Tasa de letalidad.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Cargamos las librerias necesarias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import datetime\n",
    "plt.rcParams[\"figure.figsize\"]=15,10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cargamos los datos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>Item</th>\n",
       "      <th>2020-03-02</th>\n",
       "      <th>2020-03-03</th>\n",
       "      <th>2020-03-04</th>\n",
       "      <th>2020-03-05</th>\n",
       "      <th>2020-03-06</th>\n",
       "      <th>2020-03-07</th>\n",
       "      <th>2020-03-08</th>\n",
       "      <th>2020-03-09</th>\n",
       "      <th>2020-03-10</th>\n",
       "      <th>...</th>\n",
       "      <th>2020-07-11</th>\n",
       "      <th>2020-07-12</th>\n",
       "      <th>2020-07-13</th>\n",
       "      <th>2020-07-14</th>\n",
       "      <th>2020-07-15</th>\n",
       "      <th>2020-07-16</th>\n",
       "      <th>2020-07-17</th>\n",
       "      <th>2020-07-18</th>\n",
       "      <th>2020-07-19</th>\n",
       "      <th>2020-07-20</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Casos nuevos con sintomas</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2219.0</td>\n",
       "      <td>2371.0</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>1444.0</td>\n",
       "      <td>1400.0</td>\n",
       "      <td>1949.0</td>\n",
       "      <td>2125.0</td>\n",
       "      <td>1624.0</td>\n",
       "      <td>1615.0</td>\n",
       "      <td>1599.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Casos totales</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>...</td>\n",
       "      <td>312029.0</td>\n",
       "      <td>315041.0</td>\n",
       "      <td>317657.0</td>\n",
       "      <td>319493.0</td>\n",
       "      <td>321205.0</td>\n",
       "      <td>323698.0</td>\n",
       "      <td>326539.0</td>\n",
       "      <td>328846.0</td>\n",
       "      <td>330930.0</td>\n",
       "      <td>333029.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Casos recuperados</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Fallecidos</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6881.0</td>\n",
       "      <td>6979.0</td>\n",
       "      <td>7024.0</td>\n",
       "      <td>7069.0</td>\n",
       "      <td>7186.0</td>\n",
       "      <td>7290.0</td>\n",
       "      <td>8347.0</td>\n",
       "      <td>8445.0</td>\n",
       "      <td>8503.0</td>\n",
       "      <td>8633.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Casos activos</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>...</td>\n",
       "      <td>24008.0</td>\n",
       "      <td>24166.0</td>\n",
       "      <td>24077.0</td>\n",
       "      <td>23205.0</td>\n",
       "      <td>21934.0</td>\n",
       "      <td>21107.0</td>\n",
       "      <td>21378.0</td>\n",
       "      <td>20952.0</td>\n",
       "      <td>20633.0</td>\n",
       "      <td>20404.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Casos nuevos sin sintomas</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>405.0</td>\n",
       "      <td>389.0</td>\n",
       "      <td>451.0</td>\n",
       "      <td>244.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>367.0</td>\n",
       "      <td>545.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>359.0</td>\n",
       "      <td>340.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Casos nuevos totales</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>2755.0</td>\n",
       "      <td>3012.0</td>\n",
       "      <td>2616.0</td>\n",
       "      <td>1836.0</td>\n",
       "      <td>1712.0</td>\n",
       "      <td>2475.0</td>\n",
       "      <td>2840.0</td>\n",
       "      <td>2185.0</td>\n",
       "      <td>2082.0</td>\n",
       "      <td>2099.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>Casos activos por FD</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>...</td>\n",
       "      <td>44263.0</td>\n",
       "      <td>43059.0</td>\n",
       "      <td>41658.0</td>\n",
       "      <td>40100.0</td>\n",
       "      <td>39162.0</td>\n",
       "      <td>39157.0</td>\n",
       "      <td>38450.0</td>\n",
