analise.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "4d976e27",
   "metadata": {},
   "source": [
    "# Análise estatística do dataset \"World COVID-19 Data\"\n",
    "https://www.kaggle.com/datasets/abhishek14398/world-covid19-data\n",
    "\n",
    "Arquivos utilizados:\n",
    "- CONVENIENT_global_confirmed_cases.csv\n",
    "    - Primeira linha: lista de países/regiões\n",
    "    - Segunda linha: lista de províncias/estados para alguns países apenas\n",
    "    - Primeira coluna: datas em dias\n",
    "    - Colunas seguintes, quantidade de casos confirmados\n",
    "- CONVENIENT_global_deaths.csv\n",
    "    - Primeira linha: lista de países/regiões\n",
    "    - Segunda linha: lista de províncias/estados para alguns países apenas\n",
    "    - Primeira coluna: datas em dias\n",
    "    - Colunas seguintes, quantidade de casos de mortes\n",
    "- CONVENIENT_global_metadata.csv\n",
    "    - Primeira linha: header\n",
    "    - Primeira coluna: índice\n",
    "    - Segunda coluna: países/regiões\n",
    "    - Terceira coluna: províncias/estados\n",
    "    - Quarta coluna: latitude\n",
    "    - Quinta coluna: longitude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "324e8c2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# instalação de ffmpeg:\n",
    "# !pip install ffmpeg-python\n",
    "# from IPython.display import HTML\n",
    "# Necessita do ffmpeg, então optamos por não utilizar\n",
    "\n",
    "# importando pacotes\n",
    "import os\n",
    "import warnings\n",
    "import itertools\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.animation as animation\n",
    "import plotly.express as px\n",
    "\n",
    "# ignorar warnings (limpar notebook)\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "# constantes\n",
    "DATA_FOLDER = './data'\n",
    "\n",
    "CONFIRMED_CASES_DATA = 'CONVENIENT_global_confirmed_cases.csv'\n",
    "DEATH_CASES_DATA = 'CONVENIENT_global_deaths.csv'\n",
    "LOCATION_DATA = 'CONVENIENT_global_metadata.csv'\n",
    "GAPMINDER_POP_AREA = 'gapminder_en_pop_dnst.csv'\n",
    "GAPMINDER_GDP_TOTAL = 'gapminder_gdp_total_yearly_growth.csv'\n",
    "GAPMINDER_GDPPERCAPTA = 'gapminder_gdppercapita_us_inflation_adjusted.csv'\n",
    "GAPMINDER_MEDIAN_AGE = 'gapminder_median_age_years.csv'\n",
    "GAPMINDER_POP_TOTAL = 'gapminder_population_total.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "cf49cd14",
   "metadata": {},
   "outputs": [],
   "source": [
    "# realizando a leitura dos dados\n",
    "# esses arquivos tem duas linhas de header, onde a primeira é o nome do país\n",
    "# a segunda é uma região do país, caso exista, senão, vazio (NaN)\n",
    "path_ = os.path.join(DATA_FOLDER, DEATH_CASES_DATA)\n",
    "death = pd.read_csv(path_, sep=',', header=[0,1])\n",
    "# concatena as duas linhas de header\n",
    "death.columns = [f'{i}_{j}' if j != 'nan' else f'{i}' for i, j in death.columns]\n",
    "# modifica nome da primeira coluna\n",
    "death = death.rename(columns={'Country/Region_Province/State': 'data'})\n",
    "# transformando a coluna Data no tipo Data\n",
    "death.data = pd.to_datetime(death.data)\n",
    "\n",
    "# idem para confirmed\n",
    "path_ = os.path.join(DATA_FOLDER, CONFIRMED_CASES_DATA)\n",
    "confirmed = pd.read_csv(path_, sep=',', header=[0,1])\n",
    "confirmed.columns = [f'{i}_{j}' if j != 'nan' else f'{i}' for i, j in confirmed.columns]\n",
    "confirmed = confirmed.rename(columns={'Country/Region_Province/State': 'data'})\n",
    "confirmed.data = pd.to_datetime(confirmed.data)\n",
    "\n",
    "# arquivo de latitude e longitude\n",
    "# primeira coluna de indice\n",
    "path_ = os.path.join(DATA_FOLDER, LOCATION_DATA)\n",
    "location = pd.read_csv(path_, sep=',', index_col=0)\n",
    "# no caso do location tem que criar uma nova coluna para match os nomes dos headers dos dfs death e confirmed\n",
    "location[\"Region\"] = location[\"Country/Region\"].str.cat(location[\"Province/State\"], sep=\"_\", na_rep=\"\")\n",
    "# remover _ de células onde o Province/State era NaN\n",
    "location[\"Region\"] = location[\"Region\"].str.removesuffix(\"_\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "f0e3e0ce",
   "metadata": {},
   "outputs": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country/Region</th>\n",
       "      <th>Province/State</th>\n",
       "      <th>1/23/20</th>\n",
       "      <th>1/24/20</th>\n",
       "      <th>1/25/20</th>\n",
       "      <th>1/26/20</th>\n",
       "      <th>1/27/20</th>\n",
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       "      <th>1/3/23</th>\n",
       "      <th>1/4/23</th>\n",
       "      <th>1/5/23</th>\n",
       "      <th>1/6/23</th>\n",
       "      <th>1/7/23</th>\n",
       "      <th>1/8/23</th>\n",
       "      <th>1/9/23</th>\n",
       "      <th>1/10/23</th>\n",
       "      <th>1/11/23</th>\n",
       "      <th>1/12/23</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Angola</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "    <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",
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       "      <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>284</th>\n",
       "      <td>West Bank and Gaza</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>285</th>\n",
       "      <td>Winter Olympics 2022</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>...</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>287</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>288</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>nan</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>289 rows × 1088 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "0          Country/Region Province/State 1/23/20 1/24/20 1/25/20 1/26/20  \\\n",
       "0             Afghanistan            nan     0.0     0.0     0.0     0.0   \n",
       "1                 Albania            nan     0.0     0.0     0.0     0.0   \n",
       "2                 Algeria            nan     0.0     0.0     0.0     0.0   \n",
       "3                 Andorra            nan     0.0     0.0     0.0     0.0   \n",
       "4                  Angola            nan     0.0     0.0     0.0     0.0   \n",
       "..                    ...            ...     ...     ...     ...     ...   \n",
       "284    West Bank and Gaza            nan     0.0     0.0     0.0     0.0   \n",
       "285  Winter Olympics 2022            nan     0.0     0.0     0.0     0.0   \n",
       "286                 Yemen            nan     0.0     0.0     0.0     0.0   \n",
       "287                Zambia            nan     0.0     0.0     0.0     0.0   \n",
       "288              Zimbabwe            nan     0.0     0.0     0.0     0.0   \n",
       "\n",
       "0   1/27/20 1/28/20 1/29/20 1/30/20  ... 1/3/23 1/4/23 1/5/23 1/6/23 1/7/23  \\\n",
       "0       0.0     0.0     0.0     0.0  ...    1.0    0.0    0.0    0.0    0.0   \n",
       "1       0.0     0.0     0.0     0.0  ...    1.0    0.0    0.0    0.0    0.0   \n",
       "2       0.0     0.0     0.0     0.0  ...    0.0    0.0    0.0    0.0    0.0   \n",
       "3       0.0     0.0     0.0     0.0  ...    0.0    0.0    0.0    0.0    0.0   \n",
       "4       0.0     0.0     0.0     0.0  ...    0.0    0.0    0.0    0.0    0.0   \n",
       "..      ...     ...     ...     ...  ...    ...    ...    ...    ...    ...   \n",
       "284     0.0     0.0     0.0     0.0  ...    0.0    0.0    0.0    0.0    0.0   \n",
       "285     0.0     0.0     0.0     0.0  ...    0.0    0.0    0.0    0.0    0.0   \n",
       "286     0.0     0.0     0.0     0.0  ...    0.0    0.0    0.0    0.0    0.0   \n",
       "287     0.0     0.0     0.0     0.0  ...    0.0    0.0    1.0    0.0    3.0   \n",
       "288     0.0     0.0     0.0     0.0  ...    0.0    0.0    0.0    0.0    0.0   \n",
       "\n",
       "0   1/8/23 1/9/23 1/10/23 1/11/23 1/12/23  \n",
       "0      3.0    1.0     0.0     0.0     0.0  \n",
       "1      0.0    0.0     0.0     0.0     0.0  \n",
       "2      0.0    0.0     0.0     0.0     0.0  \n",
       "3      0.0    0.0     0.0     0.0     0.0  \n",
       "4      0.0    0.0     0.0     0.0     0.0  \n",
       "..     ...    ...     ...     ...     ...  \n",
       "284    0.0    0.0     0.0     0.0     0.0  \n",
       "285    0.0    0.0     0.0     0.0     0.0  \n",
       "286    0.0    0.0     0.0     0.0     0.0  \n",
       "287    0.0    2.0     0.0     1.0     3.0  \n",
       "288    0.0    0.0     0.0     0.0     0.0  \n",
       "\n",
       "[289 rows x 1088 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path_ = os.path.join(DATA_FOLDER, DEATH_CASES_DATA)\n",
    "death = pd.read_csv(path_, sep=',', header=[0,1])\n",
    "teste = death.T.copy()\n",
    "teste.reset_index(inplace=True)\n",
    "teste.columns = teste.loc[0]\n",
    "teste.drop([0], axis=0, inplace=True)\n",
    "teste.reset_index(inplace=True, drop=True)\n",
    "teste"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "teste = teste.groupby(\"Country/Region\").sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "bd3668b4",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "Country/Region Afghanistan Albania Algeria Andorra Angola Antarctica  \\\n",
       "0                                                                      \n",
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       "0                                                      \n",
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       "\n",
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       "1/23/20                                                       0.0  ...   \n",
       "1/24/20                                                       0.0  ...   \n",
       "1/25/20                                                       0.0  ...   \n",
       "1/26/20                                                       0.0  ...   \n",
       "...                                                           ...  ...   \n",
       "1/8/23                                                       16.0  ...   \n",
       "1/9/23                                                       29.0  ...   \n",
       "1/10/23                                                      31.0  ...   \n",
       "1/11/23                                                      31.0  ...   \n",
       "1/12/23                                                     270.0  ...   \n",
       "\n",
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       "0                                                             \n",
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       "\n",
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       "0                                                                             \n",
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       "1/12/23                       0.0                  0.0   0.0    3.0      0.0  \n",
       "\n",
       "[1087 rows x 201 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "teste = teste.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "9a01789e",
   "metadata": {},
   "outputs": [
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       "      <th>2</th>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1081</th>\n",
       "      <td>2023-01-08</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1082</th>\n",
       "      <td>2023-01-09</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1083</th>\n",
       "      <td>2023-01-10</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1084</th>\n",
       "      <td>2023-01-11</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1085</th>\n",
       "      <td>2023-01-12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1086 rows × 290 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           data  Afghanistan  Albania  Algeria  Andorra  Angola  Antarctica  \\\n",
       "0    2020-01-23          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "1    2020-01-24          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "2    2020-01-25          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "3    2020-01-26          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "4    2020-01-27          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "...         ...          ...      ...      ...      ...     ...         ...   \n",
       "1081 2023-01-08          3.0      0.0      0.0      0.0     0.0         0.0   \n",
       "1082 2023-01-09          1.0      0.0      0.0      0.0     0.0         0.0   \n",
       "1083 2023-01-10          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "1084 2023-01-11          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "1085 2023-01-12          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "\n",
       "      Antigua and Barbuda  Argentina  Armenia  ...  Uruguay  Uzbekistan  \\\n",
       "0                     0.0        0.0      0.0  ...      0.0         0.0   \n",
       "1                     0.0        0.0      0.0  ...      0.0         0.0   \n",
       "2                     0.0        0.0      0.0  ...      0.0         0.0   \n",
       "3                     0.0        0.0      0.0  ...      0.0         0.0   \n",
       "4                     0.0        0.0      0.0  ...      0.0         0.0   \n",
       "...                   ...        ...      ...  ...      ...         ...   \n",
       "1081                  0.0        0.0      0.0  ...      0.0         0.0   \n",
       "1082                  0.0       78.0      0.0  ...     16.0         0.0   \n",
       "1083                  0.0        0.0      0.0  ...      0.0         0.0   \n",
       "1084                  0.0        0.0      0.0  ...      0.0         0.0   \n",
       "1085                  0.0        0.0      0.0  ...      0.0         0.0   \n",
       "\n",
       "      Vanuatu  Venezuela  Vietnam  West Bank and Gaza  Winter Olympics 2022  \\\n",
       "0         0.0        0.0      0.0                 0.0                   0.0   \n",
       "1         0.0        0.0      0.0                 0.0                   0.0   \n",
       "2         0.0        0.0      0.0                 0.0                   0.0   \n",
       "3         0.0        0.0      0.0                 0.0                   0.0   \n",
       "4         0.0        0.0      0.0                 0.0                   0.0   \n",
       "...       ...        ...      ...                 ...                   ...   \n",
       "1081      0.0        2.0      0.0                 0.0                   0.0   \n",
       "1082      0.0        0.0      0.0                 0.0                   0.0   \n",
       "1083      0.0        0.0      0.0                 0.0                   0.0   \n",
       "1084      0.0        0.0      0.0                 0.0                   0.0   \n",
       "1085      0.0        0.0      0.0                 0.0                   0.0   \n",
       "\n",
       "      Yemen  Zambia  Zimbabwe  \n",
       "0       0.0     0.0       0.0  \n",
       "1       0.0     0.0       0.0  \n",
       "2       0.0     0.0       0.0  \n",
       "3       0.0     0.0       0.0  \n",
       "4       0.0     0.0       0.0  \n",
       "...     ...     ...       ...  \n",
       "1081    0.0     0.0       0.0  \n",
       "1082    0.0     2.0       0.0  \n",
       "1083    0.0     0.0       0.0  \n",
       "1084    0.0     1.0       0.0  \n",
       "1085    0.0     3.0       0.0  \n",
       "\n",
       "[1086 rows x 290 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "death"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "419a5aa1",
   "metadata": {},
   "outputs": [],
   "source": [
    "confirmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b57cbdf0",
   "metadata": {},
   "outputs": [],
   "source": [
    "location\n",
    "# embora haja muitos valores NaN, nao podemos remover as linhas com NaN, podemos substituir, mas nao sera necessario\n",
    "# pois sera feito posteriormente\n",
    "#checar qtd de NaN e qtd em fração de Nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "95c56b11",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n",
      "True\n",
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "# confirmando se o shape de death e confirmed são iguais (mesma qtd de linhas e colunas)\n",
    "print(death.shape == confirmed.shape)\n",
    "# confirmando se as datas são iguais analisando uma a uma, somando os trues e comparando a quantidade de datas\n",
    "print(sum(death.data == confirmed.data) == death.shape[0])\n",
    "# confirmando se os nomes das colunas são iguais\n",
    "print(sum(death.columns == confirmed.columns) == (death.columns.size))\n",
    "# confirmando se o location[\"Regions\"] bate com os nomes das colunas dos outros dois dfs:\n",
    "print(sum(location[\"Region\"] == death.columns[1:]) == death.columns[1:].size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c738f05",
