{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "cb11a41f-fee7-42cb-93b1-85dcb4cdc480",
   "metadata": {},
   "source": [
    "#### Ejemplo 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "165f1734-d5b5-4b5b-9c4b-9824e260aba3",
   "metadata": {},
   "source": [
    "#### Vamos a hacer un ejemplo en pandas de un EDA bastante sencillo pero con fines educativos.\n",
    "\n",
    "#### Vamos a leer un csv directamente desde una URL de GitHub que contiene información geográfica básica de los países del mundo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "b0e7fc67-c0ec-4f4d-a1e2-6023bf94c3f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import statsmodels.api as sm\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "030d66e0-9c7a-4f5a-a6fd-75ed32f29e34",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  alpha_2 alpha_3      area           capital continent currency_code  \\\n",
      "0      AD     AND     468.0  Andorra la Vella        EU           EUR   \n",
      "1      AE     ARE   82880.0         Abu Dhabi        AS           AED   \n",
      "2      AF     AFG  647500.0             Kabul        AS           AFN   \n",
      "3      AG     ATG     443.0        St. John's       NaN           XCD   \n",
      "4      AI     AIA     102.0        The Valley       NaN           XCD   \n",
      "\n",
      "  currency_name eqivalent_fips_code fips  geoname_id          languages  \\\n",
      "0          Euro                 NaN   AN     3041565                 ca   \n",
      "1        Dirham                 NaN   AE      290557  ar-AE,fa,en,hi,ur   \n",
      "2       Afghani                 NaN   AF     1149361  fa-AF,ps,uz-AF,tk   \n",
      "3        Dollar                 NaN   AC     3576396              en-AG   \n",
      "4        Dollar                 NaN   AV     3573511              en-AI   \n",
      "\n",
      "                   name         neighbours  numeric   phone  population  \\\n",
      "0               Andorra              ES,FR       20     376       84000   \n",
      "1  United Arab Emirates              SA,OM      784     971     4975593   \n",
      "2           Afghanistan  TM,CN,IR,TJ,PK,UZ        4      93    29121286   \n",
      "3   Antigua and Barbuda                NaN       28  +1-268       86754   \n",
      "4              Anguilla                NaN      660  +1-264       13254   \n",
      "\n",
      "  postal_code_format postal_code_regex  tld  \n",
      "0              AD###  ^(?:AD)*(\\d{3})$  .ad  \n",
      "1                NaN               NaN  .ae  \n",
      "2                NaN               NaN  .af  \n",
      "3                NaN               NaN  .ag  \n",
      "4                NaN               NaN  .ai  \n"
     ]
    }
   ],
   "source": [
    "url = 'https://raw.githubusercontent.com/lorey/list-of-countries/master/csv/countries.csv'\n",
    "df = pd.read_csv(url, sep=\";\")\n",
    "print(df.head(5))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f783392-39c7-4849-981c-77becc0d30b0",
   "metadata": {},
   "source": [
    "##### Veamos cantidad de los datos básicos que nos brinda pandas:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "abcdb04a-6a73-44f1-9035-41c254ca0301",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cantidad de Filas y columnas: (252, 19)\n"
     ]
    }
   ],
   "source": [
    "print('Cantidad de Filas y columnas:',df.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2924f5f2-eb8c-4acb-b0a9-9e0d24130958",
   "metadata": {},
   "source": [
    "##### Nombre de columnas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "c8048cbc-266f-4f49-8540-7fc8b247b254",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nombre columnas: Index(['alpha_2', 'alpha_3', 'area', 'capital', 'continent', 'currency_code',\n",
      "       'currency_name', 'eqivalent_fips_code', 'fips', 'geoname_id',\n",
      "       'languages', 'name', 'neighbours', 'numeric', 'phone', 'population',\n",
      "       'postal_code_format', 'postal_code_regex', 'tld'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print('Nombre columnas:',df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "61c88ff8-128f-401c-83ee-e0a98a6cf515",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  alpha_2 alpha_3      area           capital continent currency_code  \\\n",
      "0      AD     AND     468.0  Andorra la Vella        EU           EUR   \n",
      "1      AE     ARE   82880.0         Abu Dhabi        AS           AED   \n",
      "2      AF     AFG  647500.0             Kabul        AS           AFN   \n",
      "3      AG     ATG     443.0        St. John's       NaN           XCD   \n",
      "4      AI     AIA     102.0        The Valley       NaN           XCD   \n",
      "\n",
      "  currency_name eqivalent_fips_code fips  geoname_id          languages  \\\n",
      "0          Euro                 NaN   AN     3041565                 ca   \n",
      "1        Dirham                 NaN   AE      290557  ar-AE,fa,en,hi,ur   \n",
      "2       Afghani                 NaN   AF     1149361  fa-AF,ps,uz-AF,tk   \n",
      "3        Dollar                 NaN   AC     3576396              en-AG   \n",
      "4        Dollar                 NaN   AV     3573511              en-AI   \n",
      "\n",
      "                   name         neighbours  numeric   phone  population  \\\n",
      "0               Andorra              ES,FR       20     376       84000   \n",