       "      <td>36999.0</td>\n",
       "      <td>35398.0</td>\n",
       "      <td>34472.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Casos activos por FIS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>24008.0</td>\n",
       "      <td>24166.0</td>\n",
       "      <td>24077.0</td>\n",
       "      <td>23205.0</td>\n",
       "      <td>21934.0</td>\n",
       "      <td>21107.0</td>\n",
       "      <td>21378.0</td>\n",
       "      <td>20952.0</td>\n",
       "      <td>20633.0</td>\n",
       "      <td>20404.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Casos recuperados por FIS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>281140.0</td>\n",
       "      <td>283896.0</td>\n",
       "      <td>286556.0</td>\n",
       "      <td>289219.0</td>\n",
       "      <td>292085.0</td>\n",
       "      <td>295301.0</td>\n",
       "      <td>296814.0</td>\n",
       "      <td>299449.0</td>\n",
       "      <td>301794.0</td>\n",
       "      <td>303992.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>Casos recuperados por FD</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>260885.0</td>\n",
       "      <td>265003.0</td>\n",
       "      <td>268975.0</td>\n",
       "      <td>272324.0</td>\n",
       "      <td>274857.0</td>\n",
       "      <td>277251.0</td>\n",
       "      <td>279742.0</td>\n",
       "      <td>283402.0</td>\n",
       "      <td>287029.0</td>\n",
       "      <td>289924.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>Casos confirmados recuperados</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>280161.0</td>\n",
       "      <td>283902.0</td>\n",
       "      <td>286556.0</td>\n",
       "      <td>289220.0</td>\n",
       "      <td>292085.0</td>\n",
       "      <td>295301.0</td>\n",
       "      <td>296814.0</td>\n",
       "      <td>299449.0</td>\n",
       "      <td>301794.0</td>\n",
       "      <td>303992.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>Casos activos confirmados</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>24008.0</td>\n",
       "      <td>24166.0</td>\n",
       "      <td>24077.0</td>\n",
       "      <td>23205.0</td>\n",
       "      <td>21934.0</td>\n",
       "      <td>21107.0</td>\n",
       "      <td>21378.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>Casos probables acumulados</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>38090.0</td>\n",
       "      <td>38724.0</td>\n",
       "      <td>39038.0</td>\n",
       "      <td>39219.0</td>\n",
       "      <td>39270.0</td>\n",
       "      <td>38833.0</td>\n",
       "      <td>40056.0</td>\n",
       "      <td>39477.0</td>\n",
       "      <td>38695.0</td>\n",
       "      <td>38294.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>Casos activos probables</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>6609.0</td>\n",
       "      <td>6637.0</td>\n",
       "      <td>6321.0</td>\n",
       "      <td>5800.0</td>\n",
       "      <td>5601.0</td>\n",
       "      <td>5390.0</td>\n",
       "      <td>4922.0</td>\n",
       "      <td>4227.0</td>\n",
       "      <td>3487.0</td>\n",
       "      <td>2743.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>Casos nuevos sin notificar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>188.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>160.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16 rows × 142 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Item  2020-03-02  2020-03-03  2020-03-04  \\\n",
       "0       Casos nuevos con sintomas         1.0         0.0         2.0   \n",
       "1                   Casos totales         1.0         1.0         3.0   \n",
       "2               Casos recuperados         0.0         0.0         0.0   \n",
       "3                      Fallecidos         0.0         0.0         0.0   \n",
       "4                   Casos activos         1.0         1.0         3.0   \n",
       "5       Casos nuevos sin sintomas         NaN         NaN         NaN   \n",
       "6            Casos nuevos totales         1.0         0.0         2.0   \n",
       "7            Casos activos por FD         1.0         1.0         3.0   \n",
