ad4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1d4674c0",
   "metadata": {},
   "source": [
    "# AD4: Conexión con la  API del Covid y análisis con Pandas "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "523c5a5d",
   "metadata": {},
   "source": [
    "Esta es la actividad dirigia 4, aquí mostramos las diversas tablas o gráficos con las cifras del Covid-19 tras un análisis de un sitio web que mantiene actualizados los datos desde el inicio de la pandemia. Esta actividad la realizamos con el Pandas."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "589778c7",
   "metadata": {},
   "source": [
    "Me conecto a la API: [Covid19api](https://api.covid19api.com/)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "307775c7",
   "metadata": {},
   "source": [
    "## Instalación de Pandas "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4fd868e0",
   "metadata": {},
   "source": [
    "Para poder comenzar con este proceso de análisis de los datos instalaremos pandas. Luego haremos lo mismo con el numpy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "84562c39",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pandas in c:\\users\\rcarranza\\anaconda3\\lib\\site-packages (1.4.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\rcarranza\\anaconda3\\lib\\site-packages (from pandas) (2021.3)\n",
      "Requirement already satisfied: numpy>=1.18.5 in c:\\users\\rcarranza\\anaconda3\\lib\\site-packages (from pandas) (1.21.5)\n",
      "Requirement already satisfied: python-dateutil>=2.8.1 in c:\\users\\rcarranza\\anaconda3\\lib\\site-packages (from pandas) (2.8.2)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\rcarranza\\anaconda3\\lib\\site-packages (from python-dateutil>=2.8.1->pandas) (1.16.0)\n"
     ]
    }
   ],
   "source": [
    "!pip install pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a18b7595",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: numpy in c:\\users\\rcarranza\\anaconda3\\lib\\site-packages (1.21.5)Note: you may need to restart the kernel to use updated packages.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "pip install numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ddc7d0dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: pd in c:\\users\\rcarranza\\anaconda3\\lib\\site-packages (0.0.4)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b3dd534",
   "metadata": {},
   "source": [
    "## Importar Pandas "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18afafe5",
   "metadata": {},
   "source": [
    "Procedemos a importar Pandas a pd, con esta acción esperamos que la nomeclatura al momento de establecer un código de ejecución sea más práctica."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9f56f923",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4114809e",
   "metadata": {},
   "source": [
    "## Selección de ciudades con Covid-19 "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "560ad4a8",
   "metadata": {},
   "source": [
    "Seleccionaremos el sitio Web de API, las ciudades con Covid19."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dd6d1cb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'https://api.covid19api.com/countries'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "63a65cdf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'https://api.covid19api.com/countries'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a76506a",
   "metadata": {},
   "source": [
    "## Marco de Datos "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e6aee03",
   "metadata": {},
   "source": [
    " A través de Pandas llamaremos para visualización de los datos de las ciudades con el comando: **df = pd.read_json(url)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8b8ec56c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_json(url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "536bb75a",
   "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",
       "      <td>mali</td>\n",
       "      <td>ML</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <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": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7122cab",
   "metadata": {},
   "source": [
    "# Visualización de Datos "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9970c1b",
   "metadata": {},
   "source": [
    "Se mostrará la visualización de los datos, los resultados de países como *España y Panamá*. Luego se podrá ver gráficos y ver el desarrollo del virus, al mismo tiempo que una comparación de estos dos países. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b1f7be9",
   "metadata": {},
   "source": [
    "### Datos de España "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d594758",
   "metadata": {},
   "source": [
    "Comenzamos con data frame de este país y luego conocer la posición y posteriormente mediante la url procedemos a hacer el llamado de los datos desde el primer día de la pandemia hasta la fecha actual. Se hará con: **df[df['País'] == 'España']**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e8f29852",
   "metadata": {},
   "outputs": [
    {
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       "    <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",
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      "text/plain": [
       "    Country   Slug ISO2\n",
