api-covid-pandas.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "dfa8cc68",
   "metadata": {},
   "source": [
    "# Conexion con la API del Covid-19 y analisis con Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "970b0267",
   "metadata": {},
   "source": [
    "Nos conectamos a la API https://covid19api.com/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "33c993fc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in c:\\users\\sergio rivera\\anaconda3\\lib\\site-packages (1.4.2)\n",
      "Requirement already satisfied: numpy>=1.18.5 in c:\\users\\sergio rivera\\anaconda3\\lib\\site-packages (from pandas) (1.21.5)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\sergio rivera\\anaconda3\\lib\\site-packages (from pandas) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\sergio rivera\\anaconda3\\lib\\site-packages (from pandas) (2021.3)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\sergio rivera\\anaconda3\\lib\\site-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "75dd9699",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2c32d6e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://api.covid19api.com/countries'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f8414fa4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.covid19api.com/countries'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "b3357ecd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_json(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a37fa880",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Slug</th>\n",
       "      <th>ISO2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Gibraltar</td>\n",
       "      <td>gibraltar</td>\n",
       "      <td>GI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Oman</td>\n",
       "      <td>oman</td>\n",
       "      <td>OM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>France</td>\n",
       "      <td>france</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Jersey</td>\n",
       "      <td>jersey</td>\n",
       "      <td>JE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Mali</td>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>Puerto Rico</td>\n",
       "      <td>puerto-rico</td>\n",
       "      <td>PR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>Papua New Guinea</td>\n",
       "      <td>papua-new-guinea</td>\n",
       "      <td>PG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>Saint Pierre and Miquelon</td>\n",
       "      <td>saint-pierre-and-miquelon</td>\n",
       "      <td>PM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>Timor-Leste</td>\n",
       "      <td>timor-leste</td>\n",
       "      <td>TL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>Montenegro</td>\n",
       "      <td>montenegro</td>\n",
       "      <td>ME</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>248 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Country                       Slug ISO2\n",
       "0                    Gibraltar                  gibraltar   GI\n",
       "1                         Oman                       oman   OM\n",
       "2                       France                     france   FR\n",
       "3                       Jersey                     jersey   JE\n",
       "4                         Mali                       mali   ML\n",
       "..                         ...                        ...  ...\n",
       "243                Puerto Rico                puerto-rico   PR\n",
       "244           Papua New Guinea           papua-new-guinea   PG\n",
       "245  Saint Pierre and Miquelon  saint-pierre-and-miquelon   PM\n",
       "246                Timor-Leste                timor-leste   TL\n",
       "247                 Montenegro                 montenegro   ME\n",
       "\n",
       "[248 rows x 3 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3c2b50d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Slug</th>\n",
       "      <th>ISO2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Spain</td>\n",
       "      <td>spain</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Country   Slug ISO2\n",
       "141   Spain  spain   ES"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Country'] == 'Spain']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "cbc042a9",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>CountryCode</th>\n",