       "8           Casos activos por FIS         NaN         NaN         NaN   \n",
       "9       Casos recuperados por FIS         NaN         NaN         NaN   \n",
       "10       Casos recuperados por FD         0.0         0.0         0.0   \n",
       "11  Casos confirmados recuperados         NaN         NaN         NaN   \n",
       "12      Casos activos confirmados         NaN         NaN         NaN   \n",
       "13     Casos probables acumulados         NaN         NaN         NaN   \n",
       "14        Casos activos probables         NaN         NaN         NaN   \n",
       "15     Casos nuevos sin notificar         NaN         NaN         NaN   \n",
       "\n",
       "    2020-03-05  2020-03-06  2020-03-07  2020-03-08  2020-03-09  2020-03-10  \\\n",
       "0          1.0         1.0         2.0         3.0         5.0         2.0   \n",
       "1          4.0         5.0         7.0        10.0        15.0        17.0   \n",
       "2          0.0         0.0         0.0         0.0         0.0         0.0   \n",
       "3          0.0         0.0         0.0         0.0         0.0         0.0   \n",
       "4          4.0         5.0         7.0        10.0        15.0        17.0   \n",
       "5          NaN         NaN         NaN         NaN         NaN         NaN   \n",
       "6          1.0         1.0         2.0         3.0         5.0         2.0   \n",
       "7          4.0         5.0         7.0        10.0        15.0        17.0   \n",
       "8          NaN         NaN         NaN         NaN         NaN         NaN   \n",
       "9          NaN         NaN         NaN         NaN         NaN         NaN   \n",
       "10         0.0         0.0         0.0         0.0         0.0         0.0   \n",
       "11         NaN         NaN         NaN         NaN         NaN         NaN   \n",
       "12         NaN         NaN         NaN         NaN         NaN         NaN   \n",
       "13         NaN         NaN         NaN         NaN         NaN         NaN   \n",
       "14         NaN         NaN         NaN         NaN         NaN         NaN   \n",
       "15         NaN         NaN         NaN         NaN         NaN         NaN   \n",
       "\n",
       "    ...  2020-07-11  2020-07-12  2020-07-13  2020-07-14  2020-07-15  \\\n",
       "0   ...      2219.0      2371.0      1985.0      1444.0      1400.0   \n",
       "1   ...    312029.0    315041.0    317657.0    319493.0    321205.0   \n",
       "2   ...         NaN         NaN         NaN         NaN         NaN   \n",
       "3   ...      6881.0      6979.0      7024.0      7069.0      7186.0   \n",
       "4   ...     24008.0     24166.0     24077.0     23205.0     21934.0   \n",
       "5   ...       405.0       389.0       451.0       244.0       186.0   \n",
       "6   ...      2755.0      3012.0      2616.0      1836.0      1712.0   \n",
       "7   ...     44263.0     43059.0     41658.0     40100.0     39162.0   \n",
       "8   ...     24008.0     24166.0     24077.0     23205.0     21934.0   \n",
       "9   ...    281140.0    283896.0    286556.0    289219.0    292085.0   \n",
       "10  ...    260885.0    265003.0    268975.0    272324.0    274857.0   \n",
       "11  ...    280161.0    283902.0    286556.0    289220.0    292085.0   \n",
       "12  ...     24008.0     24166.0     24077.0     23205.0     21934.0   \n",
       "13  ...     38090.0     38724.0     39038.0     39219.0     39270.0   \n",
       "14  ...      6609.0      6637.0      6321.0      5800.0      5601.0   \n",
       "15  ...         NaN         NaN         NaN         NaN         NaN   \n",
       "\n",
       "    2020-07-16  2020-07-17  2020-07-18  2020-07-19  2020-07-20  \n",
       "0       1949.0      2125.0      1624.0      1615.0      1599.0  \n",
       "1     323698.0    326539.0    328846.0    330930.0    333029.0  \n",
       "2          NaN         NaN         NaN         NaN         NaN  \n",
       "3       7290.0      8347.0      8445.0      8503.0      8633.0  \n",
       "4      21107.0     21378.0     20952.0     20633.0     20404.0  \n",
       "5        367.0       545.0       373.0       359.0       340.0  \n",