       "141   Spain  spain   ES"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Country'] == 'Spain']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "819aca4b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <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",
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       "      <th>Date</th>\n",
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       "    <tr>\n",
       "      <th>0</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>2020-01-22 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</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>2020-01-23 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <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",
       "    </tr>\n",
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       "      <th>...</th>\n",
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       "      <td>...</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",
       "    <tr>\n",
       "      <th>898</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>12973615</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-08 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     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",
       "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",
       "898   Spain          ES                         40.46 -3.75  12973615   \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 2022-07-08 00:00:00+00:00  \n",
       "\n",
       "[899 rows x 10 columns]"
      ]
     },
     "execution_count": 16,
     "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": "markdown",
   "id": "76399167",
   "metadata": {},
   "source": [
    "**Ahora**, aplicaremos un data frame para mostrar la cabecera de los resultados en España"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1bfe4c20",
   "metadata": {},
   "outputs": [
    {
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       "<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>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>2020-01-22 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</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>2020-01-23 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <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",
       "    </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": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rt_es.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "483b9471",
   "metadata": {},
   "source": [
    "**En esta oportunidad con otro data frame vizualizaremos la parte final de la tabla**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "8687d2a7",
   "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>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",
       "    <tr>\n",
       "      <th>898</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>12973615</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-08 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   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",
       "898   Spain          ES                         40.46 -3.75  12973615   \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 2022-07-08 00:00:00+00:00  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rt_es.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1570cdaf",
   "metadata": {},
   "source": [
    "## Gráfica de los datos "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9338761",
   "metadata": {},
   "source": [
    " Mediante el comando **casos_es.plot()** plotearemos los datos para que se visualicen los resultados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "c13a2ce4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Matplotlib is building the font cache; this may take a moment.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Casos de Covid-19 en España'}, xlabel='Date'>"
      ]
     },
     "execution_count": 19,
     "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": [
    "casos_es = df_rt_es.set_index('Date')['Cases']\n",
    "casos_es.plot(title=\"Casos de Covid-19 en España\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f31d3f9",
   "metadata": {},
   "source": [
    "## Datos de Panamá "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb77f3e4",
   "metadata": {},
   "source": [
    "En esta ocasión realizamos la creación de un data frame de la ciudad para conocer su posición. Posteriormente se hizo la selección de los datos a través de la **url** de **API**. Además, se creó otro data frame para hacer el llamado través de Pandas de la información del **url**. Por último se procederá a vizualizar el gráfico para conocer el compromiso del virus desde el día 1 a la actualidad. \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f6545b0",
   "metadata": {},
   "source": [
    "### Conoceremos la posición de Panamá "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "e9b86172",
   "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": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Country'] == 'Panama'] "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12eb948e",
   "metadata": {},
   "source": [
    "### Datos a través de la url de API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5b057ddd",
   "metadata": {},
   "outputs": [],
   "source": [
    "url_casos_pa = 'https://api.covid19api.com/country/panama/status/confirmed/live'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a969d0d",