       "      <th>Province</th>\n",
       "      <th>City</th>\n",
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       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-22 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
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       "      <td>40.46</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-24 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-25 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-26 00:00:00+00:00</td>\n",
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       "      <th>893</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12818184</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-03 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>894</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12818184</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-04 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12890002</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-05 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>896</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12890002</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-06 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>897</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12890002</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-07 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>898 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Country CountryCode Province City CityCode    Lat   Lon     Cases  \\\n",
       "0     Spain          ES                         40.46 -3.75         0   \n",
       "1     Spain          ES                         40.46 -3.75         0   \n",
       "2     Spain          ES                         40.46 -3.75         0   \n",
       "3     Spain          ES                         40.46 -3.75         0   \n",
       "4     Spain          ES                         40.46 -3.75         0   \n",
       "..      ...         ...      ...  ...      ...    ...   ...       ...   \n",
       "893   Spain          ES                         40.46 -3.75  12818184   \n",
       "894   Spain          ES                         40.46 -3.75  12818184   \n",
       "895   Spain          ES                         40.46 -3.75  12890002   \n",
       "896   Spain          ES                         40.46 -3.75  12890002   \n",
       "897   Spain          ES                         40.46 -3.75  12890002   \n",
       "\n",
       "        Status                      Date  \n",
       "0    confirmed 2020-01-22 00:00:00+00:00  \n",
       "1    confirmed 2020-01-23 00:00:00+00:00  \n",
       "2    confirmed 2020-01-24 00:00:00+00:00  \n",
       "3    confirmed 2020-01-25 00:00:00+00:00  \n",
       "4    confirmed 2020-01-26 00:00:00+00:00  \n",
       "..         ...                       ...  \n",
       "893  confirmed 2022-07-03 00:00:00+00:00  \n",
       "894  confirmed 2022-07-04 00:00:00+00:00  \n",
       "895  confirmed 2022-07-05 00:00:00+00:00  \n",
       "896  confirmed 2022-07-06 00:00:00+00:00  \n",
       "897  confirmed 2022-07-07 00:00:00+00:00  \n",
       "\n",
       "[898 rows x 10 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url_rt_es = 'https://api.covid19api.com/country/spain/status/confirmed/live'\n",
    "df_rt_es = pd.read_json(url_rt_es)\n",
    "df_rt_es"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ff89b32d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
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       "      <th>Country</th>\n",
       "      <th>CountryCode</th>\n",
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       "      <th>1</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
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       "      <td>2020-01-23 00:00:00+00:00</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
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       "      <td>confirmed</td>\n",
       "      <td>2020-01-24 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-25 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-26 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Country CountryCode Province City CityCode    Lat   Lon  Cases     Status  \\\n",
       "0   Spain          ES                         40.46 -3.75      0  confirmed   \n",