       "6       2475.0      2840.0      2185.0      2082.0      2099.0  \n",
       "7      39157.0     38450.0     36999.0     35398.0     34472.0  \n",
       "8      21107.0     21378.0     20952.0     20633.0     20404.0  \n",
       "9     295301.0    296814.0    299449.0    301794.0    303992.0  \n",
       "10    277251.0    279742.0    283402.0    287029.0    289924.0  \n",
       "11    295301.0    296814.0    299449.0    301794.0    303992.0  \n",
       "12     21107.0     21378.0         NaN         NaN         NaN  \n",
       "13     38833.0     40056.0     39477.0     38695.0     38294.0  \n",
       "14      5390.0      4922.0      4227.0      3487.0      2743.0  \n",
       "15         NaN         NaN       188.0       108.0       160.0  \n",
       "\n",
       "[16 rows x 142 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url  = \"https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto5/TotalesNacionales.csv\"\n",
    "data = pd.read_csv(url, error_bad_lines=False)\n",
    "data = data.rename(columns={\"Fecha\": \"Item\"}) #Le cambiamos el nombre a la columna\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "fallecidos  = data[data[\"Item\"]==\"Fallecidos\"].values.tolist()[0][1:]\n",
    "contagiados = data[data[\"Item\"]==\"Casos totales\"].values.tolist()[0][1:]\n",
    "df_letalidad = pd.DataFrame({\n",
    "    'fecha': data.columns[1:],\n",
    "    'contagiados': contagiados,\n",
    "    'fallecidos': fallecidos\n",
    "})\n",
    "df_letalidad[\"letalidad\"] = (df_letalidad[\"fallecidos\"] / df_letalidad[\"contagiados\"]) * 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def labelonbars(X, Y):\n",
    "    n       = len(X)\n",
    "    aux = 0\n",
    "    for i in range (n):\n",
    "        if float(Y[i]) == 0.0 :\n",
    "            number = \"0\"\n",
    "        else:\n",
    "            number = '{0:.1f}'.format(float(Y[i])).replace(',', '.')\n",
    "            \n",
    "        if aux == 1:    \n",
    "            plt.annotate(\n",
    "                number, xy=(X[i], Y[i]),\n",
    "                xytext =(0, 10),\n",
    "                textcoords=\"offset points\",\n",
    "                ha ='center', va='bottom',\n",
    "                size='10')\n",
    "            aux = 0\n",
    "        else: \n",
    "            aux = 1\n",
    "        \n",
    "        \n",
    "\n",
    "Y            = df_letalidad[\"letalidad\"].values.tolist()\n",
    "X            = data.columns[1:]\n",
    "plt.figure(figsize=(20, 10), dpi=80)\n",
    "plt.subplot(1, 1, 1)\n",
    "plt.plot(X, Y, 'ro-')\n",
    "labelonbars(X, Y)\n",
    "plt.xlabel('Fecha')\n",
    "plt.ylabel('Letalidad')\n",
    "plt.title('Tasa de letalidad')\n",
    "plt.grid()\n",
    "plt.xticks(X, rotation='vertical')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tasa de letalidad por regiones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Region</th>\n",
       "      <th>Arica y Parinacota</th>\n",
       "      <th>Tarapacá</th>\n",
       "      <th>Antofagasta</th>\n",
       "      <th>Atacama</th>\n",
       "      <th>Coquimbo</th>\n",
       "      <th>Valparaíso</th>\n",
       "      <th>Metropolitana</th>\n",
       "      <th>O’Higgins</th>\n",
       "      <th>Maule</th>\n",
       "      <th>Ñuble</th>\n",
       "      <th>Biobío</th>\n",
       "      <th>Araucanía</th>\n",
       "      <th>Los Ríos</th>\n",
       "      <th>Los Lagos</th>\n",
       "      <th>Aysén</th>\n",
       "      <th>Magallanes</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2020-03-05</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>2020-03-06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>2020-03-07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>135</td>\n",
       "      <td>2020-07-16</td>\n",
       "      <td>2840.0</td>\n",
       "      <td>7353.0</td>\n",
       "      <td>12500.0</td>\n",
       "      <td>1734.0</td>\n",
       "      <td>4361.0</td>\n",
       "      <td>15068.0</td>\n",
       "      <td>242572.0</td>\n",
       "      <td>8987.0</td>\n",
       "      <td>7462.0</td>\n",
       "      <td>3080.0</td>\n",
       "      <td>8994.0</td>\n",
       "      <td>3666.0</td>\n",
       "      <td>796.0</td>\n",