   "metadata": {},
   "source": [
    " ### Data frame para hacer el llamado a través de Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "11f12844",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_rt_pa = pd.read_json(url_casos_pa)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5b78fb6d",
   "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>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>932710</td>\n",
       "      <td>confirmed</td>\n",
       "      <td>2022-07-08 00:00:00+00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>899</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>900 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",
       "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  932710   \n",
       "899  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",
       "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 2022-07-08 00:00:00+00:00  \n",
       "899  confirmed 2022-07-09 00:00:00+00:00  \n",
       "\n",
       "[900 rows x 10 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_rt_pa"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd59fc23",
   "metadata": {},
   "source": [
    "### Visualizar el Gráfico"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "ae67f9b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Casos de Covid19 en Panamá'}, xlabel='Date'>"
      ]
     },
     "execution_count": 24,
     "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": [
    "casos_pa = df_rt_pa.set_index('Date')['Cases']\n",
    "casos_pa.plot(title=\"Casos de Covid19 en Panamá\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d418500c",
   "metadata": {},
   "source": [
    "# Ploteamos a los países de España y Panamá "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "239e33ab",
   "metadata": {},
   "source": [
    "Hicimos la comparación de los casos de **España y panamá**, se plotearon y se mostró la gráfica comparativa sobre el comportamiento del virus cuando comenzó la pandemia."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "65864780",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Cases</th>\n",
       "      <th>Cases</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
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       "      <th>2022-07-08 00:00:00+00:00</th>\n",
       "      <td>12973615.0</td>\n",
       "      <td>932710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-09 00:00:00+00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>925254</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>900 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Cases   Cases\n",
       "Date                                         \n",
       "2020-01-22 00:00:00+00:00         0.0       0\n",
       "2020-01-23 00:00:00+00:00         0.0       0\n",
       "2020-01-24 00:00:00+00:00         0.0       0\n",
       "2020-01-25 00:00:00+00:00         0.0       0\n",
       "2020-01-26 00:00:00+00:00         0.0       0\n",
       "...                               ...     ...\n",
       "2022-07-05 00:00:00+00:00  12890002.0  925254\n",
       "2022-07-06 00:00:00+00:00  12890002.0  925254\n",
       "2022-07-07 00:00:00+00:00  12890002.0  925254\n",
       "2022-07-08 00:00:00+00:00  12973615.0  932710\n",
       "2022-07-09 00:00:00+00:00         NaN  925254\n",
       "\n",
       "[900 rows x 2 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pa_vs_es = pd.concat([casos_es,casos_pa],axis=1)\n",
    "pa_vs_es"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1488334c",
   "metadata": {},
   "source": [
    "Ahora se procede a identificar cada columna para saber los resultados de cada país, porque en la tabla superior sólo se apreció la variable de casos.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "2f03ca5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-09 00:00:00+00:00</th>\n",
       "      <td>NaN</td>\n",
       "      <td>925254</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>900 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               España  Panamá\n",
       "Date                                         \n",
       "2020-01-22 00:00:00+00:00         0.0       0\n",
       "2020-01-23 00:00:00+00:00         0.0       0\n",
       "2020-01-24 00:00:00+00:00         0.0       0\n",
       "2020-01-25 00:00:00+00:00         0.0       0\n",
       "2020-01-26 00:00:00+00:00         0.0       0\n",
       "...                               ...     ...\n",
       "2022-07-05 00:00:00+00:00  12890002.0  925254\n",
       "2022-07-06 00:00:00+00:00  12890002.0  925254\n",
       "2022-07-07 00:00:00+00:00  12890002.0  925254\n",
       "2022-07-08 00:00:00+00:00  12973615.0  932710\n",
       "2022-07-09 00:00:00+00:00         NaN  925254\n",
       "\n",
       "[900 rows x 2 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pa_vs_es.columns = ['España', 'Panamá']\n",
    "pa_vs_es"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38dfb674",
   "metadata": {},
   "source": [
    "## Comparación de Gráficos "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "15a1a720",
   "metadata": {},
   "source": [
    "Realizamos la comparativa en la que se muestra el comportamiento del virus en ambos países y se hizo con el comando: **pa_vs_es.plot()**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "418db490",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Comparativa Covid19 España-Paanamá'}, xlabel='Date'>"
