procesar-base-de-datos.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "233220b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pandas.io import sql\n",
    "from sqlalchemy import create_engine"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c2071540",
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_file(path):\n",
    "    pd.read_csv(path, sep=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6c0ea3e",
   "metadata": {},
   "source": [
    "## Importando los archivos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "da61baa1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_eficacia = pd.read_csv('./datasets/eficacia.csv', sep=',')\n",
    "df_edad = pd.read_csv('./datasets/edad.csv', sep=',')\n",
    "df_paises = pd.read_csv('./datasets/paises.csv', sep=',')\n",
    "df_vacunas = pd.read_csv('./datasets/vacunas.csv', sep=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b169660",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "\n",
    "\n",
    "## Explorando eficacia\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8d07e497",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "vaccine                        object\n",
       "efficacy_disease_alpha        float64\n",
       "efficacy_infection_alpha      float64\n",
       "efficacy_disease_bgd          float64\n",
       "efficacy_infection_bgd        float64\n",
       "efficacy_disease_omicron      float64\n",
       "efficacy_infection_omicron    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_eficacia.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1916e499",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(12, 7)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_eficacia.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dfc6c128",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vaccine</th>\n",
       "      <th>efficacy_disease_alpha</th>\n",
       "      <th>efficacy_infection_alpha</th>\n",
       "      <th>efficacy_disease_bgd</th>\n",
       "      <th>efficacy_infection_bgd</th>\n",
       "      <th>efficacy_disease_omicron</th>\n",
       "      <th>efficacy_infection_omicron</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>astra_zeneca</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.69</td>\n",
       "      <td>0.71</td>\n",
       "      <td>0.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>cansino</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.61</td>\n",
       "      <td>0.48</td>\n",
       "      <td>0.32</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        vaccine  efficacy_disease_alpha  efficacy_infection_alpha  \\\n",
       "0  astra_zeneca                    0.94                      0.63   \n",
       "1       cansino                    0.66                      0.62   \n",
       "\n",
       "   efficacy_disease_bgd  efficacy_infection_bgd  efficacy_disease_omicron  \\\n",
       "0                  0.94                    0.69                      0.71   \n",
       "1                  0.64                    0.61                      0.48   \n",
       "\n",
       "   efficacy_infection_omicron  \n",
       "0                        0.36  \n",
       "1                        0.32  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_eficacia.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb90b60d",
   "metadata": {},
   "source": [
    "## Explorando edad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "bdeff4ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "location                                object\n",
       "date                                    object\n",
       "age_group                               object\n",
       "people_vaccinated_per_hundred          float64\n",
       "people_fully_vaccinated_per_hundred    float64\n",
       "people_with_booster_per_hundred        float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_edad.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a40cc1ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(232, 6)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_edad.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bc8da60a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>location</th>\n",
       "      <th>date</th>\n",
       "      <th>age_group</th>\n",
       "      <th>people_vaccinated_per_hundred</th>\n",
       "      <th>people_fully_vaccinated_per_hundred</th>\n",
       "      <th>people_with_booster_per_hundred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Austria</td>\n",
       "      <td>07/12/2021</td>\n",
       "      <td>0-4</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Austria</td>\n",
       "      <td>07/12/2021</td>\n",
       "      <td>5</td>\n",
       "      <td>36.61</td>\n",
       "      <td>24.16</td>\n",
       "      <td>0.28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  location        date age_group  people_vaccinated_per_hundred  \\\n",
       "0  Austria  07/12/2021       0-4                           0.19   \n",
       "1  Austria  07/12/2021         5                          36.61   \n",
       "\n",
       "   people_fully_vaccinated_per_hundred  people_with_booster_per_hundred  \n",
       "0                                 0.05                             0.00  \n",
       "1                                24.16                             0.28  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_edad.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "359bf1bf",
   "metadata": {},
   "source": [
    "## Explorando países"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "43d50726",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "code                         object\n",
       "continent                    object\n",
       "country                      object\n",
       "date                         object\n",
       "total_cases_per_million     float64\n",
       "total_deaths_per_million    float64\n",
       "population_density          float64\n",
       "cardiovasc_death_rate       float64\n",
       "diabetes_prevalence         float64\n",
       "life_expectancy             float64\n",
       "hdi                         float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_paises.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "464d8395",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(196, 11)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_paises.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4953116c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>code</th>\n",
