin, Alabama, USBarbou...   5.576002e+07   \n",
       "80   Andaman and Nicobar Islands, IndiaAndhra Prade...   1.537603e+05   \n",
       "24   Acre, BrazilAlagoas, BrazilAmapa, BrazilAmazon...   3.272539e+05   \n",
       "190  Anguilla, United KingdomBermuda, United Kingdo...   1.993084e+05   \n",
       "63   French Guiana, FranceFrench Polynesia, FranceG...   1.306596e+05   \n",
       "147  Adygea Republic, RussiaAltai Krai, RussiaAltai...   5.899722e+05   \n",
       "184                                             Turkey   1.138220e+04   \n",
       "67   Baden-Wurttemberg, GermanyBayern, GermanyBerli...   1.400206e+05   \n",
       "167  Andalusia, SpainAragon, SpainAsturias, SpainBa...   2.679851e+05   \n",
       "86   Abruzzo, ItalyBasilicata, ItalyCalabria, Italy...   2.178439e+05   \n",
       "82                                                Iran   7.379893e+03   \n",
       "7                                            Argentina   1.269881e+04   \n",
       "38   Amazonas, ColombiaAntioquia, ColombiaArauca, C...   2.688351e+05   \n",
       "81                                           Indonesia   1.558707e+03   \n",
       "143                                             Poland   1.092265e+04   \n",
       "117  Aguascalientes, MexicoBaja California, MexicoB...   1.019636e+05   \n",
       "188  Cherkasy Oblast, UkraineChernihiv Oblast, Ukra...   2.427613e+05   \n",
       "165                                       South Africa   5.860038e+03   \n",
       "128  Aruba, NetherlandsBonaire, Sint Eustatius and ...   2.675149e+05   \n",
       "142                                        Philippines   2.606124e+03   \n",
       "110  Johor, MalaysiaKedah, MalaysiaKelantan, Malays...   1.299151e+05   \n",
       "47                                             Czechia   2.319326e+04   \n",
       "33   Alberta, CanadaBritish Columbia, CanadaDiamond...   5.621980e+04   \n",
       "141  Amazonas, PeruAncash, PeruApurimac, PeruArequi...   1.640096e+05   \n",
       "178                                           Thailand   3.198404e+03   \n",
       "\n",
       "     Case_Fatality_Ratio  Cumulative Confirmed  \n",
       "186          7600.185927              56438999  \n",
       "80             46.956740              91399260  \n",
       "24             66.658983             113708341  \n",
       "190            11.388305             127207092  \n",
       "63             13.176218             137629922  \n",
       "147           250.391796             148004214  \n",
       "184             0.862480             157601884  \n",
       "67             25.414232             164731384  \n",
       "167            24.964501             171398895  \n",
       "86             44.653120             177795005  \n",
       "82              2.124709             183993595  \n",
       "7               2.042836             189732921  \n",
       "38             91.245576             194923942  \n",
       "81              3.379952             199187375  \n",
       "143             2.361019             203321226  \n",
       "117           267.131987             207314690  \n",
       "188            74.057612             211171049  \n",
       "165             2.627296             214646561  \n",
       "128            11.288161             217880704  \n",
       "142             1.806347             220736523  \n",
       "110            17.663864             223503567  \n",
       "47              1.459681             225987329  \n",
       "33             11.988604             228310385  \n",
       "141           205.400435             230615059  \n",
       "178             0.973713             232847544  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_80pct = df_countries_sorted[df_countries_sorted[\"Cumulative Confirmed\"]<= confirmed_80pct]\n",
    "df_80pct"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Does the Pareto Principle show up?\n",
    "\n",
    "Currently:\n",
    "- `df_countries` contains EVERY country in the world with COVID-19 data, and\n",
    "- `df_80pct` contains countries that make up 80% of the cases.\n",
    "\n",
    "If the Pareto principle applies to the confirmed cases of COVID-19, then we expect that `df_80pct` holds only approximately 20% of all the countries.  Let's see:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Result: 79.42% of the COVID-19 cases comes from 12.44% of the countries in the dataset.\n"
     ]
    }
   ],
   "source": [
    "pct_cases = 100 * sum(df_80pct[\"Confirmed\"]) / sum(df_countries[\"Confirmed\"])\n",
    "pct_cases = round(pct_cases, 2)\n",
    "\n",
    "pct_countries = 100 * len(df_80pct) / len(df_countries)\n",
    "pct_countries = round(pct_countries, 2)\n",
    "\n",
    "print(f\"Result: {pct_cases}% of the COVID-19 cases comes from {pct_countries}% of the countries in the dataset.\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 🔬 Checkpoint Tests 🔬"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "🎉 All Tests Passed! 🎉\n"
     ]
    }
   ],
   "source": [
    "### TEST CASE for Pareto Principle\n",
    "tada = \"\\N{PARTY POPPER}\"\n",
    "\n",
    "assert(\"confirmed_total\" in vars())\n",
    "assert(\"confirmed_80pct\" in vars())\n",
    "assert(confirmed_total > 2.9e8)\n",
    "                         \n",
    "assert(\"df_countries_sorted\" in vars())\n",
    "assert(\"Cumulative Confirmed\" in df_countries_sorted)\n",
    "assert(max(df_countries_sorted[\"Cumulative Confirmed\"]) == sum(df_countries_sorted[\"Confirmed\"]))\n",
    "assert(min(df_countries_sorted[\"Cumulative Confirmed\"]) == df_countries_sorted.iloc[0][\"Confirmed\"])\n",
    "\n",
    "assert(\"df_80pct\" in vars())\n",
    "assert(\"US\" in df_80pct[\"Country_Region\"].unique())\n",
    "assert(\"India\" in df_80pct[\"Country_Region\"].unique())\n",
    "assert(\"Tonga\" not in df_80pct[\"Country_Region\"].unique())\n",
    "\n",
    "assert(sum(df_80pct[\"Confirmed\"]) / sum(df_countries[\"Confirmed\"]) > 0.7)\n",
    "assert(sum(df_80pct[\"Confirmed\"]) / sum(df_countries[\"Confirmed\"]) < 0.9)\n",
    "\n",
    "assert(len(df_80pct[\"Confirmed\"]) / len(df_countries[\"Confirmed\"]) > 0.1)\n",
    "assert(len(df_80pct[\"Confirmed\"]) / len(df_countries[\"Confirmed\"]) < 0.2)\n",
    "\n",
    "print(f\"{tada} All Tests Passed! {tada}\")"
   ]
  },
  {
   "attachments": {},
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    "## Submission\n",
    "\n",
    "You're almost done!  All you need to do is to commit your lab to GitHub and run the GitHub Actions Grader:\n",
    "\n",
    "1.  ⚠️ **Make certain to save your work.** ⚠️ To do this, go to **File => Save All**\n",
    "\n",
    "2.  After you have saved, exit this notebook and return to https://discovery.cs.illinois.edu/microproject/covid-data-from-github/ and complete the section **\"Commit and Grade Your Notebook\"**.\n",
    "\n",
    "3. If you see a 100% grade result on your GitHub Action, you've completed this MicroProject! 🎉\n"
   ]
  }
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