       "      <td>2564.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>1589.0</td>\n",
       "      <td>323698.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>136</td>\n",
       "      <td>2020-07-17</td>\n",
       "      <td>2936.0</td>\n",
       "      <td>7451.0</td>\n",
       "      <td>12716.0</td>\n",
       "      <td>1736.0</td>\n",
       "      <td>4486.0</td>\n",
       "      <td>15261.0</td>\n",
       "      <td>244073.0</td>\n",
       "      <td>9163.0</td>\n",
       "      <td>7603.0</td>\n",
       "      <td>3095.0</td>\n",
       "      <td>9150.0</td>\n",
       "      <td>3687.0</td>\n",
       "      <td>820.0</td>\n",
       "      <td>2629.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1592.0</td>\n",
       "      <td>326539.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>137</td>\n",
       "      <td>2020-07-18</td>\n",
       "      <td>3012.0</td>\n",
       "      <td>7557.0</td>\n",
       "      <td>12907.0</td>\n",
       "      <td>1817.0</td>\n",
       "      <td>4634.0</td>\n",
       "      <td>15406.0</td>\n",
       "      <td>245161.0</td>\n",
       "      <td>9249.0</td>\n",
       "      <td>7683.0</td>\n",
       "      <td>3193.0</td>\n",
       "      <td>9300.0</td>\n",
       "      <td>3702.0</td>\n",
       "      <td>825.0</td>\n",
       "      <td>2662.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1600.0</td>\n",
       "      <td>328846.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>138</td>\n",
       "      <td>2020-07-19</td>\n",
       "      <td>3056.0</td>\n",
       "      <td>7627.0</td>\n",
       "      <td>13109.0</td>\n",
       "      <td>1857.0</td>\n",
       "      <td>4792.0</td>\n",
       "      <td>15589.0</td>\n",
       "      <td>245983.0</td>\n",
       "      <td>9366.0</td>\n",
       "      <td>7817.0</td>\n",
       "      <td>3222.0</td>\n",
       "      <td>9441.0</td>\n",
       "      <td>3724.0</td>\n",
       "      <td>833.0</td>\n",
       "      <td>2761.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1606.0</td>\n",
       "      <td>330930.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>139</td>\n",
       "      <td>2020-07-20</td>\n",
       "      <td>3188.0</td>\n",
       "      <td>7761.0</td>\n",
       "      <td>13226.0</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>4918.0</td>\n",
       "      <td>15771.0</td>\n",
       "      <td>246946.0</td>\n",
       "      <td>9472.0</td>\n",
       "      <td>7884.0</td>\n",
       "      <td>3250.0</td>\n",
       "      <td>9591.0</td>\n",
       "      <td>3747.0</td>\n",
       "      <td>843.0</td>\n",
       "      <td>2785.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1609.0</td>\n",
       "      <td>333029.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>140 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Region  Arica y Parinacota  Tarapacá  Antofagasta  Atacama  Coquimbo  \\\n",
       "0    2020-03-03                 0.0       0.0          0.0      0.0       0.0   \n",
       "1    2020-03-04                 0.0       0.0          0.0      0.0       0.0   \n",
       "2    2020-03-05                 0.0       0.0          0.0      0.0       0.0   \n",
       "3    2020-03-06                 0.0       0.0          0.0      0.0       0.0   \n",
       "4    2020-03-07                 0.0       0.0          0.0      0.0       0.0   \n",
       "..          ...                 ...       ...          ...      ...       ...   \n",
       "135  2020-07-16              2840.0    7353.0      12500.0   1734.0    4361.0   \n",
       "136  2020-07-17              2936.0    7451.0      12716.0   1736.0    4486.0   \n",
       "137  2020-07-18              3012.0    7557.0      12907.0   1817.0    4634.0   \n",
       "138  2020-07-19              3056.0    7627.0      13109.0   1857.0    4792.0   \n",
       "139  2020-07-20              3188.0    7761.0      13226.0   1895.0    4918.0   \n",
       "\n",
       "     Valparaíso  Metropolitana  O’Higgins   Maule   Ñuble  Biobío  Araucanía  \\\n",
       "0           0.0            0.0        0.0     1.0     0.0     0.0        0.0   \n",
       "1           0.0            1.0        0.0     2.0     0.0     0.0        0.0   \n",