   "metadata": {},
   "outputs": [],
   "source": [
    "# verificando informações do DF\n",
    "death.info"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "2184d316",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "0\n",
      "====================\n",
      "Andorra                                                        1\n",
      "Angola                                                         1\n",
      "Armenia                                                        1\n",
      "Australia_Australian Capital Territory                         4\n",
      "Australia_New South Wales                                      2\n",
      "                                                              ..\n",
      "United Kingdom_Cayman Islands                                  1\n",
      "United Kingdom_Montserrat                                      1\n",
      "United Kingdom_Saint Helena, Ascension and Tristan da Cunha    1\n",
      "Venezuela                                                      1\n",
      "Vietnam                                                        2\n",
      "Name: 1085, Length: 106, dtype: int32\n",
      "====================\n",
      "Afghanistan                                2\n",
      "Antigua and Barbuda                        2\n",
      "Australia_Australian Capital Territory     7\n",
      "Australia_New South Wales                  8\n",
      "Australia_Northern Territory              23\n",
      "                                          ..\n",
      "United Kingdom                             3\n",
      "Uruguay                                    1\n",
      "Vanuatu                                    2\n",
      "Yemen                                      1\n",
      "Zimbabwe                                   1\n",
      "Name: 1085, Length: 126, dtype: int32\n"
     ]
    }
   ],
   "source": [
    "# checando por dados do tipo NaN\n",
    "print(sum(death.isna().sum()))\n",
    "print(sum(confirmed.isna().sum()))\n",
    "# nao ha dados do tipo NaN\n",
    "print(\"=\"*20)\n",
    "# checando por dados negativos\n",
    "print((death.iloc[:,1:] < 0).cumsum().loc[1085][(death.iloc[:,1:] < 0).cumsum().loc[1085]>0])\n",
    "print(\"=\"*20)\n",
    "print((confirmed.iloc[:,1:] < 0).cumsum().loc[1085][(confirmed.iloc[:,1:] < 0).cumsum().loc[1085]>0])\n",
    "# dados negativos neste caso podem ser dados anteriores errados sendo corrigidas\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "6a1cafb6",
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Afghanistan</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>7.232044</td>\n",
       "      <td>15.972543</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Albania</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>3.311234</td>\n",
       "      <td>4.524262</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>21.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Algeria</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>6.336096</td>\n",
       "      <td>7.518476</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>49.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Andorra</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>0.151934</td>\n",
       "      <td>0.544711</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Angola</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>1.777164</td>\n",
       "      <td>3.100776</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>30.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>West Bank and Gaza</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>5.255985</td>\n",
       "      <td>11.210053</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>268.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Winter Olympics 2022</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yemen</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>1.988029</td>\n",
       "      <td>4.476960</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zambia</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>3.714549</td>\n",
       "      <td>9.796901</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>72.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zimbabwe</th>\n",
       "      <td>1086.0</td>\n",
       "      <td>5.190608</td>\n",
       "      <td>12.912094</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>107.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>289 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       count      mean        std  min  25%  50%  75%    max\n",
       "Afghanistan           1086.0  7.232044  15.972543  0.0  0.0  2.0  6.0  159.0\n",
       "Albania               1086.0  3.311234   4.524262  0.0  0.0  1.0  5.0   21.0\n",
       "Algeria               1086.0  6.336096   7.518476  0.0  0.0  5.0  9.0   49.0\n",
       "Andorra               1086.0  0.151934   0.544711 -2.0  0.0  0.0  0.0    7.0\n",
       "Angola                1086.0  1.777164   3.100776 -3.0  0.0  0.0  3.0   30.0\n",
       "...                      ...       ...        ...  ...  ...  ...  ...    ...\n",
       "West Bank and Gaza    1086.0  5.255985  11.210053  0.0  0.0  1.0  7.0  268.0\n",
       "Winter Olympics 2022  1086.0  0.000000   0.000000  0.0  0.0  0.0  0.0    0.0\n",
       "Yemen                 1086.0  1.988029   4.476960  0.0  0.0  0.0  2.0   60.0\n",
       "Zambia                1086.0  3.714549   9.796901  0.0  0.0  0.0  3.0   72.0\n",
       "Zimbabwe              1086.0  5.190608  12.912094  0.0  0.0  1.0  3.0  107.0\n",
       "\n",
       "[289 rows x 8 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# analise estatistica\n",
    "stats_death = death.describe().T\n",
    "stats_death"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b720f99",
   "metadata": {},
   "outputs": [],
   "source": [
    "# análise estatística\n",
    "stats_confirmed = confirmed.describe().T\n",
    "stats_confirmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ec8baec6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# eliminar variáveis de variância nula (abaixo de um limiar)\n",
    "# stats_death['CV'] = abs(stats_death['std'] * 100 / stats_death['mean'])\n",
    "# stats_confirmed['CV'] = abs(stats_confirmed['std'] * 100 / stats_confirmed['mean'])\n",
    "# print(stats_death)\n",
    "# print(stats_confirmed)\n",
    "# nao faz sentido este tratamento para este dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2829b067",
   "metadata": {},
   "outputs": [],
   "source": [
    "# checando paises com numero de mortes menores que dois\n",
    "stats_death[stats_death['max'] < 2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8a8a020b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ano</th>\n",
       "      <th>mes</th>\n",
       "      <th>Afghanistan</th>\n",
       "      <th>Albania</th>\n",
       "      <th>Algeria</th>\n",
       "      <th>Andorra</th>\n",
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       "      <th>Antigua and Barbuda</th>\n",
       "      <th>Argentina</th>\n",
       "      <th>...</th>\n",
       "      <th>Uzbekistan</th>\n",
       "      <th>Vanuatu</th>\n",
       "      <th>Venezuela</th>\n",
       "      <th>Vietnam</th>\n",
       "      <th>West Bank and Gaza</th>\n",
       "      <th>Winter Olympics 2022</th>\n",
       "      <th>Yemen</th>\n",
       "      <th>Zambia</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>data</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>202001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
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       "      <td>0.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>202002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>3</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>202003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>60.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>218.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>202004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>254.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>653.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>539.0</td>\n",
       "      <td>...</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>202005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020</td>\n",
       "      <td>6</td>\n",
       "      <td>739.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>912.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1307.0</td>\n",
       "      <td>...</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>312.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>202006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020</td>\n",
       "      <td>7</td>\n",
       "      <td>1275.0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>1210.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3543.0</td>\n",
       "      <td>...</td>\n",
       "      <td>141.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>493.0</td>\n",
       "      <td>151.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>202007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2020</td>\n",
       "      <td>8</td>\n",
       "      <td>1406.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>1510.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8660.0</td>\n",
       "      <td>...</td>\n",
       "      <td>320.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>386.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>566.0</td>\n",
       "      <td>288.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>202008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1462.0</td>\n",
       "      <td>387.0</td>\n",
       "      <td>1736.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>183.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>16937.0</td>\n",
       "      <td>...</td>\n",
       "      <td>470.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>628.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>311.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>587.0</td>\n",
       "      <td>332.0</td>\n",
       "      <td>228.0</td>\n",
       "      <td>202009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020</td>\n",
       "      <td>10</td>\n",
       "      <td>1533.0</td>\n",
       "      <td>509.0</td>\n",
       "      <td>1964.0</td>\n",
       "      <td>75.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>31002.0</td>\n",
       "      <td>...</td>\n",
       "      <td>566.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>798.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>483.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>599.0</td>\n",
       "      <td>349.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>202010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>1763.0</td>\n",
       "      <td>810.0</td>\n",
       "      <td>2431.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>348.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>38730.0</td>\n",
       "      <td>...</td>\n",
       "      <td>610.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>897.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>732.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>605.0</td>\n",
       "      <td>357.0</td>\n",
       "      <td>276.0</td>\n",
       "      <td>202011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>2189.0</td>\n",
       "      <td>1181.0</td>\n",
       "      <td>2756.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>405.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>43245.0</td>\n",
       "      <td>...</td>\n",
       "      <td>614.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1028.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>610.0</td>\n",
       "      <td>388.0</td>\n",
       "      <td>363.0</td>\n",
       "      <td>202012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>2400.0</td>\n",
       "      <td>1380.0</td>\n",
       "      <td>2891.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>466.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>47974.0</td>\n",
       "      <td>...</td>\n",
       "      <td>621.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1189.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1833.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>615.0</td>\n",
       "      <td>763.0</td>\n",
       "      <td>1217.0</td>\n",
       "      <td>202101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>2443.0</td>\n",
       "      <td>1796.0</td>\n",
       "      <td>2983.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>508.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>51965.0</td>\n",
       "      <td>...</td>\n",
       "      <td>622.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1344.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>2042.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>634.0</td>\n",
       "      <td>1091.0</td>\n",
       "      <td>1463.0</td>\n",
       "      <td>202102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>2484.0</td>\n",
       "      <td>2235.0</td>\n",
       "      <td>3093.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>537.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>55858.0</td>\n",
       "      <td>...</td>\n",
       "      <td>629.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1602.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>2627.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>888.0</td>\n",
       "      <td>1208.0</td>\n",
       "      <td>1523.0</td>\n",
       "      <td>202103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2021</td>\n",
       "      <td>4</td>\n",
       "      <td>2625.0</td>\n",
       "      <td>2394.0</td>\n",
       "      <td>3253.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>596.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>63865.0</td>\n",
       "      <td>...</td>\n",
       "      <td>649.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2136.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>3249.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1226.0</td>\n",
       "      <td>1251.0</td>\n",
       "      <td>1567.0</td>\n",
       "      <td>202104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2021</td>\n",
       "      <td>5</td>\n",
       "      <td>2944.0</td>\n",
       "      <td>2451.0</td>\n",
       "      <td>3472.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>766.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>78093.0</td>\n",
       "      <td>...</td>\n",
       "      <td>690.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2646.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>3497.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1321.0</td>\n",
       "      <td>1281.0</td>\n",
       "      <td>1594.0</td>\n",
       "      <td>202105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>4871.0</td>\n",
       "      <td>2456.0</td>\n",
       "      <td>3716.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>94304.0</td>\n",
       "      <td>...</td>\n",
       "      <td>736.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3119.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>3563.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1361.0</td>\n",
       "      <td>2199.0</td>\n",
       "      <td>1789.0</td>\n",
       "      <td>202106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2021</td>\n",
       "      <td>7</td>\n",
       "      <td>6708.0</td>\n",
       "      <td>2457.0</td>\n",
       "      <td>4254.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>1011.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>105721.0</td>\n",
       "      <td>...</td>\n",
       "      <td>874.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3591.0</td>\n",
       "      <td>1306.0</td>\n",
       "      <td>3603.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1375.0</td>\n",
       "      <td>3389.0</td>\n",
       "      <td>3532.0</td>\n",
       "      <td>202107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2021</td>\n",
       "      <td>8</td>\n",
       "      <td>7118.0</td>\n",
       "      <td>2498.0</td>\n",
       "      <td>5269.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>1217.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>111812.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1082.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4010.0</td>\n",
       "      <td>11064.0</td>\n",
       "      <td>3680.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1472.0</td>\n",
       "      <td>3602.0</td>\n",
       "      <td>4419.0</td>\n",
       "      <td>202108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2021</td>\n",
       "      <td>9</td>\n",