      ]
     },
     "execution_count": 27,
     "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": [
    "pa_vs_es.plot(title=\"Comparativa Covid19 España-Paanamá\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60bbbf9f",
   "metadata": {},
   "source": [
    "## Comparación de Países Centroamericanos "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ffdc4a2",
   "metadata": {},
   "source": [
    "Se hizo una comparación del compromiso del **virus Covid19**, en los países Centroamericanos y lo hicimos tal cual realizamos con _**España y Panamá**_."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6aaf721d",
   "metadata": {},
   "source": [
    "### Honduras "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "f849503c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Casos de Covid19 en Honduras'}, xlabel='Date'>"
      ]
     },
     "execution_count": 28,
     "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": [
    "url_casos_hnd = 'https://api.covid19api.com/country/honduras/status/confirmed/live'\n",
    "df_rt_hnd = pd.read_json(url_casos_hnd)\n",
    "casos_hnd = df_rt_hnd.set_index('Date')['Cases']\n",
    "casos_hnd.plot(title=\"Casos de Covid19 en Honduras\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea60bb8f",
   "metadata": {},
   "source": [
    "## Costa Rica "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5c9c601c",
   "metadata": {},
   "outputs": [],
   "source": [
    "url_casos_cr = 'https://api.covid19api.com/country/costa-rica/status/confirmed/live'\n",
    "df_rt_cr = pd.read_json(url_casos_cr)\n",
    "casos_cr = df_rt_cr.set_index('Date')['Cases']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "9715a0e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Casos de Covid19 en Costa Rica'}, xlabel='Date'>"
      ]
     },
     "execution_count": 31,
     "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": [
    "casos_cr.plot(title=\"Casos de Covid19 en Costa Rica\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dcaeec44",
   "metadata": {},
   "source": [
    "## Nicaragua "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "02583e12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Casos de Covid19 en Nicaraguas'}, xlabel='Date'>"
      ]
     },
     "execution_count": 32,
     "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": [
    "url_casos_ni = 'https://api.covid19api.com/country/nicaragua/status/confirmed/live'\n",
    "df_rt_ni = pd.read_json(url_casos_ni)\n",
    "casos_ni = df_rt_ni.set_index('Date')['Cases']\n",
    "casos_ni.plot(title=\"Casos de Covid19 en Nicaraguas\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd4b5be0",
   "metadata": {},
   "source": [
    "## El Salvador "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "4b4523fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Casos de Covid19 en El Salvador'}, xlabel='Date'>"
      ]
     },
     "execution_count": 33,
     "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": [
    "url_casos_elsalv = 'https://api.covid19api.com/country/el-salvador/status/confirmed/live'\n",
    "df_rt_elsalv = pd.read_json(url_casos_elsalv)\n",
    "casos_elsalv = df_rt_elsalv.set_index('Date')['Cases']\n",
    "casos_elsalv.plot(title=\"Casos de Covid19 en El Salvador\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef7af040",
   "metadata": {},
   "source": [
    "# Gráficos de Comparación de países Centroamericanos "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "dc929994",
   "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>Cases</th>\n",
       "      <th>Cases</th>\n",
       "      <th>Cases</th>\n",
       "      <th>Cases</th>\n",
       "      <th>Cases</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-22 00:00:00+00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-23 00:00:00+00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-24 00:00:00+00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-25 00:00:00+00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-26 00:00:00+00:00</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-05 00:00:00+00:00</th>\n",
       "      <td>925254</td>\n",
       "      <td>904934</td>\n",
       "      <td>427718</td>\n",
       "      <td>169646</td>\n",
       "      <td>14690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-06 00:00:00+00:00</th>\n",
       "      <td>925254</td>\n",
       "      <td>904934</td>\n",
       "      <td>427718</td>\n",
       "      <td>169646</td>\n",
       "      <td>14721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-07 00:00:00+00:00</th>\n",
       "      <td>925254</td>\n",
       "      <td>904934</td>\n",
       "      <td>427718</td>\n",
       "      <td>169646</td>\n",
       "      <td>14721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-08 00:00:00+00:00</th>\n",
       "      <td>932710</td>\n",
       "      <td>904934</td>\n",
       "      <td>429408</td>\n",
       "      <td>180970</td>\n",
       "      <td>14721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-09 00:00:00+00:00</th>\n",
       "      <td>925254</td>\n",
       "      <td>904934</td>\n",
       "      <td>429408</td>\n",
       "      <td>169646</td>\n",
       "      <td>14721</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>900 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Cases   Cases   Cases   Cases  Cases\n",