       "      <th>continent</th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>total_cases_per_million</th>\n",
       "      <th>total_deaths_per_million</th>\n",
       "      <th>population_density</th>\n",
       "      <th>cardiovasc_death_rate</th>\n",
       "      <th>diabetes_prevalence</th>\n",
       "      <th>life_expectancy</th>\n",
       "      <th>hdi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Asia</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>09/12/2021</td>\n",
       "      <td>3955.901</td>\n",
       "      <td>183.781</td>\n",
       "      <td>54.422</td>\n",
       "      <td>597.029</td>\n",
       "      <td>9.59</td>\n",
       "      <td>64.83</td>\n",
       "      <td>0.511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ALB</td>\n",
       "      <td>Europe</td>\n",
       "      <td>Albania</td>\n",
       "      <td>09/12/2021</td>\n",
       "      <td>70611.786</td>\n",
       "      <td>1088.782</td>\n",
       "      <td>104.871</td>\n",
       "      <td>304.195</td>\n",
       "      <td>10.08</td>\n",
       "      <td>78.57</td>\n",
       "      <td>0.795</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  code continent      country        date  total_cases_per_million  \\\n",
       "0  AFG      Asia  Afghanistan  09/12/2021                 3955.901   \n",
       "1  ALB    Europe      Albania  09/12/2021                70611.786   \n",
       "\n",
       "   total_deaths_per_million  population_density  cardiovasc_death_rate  \\\n",
       "0                   183.781              54.422                597.029   \n",
       "1                  1088.782             104.871                304.195   \n",
       "\n",
       "   diabetes_prevalence  life_expectancy    hdi  \n",
       "0                 9.59            64.83  0.511  \n",
       "1                10.08            78.57  0.795  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_paises.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cd03560",
   "metadata": {},
   "source": [
    "## Explorando vacunas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0cc8bacc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country         object\n",
       "continent       object\n",
       "code            object\n",
       "date            object\n",
       "pfizer           int64\n",
       "moderna          int64\n",
       "aztra_zeneca     int64\n",
       "johnson          int64\n",
       "sputnik          int64\n",
       "sinovac          int64\n",
       "sinopharm        int64\n",
       "cansino          int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_vacunas.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "ef7fc202",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(41, 12)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_vacunas.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2e4e098e",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>continent</th>\n",
       "      <th>code</th>\n",
       "      <th>date</th>\n",
       "      <th>pfizer</th>\n",
       "      <th>moderna</th>\n",
       "      <th>aztra_zeneca</th>\n",
       "      <th>johnson</th>\n",
       "      <th>sputnik</th>\n",
       "      <th>sinovac</th>\n",
       "      <th>sinopharm</th>\n",
       "      <th>cansino</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Czechia</td>\n",
       "      <td>Europe</td>\n",
       "      <td>CZE</td>\n",
       "      <td>09/12/2021</td>\n",
       "      <td>11769212</td>\n",
       "      <td>1178342</td>\n",
       "      <td>884369</td>\n",
       "      <td>399057</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>European Union</td>\n",
       "      <td>Europe</td>\n",
       "      <td>EU</td>\n",
       "      <td>09/12/2021</td>\n",
       "      <td>474558136</td>\n",
       "      <td>70560744</td>\n",
       "      <td>67256712</td>\n",
       "      <td>17652060</td>\n",
       "      <td>1845077</td>\n",
       "      <td>9</td>\n",
       "      <td>2201503</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "          country continent code        date     pfizer   moderna  \\\n",
       "0         Czechia    Europe  CZE  09/12/2021   11769212   1178342   \n",
       "1  European Union    Europe   EU  09/12/2021  474558136  70560744   \n",
       "\n",
       "   aztra_zeneca   johnson  sputnik  sinovac  sinopharm  cansino  \n",
       "0        884369    399057        0        0          0        0  \n",
       "1      67256712  17652060  1845077        9    2201503        0  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_vacunas.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "27b454df",
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Czechia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>European Union</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Hong Kong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Italy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Latvia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>South Korea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Ukraine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Uruguay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>Chile</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>Iceland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>Romania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>Switzerland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>Austria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>Belgium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>Bulgaria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>Croatia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>Denmark</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>Finland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>Ireland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>Luxembourg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>Netherlands</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>Peru</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>Poland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>Slovakia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>Sweden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>Cyprus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>Estonia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>Hungary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>Liechtenstein</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>Lithuania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>Malta</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>Norway</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>Portugal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>Slovenia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>Ecuador</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>Spain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>40</td>\n",