       "      <td>7204.0</td>\n",
       "      <td>2698.0</td>\n",
       "      <td>5812.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>1537.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>115179.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1239.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4469.0</td>\n",
       "      <td>19301.0</td>\n",
       "      <td>4098.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1721.0</td>\n",
       "      <td>3648.0</td>\n",
       "      <td>4623.0</td>\n",
       "      <td>202109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>7280.0</td>\n",
       "      <td>2924.0</td>\n",
       "      <td>5920.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>1710.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>115950.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1323.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4891.0</td>\n",
       "      <td>22083.0</td>\n",
       "      <td>4663.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1889.0</td>\n",
       "      <td>3661.0</td>\n",
       "      <td>4678.0</td>\n",
       "      <td>202110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2021</td>\n",
       "      <td>11</td>\n",
       "      <td>7308.0</td>\n",
       "      <td>3096.0</td>\n",
       "      <td>6071.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>1733.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>116589.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1402.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5144.0</td>\n",
       "      <td>25252.0</td>\n",
       "      <td>4796.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1950.0</td>\n",
       "      <td>3667.0</td>\n",
       "      <td>4707.0</td>\n",
       "      <td>202111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2021</td>\n",
       "      <td>12</td>\n",
       "      <td>7356.0</td>\n",
       "      <td>3217.0</td>\n",
       "      <td>6276.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>1770.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>117169.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1485.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5328.0</td>\n",
       "      <td>32394.0</td>\n",
       "      <td>4919.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>3734.0</td>\n",
       "      <td>5004.0</td>\n",
       "      <td>202112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2022</td>\n",
       "      <td>1</td>\n",
       "      <td>7414.0</td>\n",
       "      <td>3346.0</td>\n",
       "      <td>6579.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>121273.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1564.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5447.0</td>\n",
       "      <td>37777.0</td>\n",
       "      <td>5098.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>3917.0</td>\n",
       "      <td>5338.0</td>\n",
       "      <td>202201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2022</td>\n",
       "      <td>2</td>\n",
       "      <td>7598.0</td>\n",
       "      <td>3469.0</td>\n",
       "      <td>6835.0</td>\n",
       "      <td>151.0</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>126152.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1635.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5636.0</td>\n",
       "      <td>40252.0</td>\n",
       "      <td>5501.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2135.0</td>\n",
       "      <td>3952.0</td>\n",
       "      <td>5395.0</td>\n",
       "      <td>202202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>7670.0</td>\n",
       "      <td>3492.0</td>\n",
       "      <td>6874.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>128019.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5682.0</td>\n",
       "      <td>42493.0</td>\n",
       "      <td>5655.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2143.0</td>\n",
       "      <td>3966.0</td>\n",
       "      <td>5444.0</td>\n",
       "      <td>202203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2022</td>\n",
       "      <td>4</td>\n",
       "      <td>7683.0</td>\n",
       "      <td>3496.0</td>\n",
       "      <td>6875.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>128542.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5709.0</td>\n",
       "      <td>43041.0</td>\n",
       "      <td>5657.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2149.0</td>\n",
       "      <td>3976.0</td>\n",
       "      <td>5469.0</td>\n",
       "      <td>202204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2022</td>\n",
       "      <td>5</td>\n",
       "      <td>7705.0</td>\n",
       "      <td>3497.0</td>\n",
       "      <td>6875.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>128889.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5721.0</td>\n",
       "      <td>43079.0</td>\n",
       "      <td>5660.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2149.0</td>\n",
       "      <td>3987.0</td>\n",
       "      <td>5503.0</td>\n",
       "      <td>202205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2022</td>\n",
       "      <td>6</td>\n",
       "      <td>7723.0</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>6875.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>1900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>129070.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5732.0</td>\n",
       "      <td>43087.0</td>\n",
       "      <td>5660.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2149.0</td>\n",
       "      <td>4006.0</td>\n",
       "      <td>5555.0</td>\n",
       "      <td>202206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2022</td>\n",
       "      <td>7</td>\n",
       "      <td>7748.0</td>\n",
       "      <td>3545.0</td>\n",
       "      <td>6876.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>1912.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>129369.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5763.0</td>\n",
       "      <td>43093.0</td>\n",
       "      <td>5678.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2151.0</td>\n",
       "      <td>4015.0</td>\n",
       "      <td>5577.0</td>\n",
       "      <td>202207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2022</td>\n",
       "      <td>8</td>\n",
       "      <td>7777.0</td>\n",
       "      <td>3582.0</td>\n",
       "      <td>6878.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>129711.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5796.0</td>\n",
       "      <td>43117.0</td>\n",
       "      <td>5704.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2155.0</td>\n",
       "      <td>4016.0</td>\n",
       "      <td>5596.0</td>\n",
       "      <td>202208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2022</td>\n",
       "      <td>9</td>\n",
       "      <td>7800.0</td>\n",
       "      <td>3589.0</td>\n",
       "      <td>6879.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>129897.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5814.0</td>\n",
       "      <td>43148.0</td>\n",
       "      <td>5707.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2157.0</td>\n",
       "      <td>4017.0</td>\n",
       "      <td>5602.0</td>\n",
       "      <td>202209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2022</td>\n",
       "      <td>10</td>\n",
       "      <td>7822.0</td>\n",
       "      <td>3593.0</td>\n",
       "      <td>6881.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>129991.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5820.0</td>\n",
       "      <td>43163.0</td>\n",
       "      <td>5708.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2158.0</td>\n",
       "      <td>4017.0</td>\n",
       "      <td>5606.0</td>\n",
       "      <td>202210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2022</td>\n",
       "      <td>11</td>\n",
       "      <td>7833.0</td>\n",
       "      <td>3594.0</td>\n",
       "      <td>6881.0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>130025.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5828.0</td>\n",
       "      <td>43175.0</td>\n",
       "      <td>5708.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2159.0</td>\n",
       "      <td>4019.0</td>\n",
       "      <td>5620.0</td>\n",
       "      <td>202211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2022</td>\n",
       "      <td>12</td>\n",
       "      <td>7849.0</td>\n",
       "      <td>3595.0</td>\n",
       "      <td>6881.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>130124.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5832.0</td>\n",
       "      <td>43186.0</td>\n",
       "      <td>5708.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2159.0</td>\n",
       "      <td>4024.0</td>\n",
       "      <td>5637.0</td>\n",
       "      <td>202212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2023</td>\n",
       "      <td>1</td>\n",
       "      <td>7854.0</td>\n",
       "      <td>3596.0</td>\n",
       "      <td>6881.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>130249.0</td>\n",
       "      <td>...</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5834.0</td>\n",
       "      <td>43186.0</td>\n",
       "      <td>5708.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2159.0</td>\n",
       "      <td>4034.0</td>\n",
       "      <td>5637.0</td>\n",
       "      <td>202301</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37 rows × 292 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     ano  mes  Afghanistan  Albania  Algeria  Andorra  Angola  Antarctica  \\\n",
       "0   2020    1          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "1   2020    2          0.0      0.0      0.0      0.0     0.0         0.0   \n",
       "2   2020    3          4.0     15.0     44.0     12.0     2.0         0.0   \n",
       "3   2020    4         60.0     31.0    450.0     42.0     2.0         0.0   \n",
       "4   2020    5        254.0     33.0    653.0     51.0     4.0         0.0   \n",
       "5   2020    6        739.0     62.0    912.0     52.0    13.0         0.0   \n",
       "6   2020    7       1275.0    157.0   1210.0     52.0    52.0         0.0   \n",
       "7   2020    8       1406.0    284.0   1510.0     53.0   108.0         0.0   \n",
       "8   2020    9       1462.0    387.0   1736.0     53.0   183.0         0.0   \n",
       "9   2020   10       1533.0    509.0   1964.0     75.0   284.0         0.0   \n",
       "10  2020   11       1763.0    810.0   2431.0     76.0   348.0         0.0   \n",
       "11  2020   12       2189.0   1181.0   2756.0     84.0   405.0         0.0   \n",
       "12  2021    1       2400.0   1380.0   2891.0    101.0   466.0         0.0   \n",
       "13  2021    2       2443.0   1796.0   2983.0    110.0   508.0         0.0   \n",
       "14  2021    3       2484.0   2235.0   3093.0    115.0   537.0         0.0   \n",
       "15  2021    4       2625.0   2394.0   3253.0    125.0   596.0         0.0   \n",
       "16  2021    5       2944.0   2451.0   3472.0    127.0   766.0         0.0   \n",
       "17  2021    6       4871.0   2456.0   3716.0    127.0   900.0         0.0   \n",
       "18  2021    7       6708.0   2457.0   4254.0    128.0  1011.0         0.0   \n",
       "19  2021    8       7118.0   2498.0   5269.0    130.0  1217.0         0.0   \n",
       "20  2021    9       7204.0   2698.0   5812.0    130.0  1537.0         0.0   \n",
       "21  2021   10       7280.0   2924.0   5920.0    130.0  1710.0         0.0   \n",
       "22  2021   11       7308.0   3096.0   6071.0    131.0  1733.0         0.0   \n",
       "23  2021   12       7356.0   3217.0   6276.0    140.0  1770.0         0.0   \n",
       "24  2022    1       7414.0   3346.0   6579.0    145.0  1895.0         0.0   \n",
       "25  2022    2       7598.0   3469.0   6835.0    151.0  1900.0         0.0   \n",
       "26  2022    3       7670.0   3492.0   6874.0    153.0  1900.0         0.0   \n",
       "27  2022    4       7683.0   3496.0   6875.0    153.0  1900.0         0.0   \n",
       "28  2022    5       7705.0   3497.0   6875.0    153.0  1900.0         0.0   \n",
       "29  2022    6       7723.0   3500.0   6875.0    153.0  1900.0         0.0   \n",
       "30  2022    7       7748.0   3545.0   6876.0    153.0  1912.0         0.0   \n",
       "31  2022    8       7777.0   3582.0   6878.0    154.0  1917.0         0.0   \n",
       "32  2022    9       7800.0   3589.0   6879.0    155.0  1917.0         0.0   \n",
       "33  2022   10       7822.0   3593.0   6881.0    155.0  1917.0         0.0   \n",
       "34  2022   11       7833.0   3594.0   6881.0    157.0  1924.0         0.0   \n",
       "35  2022   12       7849.0   3595.0   6881.0    165.0  1930.0         0.0   \n",
       "36  2023    1       7854.0   3596.0   6881.0    165.0  1930.0         0.0   \n",
       "\n",
       "    Antigua and Barbuda  Argentina  ...  Uzbekistan  Vanuatu  Venezuela  \\\n",
       "0                   0.0        0.0  ...         0.0      0.0        0.0   \n",
       "1                   0.0        0.0  ...         0.0      0.0        0.0   \n",
       "2                   0.0       27.0  ...         2.0      0.0        3.0   \n",
       "3                   3.0      218.0  ...         9.0      0.0       16.0   \n",
       "4                   3.0      539.0  ...        15.0      0.0       14.0   \n",
       "5                   3.0     1307.0  ...        26.0      0.0       51.0   \n",
       "6                   3.0     3543.0  ...       141.0      0.0      164.0   \n",
       "7                   3.0     8660.0  ...       320.0      0.0      386.0   \n",
       "8                   3.0    16937.0  ...       470.0      0.0      628.0   \n",
       "9                   3.0    31002.0  ...       566.0      0.0      798.0   \n",
       "10                  4.0    38730.0  ...       610.0      0.0      897.0   \n",
       "11                  5.0    43245.0  ...       614.0      0.0     1028.0   \n",
       "12                  7.0    47974.0  ...       621.0      0.0     1189.0   \n",
       "13                 14.0    51965.0  ...       622.0      0.0     1344.0   \n",
       "14                 28.0    55858.0  ...       629.0      0.0     1602.0   \n",
       "15                 32.0    63865.0  ...       649.0      1.0     2136.0   \n",
       "16                 42.0    78093.0  ...       690.0      1.0     2646.0   \n",
       "17                 42.0    94304.0  ...       736.0      1.0     3119.0   \n",
       "18                 43.0   105721.0  ...       874.0      1.0     3591.0   \n",
       "19                 44.0   111812.0  ...      1082.0      1.0     4010.0   \n",
       "20                 79.0   115179.0  ...      1239.0      1.0     4469.0   \n",
       "21                102.0   115950.0  ...      1323.0      1.0     4891.0   \n",
       "22                117.0   116589.0  ...      1402.0      1.0     5144.0   \n",
       "23                119.0   117169.0  ...      1485.0      1.0     5328.0   \n",
       "24                127.0   121273.0  ...      1564.0      1.0     5447.0   \n",
       "25                135.0   126152.0  ...      1635.0      1.0     5636.0   \n",
       "26                135.0   128019.0  ...      1637.0      2.0     5682.0   \n",
       "27                136.0   128542.0  ...      1637.0     13.0     5709.0   \n",
       "28                138.0   128889.0  ...      1637.0     14.0     5721.0   \n",
       "29                141.0   129070.0  ...      1637.0     14.0     5732.0   \n",
       "30                144.0   129369.0  ...      1637.0     14.0     5763.0   \n",
       "31                145.0   129711.0  ...      1637.0     14.0     5796.0   \n",
       "32                146.0   129897.0  ...      1637.0     14.0     5814.0   \n",
       "33                146.0   129991.0  ...      1637.0     14.0     5820.0   \n",
       "34                146.0   130025.0  ...      1637.0     14.0     5828.0   \n",
       "35                146.0   130124.0  ...      1637.0     14.0     5832.0   \n",
       "36                146.0   130249.0  ...      1637.0     14.0     5834.0   \n",
       "\n",
       "    Vietnam  West Bank and Gaza  Winter Olympics 2022   Yemen  Zambia  \\\n",
       "0       0.0                 0.0                   0.0     0.0     0.0   \n",
       "1       0.0                 0.0                   0.0     0.0     0.0   \n",
       "2       0.0                 1.0                   0.0     0.0     0.0   \n",
       "3       0.0                 2.0                   0.0     2.0     3.0   \n",
       "4       0.0                 3.0                   0.0    80.0     7.0   \n",
       "5       0.0                 8.0                   0.0   312.0    24.0   \n",