       "Date                                                            \n",
       "2020-01-22 00:00:00+00:00       0       0       0       0      0\n",
       "2020-01-23 00:00:00+00:00       0       0       0       0      0\n",
       "2020-01-24 00:00:00+00:00       0       0       0       0      0\n",
       "2020-01-25 00:00:00+00:00       0       0       0       0      0\n",
       "2020-01-26 00:00:00+00:00       0       0       0       0      0\n",
       "...                           ...     ...     ...     ...    ...\n",
       "2022-07-05 00:00:00+00:00  925254  904934  427718  169646  14690\n",
       "2022-07-06 00:00:00+00:00  925254  904934  427718  169646  14721\n",
       "2022-07-07 00:00:00+00:00  925254  904934  427718  169646  14721\n",
       "2022-07-08 00:00:00+00:00  932710  904934  429408  180970  14721\n",
       "2022-07-09 00:00:00+00:00  925254  904934  429408  169646  14721\n",
       "\n",
       "[900 rows x 5 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ca = pd.concat([casos_pa,casos_cr,casos_hnd,casos_elsalv,casos_ni],axis=1)\n",
    "df_ca\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "788fcd21",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Panamá</th>\n",
       "      <th>Costa Rica</th>\n",
       "      <th>Honduras</th>\n",
       "      <th>El Salvador</th>\n",
       "      <th>Nicaragua</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>2020-01-23 00:00:00+00:00</th>\n",
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       "    <tr>\n",
       "      <th>2020-01-25 00:00:00+00:00</th>\n",
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       "      <th>2020-01-26 00:00:00+00:00</th>\n",
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       "      <th>2022-07-05 00:00:00+00:00</th>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-06 00:00:00+00:00</th>\n",
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       "      <td>904934</td>\n",
       "      <td>427718</td>\n",
       "      <td>169646</td>\n",
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       "    <tr>\n",
       "      <th>2022-07-07 00:00:00+00:00</th>\n",
       "      <td>925254</td>\n",
       "      <td>904934</td>\n",
       "      <td>427718</td>\n",
       "      <td>169646</td>\n",
       "      <td>14721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-08 00:00:00+00:00</th>\n",
       "      <td>932710</td>\n",
       "      <td>904934</td>\n",
       "      <td>429408</td>\n",
       "      <td>180970</td>\n",
       "      <td>14721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-07-09 00:00:00+00:00</th>\n",
       "      <td>925254</td>\n",
       "      <td>904934</td>\n",
       "      <td>429408</td>\n",
       "      <td>169646</td>\n",
       "      <td>14721</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>900 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                           Panamá  Costa Rica  Honduras  El Salvador  \\\n",
       "Date                                                                   \n",
       "2020-01-22 00:00:00+00:00       0           0         0            0   \n",
       "2020-01-23 00:00:00+00:00       0           0         0            0   \n",
       "2020-01-24 00:00:00+00:00       0           0         0            0   \n",
       "2020-01-25 00:00:00+00:00       0           0         0            0   \n",
       "2020-01-26 00:00:00+00:00       0           0         0            0   \n",
       "...                           ...         ...       ...          ...   \n",
       "2022-07-05 00:00:00+00:00  925254      904934    427718       169646   \n",
       "2022-07-06 00:00:00+00:00  925254      904934    427718       169646   \n",
       "2022-07-07 00:00:00+00:00  925254      904934    427718       169646   \n",
       "2022-07-08 00:00:00+00:00  932710      904934    429408       180970   \n",
       "2022-07-09 00:00:00+00:00  925254      904934    429408       169646   \n",
       "\n",
       "                           Nicaragua  \n",
       "Date                                  \n",
       "2020-01-22 00:00:00+00:00          0  \n",
       "2020-01-23 00:00:00+00:00          0  \n",
       "2020-01-24 00:00:00+00:00          0  \n",
       "2020-01-25 00:00:00+00:00          0  \n",
       "2020-01-26 00:00:00+00:00          0  \n",
       "...                              ...  \n",
       "2022-07-05 00:00:00+00:00      14690  \n",
       "2022-07-06 00:00:00+00:00      14721  \n",
       "2022-07-07 00:00:00+00:00      14721  \n",
       "2022-07-08 00:00:00+00:00      14721  \n",
       "2022-07-09 00:00:00+00:00      14721  \n",
       "\n",
       "[900 rows x 5 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ca.columns = ['Panamá','Costa Rica','Honduras','El Salvador','Nicaragua']\n",
    "df_ca"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d4825673",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'Comparativa Covid19 de países Centroamericanos'}, xlabel='Date'>"
      ]
     },
     "execution_count": 43,
     "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_ca.plot(title=\"Comparativa Covid19 de países Centroamericanos\", logy=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7a57bbd4",
   "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
}