       "2           0.0            2.0        0.0     2.0     0.0     0.0        0.0   \n",
       "3           0.0            3.0        0.0     2.0     0.0     0.0        0.0   \n",
       "4           0.0            4.0        0.0     2.0     0.0     0.0        0.0   \n",
       "..          ...            ...        ...     ...     ...     ...        ...   \n",
       "135     15068.0       242572.0     8987.0  7462.0  3080.0  8994.0     3666.0   \n",
       "136     15261.0       244073.0     9163.0  7603.0  3095.0  9150.0     3687.0   \n",
       "137     15406.0       245161.0     9249.0  7683.0  3193.0  9300.0     3702.0   \n",
       "138     15589.0       245983.0     9366.0  7817.0  3222.0  9441.0     3724.0   \n",
       "139     15771.0       246946.0     9472.0  7884.0  3250.0  9591.0     3747.0   \n",
       "\n",
       "     Los Ríos  Los Lagos  Aysén  Magallanes     Total  \n",
       "0         0.0        0.0    0.0         0.0       1.0  \n",
       "1         0.0        0.0    0.0         0.0       3.0  \n",
       "2         0.0        0.0    0.0         0.0       4.0  \n",
       "3         0.0        0.0    0.0         0.0       5.0  \n",
       "4         0.0        1.0    0.0         0.0       7.0  \n",
       "..        ...        ...    ...         ...       ...  \n",
       "135     796.0     2564.0   61.0      1589.0  323698.0  \n",
       "136     820.0     2629.0   69.0      1592.0  326539.0  \n",
       "137     825.0     2662.0   69.0      1600.0  328846.0  \n",
       "138     833.0     2761.0   69.0      1606.0  330930.0  \n",
       "139     843.0     2785.0   69.0      1609.0  333029.0  \n",
       "\n",
       "[140 rows x 18 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url_region  = \"https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto3/CasosTotalesCumulativo_T.csv\"\n",
    "data_region = pd.read_csv(url_region)\n",
    "data_region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "date = str(datetime.date.today())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "contagiados_total_region = data_region[data_region[\"Region\"]== date].values.tolist()[0][1:]\n",
    "regiones = data_region.columns.tolist()[1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_letalidad_regiones = pd.DataFrame({\n",
    "    'Region': regiones,\n",
    "    'contagiados': contagiados_total_region\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_fallecidos_region  = \"https://raw.githubusercontent.com/MinCiencia/Datos-COVID19/master/output/producto14/FallecidosCumulativo_T.csv\"\n",
    "data_fallecidos_region = pd.read_csv(url_fallecidos_region)\n",
    "data_fallecidos_region = data_fallecidos_region.rename(columns={'Region':'Fecha'})\n",
    "data_fallecidos_region\n",
    "fallecidos_region = data_fallecidos_region[data_fallecidos_region[\"Fecha\"]==date].values.tolist()[0][1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_letalidad_regiones[\"Fallecidos\"] = fallecidos_region"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Region</th>\n",
       "      <th>contagiados</th>\n",
       "      <th>Fallecidos</th>\n",
       "      <th>Letalidad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>Arica y Parinacota</td>\n",
       "      <td>3188.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1.254705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>Tarapacá</td>\n",
       "      <td>7761.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>1.855431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>Antofagasta</td>\n",
       "      <td>13226.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>2.215333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>Atacama</td>\n",
       "      <td>1895.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.474934</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>Coquimbo</td>\n",
       "      <td>4918.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1.098007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>Valparaíso</td>\n",
       "      <td>15771.0</td>\n",
       "      <td>427.0</td>\n",
       "      <td>2.707501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>Metropolitana</td>\n",