       "6       3.0                82.0                   0.0   493.0   151.0   \n",
       "7      34.0               152.0                   0.0   566.0   288.0   \n",
       "8      35.0               311.0                   0.0   587.0   332.0   \n",
       "9      35.0               483.0                   0.0   599.0   349.0   \n",
       "10     35.0               732.0                   0.0   605.0   357.0   \n",
       "11     35.0              1400.0                   0.0   610.0   388.0   \n",
       "12     35.0              1833.0                   0.0   615.0   763.0   \n",
       "13     35.0              2042.0                   0.0   634.0  1091.0   \n",
       "14     35.0              2627.0                   0.0   888.0  1208.0   \n",
       "15     35.0              3249.0                   0.0  1226.0  1251.0   \n",
       "16     47.0              3497.0                   0.0  1321.0  1281.0   \n",
       "17     81.0              3563.0                   0.0  1361.0  2199.0   \n",
       "18   1306.0              3603.0                   0.0  1375.0  3389.0   \n",
       "19  11064.0              3680.0                   0.0  1472.0  3602.0   \n",
       "20  19301.0              4098.0                   0.0  1721.0  3648.0   \n",
       "21  22083.0              4663.0                   0.0  1889.0  3661.0   \n",
       "22  25252.0              4796.0                   0.0  1950.0  3667.0   \n",
       "23  32394.0              4919.0                   0.0  1984.0  3734.0   \n",
       "24  37777.0              5098.0                   0.0  2012.0  3917.0   \n",
       "25  40252.0              5501.0                   0.0  2135.0  3952.0   \n",
       "26  42493.0              5655.0                   0.0  2143.0  3966.0   \n",
       "27  43041.0              5657.0                   0.0  2149.0  3976.0   \n",
       "28  43079.0              5660.0                   0.0  2149.0  3987.0   \n",
       "29  43087.0              5660.0                   0.0  2149.0  4006.0   \n",
       "30  43093.0              5678.0                   0.0  2151.0  4015.0   \n",
       "31  43117.0              5704.0                   0.0  2155.0  4016.0   \n",
       "32  43148.0              5707.0                   0.0  2157.0  4017.0   \n",
       "33  43163.0              5708.0                   0.0  2158.0  4017.0   \n",
       "34  43175.0              5708.0                   0.0  2159.0  4019.0   \n",
       "35  43186.0              5708.0                   0.0  2159.0  4024.0   \n",
       "36  43186.0              5708.0                   0.0  2159.0  4034.0   \n",
       "\n",
       "    Zimbabwe    data  \n",
       "0        0.0  202001  \n",
       "1        0.0  202002  \n",
       "2        1.0  202003  \n",
       "3        4.0  202004  \n",
       "4        4.0  202005  \n",
       "5        7.0  202006  \n",
       "6       67.0  202007  \n",
       "7      202.0  202008  \n",
       "8      228.0  202009  \n",
       "9      243.0  202010  \n",
       "10     276.0  202011  \n",
       "11     363.0  202012  \n",
       "12    1217.0  202101  \n",
       "13    1463.0  202102  \n",
       "14    1523.0  202103  \n",
       "15    1567.0  202104  \n",
       "16    1594.0  202105  \n",
       "17    1789.0  202106  \n",
       "18    3532.0  202107  \n",
       "19    4419.0  202108  \n",
       "20    4623.0  202109  \n",
       "21    4678.0  202110  \n",
       "22    4707.0  202111  \n",
       "23    5004.0  202112  \n",
       "24    5338.0  202201  \n",
       "25    5395.0  202202  \n",
       "26    5444.0  202203  \n",
       "27    5469.0  202204  \n",
       "28    5503.0  202205  \n",
       "29    5555.0  202206  \n",
       "30    5577.0  202207  \n",
       "31    5596.0  202208  \n",
       "32    5602.0  202209  \n",
       "33    5606.0  202210  \n",
       "34    5620.0  202211  \n",
       "35    5637.0  202212  \n",
       "36    5637.0  202301  \n",
       "\n",
       "[37 rows x 292 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# criando novo DF agrupando por ano e mes e somando os casos de mortes\n",
    "death_monthly = death.groupby([death.data.dt.year, death.data.dt.month])[death.columns[1:]].sum()\n",
    "# fazendo a soma cumulativa dos casos\n",
    "death_monthly = death_monthly.cumsum()\n",
    "# renomeando o indice\n",
    "death_monthly.index.rename(['ano', 'mes'], inplace=True)\n",
    "# resetando o indice para transformar em colunas do DF\n",
    "death_monthly.reset_index(inplace=True)\n",
    "# criando uma nova coluna de data unindo ano e mes e adicionando leading zero\n",
    "death_monthly[\"data\"] = death_monthly[\"ano\"].astype(str) + death_monthly[\"mes\"].astype(str).str.zfill(2)\n",
    "death_monthly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b9e88048",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ano</th>\n",
       "      <th>mes</th>\n",
       "      <th>Afghanistan</th>\n",
       "      <th>Albania</th>\n",
       "      <th>Algeria</th>\n",
       "      <th>Andorra</th>\n",
       "      <th>Angola</th>\n",
       "      <th>Antarctica</th>\n",
       "      <th>Antigua and Barbuda</th>\n",
       "      <th>Argentina</th>\n",
       "      <th>...</th>\n",
       "      <th>Uzbekistan</th>\n",
       "      <th>Vanuatu</th>\n",
       "      <th>Venezuela</th>\n",
       "      <th>Vietnam</th>\n",
       "      <th>West Bank and Gaza</th>\n",
       "      <th>Winter Olympics 2022</th>\n",
       "      <th>Yemen</th>\n",
       "      <th>Zambia</th>\n",
       "      <th>Zimbabwe</th>\n",
       "      <th>data</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>202001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020</td>\n",
       "      <td>2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>202002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>3</td>\n",
       "      <td>166.0</td>\n",
       "      <td>243.0</td>\n",
       "      <td>716.0</td>\n",
       "      <td>376.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1054.0</td>\n",
       "      <td>...</td>\n",
       "      <td>172.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>202003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>1827.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>4006.0</td>\n",
       "      <td>745.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>4428.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2039.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>333.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>344.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>202004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>15180.0</td>\n",
       "      <td>1137.0</td>\n",
       "      <td>9394.0</td>\n",
       "      <td>764.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>16851.0</td>\n",
       "      <td>...</td>\n",
       "      <td>3623.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1510.0</td>\n",
       "      <td>328.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>323.0</td>\n",
       "      <td>1057.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>202005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020</td>\n",
       "      <td>6</td>\n",
       "      <td>31445.0</td>\n",
       "      <td>2535.0</td>\n",
       "      <td>13907.0</td>\n",
       "      <td>855.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>64530.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8503.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5832.0</td>\n",
       "      <td>355.0</td>\n",
       "      <td>2428.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1158.0</td>\n",
       "      <td>1594.0</td>\n",
       "      <td>591.0</td>\n",
       "      <td>202006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020</td>\n",
       "      <td>7</td>\n",
       "      <td>36628.0</td>\n",
       "      <td>5276.0</td>\n",
       "      <td>30394.0</td>\n",
       "      <td>925.0</td>\n",
       "      <td>1148.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>191302.0</td>\n",
       "      <td>...</td>\n",
       "      <td>24009.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18574.0</td>\n",
       "      <td>558.0</td>\n",
       "      <td>11837.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1728.0</td>\n",
       "      <td>5963.0</td>\n",
       "      <td>3169.0</td>\n",
       "      <td>202007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2020</td>\n",
       "      <td>8</td>\n",
       "      <td>38248.0</td>\n",
       "      <td>9513.0</td>\n",
       "      <td>44494.0</td>\n",
       "      <td>1176.0</td>\n",
       "      <td>2654.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>417735.0</td>\n",
       "      <td>...</td>\n",
       "      <td>41893.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46728.0</td>\n",
       "      <td>1044.0</td>\n",
       "      <td>22729.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1958.0</td>\n",
       "      <td>12097.0</td>\n",
       "      <td>6497.0</td>\n",
       "      <td>202008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>39354.0</td>\n",
       "      <td>13649.0</td>\n",
       "      <td>51530.0</td>\n",
       "      <td>2050.0</td>\n",
       "      <td>4972.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>751001.0</td>\n",
       "      <td>...</td>\n",
       "      <td>56717.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>75122.0</td>\n",
       "      <td>1094.0</td>\n",
       "      <td>39899.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2034.0</td>\n",
       "      <td>14759.0</td>\n",
       "      <td>7838.0</td>\n",
       "      <td>202009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020</td>\n",
       "      <td>10</td>\n",
       "      <td>41334.0</td>\n",
       "      <td>20875.0</td>\n",
       "      <td>57942.0</td>\n",
       "      <td>4756.0</td>\n",
       "      <td>10805.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>128.0</td>\n",
       "      <td>1166924.0</td>\n",
       "      <td>...</td>\n",
       "      <td>66932.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92013.0</td>\n",
       "      <td>1180.0</td>\n",
       "      <td>53520.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2063.0</td>\n",
       "      <td>16432.0</td>\n",
       "      <td>8367.0</td>\n",
       "      <td>202010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020</td>\n",
       "      <td>11</td>\n",
       "      <td>46215.0</td>\n",
       "      <td>38182.0</td>\n",
       "      <td>83199.0</td>\n",
       "      <td>6745.0</td>\n",
       "      <td>15139.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>1424533.0</td>\n",
       "      <td>...</td>\n",
       "      <td>73094.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>102394.0</td>\n",
       "      <td>1347.0</td>\n",
       "      <td>85647.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2077.0</td>\n",
       "      <td>17647.0</td>\n",
       "      <td>9950.0</td>\n",
       "      <td>202011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2020</td>\n",
       "      <td>12</td>\n",
       "      <td>52330.0</td>\n",
       "      <td>58316.0</td>\n",
       "      <td>99610.0</td>\n",
       "      <td>8049.0</td>\n",
       "      <td>17553.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>1625514.0</td>\n",
       "      <td>...</td>\n",
       "      <td>77060.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>113558.0</td>\n",
       "      <td>1465.0</td>\n",
       "      <td>138004.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2099.0</td>\n",
       "      <td>20725.0</td>\n",
       "      <td>13867.0</td>\n",
       "      <td>202012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2021</td>\n",
       "      <td>1</td>\n",
       "      <td>55023.0</td>\n",
       "      <td>78127.0</td>\n",
       "      <td>107339.0</td>\n",
       "      <td>9937.0</td>\n",
       "      <td>19796.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>234.0</td>\n",
       "      <td>1927239.0</td>\n",
       "      <td>...</td>\n",
       "      <td>78711.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>126927.0</td>\n",
       "      <td>1817.0</td>\n",
       "      <td>158962.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2121.0</td>\n",
       "      <td>54217.0</td>\n",
       "      <td>33388.0</td>\n",
       "      <td>202101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2021</td>\n",
       "      <td>2</td>\n",
       "      <td>55714.0</td>\n",
       "      <td>107167.0</td>\n",
       "      <td>113092.0</td>\n",
       "      <td>10866.0</td>\n",
       "      <td>20807.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>730.0</td>\n",
       "      <td>2107365.0</td>\n",
       "      <td>...</td>\n",
       "      <td>79926.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>139116.0</td>\n",
       "      <td>2448.0</td>\n",
       "      <td>183612.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2285.0</td>\n",
       "      <td>78534.0</td>\n",
       "      <td>36089.0</td>\n",
       "      <td>202102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>56454.0</td>\n",
       "      <td>125157.0</td>\n",
       "      <td>117192.0</td>\n",
       "      <td>12010.0</td>\n",
       "      <td>22311.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1136.0</td>\n",
       "      <td>2348821.0</td>\n",
       "      <td>...</td>\n",
       "      <td>82869.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>160497.0</td>\n",
       "      <td>2603.0</td>\n",
       "      <td>242353.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4357.0</td>\n",
       "      <td>88418.0</td>\n",
       "      <td>36882.0</td>\n",
       "      <td>202103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2021</td>\n",
       "      <td>4</td>\n",
       "      <td>59745.0</td>\n",
       "      <td>131085.0</td>\n",
       "      <td>122108.0</td>\n",
       "      <td>13232.0</td>\n",
       "      <td>26652.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1232.0</td>\n",
       "      <td>2977363.0</td>\n",
       "      <td>...</td>\n",
       "      <td>90808.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>197683.0</td>\n",
       "      <td>2928.0</td>\n",
       "      <td>296462.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6317.0</td>\n",
       "      <td>91586.0</td>\n",
       "      <td>38257.0</td>\n",
       "      <td>202104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2021</td>\n",
       "      <td>5</td>\n",
       "      <td>71838.0</td>\n",
       "      <td>132315.0</td>\n",
       "      <td>128913.0</td>\n",
       "      <td>13727.0</td>\n",
       "      <td>34551.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1260.0</td>\n",
       "      <td>3781784.0</td>\n",
       "      <td>...</td>\n",
       "      <td>100335.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>234165.0</td>\n",
       "      <td>7432.0</td>\n",
       "      <td>308350.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6742.0</td>\n",
       "      <td>95263.0</td>\n",
       "      <td>38961.0</td>\n",
       "      <td>202105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2021</td>\n",
       "      <td>6</td>\n",
       "      <td>118659.0</td>\n",
       "      <td>132521.0</td>\n",
       "      <td>139626.0</td>\n",
       "      <td>13911.0</td>\n",
       "      <td>38849.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1263.0</td>\n",
       "      <td>4470374.0</td>\n",
       "      <td>...</td>\n",
       "      <td>110677.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>272712.0</td>\n",
       "      <td>17052.0</td>\n",
       "      <td>314167.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6920.0</td>\n",
       "      <td>154948.0</td>\n",
       "      <td>49864.0</td>\n",
       "      <td>202106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2021</td>\n",
       "      <td>7</td>\n",
       "      <td>147154.0</td>\n",
       "      <td>133081.0</td>\n",
       "      <td>171392.0</td>\n",
       "      <td>14678.0</td>\n",
       "      <td>42777.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1303.0</td>\n",
       "      <td>4929764.0</td>\n",
       "      <td>...</td>\n",
       "      <td>129327.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>305766.0</td>\n",
       "      <td>150060.0</td>\n",
       "      <td>316738.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7061.0</td>\n",
       "      <td>195816.0</td>\n",
       "      <td>108860.0</td>\n",
       "      <td>202107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2021</td>\n",
       "      <td>8</td>\n",
       "      <td>153220.0</td>\n",
       "      <td>146387.0</td>\n",