       "1   Spain          ES                         40.46 -3.75      0  confirmed   \n",
       "2   Spain          ES                         40.46 -3.75      0  confirmed   \n",
       "3   Spain          ES                         40.46 -3.75      0  confirmed   \n",
       "4   Spain          ES                         40.46 -3.75      0  confirmed   \n",
       "\n",
       "                       Date  \n",
       "0 2020-01-22 00:00:00+00:00  \n",
       "1 2020-01-23 00:00:00+00:00  \n",
       "2 2020-01-24 00:00:00+00:00  \n",
       "3 2020-01-25 00:00:00+00:00  \n",
       "4 2020-01-26 00:00:00+00:00  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rt_es.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d39ca619",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>CountryCode</th>\n",
       "      <th>Province</th>\n",
       "      <th>City</th>\n",
       "      <th>CityCode</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Cases</th>\n",
       "      <th>Status</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>893</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12818184</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-03 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>894</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12818184</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-04 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12890002</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-05 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>896</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12890002</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-06 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>897</th>\n",
       "      <td>Spain</td>\n",
       "      <td>ES</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>40.46</td>\n",
       "      <td>-3.75</td>\n",
       "      <td>12890002</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-07 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Country CountryCode Province City CityCode    Lat   Lon     Cases  \\\n",
       "893   Spain          ES                         40.46 -3.75  12818184   \n",
       "894   Spain          ES                         40.46 -3.75  12818184   \n",
       "895   Spain          ES                         40.46 -3.75  12890002   \n",
       "896   Spain          ES                         40.46 -3.75  12890002   \n",
       "897   Spain          ES                         40.46 -3.75  12890002   \n",
       "\n",
       "        Status                      Date  \n",
       "893  confirmed 2022-07-03 00:00:00+00:00  \n",
       "894  confirmed 2022-07-04 00:00:00+00:00  \n",
       "895  confirmed 2022-07-05 00:00:00+00:00  \n",
       "896  confirmed 2022-07-06 00:00:00+00:00  \n",
       "897  confirmed 2022-07-07 00:00:00+00:00  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rt_es.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "dfc23071",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Casos de Covid-19 en España desde 20/1/2020 hasta 29/6/2022'}, xlabel='Date'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_rt_es.set_index('Date')['Cases'].plot(title=\"Casos de Covid-19 en España desde 20/1/2020 hasta 29/6/2022\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "a4b48554",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>Slug</th>\n",
       "      <th>ISO2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>Panama</td>\n",
       "      <td>panama</td>\n",
       "      <td>PA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Country    Slug ISO2\n",
       "190  Panama  panama   PA"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Country'] == 'Panama']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "aabeffdf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Country</th>\n",
       "      <th>CountryCode</th>\n",
       "      <th>Province</th>\n",
       "      <th>City</th>\n",
       "      <th>CityCode</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Cases</th>\n",