       "      <td>Mexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    id         country\n",
       "0    1         Czechia\n",
       "1    2  European Union\n",
       "2    3       Hong Kong\n",
       "3    4           Italy\n",
       "4    5          Latvia\n",
       "5    6     South Korea\n",
       "6    7         Ukraine\n",
       "7    8   United States\n",
       "8    9         Uruguay\n",
       "9   10           Chile\n",
       "10  11          France\n",
       "11  12         Germany\n",
       "12  13         Iceland\n",
       "13  14         Romania\n",
       "14  15     Switzerland\n",
       "15  16         Austria\n",
       "16  17         Belgium\n",
       "17  18        Bulgaria\n",
       "18  19         Croatia\n",
       "19  20         Denmark\n",
       "20  21         Finland\n",
       "21  22         Ireland\n",
       "22  23      Luxembourg\n",
       "23  24     Netherlands\n",
       "24  25            Peru\n",
       "25  26          Poland\n",
       "26  27        Slovakia\n",
       "27  28          Sweden\n",
       "28  29          Cyprus\n",
       "29  30         Estonia\n",
       "30  31         Hungary\n",
       "31  32   Liechtenstein\n",
       "32  33       Lithuania\n",
       "33  34           Malta\n",
       "34  35          Norway\n",
       "35  36        Portugal\n",
       "36  37        Slovenia\n",
       "37  38         Ecuador\n",
       "38  39           Spain\n",
       "39  40          Mexico\n",
       "40  41           Japan"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_catalogo_paises = {\n",
    "    'id': range(1, len(df_vacunas) + 1),\n",
    "    'country': df_vacunas['country'].unique(),\n",
    "}\n",
    "df_catalogo_paises = pd.DataFrame(df_catalogo_paises)\n",
    "df_catalogo_paises.set_index('id', drop=True)\n",
    "df_catalogo_paises"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a923db25",
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'MySQLdb'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Input \u001b[0;32mIn [14]\u001b[0m, in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mio\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m sql\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01msqlalchemy\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m create_engine\n\u001b[0;32m----> 3\u001b[0m engine \u001b[38;5;241m=\u001b[39m \u001b[43mcreate_engine\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mmysql://root:root@localhost/covid\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m engine\u001b[38;5;241m.\u001b[39mconnect() \u001b[38;5;28;01mas\u001b[39;00m conn, conn\u001b[38;5;241m.\u001b[39mbegin():\n\u001b[1;32m      5\u001b[0m     df\u001b[38;5;241m.\u001b[39mto_sql(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcountries\u001b[39m\u001b[38;5;124m'\u001b[39m, conn, if_exists\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mreplace\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "File \u001b[0;32m<string>:2\u001b[0m, in \u001b[0;36mcreate_engine\u001b[0;34m(url, **kwargs)\u001b[0m\n",
      "File \u001b[0;32m/opt/conda/lib/python3.9/site-packages/sqlalchemy/util/deprecations.py:309\u001b[0m, in \u001b[0;36mdeprecated_params.<locals>.decorate.<locals>.warned\u001b[0;34m(fn, *args, **kwargs)\u001b[0m\n\u001b[1;32m    302\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m m \u001b[38;5;129;01min\u001b[39;00m kwargs:\n\u001b[1;32m    303\u001b[0m         _warn_with_version(\n\u001b[1;32m    304\u001b[0m             messages[m],\n\u001b[1;32m    305\u001b[0m             versions[m],\n\u001b[1;32m    306\u001b[0m             version_warnings[m],\n\u001b[1;32m    307\u001b[0m             stacklevel\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m,\n\u001b[1;32m    308\u001b[0m         )\n\u001b[0;32m--> 309\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/opt/conda/lib/python3.9/site-packages/sqlalchemy/engine/create.py:560\u001b[0m, in \u001b[0;36mcreate_engine\u001b[0;34m(url, **kwargs)\u001b[0m\n\u001b[1;32m    558\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m k \u001b[38;5;129;01min\u001b[39;00m kwargs:\n\u001b[1;32m    559\u001b[0m             dbapi_args[k] \u001b[38;5;241m=\u001b[39m pop_kwarg(k)\n\u001b[0;32m--> 560\u001b[0m     dbapi \u001b[38;5;241m=\u001b[39m \u001b[43mdialect_cls\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdbapi\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdbapi_args\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    562\u001b[0m dialect_args[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdbapi\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m dbapi\n\u001b[1;32m    564\u001b[0m dialect_args\u001b[38;5;241m.\u001b[39msetdefault(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcompiler_linting\u001b[39m\u001b[38;5;124m\"\u001b[39m, compiler\u001b[38;5;241m.\u001b[39mNO_LINTING)\n",
      "File \u001b[0;32m/opt/conda/lib/python3.9/site-packages/sqlalchemy/dialects/mysql/mysqldb.py:163\u001b[0m, in \u001b[0;36mMySQLDialect_mysqldb.dbapi\u001b[0;34m(cls)\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m    162\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdbapi\u001b[39m(\u001b[38;5;28mcls\u001b[39m):\n\u001b[0;32m--> 163\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43m__import__\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mMySQLdb\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'MySQLdb'"
     ]
    }
   ],
   "source": [
    "engine = create_engine('mysql://root:root@localhost/covid')\n",
    "with engine.connect() as conn, conn.begin():\n",
    "    df.to_sql('countries', conn, if_exists='replace')"
   ]
  }
 ],
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