       "      <td>196080.0</td>\n",
       "      <td>15033.0</td>\n",
       "      <td>47544.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1715.0</td>\n",
       "      <td>5185620.0</td>\n",
       "      <td>...</td>\n",
       "      <td>156394.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>334343.0</td>\n",
       "      <td>462096.0</td>\n",
       "      <td>342282.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7869.0</td>\n",
       "      <td>206327.0</td>\n",
       "      <td>124773.0</td>\n",
       "      <td>202108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2021</td>\n",
       "      <td>9</td>\n",
       "      <td>155174.0</td>\n",
       "      <td>170131.0</td>\n",
       "      <td>203359.0</td>\n",
       "      <td>15222.0</td>\n",
       "      <td>56583.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3231.0</td>\n",
       "      <td>5256902.0</td>\n",
       "      <td>...</td>\n",
       "      <td>173895.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>368968.0</td>\n",
       "      <td>790755.0</td>\n",
       "      <td>403716.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9067.0</td>\n",
       "      <td>209046.0</td>\n",
       "      <td>130820.0</td>\n",
       "      <td>202109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2021</td>\n",
       "      <td>10</td>\n",
       "      <td>156250.0</td>\n",
       "      <td>185300.0</td>\n",
       "      <td>206452.0</td>\n",
       "      <td>15516.0</td>\n",
       "      <td>64433.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4058.0</td>\n",
       "      <td>5288807.0</td>\n",
       "      <td>...</td>\n",
       "      <td>185963.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>407151.0</td>\n",
       "      <td>921122.0</td>\n",
       "      <td>452997.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9791.0</td>\n",
       "      <td>209734.0</td>\n",
       "      <td>132977.0</td>\n",
       "      <td>202110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2021</td>\n",
       "      <td>11</td>\n",
       "      <td>157289.0</td>\n",
       "      <td>199945.0</td>\n",
       "      <td>210531.0</td>\n",
       "      <td>17115.0</td>\n",
       "      <td>65168.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4141.0</td>\n",
       "      <td>5330748.0</td>\n",
       "      <td>...</td>\n",
       "      <td>193208.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>431296.0</td>\n",
       "      <td>1238082.0</td>\n",
       "      <td>460053.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10004.0</td>\n",
       "      <td>210169.0</td>\n",
       "      <td>134625.0</td>\n",
       "      <td>202111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2021</td>\n",
       "      <td>12</td>\n",
       "      <td>158084.0</td>\n",
       "      <td>210224.0</td>\n",
       "      <td>218432.0</td>\n",
       "      <td>23740.0</td>\n",
       "      <td>81593.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4283.0</td>\n",
       "      <td>5654408.0</td>\n",
       "      <td>...</td>\n",
       "      <td>198903.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>444635.0</td>\n",
       "      <td>1731257.0</td>\n",
       "      <td>469748.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10126.0</td>\n",
       "      <td>254274.0</td>\n",
       "      <td>213258.0</td>\n",
       "      <td>202112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2022</td>\n",
       "      <td>1</td>\n",
       "      <td>162926.0</td>\n",
       "      <td>258543.0</td>\n",
       "      <td>252117.0</td>\n",
       "      <td>35958.0</td>\n",
       "      <td>98116.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6627.0</td>\n",
       "      <td>8378656.0</td>\n",
       "      <td>...</td>\n",
       "      <td>223008.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>485974.0</td>\n",
       "      <td>2275727.0</td>\n",
       "      <td>524716.0</td>\n",
       "      <td>248.0</td>\n",
       "      <td>11019.0</td>\n",
       "      <td>305047.0</td>\n",
       "      <td>229666.0</td>\n",
       "      <td>202201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2022</td>\n",
       "      <td>2</td>\n",
       "      <td>173659.0</td>\n",
       "      <td>271563.0</td>\n",
       "      <td>264936.0</td>\n",
       "      <td>37999.0</td>\n",
       "      <td>98741.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7437.0</td>\n",
       "      <td>8900656.0</td>\n",
       "      <td>...</td>\n",
       "      <td>236405.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>515124.0</td>\n",
       "      <td>3443485.0</td>\n",
       "      <td>645947.0</td>\n",
       "      <td>521.0</td>\n",
       "      <td>11771.0</td>\n",
       "      <td>312750.0</td>\n",
       "      <td>236380.0</td>\n",
       "      <td>202202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>177747.0</td>\n",
       "      <td>273677.0</td>\n",
       "      <td>265671.0</td>\n",
       "      <td>40024.0</td>\n",
       "      <td>99169.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7491.0</td>\n",
       "      <td>9037911.0</td>\n",
       "      <td>...</td>\n",
       "      <td>237749.0</td>\n",
       "      <td>3379.0</td>\n",
       "      <td>520373.0</td>\n",
       "      <td>9564609.0</td>\n",
       "      <td>655750.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11806.0</td>\n",
       "      <td>316850.0</td>\n",
       "      <td>246286.0</td>\n",
       "      <td>202203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2022</td>\n",
       "      <td>4</td>\n",
       "      <td>178879.0</td>\n",
       "      <td>275107.0</td>\n",
       "      <td>265780.0</td>\n",
       "      <td>41349.0</td>\n",
       "      <td>99287.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7626.0</td>\n",
       "      <td>9072230.0</td>\n",
       "      <td>...</td>\n",
       "      <td>238596.0</td>\n",
       "      <td>7330.0</td>\n",
       "      <td>522325.0</td>\n",
       "      <td>10649809.0</td>\n",
       "      <td>657060.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11818.0</td>\n",
       "      <td>319594.0</td>\n",
       "      <td>247875.0</td>\n",
       "      <td>202204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2022</td>\n",
       "      <td>5</td>\n",
       "      <td>180347.0</td>\n",
       "      <td>276101.0</td>\n",
       "      <td>265884.0</td>\n",
       "      <td>42894.0</td>\n",
       "      <td>99761.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8253.0</td>\n",
       "      <td>9230573.0</td>\n",
       "      <td>...</td>\n",
       "      <td>239028.0</td>\n",
       "      <td>9088.0</td>\n",
       "      <td>523654.0</td>\n",
       "      <td>10719379.0</td>\n",
       "      <td>657705.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11822.0</td>\n",
       "      <td>321779.0</td>\n",
       "      <td>252398.0</td>\n",
       "      <td>202205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2022</td>\n",
       "      <td>6</td>\n",
       "      <td>182528.0</td>\n",
       "      <td>280851.0</td>\n",
       "      <td>266087.0</td>\n",
       "      <td>43774.0</td>\n",
       "      <td>101320.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8641.0</td>\n",
       "      <td>9367172.0</td>\n",
       "      <td>...</td>\n",
       "      <td>240764.0</td>\n",
       "      <td>11266.0</td>\n",
       "      <td>526022.0</td>\n",
       "      <td>10746470.0</td>\n",
       "      <td>659853.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11824.0</td>\n",
       "      <td>325857.0</td>\n",
       "      <td>255586.0</td>\n",
       "      <td>202206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2022</td>\n",
       "      <td>7</td>\n",
       "      <td>185749.0</td>\n",
       "      <td>312097.0</td>\n",
       "      <td>267454.0</td>\n",
       "      <td>45508.0</td>\n",
       "      <td>102301.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8773.0</td>\n",
       "      <td>9560307.0</td>\n",
       "      <td>...</td>\n",
       "      <td>243093.0</td>\n",
       "      <td>11724.0</td>\n",
       "      <td>535836.0</td>\n",
       "      <td>10779632.0</td>\n",
       "      <td>682096.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11877.0</td>\n",
       "      <td>329483.0</td>\n",
       "      <td>256378.0</td>\n",
       "      <td>202207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2022</td>\n",
       "      <td>8</td>\n",
       "      <td>193250.0</td>\n",
       "      <td>329352.0</td>\n",
       "      <td>270304.0</td>\n",
       "      <td>46027.0</td>\n",
       "      <td>102636.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>8974.0</td>\n",
       "      <td>9678225.0</td>\n",
       "      <td>...</td>\n",
       "      <td>243801.0</td>\n",
       "      <td>11815.0</td>\n",
       "      <td>542508.0</td>\n",
       "      <td>11411679.0</td>\n",
       "      <td>702332.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11926.0</td>\n",
       "      <td>332822.0</td>\n",
       "      <td>256726.0</td>\n",
       "      <td>202208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2022</td>\n",
       "      <td>9</td>\n",
       "      <td>199188.0</td>\n",
       "      <td>332221.0</td>\n",
       "      <td>270673.0</td>\n",
       "      <td>46227.0</td>\n",
       "      <td>103131.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9098.0</td>\n",
       "      <td>9708420.0</td>\n",
       "      <td>...</td>\n",
       "      <td>244218.0</td>\n",
       "      <td>11950.0</td>\n",
       "      <td>544803.0</td>\n",
       "      <td>11479356.0</td>\n",
       "      <td>702768.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11935.0</td>\n",
       "      <td>333531.0</td>\n",
       "      <td>257465.0</td>\n",
       "      <td>202209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2022</td>\n",
       "      <td>10</td>\n",
       "      <td>203063.0</td>\n",
       "      <td>332966.0</td>\n",
       "      <td>270838.0</td>\n",
       "      <td>46535.0</td>\n",
       "      <td>103131.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9106.0</td>\n",
       "      <td>9718875.0</td>\n",
       "      <td>...</td>\n",
       "      <td>244648.0</td>\n",
       "      <td>11981.0</td>\n",
       "      <td>545899.0</td>\n",
       "      <td>11502885.0</td>\n",
       "      <td>703036.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11939.0</td>\n",
       "      <td>333681.0</td>\n",
       "      <td>257893.0</td>\n",
       "      <td>202210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2022</td>\n",
       "      <td>11</td>\n",
       "      <td>205907.0</td>\n",
       "      <td>333343.0</td>\n",
       "      <td>271090.0</td>\n",
       "      <td>47219.0</td>\n",
       "      <td>104676.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9106.0</td>\n",
       "      <td>9727247.0</td>\n",
       "      <td>...</td>\n",
       "      <td>246520.0</td>\n",
       "      <td>11981.0</td>\n",
       "      <td>547396.0</td>\n",
       "      <td>11515908.0</td>\n",
       "      <td>703036.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11945.0</td>\n",
       "      <td>333746.0</td>\n",
       "      <td>259164.0</td>\n",
       "      <td>202211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2022</td>\n",
       "      <td>12</td>\n",
       "      <td>207559.0</td>\n",
       "      <td>333806.0</td>\n",
       "      <td>271228.0</td>\n",
       "      <td>47751.0</td>\n",
       "      <td>105095.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9106.0</td>\n",
       "      <td>9891139.0</td>\n",
       "      <td>...</td>\n",
       "      <td>249217.0</td>\n",
       "      <td>12013.0</td>\n",
       "      <td>550522.0</td>\n",
       "      <td>11525231.0</td>\n",
       "      <td>703228.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11945.0</td>\n",
       "      <td>334425.0</td>\n",
       "      <td>259981.0</td>\n",
       "      <td>202212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2023</td>\n",
       "      <td>1</td>\n",
       "      <td>207900.0</td>\n",
       "      <td>334018.0</td>\n",
       "      <td>271277.0</td>\n",
       "      <td>47781.0</td>\n",
       "      <td>105095.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>9106.0</td>\n",
       "      <td>10004679.0</td>\n",
       "      <td>...</td>\n",
       "      <td>250137.0</td>\n",
       "      <td>12014.0</td>\n",
       "      <td>550802.0</td>\n",
       "      <td>11526034.0</td>\n",
       "      <td>703228.0</td>\n",
       "      <td>535.0</td>\n",
       "      <td>11945.0</td>\n",
       "      <td>336340.0</td>\n",
       "      <td>259981.0</td>\n",
       "      <td>202301</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>37 rows × 292 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     ano  mes  Afghanistan   Albania   Algeria  Andorra    Angola  Antarctica  \\\n",
       "0   2020    1          0.0       0.0       0.0      0.0       0.0         0.0   \n",
       "1   2020    2          5.0       0.0       1.0      0.0       0.0         0.0   \n",
       "2   2020    3        166.0     243.0     716.0    376.0       7.0         0.0   \n",
       "3   2020    4       1827.0     773.0    4006.0    745.0      27.0         0.0   \n",
       "4   2020    5      15180.0    1137.0    9394.0    764.0      86.0         0.0   \n",
       "5   2020    6      31445.0    2535.0   13907.0    855.0     284.0         0.0   \n",
       "6   2020    7      36628.0    5276.0   30394.0    925.0    1148.0         0.0   \n",
       "7   2020    8      38248.0    9513.0   44494.0   1176.0    2654.0         0.0   \n",
       "8   2020    9      39354.0   13649.0   51530.0   2050.0    4972.0         0.0   \n",
       "9   2020   10      41334.0   20875.0   57942.0   4756.0   10805.0         0.0   \n",
       "10  2020   11      46215.0   38182.0   83199.0   6745.0   15139.0         0.0   \n",
       "11  2020   12      52330.0   58316.0   99610.0   8049.0   17553.0         0.0   \n",
       "12  2021    1      55023.0   78127.0  107339.0   9937.0   19796.0         0.0   \n",
       "13  2021    2      55714.0  107167.0  113092.0  10866.0   20807.0         0.0   \n",
       "14  2021    3      56454.0  125157.0  117192.0  12010.0   22311.0         0.0   \n",
       "15  2021    4      59745.0  131085.0  122108.0  13232.0   26652.0         0.0   \n",
       "16  2021    5      71838.0  132315.0  128913.0  13727.0   34551.0         0.0   \n",
       "17  2021    6     118659.0  132521.0  139626.0  13911.0   38849.0         0.0   \n",
       "18  2021    7     147154.0  133081.0  171392.0  14678.0   42777.0         0.0   \n",
       "19  2021    8     153220.0  146387.0  196080.0  15033.0   47544.0         0.0   \n",
       "20  2021    9     155174.0  170131.0  203359.0  15222.0   56583.0         0.0   \n",
       "21  2021   10     156250.0  185300.0  206452.0  15516.0   64433.0         0.0   \n",
       "22  2021   11     157289.0  199945.0  210531.0  17115.0   65168.0         0.0   \n",
       "23  2021   12     158084.0  210224.0  218432.0  23740.0   81593.0        11.0   \n",
       "24  2022    1     162926.0  258543.0  252117.0  35958.0   98116.0        11.0   \n",
       "25  2022    2     173659.0  271563.0  264936.0  37999.0   98741.0        11.0   \n",
       "26  2022    3     177747.0  273677.0  265671.0  40024.0   99169.0        11.0   \n",
       "27  2022    4     178879.0  275107.0  265780.0  41349.0   99287.0        11.0   \n",
       "28  2022    5     180347.0  276101.0  265884.0  42894.0   99761.0        11.0   \n",
       "29  2022    6     182528.0  280851.0  266087.0  43774.0  101320.0        11.0   \n",
       "30  2022    7     185749.0  312097.0  267454.0  45508.0  102301.0        11.0   \n",
       "31  2022    8     193250.0  329352.0  270304.0  46027.0  102636.0        11.0   \n",
       "32  2022    9     199188.0  332221.0  270673.0  46227.0  103131.0        11.0   \n",
       "33  2022   10     203063.0  332966.0  270838.0  46535.0  103131.0        11.0   \n",
       "34  2022   11     205907.0  333343.0  271090.0  47219.0  104676.0        11.0   \n",
       "35  2022   12     207559.0  333806.0  271228.0  47751.0  105095.0        11.0   \n",
       "36  2023    1     207900.0  334018.0  271277.0  47781.0  105095.0        11.0   \n",
       "\n",
       "    Antigua and Barbuda   Argentina  ...  Uzbekistan  Vanuatu  Venezuela  \\\n",
       "0                   0.0         0.0  ...         0.0      0.0        0.0   \n",
       "1                   0.0         0.0  ...         0.0      0.0        0.0   \n",
       "2                   7.0      1054.0  ...       172.0      0.0      135.0   \n",