      "1  United Arab Emirates              SA,OM      784     971     4975593   \n",
      "2           Afghanistan  TM,CN,IR,TJ,PK,UZ        4      93    29121286   \n",
      "3   Antigua and Barbuda                NaN       28  +1-268       86754   \n",
      "4              Anguilla                NaN      660  +1-264       13254   \n",
      "\n",
      "  postal_code_format postal_code_regex  tld  \n",
      "0              AD###  ^(?:AD)*(\\d{3})$  .ad  \n",
      "1                NaN               NaN  .ae  \n",
      "2                NaN               NaN  .af  \n",
      "3                NaN               NaN  .ag  \n",
      "4                NaN               NaN  .ai  \n"
     ]
    }
   ],
   "source": [
    "df1 = pd.read_csv(\"datos/countri.csv\",sep=\";\")\n",
    "print(df1.head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "e532b949-eb67-40c0-a9ec-495b04891080",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cantidad de Filas y columnas: (252, 19)\n",
      "Nombre columnas: Index(['alpha_2', 'alpha_3', 'area', 'capital', 'continent', 'currency_code',\n",
      "       'currency_name', 'eqivalent_fips_code', 'fips', 'geoname_id',\n",
      "       'languages', 'name', 'neighbours', 'numeric', 'phone', 'population',\n",
      "       'postal_code_format', 'postal_code_regex', 'tld'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print('Cantidad de Filas y columnas:',df1.shape)\n",
    "print('Nombre columnas:',df1.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acabc41b-ad89-4c8f-8819-c18a75e0626e",
   "metadata": {},
   "source": [
    "##### Columnas, nulos y tipo de datos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "53ab711c-079d-4417-98ab-93e5c2293d80",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 252 entries, 0 to 251\n",
      "Data columns (total 19 columns):\n",
      " #   Column               Non-Null Count  Dtype  \n",
      "---  ------               --------------  -----  \n",
      " 0   alpha_2              251 non-null    object \n",
      " 1   alpha_3              252 non-null    object \n",
      " 2   area                 252 non-null    float64\n",
      " 3   capital              246 non-null    object \n",
      " 4   continent            210 non-null    object \n",
      " 5   currency_code        251 non-null    object \n",
      " 6   currency_name        251 non-null    object \n",
      " 7   eqivalent_fips_code  1 non-null      object \n",
      " 8   fips                 249 non-null    object \n",
      " 9   geoname_id           252 non-null    int64  \n",
      " 10  languages            249 non-null    object \n",
      " 11  name                 252 non-null    object \n",
      " 12  neighbours           165 non-null    object \n",
      " 13  numeric              252 non-null    int64  \n",
      " 14  phone                247 non-null    object \n",
      " 15  population           252 non-null    int64  \n",
      " 16  postal_code_format   154 non-null    object \n",
      " 17  postal_code_regex    152 non-null    object \n",
      " 18  tld                  250 non-null    object \n",
      "dtypes: float64(1), int64(3), object(15)\n",
      "memory usage: 37.5+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56e8aa6c-29b1-4a46-aea4-71ac98d764a0",
   "metadata": {},
   "source": [
    "##### Descripción estadística de los datos numéricos\n",
    "##### Pandas filtra las features numéricas y calcula datos estadísticos que pueden ser útiles: cantidad, media, desvío estándar, valores máximo y mínimo."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "8d809d3b-e768-445e-8910-bf011d775cc2",
   "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>area</th>\n",
       "      <th>geoname_id</th>\n",
       "      <th>numeric</th>\n",
       "      <th>population</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2.520000e+02</td>\n",
       "      <td>2.520000e+02</td>\n",
       "      <td>252.000000</td>\n",
       "      <td>2.520000e+02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>5.952879e+05</td>\n",
       "      <td>2.427870e+06</td>\n",
       "      <td>434.309524</td>\n",
       "      <td>2.727679e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.904818e+06</td>\n",
       "      <td>1.632093e+06</td>\n",
       "      <td>254.663139</td>\n",
       "      <td>1.164127e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>4.951800e+04</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.098000e+03</td>\n",
       "      <td>1.163774e+06</td>\n",
       "      <td>217.000000</td>\n",
       "      <td>1.879528e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>6.489450e+04</td>\n",
       "      <td>2.367967e+06</td>\n",
       "      <td>436.000000</td>\n",
       "      <td>4.268583e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.622245e+05</td>\n",
       "      <td>3.478296e+06</td>\n",
       "      <td>652.500000</td>\n",
       "      <td>1.536688e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.710000e+07</td>\n",
       "      <td>8.505033e+06</td>\n",
       "      <td>894.000000</td>\n",
       "      <td>1.330044e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               area    geoname_id     numeric    population\n",
       "count  2.520000e+02  2.520000e+02  252.000000  2.520000e+02\n",
       "mean   5.952879e+05  2.427870e+06  434.309524  2.727679e+07\n",
       "std    1.904818e+06  1.632093e+06  254.663139  1.164127e+08\n",
       "min    0.000000e+00  4.951800e+04    0.000000  0.000000e+00\n",