       "      <th>Status</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-22 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-23 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-24 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-25 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-26 00:00:00+00:00</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>894</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>925254</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-04 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>925254</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-05 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>896</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>925254</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-06 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>897</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>925254</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-07 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>898</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>925254</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-09 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>899 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Country CountryCode Province City CityCode   Lat    Lon   Cases  \\\n",
       "0    Panama          PA                         8.54 -80.78       0   \n",
       "1    Panama          PA                         8.54 -80.78       0   \n",
       "2    Panama          PA                         8.54 -80.78       0   \n",
       "3    Panama          PA                         8.54 -80.78       0   \n",
       "4    Panama          PA                         8.54 -80.78       0   \n",
       "..      ...         ...      ...  ...      ...   ...    ...     ...   \n",
       "894  Panama          PA                         8.54 -80.78  925254   \n",
       "895  Panama          PA                         8.54 -80.78  925254   \n",
       "896  Panama          PA                         8.54 -80.78  925254   \n",
       "897  Panama          PA                         8.54 -80.78  925254   \n",
       "898  Panama          PA                         8.54 -80.78  925254   \n",
       "\n",
       "        Status                      Date  \n",
       "0    confirmed 2020-01-22 00:00:00+00:00  \n",
       "1    confirmed 2020-01-23 00:00:00+00:00  \n",
       "2    confirmed 2020-01-24 00:00:00+00:00  \n",
       "3    confirmed 2020-01-25 00:00:00+00:00  \n",
       "4    confirmed 2020-01-26 00:00:00+00:00  \n",
       "..         ...                       ...  \n",
       "894  confirmed 2022-07-04 00:00:00+00:00  \n",
       "895  confirmed 2022-07-05 00:00:00+00:00  \n",
       "896  confirmed 2022-07-06 00:00:00+00:00  \n",
       "897  confirmed 2022-07-07 00:00:00+00:00  \n",
       "898  confirmed 2022-07-09 00:00:00+00:00  \n",
       "\n",
       "[899 rows x 10 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url_rt_pa = 'https://api.covid19api.com/country/panama/status/confirmed/live'\n",
    "df_rt_pa = pd.read_json(url_rt_pa)\n",
    "df_rt_pa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6320f6cd",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>1</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
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       "      <td>confirmed</td>\n",
       "      <td>2020-01-24 00:00:00+00:00</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-25 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>0</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2020-01-26 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Country CountryCode Province City CityCode   Lat    Lon  Cases     Status  \\\n",
       "0  Panama          PA                         8.54 -80.78      0  confirmed   \n",
       "1  Panama          PA                         8.54 -80.78      0  confirmed   \n",
       "2  Panama          PA                         8.54 -80.78      0  confirmed   \n",
       "3  Panama          PA                         8.54 -80.78      0  confirmed   \n",
       "4  Panama          PA                         8.54 -80.78      0  confirmed   \n",
       "\n",
       "                       Date  \n",
       "0 2020-01-22 00:00:00+00:00  \n",
       "1 2020-01-23 00:00:00+00:00  \n",
       "2 2020-01-24 00:00:00+00:00  \n",
       "3 2020-01-25 00:00:00+00:00  \n",
       "4 2020-01-26 00:00:00+00:00  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rt_pa.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "726cb120",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>CountryCode</th>\n",
       "      <th>Province</th>\n",