       "3                  24.0      4428.0  ...      2039.0      0.0      333.0   \n",
       "4                  26.0     16851.0  ...      3623.0      0.0     1510.0   \n",
       "5                  69.0     64530.0  ...      8503.0      0.0     5832.0   \n",
       "6                  91.0    191302.0  ...     24009.0      0.0    18574.0   \n",
       "7                  94.0    417735.0  ...     41893.0      0.0    46728.0   \n",
       "8                 101.0    751001.0  ...     56717.0      0.0    75122.0   \n",
       "9                 128.0   1166924.0  ...     66932.0      0.0    92013.0   \n",
       "10                141.0   1424533.0  ...     73094.0      1.0   102394.0   \n",
       "11                159.0   1625514.0  ...     77060.0      1.0   113558.0   \n",
       "12                234.0   1927239.0  ...     78711.0      1.0   126927.0   \n",
       "13                730.0   2107365.0  ...     79926.0      1.0   139116.0   \n",
       "14               1136.0   2348821.0  ...     82869.0      3.0   160497.0   \n",
       "15               1232.0   2977363.0  ...     90808.0      4.0   197683.0   \n",
       "16               1260.0   3781784.0  ...    100335.0      4.0   234165.0   \n",
       "17               1263.0   4470374.0  ...    110677.0      4.0   272712.0   \n",
       "18               1303.0   4929764.0  ...    129327.0      4.0   305766.0   \n",
       "19               1715.0   5185620.0  ...    156394.0      4.0   334343.0   \n",
       "20               3231.0   5256902.0  ...    173895.0      4.0   368968.0   \n",
       "21               4058.0   5288807.0  ...    185963.0      6.0   407151.0   \n",
       "22               4141.0   5330748.0  ...    193208.0      6.0   431296.0   \n",
       "23               4283.0   5654408.0  ...    198903.0      7.0   444635.0   \n",
       "24               6627.0   8378656.0  ...    223008.0      7.0   485974.0   \n",
       "25               7437.0   8900656.0  ...    236405.0     18.0   515124.0   \n",
       "26               7491.0   9037911.0  ...    237749.0   3379.0   520373.0   \n",
       "27               7626.0   9072230.0  ...    238596.0   7330.0   522325.0   \n",
       "28               8253.0   9230573.0  ...    239028.0   9088.0   523654.0   \n",
       "29               8641.0   9367172.0  ...    240764.0  11266.0   526022.0   \n",
       "30               8773.0   9560307.0  ...    243093.0  11724.0   535836.0   \n",
       "31               8974.0   9678225.0  ...    243801.0  11815.0   542508.0   \n",
       "32               9098.0   9708420.0  ...    244218.0  11950.0   544803.0   \n",
       "33               9106.0   9718875.0  ...    244648.0  11981.0   545899.0   \n",
       "34               9106.0   9727247.0  ...    246520.0  11981.0   547396.0   \n",
       "35               9106.0   9891139.0  ...    249217.0  12013.0   550522.0   \n",
       "36               9106.0  10004679.0  ...    250137.0  12014.0   550802.0   \n",
       "\n",
       "       Vietnam  West Bank and Gaza  Winter Olympics 2022    Yemen    Zambia  \\\n",
       "0          2.0                 0.0                   0.0      0.0       0.0   \n",
       "1         16.0                 0.0                   0.0      0.0       0.0   \n",
       "2        212.0               119.0                   0.0      0.0      35.0   \n",
       "3        270.0               344.0                   0.0      6.0     106.0   \n",
       "4        328.0               448.0                   0.0    323.0    1057.0   \n",
       "5        355.0              2428.0                   0.0   1158.0    1594.0   \n",
       "6        558.0             11837.0                   0.0   1728.0    5963.0   \n",
       "7       1044.0             22729.0                   0.0   1958.0   12097.0   \n",
       "8       1094.0             39899.0                   0.0   2034.0   14759.0   \n",
       "9       1180.0             53520.0                   0.0   2063.0   16432.0   \n",
       "10      1347.0             85647.0                   0.0   2077.0   17647.0   \n",
       "11      1465.0            138004.0                   0.0   2099.0   20725.0   \n",
       "12      1817.0            158962.0                   0.0   2121.0   54217.0   \n",
       "13      2448.0            183612.0                   0.0   2285.0   78534.0   \n",
       "14      2603.0            242353.0                   0.0   4357.0   88418.0   \n",
       "15      2928.0            296462.0                   0.0   6317.0   91586.0   \n",
       "16      7432.0            308350.0                   0.0   6742.0   95263.0   \n",
       "17     17052.0            314167.0                   0.0   6920.0  154948.0   \n",
       "18    150060.0            316738.0                   0.0   7061.0  195816.0   \n",
       "19    462096.0            342282.0                   0.0   7869.0  206327.0   \n",
       "20    790755.0            403716.0                   0.0   9067.0  209046.0   \n",
       "21    921122.0            452997.0                   0.0   9791.0  209734.0   \n",
       "22   1238082.0            460053.0                   0.0  10004.0  210169.0   \n",
       "23   1731257.0            469748.0                   0.0  10126.0  254274.0   \n",
       "24   2275727.0            524716.0                 248.0  11019.0  305047.0   \n",
       "25   3443485.0            645947.0                 521.0  11771.0  312750.0   \n",
       "26   9564609.0            655750.0                 535.0  11806.0  316850.0   \n",
       "27  10649809.0            657060.0                 535.0  11818.0  319594.0   \n",
       "28  10719379.0            657705.0                 535.0  11822.0  321779.0   \n",
       "29  10746470.0            659853.0                 535.0  11824.0  325857.0   \n",
       "30  10779632.0            682096.0                 535.0  11877.0  329483.0   \n",
       "31  11411679.0            702332.0                 535.0  11926.0  332822.0   \n",
       "32  11479356.0            702768.0                 535.0  11935.0  333531.0   \n",
       "33  11502885.0            703036.0                 535.0  11939.0  333681.0   \n",
       "34  11515908.0            703036.0                 535.0  11945.0  333746.0   \n",
       "35  11525231.0            703228.0                 535.0  11945.0  334425.0   \n",
       "36  11526034.0            703228.0                 535.0  11945.0  336340.0   \n",
       "\n",
       "    Zimbabwe    data  \n",
       "0        0.0  202001  \n",
       "1        0.0  202002  \n",
       "2        8.0  202003  \n",
       "3       40.0  202004  \n",
       "4      178.0  202005  \n",
       "5      591.0  202006  \n",
       "6     3169.0  202007  \n",
       "7     6497.0  202008  \n",
       "8     7838.0  202009  \n",
       "9     8367.0  202010  \n",
       "10    9950.0  202011  \n",
       "11   13867.0  202012  \n",
       "12   33388.0  202101  \n",
       "13   36089.0  202102  \n",
       "14   36882.0  202103  \n",
       "15   38257.0  202104  \n",
       "16   38961.0  202105  \n",
       "17   49864.0  202106  \n",
       "18  108860.0  202107  \n",
       "19  124773.0  202108  \n",
       "20  130820.0  202109  \n",
       "21  132977.0  202110  \n",
       "22  134625.0  202111  \n",
       "23  213258.0  202112  \n",
       "24  229666.0  202201  \n",
       "25  236380.0  202202  \n",
       "26  246286.0  202203  \n",
       "27  247875.0  202204  \n",
       "28  252398.0  202205  \n",
       "29  255586.0  202206  \n",
       "30  256378.0  202207  \n",
       "31  256726.0  202208  \n",
       "32  257465.0  202209  \n",
       "33  257893.0  202210  \n",
       "34  259164.0  202211  \n",
       "35  259981.0  202212  \n",
       "36  259981.0  202301  \n",
       "\n",
       "[37 rows x 292 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# idem para confirmed\n",
    "confirmed_monthly = confirmed.groupby([confirmed.data.dt.year, confirmed.data.dt.month])[confirmed.columns[1:]].sum()\n",
    "confirmed_monthly = confirmed_monthly.cumsum()\n",
    "confirmed_monthly.index.rename(['ano', 'mes'], inplace=True)\n",
    "confirmed_monthly.reset_index(inplace=True)\n",
    "confirmed_monthly[\"data\"] = confirmed_monthly[\"ano\"].astype(str) + confirmed_monthly[\"mes\"].astype(str).str.zfill(2)\n",
    "confirmed_monthly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2214fd62",
   "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>data</th>\n",
       "      <th>confirmed</th>\n",
       "      <th>death</th>\n",
       "      <th>pais</th>\n",
       "      <th>lat</th>\n",
       "      <th>lon</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>202001</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>34.039110</td>\n",
       "      <td>67.709953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>202002</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>34.039110</td>\n",
       "      <td>67.709953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>202003</td>\n",
       "      <td>166.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>34.039110</td>\n",
       "      <td>67.709953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>202004</td>\n",
       "      <td>1827.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>34.039110</td>\n",
       "      <td>67.709953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>202005</td>\n",
       "      <td>15180.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>34.039110</td>\n",
       "      <td>67.709953</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10688</th>\n",
       "      <td>202209</td>\n",
       "      <td>257465.0</td>\n",
       "      <td>5602.0</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-18.915438</td>\n",
       "      <td>29.154857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10689</th>\n",
       "      <td>202210</td>\n",
       "      <td>257893.0</td>\n",
       "      <td>5606.0</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-18.915438</td>\n",
       "      <td>29.154857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10690</th>\n",
       "      <td>202211</td>\n",
       "      <td>259164.0</td>\n",
       "      <td>5620.0</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-18.915438</td>\n",
       "      <td>29.154857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10691</th>\n",
       "      <td>202212</td>\n",
       "      <td>259981.0</td>\n",
       "      <td>5637.0</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-18.915438</td>\n",
       "      <td>29.154857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10692</th>\n",
       "      <td>202301</td>\n",
       "      <td>259981.0</td>\n",
       "      <td>5637.0</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>-18.915438</td>\n",
       "      <td>29.154857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10693 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         data  confirmed   death         pais        lat        lon\n",
       "0      202001        0.0     0.0  Afghanistan  34.039110  67.709953\n",
       "1      202002        5.0     0.0  Afghanistan  34.039110  67.709953\n",
       "2      202003      166.0     4.0  Afghanistan  34.039110  67.709953\n",
       "3      202004     1827.0    60.0  Afghanistan  34.039110  67.709953\n",
       "4      202005    15180.0   254.0  Afghanistan  34.039110  67.709953\n",
       "...       ...        ...     ...          ...        ...        ...\n",
       "10688  202209   257465.0  5602.0     Zimbabwe -18.915438  29.154857\n",
       "10689  202210   257893.0  5606.0     Zimbabwe -18.915438  29.154857\n",
       "10690  202211   259164.0  5620.0     Zimbabwe -18.915438  29.154857\n",
       "10691  202212   259981.0  5637.0     Zimbabwe -18.915438  29.154857\n",
       "10692  202301   259981.0  5637.0     Zimbabwe -18.915438  29.154857\n",
       "\n",
       "[10693 rows x 6 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# criando novo dataframe com o formato apropriado para utilizar plotly.express.scatter_geo:\n",
    "# data - confirmed - pais - lat - lon\n",
    "# para utilizar com scatter_geo\n",
    "novo_df = pd.DataFrame(columns=['data', 'confirmed', 'death', 'pais', 'lat', 'lon'])\n",
    "for coluna in confirmed_monthly.columns[2:-1]:\n",
    "    temp = confirmed_monthly[['data', coluna]]\n",
    "    temp[\"death\"] = death_monthly[[coluna]]\n",
    "    temp['pais'] = temp.columns[1]\n",
    "    temp['lat'] = location[location[\"Region\"] == coluna]['Lat'].values[0]\n",
    "    temp['lon'] = location[location[\"Region\"] == coluna]['Long'].values[0]\n",
    "    temp.columns = ['data', 'confirmed', 'death', 'pais', 'lat', 'lon']\n",
    "    novo_df = pd.concat([novo_df, temp], ignore_index=True)\n",
    "# novo_df[novo_df['confirmed'] < 0] = 0\n",
    "novo_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "11d02a8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "novo_df[novo_df[\"pais\"] == \"Brazil\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8d1c3fd2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plotando animacao com scatterplot durante a pandemia para verificar se há países onde há crescimento exagerado\n",
    "fig = px.scatter_geo(novo_df,\n",
    "                     lat=novo_df['lat'],\n",
    "                     lon=novo_df['lon'],\n",
    "                     color=novo_df['pais'], # which column to use to set the color of markers\n",
    "                     hover_name=\"pais\", # column added to hover information\n",
    "                     size=\"confirmed\", # size of markers\n",
    "                     projection=\"natural earth\",\n",
    "                     animation_frame='data',\n",
    "                     animation_group='pais',\n",
    "                     width=1600,\n",
    "                     height=800)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3e0531f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plotando animacao com scatterplot durante a pandemia para verificar se há países onde há crescimento exagerado\n",
    "fig = px.scatter_geo(novo_df,\n",
    "                     lat=novo_df['lat'],\n",
    "                     lon=novo_df['lon'],\n",
    "                     color=novo_df['pais'], # which column to use to set the color of markers\n",
    "                     hover_name=\"pais\", # column added to hover information\n",
    "                     size=\"death\", # size of markers\n",
    "                     projection=\"natural earth\",\n",
    "                     animation_frame='data',\n",
    "                     animation_group='pais',\n",
    "                     width=1600,\n",
    "                     height=800)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b9ee3b2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plotando grafico de linhas com os valores acumulados por pais\n",
    "fig = px.line(novo_df, x=\"data\", y=\"confirmed\", color='pais', width=1600, height=800)\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e961e172",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plotando grafico de linhas com os valores acumulados por pais\n",
    "fig = px.line(novo_df, x=\"data\", y=\"death\", color='pais', width=1600, height=800)\n",
    "fig.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "id": "a59000ec",
   "metadata": {},
   "source": [
    "# PAREI AQUI\n",
    "# Analisando dados do COVID-19 em conjunto com dados sócio-econômicos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c45c6a11",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\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</th>\n",
       "      <th>1960</th>\n",
       "      <th>1961</th>\n",
       "      <th>1962</th>\n",
       "      <th>1963</th>\n",
       "      <th>1964</th>\n",
       "      <th>1965</th>\n",
       "      <th>1966</th>\n",
       "      <th>1967</th>\n",
       "      <th>1968</th>\n",
       "      <th>...</th>\n",
       "      <th>2010</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "      <th>2013</th>\n",
       "      <th>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Aruba</td>\n",
       "      <td>308</td>\n",
       "      <td>312</td>\n",
       "      <td>315</td>\n",
       "      <td>317</td>\n",
       "      <td>319</td>\n",
       "      <td>321</td>\n",
       "      <td>322</td>\n",
       "      <td>324</td>\n",
       "      <td>326</td>\n",
       "      <td>...</td>\n",
       "      <td>567</td>\n",
       "      <td>570</td>\n",
       "      <td>573</td>\n",
       "      <td>577</td>\n",
       "      <td>580</td>\n",
       "      <td>583</td>\n",
       "      <td>585</td>\n",
       "      <td>588</td>\n",
       "      <td>591</td>\n",
       "      <td>593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>14</td>\n",
       "      <td>14.3</td>\n",