       "25%    1.098000e+03  1.163774e+06  217.000000  1.879528e+05\n",
       "50%    6.489450e+04  2.367967e+06  436.000000  4.268583e+06\n",
       "75%    3.622245e+05  3.478296e+06  652.500000  1.536688e+07\n",
       "max    1.710000e+07  8.505033e+06  894.000000  1.330044e+09"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ca5e848-661b-4cf0-96a6-11104fad61ca",
   "metadata": {},
   "source": [
    "##### Verifiquemos si hay correlación entre los datos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "b35daff8-1118-4a0d-bc78-bca70b745e72",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corr = df.set_index('alpha_3').select_dtypes(include=['number']).corr()\n",
    "sm.graphics.plot_corr(corr, xnames=list(corr.columns))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "daf9acd4-af23-4dd2-8b67-87824f71ed3f",
   "metadata": {},
   "source": [
    "##### En este caso vemos baja correlación entre las variables. Dependiendo del algoritmo que utilicemos podría ser una buena decisión eliminar features que tuvieran alta correlación"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07c273c7-1421-4c8c-8447-863b686189c1",
   "metadata": {},
   "source": [
    "##### Cargamos un segundo archivo csv para ahondar en el crecimiento de la población en los últimos años, filtramos a España y visualizamos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "13f858a2-c09e-4682-a667-529368c9e728",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       country  year  population\n",
      "0  Afghanistan  1952     8425333\n",
      "1  Afghanistan  1957     9240934\n",
      "2  Afghanistan  1962    10267083\n",
      "3  Afghanistan  1967    11537966\n",
      "4  Afghanistan  1972    13079460\n"
     ]
    }
   ],
   "source": [
    "df1 = pd.read_csv(\"datos/countri2.csv\")\n",
    "print(df1.head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "3ffa2044-685b-43ce-8234-2aa538a41423",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "       country  year  population\n",
      "0  Afghanistan  1952     8425333\n",
      "1  Afghanistan  1957     9240934\n",
      "2  Afghanistan  1962    10267083\n",
      "3  Afghanistan  1967    11537966\n",
      "4  Afghanistan  1972    13079460\n"
     ]
    }
   ],
   "source": [
    "url = 'https://raw.githubusercontent.com/DrueStaples/Population_Growth/master/countries.csv'\n",
    "df_pop = pd.read_csv(url)\n",
    "print(df_pop.head(5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "de9d812e-0bc6-4d1c-868f-a14da55c5f46",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     country  year  population\n",
      "1416   Spain  1952    28549870\n",
      "1417   Spain  1957    29841614\n",
      "1418   Spain  1962    31158061\n",
      "1419   Spain  1967    32850275\n",
      "1420   Spain  1972    34513161\n"
     ]
    }
   ],
   "source": [
    "df_pop_es = df_pop[df_pop[\"country\"] == 'Spain' ]\n",
    "print(df_pop_es.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "5cde23d3-0165-42de-8dc8-69e6f67f8819",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     country  year  population\n",
      "1416   Spain  1952    28549870\n",
      "1417   Spain  1957    29841614\n",
      "1418   Spain  1962    31158061\n",
      "1419   Spain  1967    32850275\n",
      "1420   Spain  1972    34513161\n"
     ]
    }
   ],
   "source": [
    "df_pop_es.drop(['country'],axis=1)\n",
    "print(df_pop_es.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "c79052a1-adc2-47d7-a44b-7da5cb2a0881",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     country  year  population\n",
      "1416   Spain  1952    28549870\n",
      "1417   Spain  1957    29841614\n",
      "1418   Spain  1962    31158061\n",
      "1419   Spain  1967    32850275\n",
      "1420   Spain  1972    34513161\n"
     ]
    },
    {
     "data": {
      "image/png": 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ARLiQLtN81TPPPKM///nP+uCDD5qdl5ycrOTk5MB6WlqaKisrtWTJkiYv7bjdbrnd7pZGAwAADtKiMyPPPvusNm3apB07dmjAgAEh7z9hwgQdOXKkJYcGAABtTEhnRowxevbZZ7Vx40YVFxcrKSmpRQctKyuTx+Np0b4AAKBtCamMzJ8/X7/97W/1H//xH+revbuqq6slSbGxserSpYuka/d7VFVVae3atZKkgoICDR48WCkpKaqvr9e6devk9Xrl9XrD/FQAAIAThVRGli9fLkm69957g8bXrFmjxx9/XJLk8/lUUVER2FZfX6+cnBxVVVWpS5cuSklJ0ebNm5WVlXVryQEAQJsQ8mWaGykqKgpaz83NVW5ubkihAABA+8F30wAAAKsoIwAAwCrKCAAAsIoyAgAArKKMAAAAqygjAADAKsoIAACwijICAACsoowAAACrKCMAAMAqyggAALCKMgIAAKyijAAAAKsoIwAAwCrKCAAAsIoyAgAArKKMAAAAqygjAADAKsoIAACwijICAACsoowAAACrKCMAAMAqyggAALCKMgIAAKyijAAAAKsoIwAAwCrKCAAAsIoyAgAArKKMAAAAqygjAADAKsoIAACwijICAACsCqmM5Ofn684771T37t3Vr18/ffe739Xhw4dvuN/OnTuVmpqqzp07a8iQIVqxYkWLAwMAgLYlpDKyc+dOzZ8/X3v27NH27dt1+fJlZWRkqK6ursl9jh07pqysLKWnp6usrEwLFy7UggUL5PV6bzk8AABwvuhQJm/dujVofc2aNerXr59KS0s1adKkRvdZsWKFBg4cqIKCAknSiBEjVFJSoiVLlmjGjBktSw0AANqMW7pnpKamRpLUq1evJufs3r1bGRkZQWNTp05VSUmJLl261Og+fr9ftbW1QQsAAGibWlxGjDHKzs7WPffco1GjRjU5r7q6WnFxcUFjcXFxunz5ss6cOdPoPvn5+YqNjQ0siYmJLY0JAAAiXIvLyDPPPKM///nPeuONN2441+VyBa0bYxodvy4vL081NTWBpbKysqUxAQBAhAvpnpHrnn32WW3atEm7du3SgAEDmp0bHx+v6urqoLHTp08rOjpavXv3bnQft9stt9vdkmgAAMBhQjozYozRM888ow0bNui9995TUlLSDfdJS0vT9u3bg8a2bdum8ePHq2PHjqGlBQAAbU5IZWT+/Plat26dfvvb36p79+6qrq5WdXW1vvzyy8CcvLw8zZo1K7A+b948nThxQtnZ2Tp48KBWr16twsJC5eTkhO9ZAAAAxwqpjCxfvlw1NTW699575fF4Asubb74ZmOPz+VRRURFYT0pK0pYtW1RcXKyxY8fqZz/7mZYuXcrbegEAgKQQ7xm5fuNpc4qKihqMTZ48Wfv27QvlUAAAoJ3gu2kAAIBVlBEAAGAVZQQAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVlBEAAGAVZQQAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVlBEAAGAVZQQAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVSGXkV27dmn69OlKSEiQy+XS22+/3ez84uJiuVyuBsuhQ4damhkAALQh0aHuUFdXpzFjxmjOnDmaMWPGTe93+PBhxcTEBNb79u0b6qEBAEAbFHIZyczMVGZmZsgH6tevn3r06HFTc/1+v/x+f2C9trY25OMBAABnaLV7RsaNGyePx6MpU6Zox44dzc7Nz89XbGxsYElMTGyllAAAoLV97WXE4/Fo5cqV8nq92rBhg5KTkzVlyhTt2rWryX3y8vJUU1MTWCorK7/umAAAwJKQL9OEKjk5WcnJyYH1tLQ0VVZWasmSJZo0aVKj+7jdbrnd7q87GgAAiABW3to7YcIEHTlyxMahAQBAhLFSRsrKyuTxeGwcGgAARJiQL9NcvHhRR48eDawfO3ZM5eXl6tWrlwYOHKi8vDxVVVVp7dq1kqSCggINHjxYKSkpqq+v17p16+T1euX1esP3LAAAgGOFXEZKSkp03333Bdazs7MlSbNnz1ZRUZF8Pp8qKioC2+vr65WTk6Oqqip16dJFKSkp2rx5s7KyssIQHwAAOF3IZeTee++VMabJ7UVFRUHrubm5ys3NDTkYAABoH/huGgAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVlBEAAGAVZQQAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVlBEAAGAVZQQAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVIZeRXbt2afr06UpISJDL5dLbb799w3127typ1NRUde7cWUOGDNGKFStakhUAALRBIZeRuro6jRkzRsuWLbup+ceOHVNWVpbS09NVVlamhQsXasGCBfJ6vSGHBQAAbU90qDtkZmYqMzPzpuevWLFCAwcOVEFBgSRpxIgRKikp0ZIlSzRjxoxQDw8AANqYr/2ekd27dysjIyNobOrUqSopKdGlS5ca3cfv96u2tjZoAQAAbdPXXkaqq6sVFxcXNBYXF6fLly/rzJkzje6Tn5+v2NjYwJKYmPh1xwQAAJa0yrtpXC5X0LoxptHx6/Ly8lRTUxNYKisrv/aMAADAjpDvGQlVfHy8qqurg8ZOnz6t6Oho9e7du9F93G633G731x0NAABEgK/9zEhaWpq2b98eNLZt2zaNHz9eHTt2/LoPDwAAIlzIZeTixYsqLy9XeXm5pGtv3S0vL1dFRYWka5dYZs2aFZg/b948nThxQtnZ2Tp48KBWr16twsJC5eTkhOcZAAAARwv5Mk1JSYnuu+++wHp2drYkafbs2SoqKpLP5wsUE0lKSkrSli1b9Pzzz+v1119XQkKCli5dytt6AQCApBaUkXvvvTdwA2pjioqKGoxNnjxZ+/btC/VQAACgHeC7aQAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVlBEAAGAVZQQAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVlBEAAGAVZQQAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVLSojv/rVr5SUlKTOnTsrNTVV77//fpNzi4uL5XK5GiyHDh1qcWgAANB2hFxG3nzzTT333HNatGiRysrKlJ6erszMTFVUVDS73+HDh+Xz+QLLsGHDWhwaAAC0HSGXkZ///OeaO3eunnzySY0YMUIFBQVKTEzU8uXLm92vX79+io+PDyxRUVFNzvX7/aqtrQ1aAABA2xRSGamvr1dpaakyMjKCxjMyMvTRRx81u++4cePk8Xg0ZcoU7dixo9m5+fn5io2NDSyJiYmhxAQAAA4SUhk5c+aMrly5ori4uKDxuLg4VVdXN7qPx+PRypUr5fV6tWHDBiUnJ2vKlCnatWtXk8fJy8tTTU1NYKmsrAwlJgAAcJDoluzkcrmC1o0xDcauS05OVnJycmA9LS1NlZWVWrJkiSZNmtToPm63W263uyXRAACAw4R0ZqRPnz6KiopqcBbk9OnTDc6WNGfChAk6cuRIKIcGAABtVEhlpFOnTkpNTdX27duDxrdv366JEyfe9OOUlZXJ4/GEcmgAANBGhXyZJjs7WzNnztT48eOVlpamlStXqqKiQvPmzZN07X6PqqoqrV27VpJUUFCgwYMHKyUlRfX19Vq3bp28Xq+8Xm94nwkAAHCkkMvII488orNnz+qll16Sz+fTqFGjtGXLFg0aNEiS5PP5gj5zpL6+Xjk5OaqqqlKXLl2UkpKizZs3KysrK3zPAgAAOFaLbmD94Q9/qB/+8IeNbisqKgpaz83NVW5ubksOAwAA2gG+mwYAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVlBEAAGAVZQQAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgFWUEAABYRRkBAABWUUYAAIBVlBEAAGAVZQQAAFhFGQEAAFZRRgAAgFWUEQAAYBVlBAAAWEUZAQAAVlFGAACAVZQRAABgVYvKyK9+9SslJSWpc+fOSk1N1fvvv9/s/J07dyo1NVWdO3fWkCFDtGLFihaFBQAAbU/IZeTNN9/Uc889p0WLFqmsrEzp6enKzMxURUVFo/OPHTumrKwspaenq6ysTAsXLtSCBQvk9XpvOTwAAHC+kMvIz3/+c82dO1dPPvmkRowYoYKCAiUmJmr58uWNzl+xYoUGDhyogoICjRgxQk8++aSeeOIJLVmy5JbDAwAA54sOZXJ9fb1KS0v1k5/8JGg8IyNDH330UaP77N69WxkZGUFjU6dOVWFhoS5duqSOHTs22Mfv98vv9wfWa2pqJEm1tbU3zHjV//9uOCdUN3PcUIU7pxMySuHP6YSMEj/vcHFCRomfd7g4IaPEz/tm5hhjmp9oQlBVVWUkmQ8//DBofPHixWb48OGN7jNs2DCzePHioLEPP/zQSDInT55sdJ8XX3zRSGJhYWFhYWFpA0tlZWWz/SKkMyPXuVyuoHVjTIOxG81vbPy6vLw8ZWdnB9avXr2qL774Qr179272OKGora1VYmKiKisrFRMTE5bHDDcyho8TcpIxfJyQk4zh44Sc7TWjMUYXLlxQQkJCs/NCKiN9+vRRVFSUqqurg8ZPnz6tuLi4RveJj49vdH50dLR69+7d6D5ut1tutztorEePHqFEvWkxMTER+4txHRnDxwk5yRg+TshJxvBxQs72mDE2NvaGc0K6gbVTp05KTU3V9u3bg8a3b9+uiRMnNrpPWlpag/nbtm3T+PHjG71fBAAAtC8hv5smOztbq1at0urVq3Xw4EE9//zzqqio0Lx58yRdu8Qya9aswPx58+bpxIkTys7O1sGDB7V69WoVFhYqJycnfM8CAAA4Vsj3jDzyyCM6e/asXnrpJfl8Po0aNUpbtmzRoEGDJEk+ny/oM0eSkpK0ZcsWPf/883r99deVkJCgpUuXasaMGeF7Fi3gdrv14osvNrgcFEnIGD5OyEnG8HFCTjKGjxNykrF5LmNu9H4bAACArw/fTQMAAKyijAAAAKsoIwAAwCrKCAAAsIoyAgAArKKMAAAAqygjAADAqhZ9UZ7TnT9/Xr/73e9UUVGhQYMG6Qc/+MFNfXb+16m0tFSpqalWM9ys06dP68CBA0pNTVVMTIxOnTqlX//617p69aqmTZumO+64w3ZESdJnn32mDz74QD6fT1FRUUpKStIDDzwQUd8LceTIEX300Ueqrq6Wy+VSXFycJk6cqGHDhtmOdlPq6upUWlqqSZMm2Y7iCFeuXFFUVFRg/U9/+pP8fr/S0tIi+usx5syZo8WLF9/wy85sOXfunI4ePSqPx6MBAwbYjtNAJL7mSBH2utPsd/q2ETNmzDBer9cYY8yBAwdMnz59TN++fc1dd91l4uLiTHx8vPnkk0+sZnS5XGbIkCFm8eLF5vPPP7eapTk7duwwXbt2NS6Xy3g8HvPxxx+bAQMGmGHDhpnk5GTjdrvNH//4R6sZL168aL7//e8bl8tlXC6X6dChg4mPjzdRUVGmW7duZtmyZVbzGWPM+fPnzUMPPWRcLpfp0aOHGT58uBk2bJjp0aOH6dChg3n44YdNTU2N7Zg3VF5ebjp06GA1Q319vXnhhRfMbbfdZu68806zevXqoO3V1dXWM548edLcfffdJioqykyaNMl88cUXZtq0aYHf0eHDh5uTJ09azWiMMR9//HGjS8eOHc3GjRsD6zbl5eWZuro6Y8y1n/1TTz1lOnToEPi7/r3vfc98+eWXVjM64TXHmMh63WkXZaRPnz7m008/NcYYk5mZaR599FHj9/uNMdd+mefOnWsyMjJsRjQul8s89dRTJi4uzkRHR5tp06aZjRs3msuXL1vN9dfuvvtuM3/+fHPhwgXz6quvmgEDBpj58+cHtufk5JiJEydaTGjM008/be6++25TXl5uDh06ZGbMmGFyc3NNXV2dKSwsNN/4xjfMb37zG6sZZ86cae644w6zZ8+eBtv27NljRo8ebWbNmmUhWWgioYy8+OKLJi4uzrz66qtm0aJFJjY21jz99NOB7dXV1cblcllMeO3nPXHiRLNp0ybzyCOPmIkTJ5r09HTz+eefm4qKCpOenh7098iW6y/o10vSV5evvuDb1KFDB3Pq1CljjDGLFy82ffv2NV6v11RVVZl33nnH9O/f37z00ktWMzrhNceYyHrdaRdlpEuXLubo0aPGGGM8Ho/Zt29f0PbDhw+b2NhYC8n+j8vlMqdOnTKXLl0yb731lsnKyjJRUVEmLi7O5ObmmkOHDlnNd11MTEzgz/LSpUsmOjralJWVBbZ/+umn1v8s+/TpY0pKSgLrX3zxhencuXPgf1PLli0zY8eOtRXPGGNMbGxso0Xkut27d1v/czTGmJ49eza7xMTEWH9xGjp0qHnnnXcC60ePHjXDhg0zjz/+uLl69WpEnBnxeDxm9+7dxhhjzp49a1wul3n33XcD29977z0zZMgQW/ECxowZY6ZNm2YOHjxojh8/bo4fP26OHTtmoqOjzfbt2wNjNl3/t9IYY8aOHWsKCwuDtr/55ptmxIgRNqIFOOE1x5jIet1pFzewjh49Wu+9954kKT4+XidOnAjafuLECXXp0sVGtAaio6M1Y8YMbd68WSdOnND8+fP11ltvaeTIkRFxXb5Tp076y1/+Ikmqr6/X1atXA+uS9OWXX1q/9n358uWg+0K6deumy5cvq66uTpKUkZGhQ4cO2YoX4HK5WrStNfn9fj3xxBP6xS9+0ejyD//wD7YjqqqqSqNGjQqs33bbbSouLtbu3bs1c+ZMXblyxWK6a86dO6f+/ftLknr16qVvfOMbgS8Xla5l9vl8tuIF/Nd