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       "      <th>894</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
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       "      <td>2022-07-04 00:00:00+00:00</td>\n",
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       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
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       "      <td></td>\n",
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       "    <tr>\n",
       "      <th>896</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>925254</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-06 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>897</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>925254</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-07 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>898</th>\n",
       "      <td>Panama</td>\n",
       "      <td>PA</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>8.54</td>\n",
       "      <td>-80.78</td>\n",
       "      <td>925254</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-09 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Country CountryCode Province City CityCode   Lat    Lon   Cases  \\\n",
       "894  Panama          PA                         8.54 -80.78  925254   \n",
       "895  Panama          PA                         8.54 -80.78  925254   \n",
       "896  Panama          PA                         8.54 -80.78  925254   \n",
       "897  Panama          PA                         8.54 -80.78  925254   \n",
       "898  Panama          PA                         8.54 -80.78  925254   \n",
       "\n",
       "        Status                      Date  \n",
       "894  confirmed 2022-07-04 00:00:00+00:00  \n",
       "895  confirmed 2022-07-05 00:00:00+00:00  \n",
       "896  confirmed 2022-07-06 00:00:00+00:00  \n",
       "897  confirmed 2022-07-07 00:00:00+00:00  \n",
       "898  confirmed 2022-07-09 00:00:00+00:00  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rt_pa.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d873a071",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Casos de Covid-19 en Panamá desde 20/1/2020 hasta 29/6/2022'}, xlabel='Date'>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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uk4buyvse7kJimV/WrxpZVhauT3pdIPZtQA8/fgx77hZcDJwVNf9AXN/xP6KG38jed3c1WOYGyvUWLjkHX5MD238NrjtjGYHrLw0sa6Svv80+/hvAOD/uYeAXgWkn475A9S1nMFF35QXGNbhP+PEKDAt8/iyu38bz/LwLcHdfFQam3Wtb+X3oxsDnS4HX/PsuuFtly3Gt2YuiY0eVe6gvbzn135U30dd/id9+//B13jewX2zz9TXaz5OCuzN1K+5uvfruyrsX162zHdctO72B8r2JO1iWB16vBMbn4LpyK3D71wWBcQVAftTy1vD5/Wowrjvo46hpV+MO5MHY90XtD2/huqGWRdXR/+G+F8F5FwXGdwL+gksWRTRwt1lD+yR7f+fP8XVdhjsR+6wOcS3oZX77FOFuWInUwxG4VmepH56MaynswLXofkgj39NmbJ+/+vrdDjwF9PLDxS+/V9TyjgE+8sspYM/1p9OBl6OmVfacEEVe1wfGj8d9p3bhbgAa35x9Ctejpey5WzHyavQYE7m4ZYwxDRJ3N9UCoJ8246AhIj/EdS/+sK3Lluh8q+5Pqtqs/5UUkXtwJw33tG3JWs4eaWKMaY4sXCukuWeya3D/GmHaR0Nd7/VZQIzXjbWYjDHGxBR7iKsxxpiYEnddeT179tTBgweHXQxjjOlQ5s2bt0VVc5uesu3FXWIaPHgwBQUFYRfDGGM6FBGp75/5Q2FdecYYY2KKJSZjjDExxRKTMcaYmGKJyRhjTEyxxGSMMSamWGIyxhgTU+LudnFjjEkkc9eU8O4n7oHgvbPSOS9/QBNzxD5LTMYY0wGpKre+spT7/7PnFzLGDci2xGSMMab9lVfVcN1zH/LyhxuZNq4fPzt9NFkZDf6QbodjickYYzqQXbtr+fr/zWXe2lJ+OHUkVx53AHv/uGzHZ4nJGGM6iJKK3Vz9xHzmflrCndPHc8bYfmEXqU1YYjLGmA6geEcl593/Dhu2VfKHc8fGbVICS0zGGBPztpZXcdFf3qe4rIq/Xj6RwwblhF2kNmWJyRhjYlhJxW7Ovf8d1pfu4qEZh8d9UgJLTMYYE9N+/PyHFJbs4tFLJjBxaI+wi9Mu7MkPxhgTo/63cguzFhXx7ROHJ0xSAktMxhgTk3ZUVnPDS4vIy87gkqOHhF2cdmVdecYYE4Nuemkxq7dU8PDXDic9NTns4rQrazEZY0yMWbxhB8/NL+TyY4dyzPDcsIvT7iwxGWNMjPnTmyvo0imFK449IOyihMISkzHGxJB5n5bwz482cfGRg8nqHD/Pv9sXlpiMMSZG7NpdyxWPzWdgTmcuPSaxbngIspsfjDEmRjw1dy2by6p46vJJZHdOC7s4obEWkzHGxIDdNXU88J9VHD64e0L9z1J9LDEZY0wMeH5+IRu2V/LN44eFXZTQWWIyxpiQrSwu46a/L+bQgdlMHpF4t4dHs8RkjDEh+/2s5aQkCfd99bC4+9G/lrDEZIwxIVq2qYxXF23ia0cPoVe39LCLExOalZhE5LsiskhEPhaRv4pIuojkiMhsEVnh/3YPTP9jEVkpIstE5OTA8MNE5CM/7k7xpwYi0klEnvLD3xORwYF5ZvgYK0RkRiuuuzHGhO7uN1cCcNERg0IuSexoMjGJSB5wDZCvqgcBycB04DrgdVUdDrzuPyMio/34McBU4B4RiTzo6V7gcmC4f031wy8BSlV1GHA78Bu/rBzgBmAiMAG4IZgAjTGmI5u9uIiXFm7goLxu9OzSKezixIzmduWlABkikgJ0BjYAZwIz/fiZwDT//kzgSVWtUtXVwEpggoj0Bbqp6juqqsAjUfNElvUscIJvTZ0MzFbVElUtBWazJ5kZY0yHVVVTyy0vL2ZobiaPXzIp7OLElCYTk6quB34PrAU2AttV9V9Ab1Xd6KfZCPTys+QB6wKLKPTD8vz76OF7zaOqNcB2oEcjy9qLiFwuIgUiUrB58+amVskYY0I3c84a1pbs5MYzxiTso4ca0pyuvO64Fs0