       "      <td>14.6</td>\n",
       "      <td>14.9</td>\n",
       "      <td>15.3</td>\n",
       "      <td>15.6</td>\n",
       "      <td>15.9</td>\n",
       "      <td>16.3</td>\n",
       "      <td>16.7</td>\n",
       "      <td>...</td>\n",
       "      <td>46.1</td>\n",
       "      <td>47.7</td>\n",
       "      <td>49.4</td>\n",
       "      <td>51.1</td>\n",
       "      <td>52.7</td>\n",
       "      <td>54.2</td>\n",
       "      <td>55.6</td>\n",
       "      <td>56.9</td>\n",
       "      <td>58.3</td>\n",
       "      <td>59.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Angola</td>\n",
       "      <td>4.44</td>\n",
       "      <td>4.5</td>\n",
       "      <td>4.56</td>\n",
       "      <td>4.6</td>\n",
       "      <td>4.63</td>\n",
       "      <td>4.64</td>\n",
       "      <td>4.63</td>\n",
       "      <td>4.63</td>\n",
       "      <td>4.66</td>\n",
       "      <td>...</td>\n",
       "      <td>19.4</td>\n",
       "      <td>20.1</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.4</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.7</td>\n",
       "      <td>25.5</td>\n",
       "      <td>26.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Albania</td>\n",
       "      <td>60.6</td>\n",
       "      <td>62.5</td>\n",
       "      <td>64.3</td>\n",
       "      <td>66.2</td>\n",
       "      <td>68.1</td>\n",
       "      <td>69.9</td>\n",
       "      <td>71.7</td>\n",
       "      <td>73.8</td>\n",
       "      <td>76</td>\n",
       "      <td>...</td>\n",
       "      <td>106</td>\n",
       "      <td>106</td>\n",
       "      <td>106</td>\n",
       "      <td>105</td>\n",
       "      <td>105</td>\n",
       "      <td>105</td>\n",
       "      <td>105</td>\n",
       "      <td>105</td>\n",
       "      <td>104</td>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Andorra</td>\n",
       "      <td>30.6</td>\n",
       "      <td>32.7</td>\n",
       "      <td>34.9</td>\n",
       "      <td>37.2</td>\n",
       "      <td>39.5</td>\n",
       "      <td>41.8</td>\n",
       "      <td>44.2</td>\n",
       "      <td>46.6</td>\n",
       "      <td>49</td>\n",
       "      <td>...</td>\n",
       "      <td>178</td>\n",
       "      <td>175</td>\n",
       "      <td>172</td>\n",
       "      <td>169</td>\n",
       "      <td>166</td>\n",
       "      <td>164</td>\n",
       "      <td>164</td>\n",
       "      <td>164</td>\n",
       "      <td>164</td>\n",
       "      <td>164</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>Samoa</td>\n",
       "      <td>39.6</td>\n",
       "      <td>40.9</td>\n",
       "      <td>42.2</td>\n",
       "      <td>43.6</td>\n",
       "      <td>44.9</td>\n",
       "      <td>46.2</td>\n",
       "      <td>47.4</td>\n",
       "      <td>48.6</td>\n",
       "      <td>49.6</td>\n",
       "      <td>...</td>\n",
       "      <td>66.2</td>\n",
       "      <td>66.8</td>\n",
       "      <td>67.4</td>\n",
       "      <td>67.9</td>\n",
       "      <td>68.4</td>\n",
       "      <td>68.7</td>\n",
       "      <td>69</td>\n",
       "      <td>69.3</td>\n",
       "      <td>69.6</td>\n",
       "      <td>70.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>Yemen</td>\n",
       "      <td>10.2</td>\n",
       "      <td>10.4</td>\n",
       "      <td>10.5</td>\n",
       "      <td>10.7</td>\n",
       "      <td>10.8</td>\n",
       "      <td>11</td>\n",
       "      <td>11.2</td>\n",
       "      <td>11.4</td>\n",
       "      <td>11.5</td>\n",
       "      <td>...</td>\n",
       "      <td>45.1</td>\n",
       "      <td>46.4</td>\n",
       "      <td>47.6</td>\n",
       "      <td>48.9</td>\n",
       "      <td>50.2</td>\n",
       "      <td>51.5</td>\n",
       "      <td>52.7</td>\n",
       "      <td>54</td>\n",
       "      <td>55.2</td>\n",
       "      <td>56.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>South Africa</td>\n",
       "      <td>14.4</td>\n",
       "      <td>14.8</td>\n",
       "      <td>15.2</td>\n",
       "      <td>15.6</td>\n",
       "      <td>16</td>\n",
       "      <td>16.4</td>\n",
       "      <td>16.8</td>\n",
       "      <td>17.3</td>\n",
       "      <td>17.7</td>\n",
       "      <td>...</td>\n",
       "      <td>42.9</td>\n",
       "      <td>43.6</td>\n",
       "      <td>44.3</td>\n",
       "      <td>45</td>\n",
       "      <td>45.7</td>\n",
       "      <td>46.3</td>\n",
       "      <td>47</td>\n",
       "      <td>47.6</td>\n",
       "      <td>48.3</td>\n",
       "      <td>48.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>Zambia</td>\n",
       "      <td>4.26</td>\n",
       "      <td>4.39</td>\n",
       "      <td>4.52</td>\n",
       "      <td>4.66</td>\n",
       "      <td>4.8</td>\n",
       "      <td>4.95</td>\n",
       "      <td>5.11</td>\n",
       "      <td>5.27</td>\n",
       "      <td>5.44</td>\n",
       "      <td>...</td>\n",
       "      <td>18.9</td>\n",
       "      <td>19.5</td>\n",
       "      <td>20.1</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.3</td>\n",
       "      <td>24</td>\n",
       "      <td>24.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>10.1</td>\n",
       "      <td>10.4</td>\n",
       "      <td>10.8</td>\n",
       "      <td>11.2</td>\n",
       "      <td>11.6</td>\n",
       "      <td>12</td>\n",
       "      <td>12.4</td>\n",
       "      <td>12.8</td>\n",
       "      <td>13.2</td>\n",
       "      <td>...</td>\n",
       "      <td>33.3</td>\n",
       "      <td>33.9</td>\n",
       "      <td>34.5</td>\n",
       "      <td>35.1</td>\n",
       "      <td>35.7</td>\n",
       "      <td>36.3</td>\n",
       "      <td>36.8</td>\n",
       "      <td>37.3</td>\n",
       "      <td>37.9</td>\n",
       "      <td>38.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>217 rows × 61 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          country  1960  1961  1962  1963  1964  1965  1966  1967  1968  ...  \\\n",
       "0           Aruba   308   312   315   317   319   321   322   324   326  ...   \n",
       "1     Afghanistan    14  14.3  14.6  14.9  15.3  15.6  15.9  16.3  16.7  ...   \n",
       "2          Angola  4.44   4.5  4.56   4.6  4.63  4.64  4.63  4.63  4.66  ...   \n",
       "3         Albania  60.6  62.5  64.3  66.2  68.1  69.9  71.7  73.8    76  ...   \n",
       "4         Andorra  30.6  32.7  34.9  37.2  39.5  41.8  44.2  46.6    49  ...   \n",
       "..            ...   ...   ...   ...   ...   ...   ...   ...   ...   ...  ...   \n",
       "212         Samoa  39.6  40.9  42.2  43.6  44.9  46.2  47.4  48.6  49.6  ...   \n",
       "213         Yemen  10.2  10.4  10.5  10.7  10.8    11  11.2  11.4  11.5  ...   \n",
       "214  South Africa  14.4  14.8  15.2  15.6    16  16.4  16.8  17.3  17.7  ...   \n",
       "215        Zambia  4.26  4.39  4.52  4.66   4.8  4.95  5.11  5.27  5.44  ...   \n",
       "216      Zimbabwe  10.1  10.4  10.8  11.2  11.6    12  12.4  12.8  13.2  ...   \n",
       "\n",
       "     2010  2011  2012  2013  2014  2015  2016  2017  2018  2019  \n",
       "0     567   570   573   577   580   583   585   588   591   593  \n",
       "1    46.1  47.7  49.4  51.1  52.7  54.2  55.6  56.9  58.3  59.6  \n",
       "2    19.4  20.1  20.9  21.6  22.4  23.1  23.9  24.7  25.5  26.4  \n",
       "3     106   106   106   105   105   105   105   105   104   104  \n",
       "4     178   175   172   169   166   164   164   164   164   164  \n",
       "..    ...   ...   ...   ...   ...   ...   ...   ...   ...   ...  \n",
       "212  66.2  66.8  67.4  67.9  68.4  68.7    69  69.3  69.6  70.1  \n",
       "213  45.1  46.4  47.6  48.9  50.2  51.5  52.7    54  55.2  56.5  \n",
       "214  42.9  43.6  44.3    45  45.7  46.3    47  47.6  48.3  48.9  \n",
       "215  18.9  19.5  20.1  20.7  21.4    22  22.7  23.3    24  24.7  \n",
       "216  33.3  33.9  34.5  35.1  35.7  36.3  36.8  37.3  37.9  38.4  \n",
       "\n",
       "[217 rows x 61 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# realizando a leitura dos dados\n",
    "# esses arquivos tem uma linha de header\n",
    "# a segunda é uma região do país, caso exista, senão, vazio (NaN)\n",
    "path_ = os.path.join(DATA_FOLDER, GAPMINDER_POP_AREA)\n",
    "pop_area = pd.read_csv(path_, sep=',')\n",
    "pop_area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1b9c81cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25.4"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "float(pop_area[pop_area[\"country\"] == \"Brazil\"][\"2019\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "657cdd4f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Afghanistan  -  1    59.6\n",
      "Name: 2019, dtype: object\n",
      "Albania  -  3    104\n",
      "Name: 2019, dtype: object\n",
      "Algeria  -  54    18.4\n",
      "Name: 2019, dtype: object\n",
      "Andorra  -  4    164\n",
      "Name: 2019, dtype: object\n",
      "Angola  -  2    26.4\n",
      "Name: 2019, dtype: object\n",
      "Antarctica  -  Series([], Name: 2019, dtype: object)\n",
      "Antigua and Barbuda  -  9    223\n",
      "Name: 2019, dtype: object\n",
      "Argentina  -  6    16.6\n",
      "Name: 2019, dtype: object\n",
      "Armenia  -  7    104\n",
      "Name: 2019, dtype: object\n",
      "Australia_Australian Capital Territory  -  Series([], Name: 2019, dtype: object)\n",
      "Australia_New South Wales  -  Series([], Name: 2019, dtype: object)\n",
      "Australia_Northern Territory  -  Series([], Name: 2019, dtype: object)\n",
      "Australia_Queensland  -  Series([], Name: 2019, dtype: object)\n",
      "Australia_South Australia  -  Series([], Name: 2019, dtype: object)\n",
      "Australia_Tasmania  -  Series([], Name: 2019, dtype: object)\n",
      "Australia_Victoria  -  Series([], Name: 2019, dtype: object)\n",
      "Australia_Western Australia  -  Series([], Name: 2019, dtype: object)\n",
      "Austria  -  11    108\n",
      "Name: 2019, dtype: object\n",
      "Azerbaijan  -  12    122\n",
      "Name: 2019, dtype: object\n",
      "Bahamas  -  20    39.3\n",
      "Name: 2019, dtype: object\n",
      "Bahrain  -  19    2180\n",
      "Name: 2019, dtype: object\n",
      "Bangladesh  -  17    1270\n",
      "Name: 2019, dtype: object\n",
      "Barbados  -  27    668\n",
      "Name: 2019, dtype: object\n",
      "Belarus  -  22    46.2\n",
      "Name: 2019, dtype: object\n",
      "Belgium  -  14    381\n",
      "Name: 2019, dtype: object\n",
      "Belize  -  23    17.4\n",
      "Name: 2019, dtype: object\n",
      "Benin  -  15    108\n",
      "Name: 2019, dtype: object\n",
      "Bhutan  -  29    20.2\n",
      "Name: 2019, dtype: object\n",
      "Bolivia  -  25    10.8\n",
      "Name: 2019, dtype: object\n",
      "Bosnia and Herzegovina  -  21    64.1\n",
      "Name: 2019, dtype: object\n",
      "Botswana  -  30    4.15\n",
      "Name: 2019, dtype: object\n",
      "Brazil  -  26    25.4\n",
      "Name: 2019, dtype: object\n",
      "Brunei  -  28    83\n",
      "Name: 2019, dtype: object\n",
      "Bulgaria  -  18    63.9\n",
      "Name: 2019, dtype: object\n",
      "Burkina Faso  -  16    76.4\n",
      "Name: 2019, dtype: object\n",
      "Burma  -  Series([], Name: 2019, dtype: object)\n",
      "Burundi  -  13    463\n",
      "Name: 2019, dtype: object\n",
      "Cabo Verde  -  Series([], Name: 2019, dtype: object)\n",
      "Cambodia  -  101    94.7\n",
      "Name: 2019, dtype: object\n",
      "Cameroon  -  38    56.2\n",
      "Name: 2019, dtype: object\n",
      "Canada_Alberta  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_British Columbia  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Diamond Princess  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Grand Princess  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Manitoba  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_New Brunswick  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Newfoundland and Labrador  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Northwest Territories  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Nova Scotia  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Nunavut  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Ontario  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Prince Edward Island  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Quebec  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Repatriated Travellers  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Saskatchewan  -  Series([], Name: 2019, dtype: object)\n",
      "Canada_Yukon  -  Series([], Name: 2019, dtype: object)\n",
      "Central African Republic  -  31    7.75\n",
      "Name: 2019, dtype: object\n",
      "Chad  -  189    13\n",
      "Name: 2019, dtype: object\n",
      "Chile  -  35    25.7\n",
      "Name: 2019, dtype: object\n",
      "China_Anhui  -  Series([], Name: 2019, dtype: object)\n",
      "China_Beijing  -  Series([], Name: 2019, dtype: object)\n",
      "China_Chongqing  -  Series([], Name: 2019, dtype: object)\n",
      "China_Fujian  -  Series([], Name: 2019, dtype: object)\n",
      "China_Gansu  -  Series([], Name: 2019, dtype: object)\n",
      "China_Guangdong  -  Series([], Name: 2019, dtype: object)\n",
      "China_Guangxi  -  Series([], Name: 2019, dtype: object)\n",
      "China_Guizhou  -  Series([], Name: 2019, dtype: object)\n",
      "China_Hainan  -  Series([], Name: 2019, dtype: object)\n",
      "China_Hebei  -  Series([], Name: 2019, dtype: object)\n",
      "China_Heilongjiang  -  Series([], Name: 2019, dtype: object)\n",
      "China_Henan  -  Series([], Name: 2019, dtype: object)\n",
      "China_Hong Kong  -  Series([], Name: 2019, dtype: object)\n",
      "China_Hubei  -  Series([], Name: 2019, dtype: object)\n",
      "China_Hunan  -  Series([], Name: 2019, dtype: object)\n",
      "China_Inner Mongolia  -  Series([], Name: 2019, dtype: object)\n",
      "China_Jiangsu  -  Series([], Name: 2019, dtype: object)\n",
      "China_Jiangxi  -  Series([], Name: 2019, dtype: object)\n",
      "China_Jilin  -  Series([], Name: 2019, dtype: object)\n",
      "China_Liaoning  -  Series([], Name: 2019, dtype: object)\n",
      "China_Macau  -  Series([], Name: 2019, dtype: object)\n",
      "China_Ningxia  -  Series([], Name: 2019, dtype: object)\n",
      "China_Qinghai  -  Series([], Name: 2019, dtype: object)\n",
      "China_Shaanxi  -  Series([], Name: 2019, dtype: object)\n",
      "China_Shandong  -  Series([], Name: 2019, dtype: object)\n",
      "China_Shanghai  -  Series([], Name: 2019, dtype: object)\n",
      "China_Shanxi  -  Series([], Name: 2019, dtype: object)\n",
      "China_Sichuan  -  Series([], Name: 2019, dtype: object)\n",
      "China_Tianjin  -  Series([], Name: 2019, dtype: object)\n",
      "China_Tibet  -  Series([], Name: 2019, dtype: object)\n",
      "China_Unknown  -  Series([], Name: 2019, dtype: object)\n",
      "China_Xinjiang  -  Series([], Name: 2019, dtype: object)\n",
      "China_Yunnan  -  Series([], Name: 2019, dtype: object)\n",
      "China_Zhejiang  -  Series([], Name: 2019, dtype: object)\n",
      "Colombia  -  41    45.9\n",
      "Name: 2019, dtype: object\n",
      "Comoros  -  42    467\n",
      "Name: 2019, dtype: object\n",
      "Congo (Brazzaville)  -  Series([], Name: 2019, dtype: object)\n",
      "Congo (Kinshasa)  -  Series([], Name: 2019, dtype: object)\n",
      "Costa Rica  -  44    99.8\n",
      "Name: 2019, dtype: object\n",
      "Cote d'Ivoire  -  37    83\n",
      "Name: 2019, dtype: object\n",
      "Croatia  -  84    71.5\n",
      "Name: 2019, dtype: object\n",
      "Cuba  -  45    109\n",
      "Name: 2019, dtype: object\n",
      "Cyprus  -  47    131\n",
      "Name: 2019, dtype: object\n",
      "Czechia  -  Series([], Name: 2019, dtype: object)\n",
      "Denmark_Faroe Islands  -  Series([], Name: 2019, dtype: object)\n",
      "Denmark_Greenland  -  Series([], Name: 2019, dtype: object)\n",
      "Denmark  -  52    146\n",
      "Name: 2019, dtype: object\n",
      "Diamond Princess  -  Series([], Name: 2019, dtype: object)\n",
      "Djibouti  -  50    42.6\n",
      "Name: 2019, dtype: object\n",
      "Dominica  -  51    96\n",
      "Name: 2019, dtype: object\n",
      "Dominican Republic  -  53    225\n",
      "Name: 2019, dtype: object\n",
      "Ecuador  -  55    71\n",
      "Name: 2019, dtype: object\n",
      "Egypt  -  56    103\n",
      "Name: 2019, dtype: object\n",
      "El Salvador  -  174    313\n",
      "Name: 2019, dtype: object\n",
      "Equatorial Guinea  -  75    50\n",
      "Name: 2019, dtype: object\n",
      "Eritrea  -  57    35.1\n",
      "Name: 2019, dtype: object\n",
      "Estonia  -  59    30.6\n",
      "Name: 2019, dtype: object\n",
      "Eswatini  -  184    67.5\n",
      "Name: 2019, dtype: object\n",