//ZeGDh2qGTNm6IsvvtCgQYM0ePBgSVJCQoIGDRoUlNuW638/Kisr9a1vfSto27e+9a0G/8a3Nie95kgR8rrTarXHot///vemV69eZs2aNWbNmjVm8ODBZtWqVebDDz80q1evNomJieaFF16wmvGrpx4b8+6775pHH320FRM17uGHHzbf+c53zAcffGCefvppM378eDNt2jRz8eJFU1dXZ77//e+bBx980GrGBx54IOiU96uvvmo8Hk9gfd++faZPnz42ogX83d/9nRk9erTZu3dvg2179+41Y8eONTNnzrSQLNjEiRNNQUFBk9sj4TJNUlJS0FmG66qqqszw4cPNt7/9besZBw4caP70pz8F1n/84x+bs2fPBtbLy8ut/05+1ZYtW8yAAQPMP//zP5srV66Y6Ohoc+DAAduxjDHX/je/ePFi89prr5mEhASza9euoO3l5eWmZ8+eltJd44TXHGMi63WnXZQRY4x56623zIABAxpcD+3cubN57rnnrN+b8dVTj5Hs008/NUOHDjUul8ukpKSYqqoq89BDD5no6GgTHR1t+vbta0pLS61mLC0tNb169TLx8fFm4MCBplOnTuaNN94IbF+2bJn1+zHOnTtnHnzwQeNyuUzPnj1NcnKyuf32203Pnj1Nhw4dTGZmpjl37pzVjMZcuyb/05/+tMntFRUV5vHHH2/FRA3NnTvXPPHEE41u+/zzz83QoUOtl5GHHnqo2VK3bNkyc//997diohurrq42mZmZ5p577omoMjJo0CAzePDgwPLXf66/+MUvzIQJEyyl+z+R/ppjTGS97riMMaZ1zsHYd+XKFe3bt0+fffaZrl69Ko/Ho9TUVHXv3t12NO3cuVN33323oqOd8W7rs2fPqnfv3oH1//zP/9SXX36ptLS0oHFbfD6ffv/738vv9+v+++/XyJEjbUdq1KFDh7R7925VV1dLunZKNy0tTbfffrvlZM5x4sQJHTp0SFOnTm10u8/n07Zt2zR79uxWTnbz9u7dqy5dugRdbooUS5cu1Y4dO/TLX/4yIt82+9f27Nkjt9utcePG2Y4S0a85UmS97rSrMgIAACJPu7iB9UbOnTuntWvX2o7RLCdklJyRM5IyXr16tcnxioqKVk7TNCfkJGP4OCEnGcMnEnJSRiRVVFRozpw5tmM0ywkZJWfkjISMtbW1+tu//Vt17dpVcXFxevHFF4Pe9fG///u/SkpKspjwGifkJGP4OCEnGcMnknLav1DUCmpra5vdfuHChVZK0jQnZJSckdMJGf/xH/9RH3/8sf793/9d58+f18svv6zS0lJt2LBBnTp1kiRFwhVUJ+QkY/g4IScZwyeictq5b7Z1Xf/UwKaWSPhUQSdkdEpOJ2QcOHCg2bFjR2D9zJkz5q677jIZGRnmL3/5S0R8UJcxzshJxvBxQk4yhk8k5WwXN7DGxsZq0aJFuuuuuxrdfuTIEf393/+91Q9HckJGyRk5nZCxa9eu+u///u+gU6AXLlzQ1KlT1aVLF61atUpDhw61/vN2Qk4yho8TcpIxfCIpZ7u4TPPNb35TkjR58uRGt/fo0cP6KTMnZJSckdMJGRMTE3Xw4MGgfwS6d++ubdu2KSMjQ9/73vcspvs/TshJxvBxQk4yhk8k5WwXN7A++uij6ty5c5Pb4+Pj9eKLL7ZiooackFFyRk4nZMzIyNCaNWsajHfr1k1//OMfm83fmpyQk4zh44ScZAyfSMrZLi7TAJHm3LlzOnnypFJSUhrdfvHiRZWWljZ5dqe1OCEnGcPHCTnJGD6RlJMyAgAArGoXl2maMmTIEB05csR2jGY5IaPkjJxkDB8n5CRj+DghJxnDx0bOdnED69KlSxsdr6io0Jo1axQfHy9JWrBgQWvGCuKEjJIzcpIxfJyQk4zh44ScZAyfSMrZLi7TdOjQQf3792/wZUAnTpxQQkKCOnbsKJfLpc8++8xSQmdklJyRk4zh44ScZAwfJ+QkY/hEVM5W+TQTy55++mkzduxY88knnwSNR9LXYjshozHOyEnG8HFCTjKGjxNykjF8IilnuygjxhizceNGk5iYaH75y18GxiLtF8MJGY1xRk4yho8TcpIxfJyQk4zhEyk5200ZMcaYzz//3Nx///3mwQcfND6fLyJ/MZyQ0Rhn5CRj+DghJxnDxwk5yRg+kZCzXb2bpn///nr33Xc1adIkjRs3zvqncDbGCRklZ+QkY/g4IScZw8cJOckYPpGQs13cwNqY0tJSffDBB5o1a5Z69uxpO06jnJBRckZOMoaPE3KSMXyckJOM4WMtZ6ueh4lQFRUVZs6cObZjNMsJGY1xRk4yho8TcpIxfJyQk4zh05o52+2Zka/6+OOP9c1vftP6Nyg2xwkZJWfkJGP4OCEnGcPHCTnJGD6tmbNdfOjZpk2bmt1u+73ekjMySs7IScbwcUJOMoaPE3KSMXwiKWe7ODPSoUMHuVyuZm/KcblcVluqEzJKzshJxvBxQk4yho8TcpIxfCIpZ7t4N43H45HX69XVq1cbXfbt22c7oiMySs7IScbwcUJOMoaPE3KSMXwiKWe7KCOpqanN/qHeqBm2BidklJyRk4zh44ScZAwfJ+QkY/hEUs52cc/ICy+8oLq6uia3Dx06VDt27GjFRA05IaPkjJxkDB8n5CRj+DghJxnDJ5Jytot7RgAAQORqF5dpAABA5KKMAAAAqygjAADAKsoIAACwijICAACsoowAAACrKCMAAMCq/w+OR36h1eflNwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_pop_es.drop(['country'],axis=1)['population'].plot(kind='bar')\n",
    "print(df_pop_es.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00dd47d6-add7-46f9-a93f-dd7c8ff57275",
   "metadata": {},
   "source": [
    "##### Crecimiento de la Población de España. El eje x no está establecido y aparece un id de fila."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42f0962d-8e1c-4f17-b346-453e647f9487",
   "metadata": {},
   "source": [
    "##### Hagamos la comparativa con otro país, por ejemplo con el crecimiento poblacional en Argentina"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9843322f-cab3-459e-8fc6-94ee0c8b323c",
   "metadata": {},
   "source": [
    "##### Gráfica comparativa de crecimiento poblacional entre España y Argentina entre los años 1952 al 2007"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "47e4eb34-df6f-4823-bdeb-0323a63dc650",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_pop_es = df_pop[df_pop[\"country\"] == 'Spain' ]\n",
    "df_pop_ar = df_pop[(df_pop[\"country\"] == 'Argentina')]\n",
    " \n",
    "anios = df_pop_es['year'].unique()\n",
    "pop_ar = df_pop_ar['population'].values\n",
    "pop_es = df_pop_es['population'].values\n",
    " \n",
    "df_plot = pd.DataFrame({'Argentina': pop_ar,\n",
    "                    'Spain': pop_es}, \n",
    "                       index=anios)\n",
    "df_plot.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "id": "c8e6a5db-0b9c-4fa2-be2b-ab49d4ac1eb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VOsdi/PjxGjBggPr06fO7286dO1dRUVGeR3x8fEV2CQAAHKDcxWLFihXavn275s6de17bT5s2Tbm5uZ7HoUOHyh0SAAA4Q7kOhRw6dEh333233n///fP+6mBISIhCQkIqFA4AcAEo6zCDn1/HCMWVq1hs27ZNOTk56tSpk+e1M2fO6KOPPtIzzzwjt9vtdUMsAABwYSlXsejdu7cyM70vpDFmzBi1atVK999/P6UCAPwJKwHwgXIVi4iICLVt29brtbCwMMXExBR73aayrhhWGXx1pbSZM2dq1apVysjIqNT9jB49WsePH/e6QdpvJScnq0OHDlyfBABQLlx506KjR4/qrrvu0sUXX6yQkBDFx8dr0KBBWr9+va+jldvbb7+tRx991NcxAAAO84dvQpaenm4hhvNlZWWpR48eio6O1p///Ge1a9dOp0+f1nvvvafx48dr165dvo5YLrVr1/Z1BACAA7FiYcmdd94pl8ulTz75RNdee61atGihNm3aaOLEidqyZYsk6eDBgxoyZIjCw8MVGRmp6667TseOHSv1ZxYVFWnWrFlq2LChQkJC1KFDB61Zs8YznpWVJZfLpddff109e/ZUrVq11LlzZ3399df69NNPlZSUpPDwcPXv31/fffddsZ//yCOPqG7duoqMjNRtt92mgoICz1hycrLuuecez/OXX35ZSUlJioiIUL169XTjjTcqJyfHwswBAKoTZ9w23c/9+OOPWrNmjebMmaOwsLBi49HR0TLGaOjQoQoLC9OHH36owsJC3Xnnnbr++utLXfV58sknNX/+fP3tb39Tx44dtWTJEg0ePFhffvmlmjdv7tluxowZWrhwoRo1aqSxY8dqxIgRioyM1JNPPqnQ0FBdd911evjhh7Vo0SLPe9avX6+aNWtqw4YNysrK0pgxY1SnTh3NmTOnxCwFBQV69NFH1bJlS+Xk5Ojee+/V6NGj9a9//euPTR7gVJwYCZSIYmHB3r17ZYxRq1atSt1m3bp1+vzzz3XgwAHP1UdfeukltWnTRp9++qk6d+5c7D3z5s3T/fffrxtuuEGS9MQTT2jDhg1auHChnn32Wc92kyZNUr9+/SRJd999t0aMGKH169erR48ekqRx48YpLS3N62cHBwdryZIlCg0NVZs2bTRr1ixNnjxZjz76