QoB+QKSJfbWyWeoZpI8NbOs+eAaoPqGq+qubn5tqtlsaY2La5rIq7Xl/J8SNzOdZuD/+c5nTlnQisVtXNqloNPA8cCRT57jn832I/fSEwIDB/f1zXX6F/Hz18r3l8d2EWUNLIsowxpkMqq6zmyw+8Q1VtHT85bVTYxYlJzUlMa4FJItLZX/c5AVgCvARE7pKbAbzo378ETPd32g3B3eTwvu/uKxORSX45F0XNE1nWOcAb/jrULGCKiHT3LbcpfpgxxnQ4ldW1XP3EB6zZUsHDFx/OsF5dwy5STGryIa6q+p6IPAvMB2qAD4AHgC7A0yJyCS55neunXyQiTwOL/fRXqWqtX9yVwMNABvCKfwE8BDwqIitxLaXpflklInILMNdPd7OqluzXGhtjTDtbtbmcFxds4PH31rKlvIpbv3QwRw7rGXaxYpa4hkn8yM/P14KCgrCLYYxJUHV1ysrN5cz/tJQlG3fw3uoSlm4qA2DyyFwuO2YoR8VgUhKReaqaH3Y5wH72whhj9ll1bR2fbt3JyuJyPtlczpotFXy6dSefllSwuayKOn++n5mWzJi8LH52+mhOPbgPfbMywi14B2GJyRhjGlBVU8uKonIWb9jB8qIyCkt3sXJzOZ9uraC6dk9vU27XTgzpkckxw3Ppm5VOXnYGk4b2YGBOZ5KS7Nl3+8oSkzHGBKwsLuOxd9fy7qqtrCwup8Y3f9JTk+iXncEBuV04aXRvhvfqwrBeXRia24UunexQ2ppsaxpjDDB/bSm/n7WMOZ9sJS0liSOG9uCEUb0Y3TeL0f26MchaP+3GEpMxJqHV1NZx5+sruPutT+icmszFRw7mW18YRg97dl1oLDEZYxJWXZ3yvacX8tLCDRwxtAf3X3QY3dLt8UBhs8RkjElYT85dx0sLN3DNCcP5zgnDrasuRlhiMsYkpI3bd3H9Cx8xcUgO3z1xuP1ybAyxX7A1xiSk7z61AIBvHj/MklKMscRkjEk4/1u5hXdXlTB5ZC7H2dO9Y44lJmNMwvnXok0A3H7euHALYuplickYk1BUldeWFDO2fxbdM9PCLo6phyUmY0xCWVi4nfXbdtE/p3PYRTENsMRkjEkod7y2HIBrp4wMuSSmIZaYjDEJo7iskreWb6Z/9wwG98wMuzimAZaYjDEJ438rt6AK9194WNhFMY2wxGSMSRgFa0rp2imFA/t0C7sophGWmIwxCaNgTSnjB3Un2R49FNMsMRljEsL2XdUsLy4jf1D3sItimmCJyRiTEBZv2IEqjBuQHXZRTBMsMRljEkJxWSUAfbPSQy6JaYolJmNMQthavhuAnvYDgDHPEpMxJiFsKa8iJUnIyrAfAox1lpiMMXGvsrqWp+auY2BOZ/sxwA7AEpMxJu69u2orWyt2c9SwnmEXxTSDJSZjTNwr2uFufPjGcUNDLolpDktMxpi4t750FwC5Xe3Gh47AEpMxJu7d+cZKunZKoVNKcthFMc1gickYE9e27XS3iU8+sFfIJTHNZYnJGBPXPtlcAcC0cf1CLolprmYlJhHJFpFnRWSpiCwRkSNEJEdEZovICv+3e2D6H4vIShFZJiInB4YfJiIf+XF3ioj44Z1E5Ck//D0RGRyYZ4aPsUJEZrTiuhtjEsDqLS4xDbHfX+owmttiugN4VVUPBMYCS4DrgNdVdTjwuv+MiIwGpgNjgKnAPSIS6di9F7gcGO5fU/3wS4BSVR0G3A78xi8rB7gBmAhMAG4IJkBjjGnKqs3lpCQJA+yn1DuMJhOTiHQDjgUeAlDV3aq6DTgTmOknmwlM8+/PBJ5U1SpVXQ2sBCaISF+gm6q+o6oKPBI1T2RZzwIn+NbUycBsVS1R1VJgNnuSmTHGNGnV5goG9uhMarJduegomlNTQ4HNwP+JyAci8qCIZAK9VXUjgP8bubKYB6wLzF/oh+X599HD95pHVWuA7UCPRpa1FxG5XEQKRKRg8+bNzVglY0yiWL2lgqHWjdehNCcxpQCHAveq6nigAt9t14D6nvehjQxv6Tx7Bqg+oKr5qpqfm5vbSNGMMYmktk5ZvbWCobldwi6K2QfNSUyFQKGqvuc/P4tLVEW+ew7/tzgw/YDA/P2BDX54/3qG7zWPiKQAWUBJI8syxpgmbdi2i901ddZi6mCaTEyquglYJyIj/aATgMXAS0DkLrkZwIv+/UvAdH+n3RDcTQ7v++6+MhGZ5K8fXRQ1T2RZ5wBv+OtQs4ApItLd3/QwxQ8zxpgmLd1UBmAtpg4mpZnTfQt4XETSgFXA13BJ7WkRuQRYC5wLoKqLRORpXPKqAa5S1Vq/nCuBh4EM4BX/AndjxaMishLXUprul1UiIrcAc/10N6tqSQvX1RiTYN5cVkyXTimMHZAVdlHMPhDXMIkf+fn5WlBQEHYxjDEx4OTb/0Pf7HQe/tqEsIsS80Rknqrmh10OsCc/GGPiVFllNcuLyxg3IDvsoph9ZInJGBOXPlq/HVUsMXVAlpiMMXEp8lMXQ3vajQ8djSUmY0xcKi6rAuw3mDoiS0zGmLj01rJiMtOSyUiz32DqaCwxGWPizvZd1cxdU0p257Swi2JawBKTMSbuvLG0CIBffengkEtiWsISkzEmrqgq9721imG9unDMsJ5hF8e0gCUmY0xcKfi0lGVFZVx+zFCSkup7DrSJdZaYjDFx5ZmCdXROS+a0Q/qGXRTTQpaYjDFxo7q2jn98uJHTDu5LZqfmPgrUxBpLTMaYuLGiqJyK3bUcM8J+l60js8RkjIkLW8uruOetlQCM7W9PE+/IrK1rjOnwqmpqOeueOawr3cnXjxrCoB72w4AdmSUmY0yHtqKojB88+yFrS3Zy71cO5ZSD7aaHjs4SkzGmQ6mqqWXpxjIWbdjBa0uKeGNpMWkpSXzjuKFMGdMn7OKZVmCJyRgTU+rqlC3lVRRu20Vh6S7Wl+5i/badn71fW7KTqpo6ALI7p3LJ0UP4xnFD6dU1PeSSm9ZiickY0+ZUlW07q9lcXsXmMvcq3bmbssoatpZXfTa8uKyKjdsr2e0TT0R251TysjMY0jOTY0fkckj/LA4d2J1+2Rkk2z/Rxh1LTMaY/bZ9VzWFpa5VU1i6iw3bdlG0o5LisiqKd1RStKOKXdW19c7bLT2F3K6d6NU1nUP6ZzN1TDr9u2eQ1z2DvOzO5HXPoIv9T1JCsdo2xjRbVU0tizbsYNmmss9ey4vK2Fqxe6/pMlKT6d2tE726pXNw/2xO6NqJvlnp9O6WTm7XTuR27URO5zS6pKeQmmz/tWL2ZonJGNOgyupa3l21lfdXlzB3TQkLC7d/1s3WOS2Z4b27cuKo3hzQK5MB3TvTv3tn+nfPILtzKiLWxWZaxhKTMWYvtXXKu6u28uKC9bzy8SbKKmtISRLG5GUx44hBHDYohzH9upGXnWEPSTVtwhKTMQaAkordPDxnDc8WrGPD9kq6dErh5DF9OGNsXyYMyaFzmh0uTPuwPc2YBLd9ZzV3vL6Cp+auZWd1LccOz+X600Zx4qjepKfaz5Kb9meJyZgEtWpzOQ/PWcMT761FgTMO6ctVxw9jeO+uYRfNJDhLTMYkmOKySu7/9ypmzlmDAmeO7cdFRw5m3IDssItmDGCJyZiEUV1bx0Nvr+aPry2nqqaO6YcP4LsnjbAnJpiYY4nJmDinqry4YAN/mL2MdSW7OGl0b3409UCG9eoSdtGMqZclJmPi2KIN27nl5cW8u6qEg/OyuOniMXzhwN5hF8uYRjX7X65FJFlEPhCRl/3nHBGZLSIr/N/ugWl/LCIrRWSZiJwcGH6YiHzkx90p/j/wRKSTiDzlh78nIoMD88zwMVaIyIxWWWtj4lxVTS2/m7WUM+56m+VF5dwy7SD+dtVRlpRMh7AvzwL5NrAk8Pk64HVVHQ687j8jIqOB6cAYYCpwj4hE7jm9F7gcGO5fU/3wS4BSVR0G3A78xi8rB7gBmAhMAG4IJkBjzN5UlVc+2shxv32Lu9/8hLMP7c+bP5jMhZMG2cNOTYfRrMQkIv2B04AHA4PPBGb69zOBaYHhT6pqlaquBlYCE0SkL9BNVd9RVQUeiZonsqxngRN8a+pkYLaqlqhqKTCbPcnMGBOwaMN2LvrL+1z5+HxyMtN4/NKJ/O7csWRlpIZdNGP2SXOvMf0R+CEQ/AeH3qq6EUBVN4pILz88D3g3MF2hH1bt30cPj8yzzi+rRkS2Az2Cw+uZ5zMicjmuJcbAgQObuUrGxIeSit3c9+9PeOjt1XRLT+Gnp43i4iMHk2IPRzUdVJOJSUROB4pVdZ6ITG7GMuvrL9BGhrd0nj0DVB8AHgDIz8//3Hhj4tH6bbt48L+r+Ov7a6msruP8CQO47pRR1kIyHV5zWkxHAV8UkVOBdKCbiDwGFIlIX99a6gsU++kLgQGB+fsDG/zw/vUMD85TKCIpQBZQ4odPjprnrWavnTFxaOmmHTz439X87YP1AJw5Lo/Ljh3CgX26hVwyY1pHk4lJVX8M/BjAt5h+oKpfFZHfATOAW/3fF/0sLwFPiMhtQD/cTQ7vq2qtiJSJyCTgPeAi4K7APDOAd4BzgDdUVUVkFvCrwA0PUyJlMSaRrN26k7eWF/PCB+v5YO020lOT+OqkQVx6zBD6d+8cdvGMaVX7839MtwJPi8glwFrgXABVXSQiTwOLgRrgKlWN/HTllcDDQAbwin8BPAQ8KiIrcS2l6X5ZJSJyCzDXT3ezqpbsR5mN6RCqamopWFPKm0uLeXNZMZ9srgDggNxMfn76aKaNzyMnMy3kUhrTNsTdIBc/8vPztaCgIOxiGLNPVJUVxeW888lW3l65hTkrt1Cxu5a0lCQmDe3B8SNzmTyyF0N6ZoZdVBOnRGSequaHXQ6wJz8Y0+4qq2tZWVzufpq8qIylm8pYvGE7W8rdz5P3757BWYfmcfzIXhxxQA/7HSSTcGyPN6aN1NUp67ftYvHGHSzZuIPlPgmt2VJBne+oSEtJYlhuF44dkcukIT044oAeDMixa0YmsVliMqaV7KispmBNCe+tLmH+p6Us3rCDit3u8qoIDMrpzMg+XTn94L6M7NONkX26MrhHZ/t/I2OiWGIypoXKq2p4e8Vm5q4pZe6aEj5ev506hdRk4aC8LM45rD8H9nUJ6MA+Xa1Lzphmsm+KMfugeEcls5cUMXtxEXNWbmV3bR1pKUmM65/N1ccPY9LQHowf2J2MNPtJcmNayhKTMU1YWVzOrEWb+NfiIhau2wbAwJzOXHjEIE4a3ZvDBnUn1brjjGk1lpiMqUfRjkpeXLCef3y06bNkNLZ/Fj+YMoKTRvdhRO8u+F9tMca0MktMxgTM+WQLj8z5lNlLiqitU8b068ZPTxvF6Yf0o0+W/QS5Me3BEpMxwOotFfzyH4t5bUkx3TuncunRQ5g+YaD9Q6sxIbDEZBKaqvLQ26v5zatLSU1O4vpTD2TGkYPplGI3LxgTFktMJmFt27mbHzyzkNeWFDNldG9+cdZB9Opq3XXGhM0Sk0lI23dW86V757CuZCc3nDGai48cbDczGBMjLDGZhFNdW8eVj89jXclOHvn6RI44oEfYRTLGBFhiMgmlrk75zpMLmPPJVn5/7lhLSsbEIPuvQJNQ7npjJf/4aCM/mnog5xzWv+kZjDHtzhKTSRifbq3grjdWcOa4flxx3NCwi2OMaYAlJpMwfv+v5aQkC9efOspudDAmhlliMgnh5Q838PeFG7j8mKH07ma3hBsTyywxmbhXW6f84V/LGd23G986YXjYxTHGNMESk4l7/15ezOotFVw5+QB7CrgxHYB9S03ce6agkB6ZaUw9qE/YRTHGNIMlJhPXPtlczuzFRZw1Ps9aS8Z0EPZNNXGrsrqWbz42n67pKVx+rN0ebkxHYU9+MHHrztdXsKyojIe/dji97E48YzoMazGZuFRZXcsT76/llIP6MHlkr7CLY4zZB5aYTFx65eONbNtZzVcnDQq7KMaYfWSJycSdsspq/vCv5RyQm8kRQ+0hrcZ0NHaNycSdP/xrOeu37eLZK44gKckePWRMR2MtJhNXPl6/nUfeWcOFkwZx2KCcsItjjGkBS0wmbtTVKT/528fkZKbx/Skjwy6OMaaFmkxMIjJARN4UkSUiskhEvu2H54jIbBFZ4f92D8zzYxFZKSLLROTkwPDDROQjP+5O8Y94FpFOIvKUH/6eiAwOzDPDx1ghIjNade1NXHly7joWrtvGT04bRVZGatjFMca0UHNaTDXA91V1FDAJuEpERgPXAa+r6nDgdf8ZP246MAaYCtwjIsl+WfcClwPD/WuqH34JUKqqw4Dbgd/4ZeUANwATgQnADcEEaEzE1vIqfvPqUiYNzWHauLywi2OM2Q9NJiZV3aiq8/37MmAJkAecCcz0k80Epvn3ZwJPqmqVqq4GVgITRKQv0E1V31FVBR6JmieyrGeBE3xr6mRgtqqWqGopMJs9ycyYz/z6laVUVNXwi2kH2W8tGdPB7dM1Jt/FNh54D+itqhvBJS8g8l+MecC6wGyFfliefx89fK95VLUG2A70aGRZ0eW6XEQKRKRg8+bN+7JKJg48U7COZ+cVctmxQxnWq2vYxTHG7KdmJyYR6QI8B3xHVXc0Nmk9w7SR4S2dZ88A1QdUNV9V83Nzcxspmok3qzaX87MXP+bIA3rwvZNGhF0cY0wraFZiEpFUXFJ6XFWf94OLfPcc/m+xH14IDAjM3h/Y4If3r2f4XvOISAqQBZQ0sixjKK3YzSUzC8hITea288bZ08ONiRPNuStPgIeAJap6W2DUS0DkLrkZwIuB4dP9nXZDcDc5vO+7+8pEZJJf5kVR80SWdQ7whr8ONQuYIiLd/U0PU/wwk+Cqamr5xmPzWF+6iwcuyqdPlj2k1Zh40ZwnPxwFXAh8JCIL/LDrgVuBp0XkEmAtcC6Aqi4SkaeBxbg7+q5S1Vo/35XAw0AG8Ip/gUt8j4rISlxLabpfVomI3ALM9dPdrKolLVtVEy9Uleue+4j3V5dwx/RxHD7Y/pHWmHgirmESP/Lz87WgoCDsYpg2Ulun/PbVpdz/n1X8YMoIrv7C8LCLZExcEJF5qpofdjnAnpVnOpCKqhq++fh8/r18MxdMHMhVxw8Lu0jGmDZgicl0CEs37eD7Ty9kycYd/PKsg7hgwkD7fyVj4pQlJhPTqmvruO+tT7jzjRV0S0/lzxflc8Ko3mEXyxjThiwxmZi1ZOMOfvDMQhZt2MEZY/tx0xfHkJOZFnaxjDFtzBKTiTlby6u48/UVPP7eWrI7p3HfVw9j6kF9wi6WMaadWGIyMeOjwu08N7+Q5+YVsrO6li8fPoBrp4yku7WSjEkolphMqEoqdvPigvU8O6+QRRt20CkliRNG9eJ7J41kWK8uYRfPGBMCS0ym3e2uqePNZcU8N6+QN5YWU1OnjO7bjZu+OIZp4/Pst5SMSXCWmEy7WVFUxjPzXFfd1ord9OzSiYuPHMzZh/VnVN9uYRfPGBMjLDGZNrWjspqXF27k6YJ1LFi3jZQk4QsH9uLLhw/guBG5pNiDV40xUSwxmVZXV6e8u2orz8wr5JWPN1JZXceI3l346WmjmDY+j55dOoVdRGNMDLPEZFpNYelOniko5Nl5hazftouunVI4+9D+nJc/gEP6Z9mTGowxzWKJyeyXqppa/rWoiKcL1vH2yi0AHD2sJz865UCmjO5NempyyCU0xnQ0lphMiyzdtIOn5q7jbx+sp3RnNXnZGXz7hOGcc1h/+nfvHHbxjDEdmCUm02w1tXU8/8F6Hn9vLQvXbSMtOYmTxvTmy/kDOGpYT5KTrKvOGLP/LDGZJq0r2cnz89fz8ocbWFFczsjeXfnZ6aM5a3yePbvOGNPqLDGZBpVVVnPvW5/w4H9Xs7u2joPzsrjvq4dy8pg+diODMabNWGIyn1NXpzw7v5DfvrqULeW7OWt8Ht89cQQDe9i1I2NM27PEZPYyf20pt7y8mA/WbuOwQd15aMbhjB2QHXaxjDEJxBKTAaBoRyW/+ucSXlywgdyunfjdOYdw9qH9SbIbGowx7cwSU4KrrK7lsXc/5Y+vrWB3bR3f+sIwrjjuADI72a5hjAmHHX0SVF2d8sy8dfxu1jK2lO9m8shcbvriGAb1yAy7aMaYBGeJKQGtLC7n2mcX8sHabeQP6s5d5x/KpKE5dqedMSYmWGJKIJXVtTz09mrueH0FmWnJ3HbeWM4an2cJyRgTUywxJYDaOuXvCzdw2+zlrC3ZySkH9eGmM8fQq2t62EUzxpjPscQUx1SVWYs2cdvs5SwvKmdU3248dslEjh7eM+yiGWNMgywxxaHdNXX87YP1PPT2apYVlTE0N5M/XTCeUw/qa7d/G2NiniWmOLKyuJyH56xm1qIiNpdVMapvN247byxfHNvPfinWGNNhWGLqwCqra5m/tpT3VpUw55MtzF1TSlpKEkcP68nFRw7mmOE97cYGY0yH0yESk4hMBe4AkoEHVfXWkIvULqpr6yjaUcnG7ZVs2LaLDdvc343bd7F+WyUri8uorlWSBMb0y+L7J43gyxMG2E0NxpgOLeYTk4gkA3cDJwGFwFwReUlVF4dbsv1TU1vH1ordeyWejdsrWb9tFxt9Eiouq6RO954vKyOVvlnp5GVncOzwnkwcmkP+4By6paeGsyLGGNPKYj4xAROAlaq6CkBEngTOBFo1Me3aXcuj765BFRRQhTp1WUFVqVP8OPce1b2mi7zXz97vmae6to6Sit1sKa9ia8VutpZXsW1XNRqVdNJSksjLzqBvVjpHD+9Jv6x0+mVn0Dc7g7