       "      <td>246946.0</td>\n",
       "      <td>7053.0</td>\n",
       "      <td>2.856090</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>O’Higgins</td>\n",
       "      <td>9472.0</td>\n",
       "      <td>183.0</td>\n",
       "      <td>1.932010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>Maule</td>\n",
       "      <td>7884.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>1.661593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>Ñuble</td>\n",
       "      <td>3250.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1.661538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>10</td>\n",
       "      <td>Biobío</td>\n",
       "      <td>9591.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>1.032218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>11</td>\n",
       "      <td>Araucanía</td>\n",
       "      <td>3747.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>1.894849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>12</td>\n",
       "      <td>Los Ríos</td>\n",
       "      <td>843.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.542112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>13</td>\n",
       "      <td>Los Lagos</td>\n",
       "      <td>2785.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1.149013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>14</td>\n",
       "      <td>Aysén</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.449275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>15</td>\n",
       "      <td>Magallanes</td>\n",
       "      <td>1609.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>1.740211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>16</td>\n",
       "      <td>Total</td>\n",
       "      <td>333029.0</td>\n",
       "      <td>8633.0</td>\n",
       "      <td>2.592267</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Region  contagiados  Fallecidos  Letalidad\n",
       "0   Arica y Parinacota       3188.0        40.0   1.254705\n",
       "1             Tarapacá       7761.0       144.0   1.855431\n",
       "2          Antofagasta      13226.0       293.0   2.215333\n",
       "3              Atacama       1895.0         9.0   0.474934\n",
       "4             Coquimbo       4918.0        54.0   1.098007\n",
       "5           Valparaíso      15771.0       427.0   2.707501\n",
       "6        Metropolitana     246946.0      7053.0   2.856090\n",
       "7            O’Higgins       9472.0       183.0   1.932010\n",
       "8                Maule       7884.0       131.0   1.661593\n",
       "9                Ñuble       3250.0        54.0   1.661538\n",
       "10              Biobío       9591.0        99.0   1.032218\n",
       "11           Araucanía       3747.0        71.0   1.894849\n",
       "12            Los Ríos        843.0        13.0   1.542112\n",
       "13           Los Lagos       2785.0        32.0   1.149013\n",
       "14               Aysén         69.0         1.0   1.449275\n",
       "15          Magallanes       1609.0        28.0   1.740211\n",
       "16               Total     333029.0      8633.0   2.592267"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_letalidad_regiones[\"Letalidad\"] = (df_letalidad_regiones[\"Fallecidos\"]/df_letalidad_regiones[\"contagiados\"]) * 100\n",
    "df_letalidad_regiones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = regiones\n",
    "Y = df_letalidad_regiones[\"Letalidad\"].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def labelonbars(X, Y):\n",
    "    n       = len(X)\n",
    "    aux = 0\n",
    "    for i in range (n):\n",
    "        number = '{0:.1f}'.format(float(Y[i])).replace(',', '.')\n",
    "        plt.annotate(\n",
    "                number, xy=(X[i], Y[i]),\n",
    "                xytext =(0, 1),\n",
    "                textcoords=\"offset points\",\n",
    "                ha ='center', va='bottom',\n",
    "                size='10')    \n",
    "            \n",
    "plt.figure(figsize=(15, 10), dpi=80)\n",
    "plt.bar(X, Y, color='#C41515')\n",
    "plt.title(\"Tasa de letalidad\")\n",
    "labelonbars(X, Y)\n",
    "plt.xticks(X, rotation='vertical')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}