qAICii9kjR071vPfF198sZ566il16dJFJ0+eVHh4+HnOFACguuNQiAVnbzDmcrlK3Wbnzp2Kj4/3uqR569atFR0drZ07dxbbPi8vT0eOHPGUg7N69OhRbPtzbwQXGxsrSUpMTPR67beHLdq3b6/Q0FDP827duunkyZOlXhl1x44dGjJkiBo3bqyIiAglJydL+vXwDgAAZ1EsLGjevLlcLleJBeEsY0yJxaO018/67VhJ2wcFBRXb/revFRUVlf1LlLI/ScrPz1ffvn0VHh6ul19+WZ9++qlWrlwpSV7nZQAAQLGwoHbt2urXr5+effZZ5efnFxs/fvy4WrdurYMHD3qtCHz11VfKzc3VJZdcUuw9kZGRql+/vjZt2uT1+ubNm0vcvrw+++wz/fzzz57nW7ZsUXh4uBo2bFhs2127dun777/X448/rp49e6pVq1acuAkAKBHnWFjy3HPPqXv37urSpYtmzZqldu3aqbCwUGvXrtWiRYv01VdfqV27dho5cqQWLlzoOXmzV69eSkpKKvFnTp48WTNmzFDTpk3VoUMHLV26VBkZGVq+fPkfzltQUKBx48bpwQcf1DfffKMZM2ZowoQJJZ5f0ahRIwUHB+vpp5/W7bffri+++IJrXACodppMfbfUsazzuz0W5JBi4asrYZZHQkKCtm/frjlz5ui+++5Tdna2LrroInXq1EmLFi2Sy+XSqlWrdNddd+lPf/qTAgIC1L9/fz399NOl/sz//u//Vl5enu677z7l5OSodevWWr16tdc3Qiqqd+/eat68uf70pz/J7Xbrhhtu0MyZM0vc9qKLLlJaWpqmT5+up556SpdeeqnmzZunwYMH/+EcAIDqxWXOnnlYRfLy8hQVFaXc3FxFRkZ6jf3yyy86cOCAEhISzvvuqfBvfKaoECd8lZOM9vhJzrJXLG4sdSwxoVGpY5XxD+PSclZ2xrL+/j4X51gAAABrKBYAAMAaR5xjAQC4MJV1d2snnH93IfLLFYsqPu0DlYjPEgAuLH5VLAIDAyVx0aXq5OxnefazBQBUb351KKRGjRoKDQ3Vd999p6CgoBKvqQDnKCoq0nfffafQ0FDVqOFXf9QAAJXEr/5v73K5FBcXpwMHDuibb77xdRxYEBAQoEaNGpV52XIAQPXhV8VC+vWum82bN+dwSDURHBzMyhMAXED8rlhIv/4rl4spAQDgPPxTEgAAWEOxAAAA1lAsAACANX55jgWASuInN3sCUH2xYgEAAKxhxQIAUOnKviV5FQZBpWPFAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA03IQNs4ZbkAMCKBQAAsIdiAQAArOFQCABcgBKXJZY6lpmaWYVJUN2wYgEAAKxhxQIAHK7J1HdLfD2rZhUHAcSKBQAAsIhiAQAArKFYAAAAaygWAADAGooFAACwhmIBAACsoVgAAABruI4FnIEbfAGAI7BiAQAArKFYAAAAaygWAADAGooFAACwhmIBAACsoVgAAABrKBYAAMAaigUAALCGYgEAAKzhypsAUIomU98tdSyrZhUGARyEFQsAAGANxQIAAFhDsQAAANZwjsWFjruGAgAsolgAgGWJyxJLHctMzazCJEDV41AIAACwhmIBAACsoVgAAABrKBYAAMCachWLRYsWqV27doqMjFRkZKS6deum//3f/62sbAAAwGHKVSwaNmyoxx9/XFu3btXWrVt15ZVXasiQIfryyy8rKx8AAHCQcn3ddNCgQV7P58yZo0WLFmnLli1q06ZNie9xu91yu92e53l5eRWICQAAnKDC51icOXNGK1asUH5+vrp161bqdnPnzlVUVJTnER8fX9FdAgAAP1fuC2RlZmaqW7du+uWXXxQeHq6VK1eqdevWpW4/bdo0TZw40fM8Ly/vwikXXNUSAHCBKXexaNmypTIyMnT8+HG99dZbSk1N1YcfflhquQgJCVFISMgfDgoAAPxfuYtFcHCwmjVrJklKSkrSp59+qieffFJ/+9vfrIcDAADO8oevY2GM8To5EwAAXLjKtWIxffp0paSkKD4+XidOnNCKFSuUnp6uNWvWVFY+ANVUk6nvljqWVbMKgwCwqlzF4tixY7r55puVnZ2tqKgotWvXTmvWrNFVV11VWfkAAICDlKtYLF68uLJyAACAaoB7hQAAAGsoFgAAwBqKBQAAsIZiAQAArCn3BbL8BpfLBgDA77BiAQAArKFYAAAAaygWAADAGooFAACwhmIBAACsce63QgBckBKXJZY6lpmaWYVJAJSEFQsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3fCgGqoSZT3y3x9ayaVRwEwAWHFQsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFjDbdMBSJISlyWWOpaZmlmFSQA4GSsWAADAGooFAACwhkMhQDk0mfpuqWNZNaswCAD4KVYsAACANRQLAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANdzdFH6DO4cCgPOxYgEAAKyhWAAAAGs4FAJUgcRliaWOZaZmVmESAKhcrFgAAABrKBYAAMAaigUAALCGYgEAAKyhWAAAAGsoFgAAwBqKBQAAsIZiAQAArKFYAAAAa7jy5gWitBt8cXMvAIBNrFgAAABrKBYAAMAaigUAALCGYgEAAKyhWAAAAGsoFgAAwJpyFYu5c+eqc+fOioiIUN26dTV06FDt3r27srIBAACHKVex+PDDDzV+/Hht2bJFa9euVWFhofr27av8/PzKygcAABykXBfIWrNmjdfzpUuXqm7dutq2bZv+9Kc/WQ0GAACc5w9deTM3N1eSVLt27VK3cbvdcrvdnud5eXl/ZJcAAMCPVfjkTWOMJk6cqMsvv1xt27Ytdbu5c+cqKirK84iPj6/oLgEAgJ+r8IrFhAkT9Pnnn2vTpk1lbjdt2jRNnDjR8zwvL49yAasSlyWWOpaZmlmFSQAAFSoWd911l1avXq2PPvpIDRs2LHPbkJAQhYSEVCgcAABwlnIVC2OM7rrrLq1cuVLp6elKSEiorFyOUdpdQyXuHAoAuPCUq1iMHz9er7zyiv7xj38oIiJCR48elSRFRUWpVq1alRIQAAA4R7lO3ly0aJFyc3OVnJysuLg4z+O1116rrHwAAMBByn0oBAAAoDTcKwQAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYU+HbplcFbvAFAICzsGIBAACsoVgAAABrKBYAAMAaigUAALCGYgEAAKyhWAAAAGv8+uum8K3EZYmljmWmZlZhEgCAU7BiAQAArKFYAAAAaygWAADAGooFAACwhmIBAACsoVgAAABrKBYAAMAaigUAALCGYgEAAKyhWAAAAGsoFgAAwBqKBQAAsIZiAQAArKFYAAAAaygWAADAGooFAACwhmIBAACsoVgAAABrKBYAAMCaGr4OcKFKXJZY6lhmamYVJgEAwB5WLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1tTwdYDKkLgssdSxzNTMKkwCAMCFhRULAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYQ7EAAADWlLtYfPTRRxo0aJDq168vl8ulVatWVUIsAADgROUuFvn5+Wrfvr2eeeaZysgDAAAcrEZ535CSkqKUlJTz3t7tdsvtdnue5+XllXeXAADAISr9HIu5c+cqKirK84iPj6/sXQIAAB+p9GIxbdo05ebmeh6HDh2q7F0CAAAfKfehkPIKCQlRSEhIZe8GAAD4Ab5uCgAArKFYAAAAa8p9KOTkyZPau3ev5/mBAweUkZGh2rVrq1GjRlbDAQAAZyl3sdi6dauuuOIKz/OJEydKklJTU5WWlmYtGAAAcJ5yF4vk5GQZYyojCwAAcDjOsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYQ7EAAADWUCwAAIA1FAsAAGANxQIAAFhDsQAAANZQLAAAgDUUCwAAYA3FAgAAWEOxAAAA1lAsAACANRQLAABgDcUCAABYU6Fi8dxzzykhIUE1a9ZUp06dtHHjRtu5AACAA5W7WLz22mu655579MADD2jHjh3q2bOnUlJSdPDgwcrIBwAAHKTcxeIvf/mLxo0bp1tuuUWXXHKJFi5cqPj4eC1atKgy8gEAAAepUZ6NCwoKtG3bNk2dOtXr9b59+2rz5s0lvsftdsvtdnue5+bmSpLy8vJ+d39F7lOljuW5TKljZ34+U/r7zmO/5eGEjFLpOZ2QUfKfnE7IKPF52+KEjBKfty1OyCj57vM+u50xpe/n7Abn7fDhw0aS+fjjj71enzNnjmnRokWJ75kxY4aRxIMHDx48ePCoBo9Dhw6V2RXKtWJxlsvl8npujCn22lnTpk3TxIkTPc+Lior0448/KiYmptT3lEdeXp7i4+N16NAhRUZG/uGfV1mckJOM9jghJxntcUJOMtrjhJyVkdEYoxMnTqh+/fplbleuYlGnTh0FBgbq6NGjXq/n5OQoNja2xPeEhIQoJCTE67Xo6Ojy7Pa8REZG+u0HfC4n5CSjPU7ISUZ7nJCTjPY4IaftjFFRUb+7TblO3gwODlanTp20du1ar9fXrl2r7t27ly8dAACodsp9KGTixIm6+eablZSUpG7duunvf/+7Dh48qNtvv70y8gEAAAcpd7G4/vrr9cMPP2jWrFnKzs5W27Zt9a9//UuNGzeujHy/KyQkRDNmzCh2uMXfOCEnGe1xQk4y2uOEnGS0xwk5fZnRZX73eyMAAADnh3uFAAAAaygWAADAGooFAACwhmIBAACsoVgAAABrKBYAAMAaigUAAA62bds2X0fwQrGoBP72ITsZc2kH82gPc2mPE+by9OnTmjJlipo1a6YuXbpo6dKlXuPHjh1TYGCgj9L9qnPnzmratKkee+wxHT582KdZJAcWCz5kO5wwjxJzaYsT5lFiLm1xwjxKzpjLOXPm6MUXX9Ttt9+uvn376t5779Vtt93mtY0/XGeyd+/eeuqpp9SkSRMNHDhQq1at0pkzZ3wTpsybqvuhGTNmmNjYWPM///M/5oEHHjBRUVHmv/7rvzzjR48eNS6Xy4cJjXG5XObWW281sbGxpkaNGmbAgAFm5cqVprCw0Ke5zuWEeTSGubTFCfNoDHNpixPm0RhnzGWzZs3MP//5T8/zvXv3mubNm5vRo0eboqIic/ToURMQEODDhL/O47Fjx8zp06fNm2++aa6++moTGBhoYmNjzZQpU8yuXbuqNI/jigUfsh1OmEdjmEtbnDCPxjCXtjhhHo1xxlzWqlXLHDhwwOu1w4cPm5YtW5qRI0eaw4cP+3wuz87jub799lsza9Ysc/HFF5uAgADTs2fPKsvjuGLBh2yHE+bRGObSFifMozHMpS1OmEdjnDGXCQkJZt26dcVeP3z4sGnRooXp06ePz+cyICCg2Dyea926debGG2+ssjyOKxZ8yHY4YR6NYS5tccI8GsNc2uKEeTTGGXM5btw4M3bs2BLHvv32W9OsWTOfz2VJBc2XHHd301tuuUXGGC1evLjY2OHDh5WcnKz9+/f77qQVSQEBATp69Kjq1q3rswy/xwnzKDGXtjhhHiXm0hYnzKPkjLn85ptvtGvXLvXr16/E8ezsbL3//vtKTU2t4mT/9uGHH6pHjx6qUaOGzzJ48WGpqZCsrCyzZs2aUsePHDli0tLSqjBRcenp6eb06dM+zfB7nDCPxjCXtjhhHo1hLm1xwjwa44y5RPk5bsUCAICqZIzRunXrtHnzZh09elQul0uxsbHq0aOHevfuLZfL5euIfpWxWhSLjIwM7dmzR3FxcerRo4dffMi/5W8Z3W63AgICFBQUJEnat2+flixZooMHD6px48YaN26cEhISfJpRckbOt956SykpKQoNDfVpjrI4IeNZn332mbZv367k5GQlJCToyy+/1LPPPquioiJdc801pS5Jk7G4Dz74QJs2bVJ2drYCAwOVkJCgwYMHq3nz5r6O5sWfcx4+fFgDBw5UZmam2rZtq9jYWBljlJOToy+++ELt27fX6tWr1aBBAzKe5bvFkooZMWKEycvLM8YYc+LECdO3b1/jcrlMcHCwcblcJikpyfz0009k/B1XXHGFeeutt4wxxmzatMmEhISYdu3ameuvv9507NjRhIaGms2bN/s0ozHOyOlyuUxERIS59dZbzZYtW3yapTROyGiMMW+++aYJDAw0MTExJiIiwqxbt85ER0ebPn36mH79+pnAwECzfPlyMv6OY8eOmS5duhiXy2UCAwNNQECA6dSpk6lXr54JDAw0kydP9mm+s5yQc/DgwebKK680R44cKTZ25MgRc+WVV5ohQ4ZUfbBz+FtGxxWLc88injRpkklISDDbtm0zxhiTmZlpLrnkEnPvvff6MqIjMkZHR5u9e/caY4zp1atXsTwPPvig6dGjhy+ieXFCTpfLZWbNmmU6duxoXC6XadOmjVmwYIH5/vvvfZrrXE7IaIwxl156qZk9e7YxxphXX33VREdHm1mzZnnG582bZzp06OCreMYYZ2S8/vrrzdChQ81PP/1kTp06ZcaPH29GjRpljDFm/fr1JiYmxixcuNCnGY1xRs6wsDCTkZFR6vj27dtNWFhYFSYqzt8yOq5YnPu1mjZt2pjXXnvNa/zdd981zZs390U0DydkDAsLMzt37jTGGBMbG1vsD+XevXtNeHi4L6J5cULOcz/vrVu3mjvuuMNER0ebkJAQM3z4cPP+++/7NJ8xzshozK+f99nrLxQVFZmgoCDz+eefe8b37dvn88/bCRkjIyPNF1984Xl+8uRJExQUZHJzc40xxrz00kumZcuWvorn4YScderUMR988EGp4+vXrzd16tSpwkTF+VtGx90rRJLn/IRjx46pbdu2XmNt2rTRoUOHfBHLi79n7Nq1q/75z39Kkpo2barPPvvMazwjI0O1a9f2RTQvTsl5VqdOnfTcc88pOztbzz//vL777jv1799fTZo08XU0D3/OGBERoR9++EGSdPz4cRUWFnqeS9IPP/yg8PBwX8WT5IyMISEhXudxBQQE6MyZMyosLJQkde/eXVlZWT5K929OyHnDDTcoNTVVb775pnJzcz2v5+bm6s0339SYMWN04403+jChH2assgpjicvlMrfddpu59957Td26dc369eu9xrdu3erz9uiEjJs3bzZRUVFmxowZ5umnnzZ16tQxDz74oFm+fLl5+OGHTXR0tHniiSd8mtEpOX/vIj979uwx06dPr8JExTkhozHG3HTTTaZr167m5ZdfNoMGDTL9+/c3l112mdm5c6fZtWuX6dWrl7n22mvJ+DuuueYaM2zYMHPy5ElTUFBg7rnnHtOsWTPP+JYtW0y9evV8mPBXTsjpdrvN7bffboKDg01AQICpWbOmqVmzpgkICDDBwcHmjjvuMG63m4zncFyx6NWrl0lOTvY8XnjhBa/xWbNmmV69evkm3P/nhIzG/PqX9mWXXWZcLpfXo0GDBj4/rnkuf8/pb1e9K4kTMhrz682x+vTpY8LDw01KSorJzc01EyZMMC6XywQEBJjmzZt7zrkhY+n27dtnmjZtamrUqGGCgoJMdHS0Wbt2rWd86dKlZurUqT5M+Cun5DTGmNzcXLN+/XrzyiuvmFdeecV88MEHnkM2/sJfMlaLr5uea//+/QoODlbDhg19HaVU/pbxu+++0/79+1VUVKS4uDi/WBIvib/m/Oabb9SoUSOff4W4LE7IWJb9+/fr1KlTatWqlf9cXfA3/C3jqVOntGnTJhUUFOiyyy5TnTp1fB2pRE7JifNX7YoFAAA25efn65VXXinx4lMjRoxQWFiYryP6VUZHFouff/5Zr776arELqgwdOlS9e/f2dTxJZLTJCTnJaI8TcpLRHn/P+dVXX+mqq67SqVOn1KtXL6+LT3344YcKCwvT+++/r9atW5PxrCo/+PIH7dmzxzRu3NjExMSYuLg443K5zIABA0zXrl1NYGCgGT58uM+vPU/GCysnGS+snGS8sHImJyebG264ocSTH91utxkxYoRJTk72QbJ/87eMjisWKSkp5rbbbjNnzpwxxhgzd+5ck5KSYowx5uuvvzZNmjQxM2bM8GFCMtrkhJxktMcJOclojxNy1qpVy3z55ZeljmdmZppatWpVYaLi/C2j44pFaGio+frrrz3P3W63CQoK8lxBcNWqVaZJkya+imeMIaNNTshJRnuckJOM9jghZ/369c2qVatKHV+5cqWpX79+FSYqzt8y+v7U5XKKjo7WiRMnPM9PnTqlwsJCBQcHS5LatWun7OxsX8WTREabnJCTjPY4IScZ7XFCzltvvVWpqal68MEHddVVVyk2NlYul0tHjx7V2rVr9dhjj+mee+4h47mqrMJYkpqaanr16mV27txp9u/f77kZ1Vnp6ekmPj7ehwnJaJMTcpLRHifkJKM9Tsn5+OOPe84BCQgIMAEBAcblcpm4uDifX6DvLH/K6LhicezYMc/FkgICAkyTJk3M9u3bPeNvvPGGeeqpp3yYkIw2OSEnGe1xQk4y2uOUnGft37/fbN682WzevNns37/f13FK5A8ZHfl1U0nas2eP3G6331yMpiRktMcJOclojxNyktEep+TEefJJnalEBw8eNGPGjPF1jDKR0R4n5CSjPU7ISUZ7/CXnqVOnzMaNG0v85sXPP/9sli1b5oNU3vwpY7UrFhkZGSYgIMDXMcpERnuckJOM9jghJxnt8Yecu3fvNo0bN/YcrunVq5c5cuSIZ/zo0aNk/A3HrTmtXr26zPH9+/dXUZLSkdEeJ+Qkoz1OyElGe5yQ8/7771diYqK2bt2q48ePa+LEierRo4fS09PVqFEjX8eT5H8ZHXeORUBAgFwul8qK7XK5dObMmSpM5Y2M9jghJxntcUJOMtrjhJyxsbFat26dEhMTPa+NHz9e77zzjjZs2KCwsDDVr1+fjOcIqJK9WBQXF6e33npLRUVFJT62b9/u64hktMgJOclojxNyktEeJ+T8+eefi51Q+uyzz2rw4MHq1auXvv76ax8l+zd/y+i4YtGpU6cy/7D9XvutCmS0xwk5yWiPE3KS0R4n5GzVqpW2bt1a7PWnn35aQ4YM0eDBg32Qypu/ZXTcORaTJ09Wfn5+qePNmjXThg0bqjBRcWS0xwk5yWiPE3KS0R4n5Lzmmmv06quv6uabby429swzz6ioqEh//etffZDs3/wto+POsQAAAP7LcYdCAACA/6JYAAAAaygWAADAGooFAACwhmIBAACsoVgAAABrKBYAAMCa/wd0nz0tgCFJIAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_pop_es = df_pop[df_pop[\"country\"] == 'Spain' ]\n",
    "df_pop_ar = df_pop[(df_pop[\"country\"] == 'Argentina')]\n",
    "df_pop_co = df_pop[(df_pop[\"country\"] == 'Colombia')]\n",
    "\n",
    "anios = df_pop['year'].unique()\n",
    "pop_ar = df_pop_ar['population'].values\n",
    "pop_es = df_pop_es['population'].values\n",
    "pop_co = df_pop_co['population'].values\n",
    "df_plot = pd.DataFrame({'Argentina': pop_ar,\n",
    "                    'Spain': pop_es,\n",
    "                       'Colombia' : pop_co}, \n",
    "                       index=anios)\n",
    "df_plot.plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "id": "349c53d9-c841-464a-86c0-d2179f003da7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_pop_es = df_pop[df_pop[\"country\"] == 'Spain' ]\n",
    "df_pop_ar = df_pop[(df_pop[\"country\"] == 'Argentina')]\n",
    "df_pop_co = df_pop[(df_pop[\"country\"] == 'Colombia')]\n",
    "df_pop_af = df_pop[(df_pop[\"country\"] == 'Afghanistan')]\n",
    "\n",
    "anios = df_pop['year'].unique()\n",
    "pop_ar = df_pop_ar['population'].values\n",
    "pop_es = df_pop_es['population'].values\n",
    "pop_co = df_pop_co['population'].values\n",
    "pop_af = df_pop_af['population'].values\n",
    "df_plot = pd.DataFrame({'Argentina': pop_ar,\n",
    "                    'Spain': pop_es,\n",
    "                       'Colombia' : pop_co,\n",
    "                       'Afghanistan' : pop_af}, \n",
    "                       index=anios)\n",