zsdPpmZdijgowxca8jHOXygHWBz4XAxOAEInI5cDnAwIEDWxSkYncNv/rn0n2aRwSSRBD/XoLvEZL8sJRkISczjZ6ZnRjeqwuThuaQk9mJXl3dq29WBv2y08nJTLNrQsaYhNcRElN9R+q92hqq+gDwAEB+fr7WM32Tcjqn8fFNJ3+WWJJ8gtg7+exJNsYYY9pGR0hMhcCAwOf+wIbWDpKUJHSxbjJjjAldR/jnlrnAcBEZIiJpwHTgpZDLZIwxpo3EfBNBVWtE5GpgFu528b+o6qKQi2WMMaaNxHxiAlDVfwL/DLscxhhj2l5H6MozxhiTQCwxGWOMiSmWmIwxxsQU0ejHD3RwIrIZ+LSJyXoCW9qhOLES12JbbIsdv7FbK+4gVc1theXst7hLTM0hIgWqmp8ocS22xbbY8Rs7zHVuK9aVZ4wxJqZYYjLGGBNTEjUxPZBgcS22xbbY8Rs7zHVuEwl5jckYY0zsStQWkzHGmBhlickYY0xMscRkjDEmpsRlYpIQf8lPREaFGPv7IjLFv2/XbSAiWYH37R07lPq2ug5n21t9x/8vlcZVYhKRM0VkJjA2pPh3Af8UkcHtHHeKiMwCfgRcBKDtdFeLiHxBRBYA94rI9e0cO7T6trpu37r28a2+ad9tHpYO8bMXjRERUVUVkeOBW4Bq4AgR+VRVS9sjdmBQDlAKnCgij6pqVVvGBlKBnwPHAb8G0oDDRSQVqGnrHVhEugDX47b7+8BMEemsqj9tw5ih1LfVdfvXtY9r9R1CfYetQ7eYonae1cDJwLXAROCQ9ootIsl+8LvAvcBXgOFtHVtVdwMvquox/jerSoHpqlrdDgeqJKALsA74QFXXAZcCXxaRA9soZij1bXXd/nXt41p9h1DfsaDDJib/q7bPi8h3RaSPqq5R1Y2q+gZQBBwnInltHPs7ItJPVWvF/ez7VOAF4E1guoh8SURa9aGIUevdV1Xn+uGpqvpvYJWInNKaMQOxvykiZwOoah2gQC7uoIWqrsKt/81++lbrCw+rvq2u27+u/fKsvtuxvmNNh0xMInIWMAO4E3fm9FMRGReY5HFgBO7MKjjffn95omKPBa4XkcP8GU6Bqm4BVgDXAL8EWvPgHL3ePxGRSH97jYjk4J6sXttaMX3criJyH65rYaaIpACoahGwGPhOYPLrgIkiMqa1zuzCqm+r6/ava18Gq+92qu9Y1SETE26HvFdV3wRuxDXzr4mMVNUPgbnAQeIu2P7ID2+NL099sa/0404Tkf/iLlT+Ddf839EKMRuL/W1w66aqJUAGcDx81gWz31S1DPi3qvYBXgbuDoy+GRgnIqeKSCd/dv0yro+8tYRV31bX7V/XYPUdid3m9R2rYnrlos+AAp9XARcAqOqnwD+ATBH5YmDyv+L6wZ/C/V7JPp1R7WPsbBE5ArgDmKOq41T1IqAPsM+3mO7nej8GTBCRdH/gaK3YL/m/3wHOF5HhvhzlwG+B6bgzzJuBY4CN+xq7kbK0eX3vQ9xWret9jN2qdd1I7Hap67C+34n63e5IYjoxEXUmFjgjehbYKSJn+s8bgbeA0eJ0we1IHwGHqOq1UfO3duw3gGOBx1X1R4HZzlLVD/YhZktiv4Vfbz8sA3iSljf5642tqhUikqSqm4B7gAcD0zwJ/ArXtZELnOK7fvaZ7LnY3K71vQ9xW7uuW7TOftj+1nW9sdurrok6/rRjfe9L3Nau7xatsx+23/XdUcRkYhKRI0TkGeB3IjI68uWJ9Hfj7lB5AbhSRERVt+Muyqb7iq4Evq2qp6nqPp3NtTB2po9dJyLJkWa2qla203p3CuzgL6rqn1W1upVif7Y+Eap6HTDEz9NHRCaq6lLgBlW9UlXXtyD2zX7ZtYHhkS9km9R3C+O2Zl23ZJ1bq67rjd3Wde3jTBCRx4Bfi8jBkZiBJNlW9d2SuK1V3y1d5/2u744o5hKTiPQC/gT8E9iK62f9OoCq1vjJMoBZuLOKB0SkHzAe9z8OqGqNqha3c+waP11tC7vQ9jt2JH4rx671X8ouQFZgtt8A/wP+A6T7afe5j19EZgAzcRe4z/PDIhfcI8tr9frez7j7W9f7HTsSv7Vjt3FdJ4nIDbgW2Cu4/6O8Cv8Ps4H1adX6boW4La7v1oodNW38U9WYegEnAX/17zNx/7vwMnCgH/YLXAWOx/3T2y9wTd57gGSL3SaxbwFeBY7xn08BlgK/B1L3M/aJQH9gCrA2MDzZ/72xLdY7rLgdIPYNbVXXfnmXAIf69z1wB+v8wPi2qu9Q4oYdu6O+wi8ATMP9R/lp/nMu7pbMA/znHP9l+Q3QGXgiMi6wjM4Wu/1iA6OBAfsZ+3T/ORl/wAPeBm4JTNurtdY7rLgdPfb+1HUD+1pnX4ZO/vPTwBltWN/tGjfs2PHyCi+wOxj+Ddc9cAVQDJzjx90K/NG/TwKOBv4M5ATmT7LY7R57f85Y64t9lh+X5v+OAbYDveuZv0XrHVbcOIi9v62EBuMHpkkF5gAj2qO+2zJu2LHj7RVeYJgEXBv4fCHudkxw/a+vAif6z6Nwt7BmtkYFWuzYiu0/R7qSHgT+z78/pS33s7aMm8ixmxPfDzsYeMG/7wpM8O+lo8UNO3a8vdr15gcRuUhEJotIZ2Ae8Igfnoz7r/JFftKPcLdF/lFEhgEn4G5PTYXPHpFisTt+7I/8Z8E98gZVvRSYISKlwNjou8RiOW4ix97H+JG7THvgbpG+GNeKONjfkaYdIW7YseNZmz9d3H8J+uD6UeuAT4DLcLd7FolIsrrnUY3C3wnkD4IP+7vFrgMOBC5T1W0WO65id/exFVARGQTcDvwXuEpVP471uIkcez/iR+40Oxk4H6gCvqLuiQ4xHTfs2AmjLZtj7OkuGAE85t+nAHcBz0dN8whwnn/fJ7CMNIsd97Fz/d9sfNdGR4ibyLH3M35v//co4MsdJW7YsRPp1SYtJt9svRlIFpF/At3w/62sqjUicg2wQUSOU/fUXIByYLW4f/z7kohMVdVCdQ9QtNjxH/tUVV2L+62fmI6byLFbMf4pqvq/jhA37NgJqbUzHe6HrRbifrvkMtwdKlOBtQTOznAPR3zTv0/G/Tf3p8Af8Wd0Fttix1rcRI5t9R3ONk/EV+sv0D3U8cLA53t8hV0MzPPDknB9tE8Dg4ADfOUdarEtdizHTeTYVt/hbPNEfLX+At0/k3ViTz/rV4Bf+/cLgG/59/nAkxbbYnekuIkc2+o7nG2eiK9Wv11cVXeqapXuea7TScBm//5rwCgReRn32Pp50PKfJ7DYiRs7Edc57Nhhxk/kbZ6Q2irj4fpYk3DPhRrmhw3D3Ql0NJBnsS12R42byLGtvsPZ5on0ast/sK3D/XPmFuAQf0bxM6BOVd/WFjwu32Jb7BiKm8ixw4yfyNs8cbRl1sM9oqMO97DIS9oz41rsxImdiOscdmyr73C2eaK8xG/sNiEi/XHPi7pNVavaLJDFTujYibjOYccOM34ib/NE0aaJyRhjjNlX7foQV2OMMaYplpiMMcbEFEtMxhhjYoolJmOMMTHFEpMxxpiYYonJmP0kIrUiskBEFonIQhH5njTxS7AiMlhELmivMhrTkVhiMmb/7VLVcao6BvcctVOBG5qYZzBgicmYetj/MRmzn0SkXFW7BD4PBeYCPXE/gfAokOlHX62qc0TkXWAUsBqYCdwJ3ApMxj3J+m5Vvb/dVsKYGGKJyZj9FJ2Y/LBS4ECgDPcstUoRGQ78VVXzRWQy8ANVPd1PfznQS1V/ISKdgP8B56rq6vZcF2NiQZv8tLoxhsjPHqQCfxKRcbif4h7RwPRTcA8GPcd/zgKG41pUxiQUS0zGtDLflVcLFOOuNRUBY3HXdCsbmg33g3Oz2qWQxsQwu/nBmFYkIrnAfcCf1PWTZwEbVbUO9/DPZD9pGdA1MOss4EoRSfXLGSEimRiTgKzFZMz+yxCRBbhuuxrczQ63+XH3AM+JyLnAm0CFH/4hUCMiC4GHgTtwd+rN979+uhmY1j7FNya22M0PxhhjYop15RljjIkplpiMMcbEFEtMxhhjYoolJmOMMTHFEpMxxpiYYonJGGNMTLHEZIwxJqb8P2fZvjEaiskgAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_rt_pa.set_index('Date')['Cases'].plot(title=\"Casos de Covid-19 en Panamá desde 20/1/2020 hasta 29/6/2022\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "022d7b3b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}