      "Ethiopia  -  60    102\n",
      "Name: 2019, dtype: object\n",
      "Fiji  -  62    49.1\n",
      "Name: 2019, dtype: object\n",
      "Finland  -  61    18.2\n",
      "Name: 2019, dtype: object\n",
      "France_French Guiana  -  Series([], Name: 2019, dtype: object)\n",
      "France_French Polynesia  -  Series([], Name: 2019, dtype: object)\n",
      "France_Guadeloupe  -  Series([], Name: 2019, dtype: object)\n",
      "France_Martinique  -  Series([], Name: 2019, dtype: object)\n",
      "France_Mayotte  -  Series([], Name: 2019, dtype: object)\n",
      "France_New Caledonia  -  Series([], Name: 2019, dtype: object)\n",
      "France_Reunion  -  Series([], Name: 2019, dtype: object)\n",
      "France_Saint Barthelemy  -  Series([], Name: 2019, dtype: object)\n",
      "France_Saint Pierre and Miquelon  -  Series([], Name: 2019, dtype: object)\n",
      "France_St Martin  -  Series([], Name: 2019, dtype: object)\n",
      "France_Wallis and Futuna  -  Series([], Name: 2019, dtype: object)\n",
      "France  -  63    123\n",
      "Name: 2019, dtype: object\n",
      "Gabon  -  66    8.64\n",
      "Name: 2019, dtype: object\n",
      "Gambia  -  73    239\n",
      "Name: 2019, dtype: object\n",
      "Georgia  -  69    65.1\n",
      "Name: 2019, dtype: object\n",
      "Germany  -  49    238\n",
      "Name: 2019, dtype: object\n",
      "Ghana  -  70    137\n",
      "Name: 2019, dtype: object\n",
      "Greece  -  76    83\n",
      "Name: 2019, dtype: object\n",
      "Grenada  -  77    331\n",
      "Name: 2019, dtype: object\n",
      "Guatemala  -  79    157\n",
      "Name: 2019, dtype: object\n",
      "Guinea  -  72    53.4\n",
      "Name: 2019, dtype: object\n",
      "Guinea-Bissau  -  74    70\n",
      "Name: 2019, dtype: object\n",
      "Guyana  -  81    4\n",
      "Name: 2019, dtype: object\n",
      "Haiti  -  85    414\n",
      "Name: 2019, dtype: object\n",
      "Holy See  -  Series([], Name: 2019, dtype: object)\n",
      "Honduras  -  83    88.5\n",
      "Name: 2019, dtype: object\n",
      "Hungary  -  86    107\n",
      "Name: 2019, dtype: object\n",
      "Iceland  -  92    3.63\n",
      "Name: 2019, dtype: object\n",
      "India  -  88    464\n",
      "Name: 2019, dtype: object\n",
      "Indonesia  -  87    146\n",
      "Name: 2019, dtype: object\n",
      "Iran  -  90    51.6\n",
      "Name: 2019, dtype: object\n",
      "Iraq  -  91    92.7\n",
      "Name: 2019, dtype: object\n",
      "Ireland  -  89    72.4\n",
      "Name: 2019, dtype: object\n",
      "Israel  -  93    426\n",
      "Name: 2019, dtype: object\n",
      "Italy  -  94    200\n",
      "Name: 2019, dtype: object\n",
      "Jamaica  -  95    273\n",
      "Name: 2019, dtype: object\n",
      "Japan  -  97    345\n",
      "Name: 2019, dtype: object\n",
      "Jordan  -  96    115\n",
      "Name: 2019, dtype: object\n",
      "Kazakhstan  -  98    6.95\n",
      "Name: 2019, dtype: object\n",
      "Kenya  -  99    94.5\n",
      "Name: 2019, dtype: object\n",
      "Kiribati  -  102    147\n",
      "Name: 2019, dtype: object\n",
      "Korea, North  -  Series([], Name: 2019, dtype: object)\n",
      "Korea, South  -  Series([], Name: 2019, dtype: object)\n",
      "Kosovo  -  105    NaN\n",
      "Name: 2019, dtype: object\n",
      "Kuwait  -  106    240\n",
      "Name: 2019, dtype: object\n",
      "Kyrgyzstan  -  Series([], Name: 2019, dtype: object)\n",
      "Laos  -  Series([], Name: 2019, dtype: object)\n",
      "Latvia  -  117    30.6\n",
      "Name: 2019, dtype: object\n",
      "Lebanon  -  108    667\n",
      "Name: 2019, dtype: object\n",
      "Lesotho  -  114    70.6\n",
      "Name: 2019, dtype: object\n",
      "Liberia  -  109    52.5\n",
      "Name: 2019, dtype: object\n",
      "Libya  -  110    3.91\n",
      "Name: 2019, dtype: object\n",
      "Liechtenstein  -  112    238\n",
      "Name: 2019, dtype: object\n",
      "Lithuania  -  115    44.6\n",
      "Name: 2019, dtype: object\n",
      "Luxembourg  -  116    259\n",
      "Name: 2019, dtype: object\n",
      "MS Zaandam  -  Series([], Name: 2019, dtype: object)\n",
      "Madagascar  -  123    47.6\n",
      "Name: 2019, dtype: object\n",
      "Malawi  -  137    203\n",
      "Name: 2019, dtype: object\n",
      "Malaysia  -  138    98.5\n",
      "Name: 2019, dtype: object\n",
      "Maldives  -  124    1800\n",
      "Name: 2019, dtype: object\n",
      "Mali  -  128    16.6\n",
      "Name: 2019, dtype: object\n",
      "Malta  -  129    1610\n",
      "Name: 2019, dtype: object\n",
      "Marshall Islands  -  126    329\n",
      "Name: 2019, dtype: object\n",
      "Mauritania  -  135    4.51\n",
      "Name: 2019, dtype: object\n",
      "Mauritius  -  136    624\n",
      "Name: 2019, dtype: object\n",
      "Mexico  -  125    66.3\n",
      "Name: 2019, dtype: object\n",
      "Micronesia  -  Series([], Name: 2019, dtype: object)\n",
      "Moldova  -  122    91.2\n",
      "Name: 2019, dtype: object\n",
      "Monaco  -  121    19.4k\n",
      "Name: 2019, dtype: object\n",
      "Mongolia  -  132    2.11\n",
      "Name: 2019, dtype: object\n",
      "Montenegro  -  131    46.2\n",
      "Name: 2019, dtype: object\n",
      "Morocco  -  120    82.7\n",
      "Name: 2019, dtype: object\n",
      "Mozambique  -  134    39.7\n",
      "Name: 2019, dtype: object\n",
      "Namibia  -  139    3.09\n",
      "Name: 2019, dtype: object\n",
      "Nauru  -  148    542\n",
      "Name: 2019, dtype: object\n",
      "Nepal  -  147    203\n",
      "Name: 2019, dtype: object\n",
      "Netherlands_Aruba  -  Series([], Name: 2019, dtype: object)\n",
      "Netherlands_Bonaire, Sint Eustatius and Saba  -  Series([], Name: 2019, dtype: object)\n",
      "Netherlands_Curacao  -  Series([], Name: 2019, dtype: object)\n",
      "Netherlands_Sint Maarten  -  Series([], Name: 2019, dtype: object)\n",
      "Netherlands  -  144    518\n",
      "Name: 2019, dtype: object\n",
      "New Zealand_Cook Islands  -  Series([], Name: 2019, dtype: object)\n",
      "New Zealand_Niue  -  Series([], Name: 2019, dtype: object)\n",
      "New Zealand  -  149    19.3\n",
      "Name: 2019, dtype: object\n",
      "Nicaragua  -  143    55\n",
      "Name: 2019, dtype: object\n",
      "Niger  -  141    19.1\n",
      "Name: 2019, dtype: object\n",
      "Nigeria  -  142    226\n",
      "Name: 2019, dtype: object\n",
      "North Macedonia  -  127    82.2\n",
      "Name: 2019, dtype: object\n",
      "Norway  -  146    14.7\n",
      "Name: 2019, dtype: object\n",
      "Oman  -  150    16.5\n",
      "Name: 2019, dtype: object\n",
      "Pakistan  -  151    287\n",
      "Name: 2019, dtype: object\n",
      "Palau  -  155    39.3\n",
      "Name: 2019, dtype: object\n",
      "Panama  -  152    58.2\n",
      "Name: 2019, dtype: object\n",
      "Papua New Guinea  -  156    19.8\n",
      "Name: 2019, dtype: object\n",
      "Paraguay  -  161    18\n",
      "Name: 2019, dtype: object\n",
      "Peru  -  153    25.8\n",
      "Name: 2019, dtype: object\n",
      "Philippines  -  154    368\n",
      "Name: 2019, dtype: object\n",
      "Poland  -  157    124\n",
      "Name: 2019, dtype: object\n",
      "Portugal  -  160    112\n",
      "Name: 2019, dtype: object\n",
      "Qatar  -  164    251\n",
      "Name: 2019, dtype: object\n",
      "Romania  -  165    83.7\n",
      "Name: 2019, dtype: object\n",
      "Russia  -  166    8.8\n",
      "Name: 2019, dtype: object\n",
      "Rwanda  -  167    525\n",
      "Name: 2019, dtype: object\n",
      "Saint Kitts and Nevis  -  Series([], Name: 2019, dtype: object)\n",
      "Saint Lucia  -  Series([], Name: 2019, dtype: object)\n",
      "Saint Vincent and the Grenadines  -  Series([], Name: 2019, dtype: object)\n",
      "Samoa  -  212    70.1\n",
      "Name: 2019, dtype: object\n",
      "San Marino  -  175    566\n",
      "Name: 2019, dtype: object\n",
      "Sao Tome and Principe  -  179    228\n",
      "Name: 2019, dtype: object\n",
      "Saudi Arabia  -  168    16.2\n",
      "Name: 2019, dtype: object\n",
      "Senegal  -  170    87\n",
      "Name: 2019, dtype: object\n",
      "Serbia  -  177    78.9\n",
      "Name: 2019, dtype: object\n",
      "Seychelles  -  186    214\n",
      "Name: 2019, dtype: object\n",
      "Sierra Leone  -  173    111\n",
      "Name: 2019, dtype: object\n",
      "Singapore  -  171    8020\n",
      "Name: 2019, dtype: object\n",
      "Slovakia  -  Series([], Name: 2019, dtype: object)\n",
      "Slovenia  -  182    104\n",
      "Name: 2019, dtype: object\n",
      "Solomon Islands  -  172    24.5\n",
      "Name: 2019, dtype: object\n",
      "Somalia  -  176    25.3\n",
      "Name: 2019, dtype: object\n",
      "South Africa  -  214    48.9\n",
      "Name: 2019, dtype: object\n",
      "South Sudan  -  178    17.7\n",
      "Name: 2019, dtype: object\n",
      "Spain  -  58    94.8\n",
      "Name: 2019, dtype: object\n",
      "Sri Lanka  -  113    354\n",
      "Name: 2019, dtype: object\n",
      "Sudan  -  169    23.7\n",
      "Name: 2019, dtype: object\n",
      "Summer Olympics 2020  -  Series([], Name: 2019, dtype: object)\n",
      "Suriname  -  180    3.76\n",
      "Name: 2019, dtype: object\n",
      "Sweden  -  183    25.4\n",
      "Name: 2019, dtype: object\n",
      "Switzerland  -  34    219\n",
      "Name: 2019, dtype: object\n",
      "Syria  -  187    95.3\n",
      "Name: 2019, dtype: object\n",
      "Taiwan*  -  Series([], Name: 2019, dtype: object)\n",
      "Tajikistan  -  192    68.7\n",
      "Name: 2019, dtype: object\n",
      "Tanzania  -  200    67.4\n",
      "Name: 2019, dtype: object\n",
      "Thailand  -  191    137\n",
      "Name: 2019, dtype: object\n",
      "Timor-Leste  -  194    88.7\n",
      "Name: 2019, dtype: object\n",
      "Togo  -  190    152\n",
      "Name: 2019, dtype: object\n",
      "Tonga  -  195    147\n",
      "Name: 2019, dtype: object\n",
      "Trinidad and Tobago  -  196    273\n",
      "Name: 2019, dtype: object\n",
      "Tunisia  -  197    76.1\n",
      "Name: 2019, dtype: object\n",
      "Turkey  -  198    110\n",
      "Name: 2019, dtype: object\n",
      "Tuvalu  -  199    393\n",
      "Name: 2019, dtype: object\n",
      "US  -  Series([], Name: 2019, dtype: object)\n",
      "Uganda  -  201    228\n",
      "Name: 2019, dtype: object\n",
      "Ukraine  -  202    76.2\n",
      "Name: 2019, dtype: object\n",
      "United Arab Emirates  -  5    139\n",
      "Name: 2019, dtype: object\n",
      "United Kingdom_Anguilla  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Bermuda  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_British Virgin Islands  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Cayman Islands  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Channel Islands  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Falkland Islands (Malvinas)  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Gibraltar  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Guernsey  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Isle of Man  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Jersey  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Montserrat  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Pitcairn Islands  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Saint Helena, Ascension and Tristan da Cunha  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom_Turks and Caicos Islands  -  Series([], Name: 2019, dtype: object)\n",
      "United Kingdom  -  68    278\n",
      "Name: 2019, dtype: object\n",
      "Uruguay  -  203    19.8\n",
      "Name: 2019, dtype: object\n",
      "Uzbekistan  -  205    77.7\n",
      "Name: 2019, dtype: object\n",
      "Vanuatu  -  211    25.2\n",
      "Name: 2019, dtype: object\n",
      "Venezuela  -  207    32.2\n",
      "Name: 2019, dtype: object\n",
      "Vietnam  -  210    314\n",
      "Name: 2019, dtype: object\n",
      "West Bank and Gaza  -  Series([], Name: 2019, dtype: object)\n",
      "Winter Olympics 2022  -  Series([], Name: 2019, dtype: object)\n",
      "Yemen  -  213    56.5\n",
      "Name: 2019, dtype: object\n",
      "Zambia  -  215    24.7\n",
      "Name: 2019, dtype: object\n",
      "Zimbabwe  -  216    38.4\n",
      "Name: 2019, dtype: object\n"
     ]
    }
   ],
   "source": [
    "for pais in confirmed_monthly.columns[2:-1]:\n",
    "    print(pais, \" - \", pop_area[pop_area[\"country\"] == pais][\"2019\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee9cee77",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Pergunta 1: Há relação entre população e quantidade de casos?\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32185aa1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# focando em dados do Brasil:\n",
    "brasil = pd.DataFrame().assign(data=confirmed.Data, confirmed=confirmed.Brazil, death=death.Brazil)\n",
    "brasil[\"confirmed_ac\"] = brasil[\"confirmed\"].cumsum()\n",
    "brasil[\"death_ac\"] = brasil[\"death\"].cumsum()\n",
    "brasil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbd65f74",
   "metadata": {},
   "outputs": [],
   "source": [
    "# checando por valores negativos:\n",
    "print(brasil[brasil[\"confirmed\"] < 0])\n",
    "print(brasil[brasil[\"death\"] < 0])\n",
    "# valores negativos possivelmente se devem a reavaliações ou retratação\n",
    "# de dados anteriores errados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "df598b04",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = px.data.gapminder().query(\"year == 2007\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2fe34989",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(10,7))\n",
    "plt.plot(brasil.data, brasil.confirmed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8949f650",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(10,7))\n",
    "plt.plot(brasil[(brasil[\"data\"] > \"2022-09-19\") & (brasil[\"data\"] < \"2022-09-22\")].data, brasil[(brasil[\"data\"] > \"2022-09-19\") & (brasil[\"data\"] < \"2022-09-22\")].confirmed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "adc68949",
   "metadata": {},
   "outputs": [],
   "source": [
    "brasil[(brasil[\"data\"] > \"2022-09-19\") & (brasil[\"data\"] < \"2022-09-22\")]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a9ecc3a1",
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(brasil.data, brasil.confirmed_ac)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7baa6628",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = px.data.gapminder().query(\"year == 2007\")\n",
    "fig = px.scatter_geo(df, locations=\"iso_alpha\",\n",
    "                     color=\"continent\", # which column to use to set the color of markers\n",
    "                     hover_name=\"country\", # column added to hover information\n",
    "                     size=\"pop\", # size of markers\n",
    "                     projection=\"natural earth\")\n",
    "# fig = px.scatter_geo(geo_df,\n",
    "#                     lat=geo_df.geometry.y,\n",
    "#                     lon=geo_df.geometry.x,\n",
    "#                     hover_name=\"name\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b05b081c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "235b34ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = px.data.gapminder()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "88827085",
   "metadata": {},
   "outputs": [],
   "source": [
    "novo_confirmed_2 = confirmed.copy()\n",
    "novo_confirmed_2.drop('Total', inplace=True)\n",
    "novo_confirmed_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbe44d0f",
   "metadata": {},
   "outputs": [],
   "source": [
    "location\n",
    "location[location[\"Country/Region\"] == \"Brazil\"]['Lat'].values[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e20a38b1",
   "metadata": {},
   "outputs": [],
   "source": [
    "#checa se tem menor que zero\n",
    "empty_df[empty_df['confirmed'] < 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ab5350b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.set_xlim([0, 10])\n",
    "\n",
    "scat = ax.scatter(1, 0)\n",
    "x = np.linspace(0, 10)\n",
    "\n",
    "\n",
    "def animate(i):\n",
    "    scat.set_offsets((x[i], 0))\n",
    "    return scat,\n",
    "\n",
    "ani = animation.FuncAnimation(fig, animate, repeat=True,\n",
    "                                    frames=len(x) - 1, interval=50)\n",
    "\n",
    "# To save the animation using Pillow as a gif\n",
    "writer = animation.PillowWriter(fps=15,\n",
    "                                metadata=dict(artist='Me'),\n",
    "                                bitrate=1800)\n",
    "ani.save('scatter.gif', writer=writer)\n",
    "# plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "55d4f787",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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