    "df_plot.plot(kind='bar')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fe68c83-0f12-4770-a81e-897020e5a978",
   "metadata": {},
   "source": [
    "##### Ahora filtremos todos los paises hispano-hablantes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "acfdc56a-1dda-42f5-88eb-28ba6d567c17",
   "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>alpha_2</th>\n",
       "      <th>alpha_3</th>\n",
       "      <th>area</th>\n",
       "      <th>capital</th>\n",
       "      <th>continent</th>\n",
       "      <th>currency_code</th>\n",
       "      <th>currency_name</th>\n",
       "      <th>eqivalent_fips_code</th>\n",
       "      <th>fips</th>\n",
       "      <th>geoname_id</th>\n",
       "      <th>languages</th>\n",
       "      <th>name</th>\n",
       "      <th>neighbours</th>\n",
       "      <th>numeric</th>\n",
       "      <th>phone</th>\n",
       "      <th>population</th>\n",
       "      <th>postal_code_format</th>\n",
       "      <th>postal_code_regex</th>\n",
       "      <th>tld</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AD</td>\n",
       "      <td>AND</td>\n",
       "      <td>468.0</td>\n",
       "      <td>Andorra la Vella</td>\n",
       "      <td>EU</td>\n",
       "      <td>EUR</td>\n",
       "      <td>Euro</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AN</td>\n",
       "      <td>3041565</td>\n",
       "      <td>ca</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>ES,FR</td>\n",
       "      <td>20</td>\n",
       "      <td>376</td>\n",
       "      <td>84000</td>\n",
       "      <td>AD###</td>\n",
       "      <td>^(?:AD)*(\\d{3})$</td>\n",
       "      <td>.ad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AE</td>\n",
       "      <td>ARE</td>\n",
       "      <td>82880.0</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>AS</td>\n",
       "      <td>AED</td>\n",
       "      <td>Dirham</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AE</td>\n",
       "      <td>290557</td>\n",
       "      <td>ar-AE,fa,en,hi,ur</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>SA,OM</td>\n",
       "      <td>784</td>\n",
       "      <td>971</td>\n",
       "      <td>4975593</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>.ae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>647500.0</td>\n",
       "      <td>Kabul</td>\n",
       "      <td>AS</td>\n",
       "      <td>AFN</td>\n",
       "      <td>Afghani</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AF</td>\n",
       "      <td>1149361</td>\n",
       "      <td>fa-AF,ps,uz-AF,tk</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>TM,CN,IR,TJ,PK,UZ</td>\n",
       "      <td>4</td>\n",
       "      <td>93</td>\n",
       "      <td>29121286</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>.af</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AG</td>\n",
       "      <td>ATG</td>\n",
       "      <td>443.0</td>\n",
       "      <td>St. John's</td>\n",
       "      <td>NaN</td>\n",
       "      <td>XCD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AC</td>\n",
       "      <td>3576396</td>\n",
       "      <td>en-AG</td>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>NaN</td>\n",
       "      <td>28</td>\n",
       "      <td>+1-268</td>\n",
       "      <td>86754</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>.ag</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AI</td>\n",
       "      <td>AIA</td>\n",
       "      <td>102.0</td>\n",
       "      <td>The Valley</td>\n",
       "      <td>NaN</td>\n",
       "      <td>XCD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AV</td>\n",
       "      <td>3573511</td>\n",
       "      <td>en-AI</td>\n",
       "      <td>Anguilla</td>\n",
       "      <td>NaN</td>\n",
       "      <td>660</td>\n",
       "      <td>+1-264</td>\n",
       "      <td>13254</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>.ai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>ZA</td>\n",
       "      <td>ZAF</td>\n",
       "      <td>1219912.0</td>\n",
       "      <td>Pretoria</td>\n",
       "      <td>AF</td>\n",
       "      <td>ZAR</td>\n",
       "      <td>Rand</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SF</td>\n",
       "      <td>953987</td>\n",
       "      <td>zu,xh,af,nso,en-ZA,tn,st,ts,ss,ve,nr</td>\n",
       "      <td>South Africa</td>\n",
       "      <td>ZW,SZ,MZ,BW,NA,LS</td>\n",
       "      <td>710</td>\n",
       "      <td>27</td>\n",
       "      <td>49000000</td>\n",
       "      <td>####</td>\n",
       "      <td>^(\\d{4})$</td>\n",
       "      <td>.za</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>ZM</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>752614.0</td>\n",
       "      <td>Lusaka</td>\n",
       "      <td>AF</td>\n",
       "      <td>ZMW</td>\n",
       "      <td>Kwacha</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ZA</td>\n",
       "      <td>895949</td>\n",
       "      <td>en-ZM,bem,loz,lun,lue,ny,toi</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>ZW,TZ,MZ,CD,NA,MW,AO</td>\n",
       "      <td>894</td>\n",
       "      <td>260</td>\n",
       "      <td>13460305</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.zm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>ZW</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>390580.0</td>\n",
       "      <td>Harare</td>\n",
       "      <td>AF</td>\n",
       "      <td>ZWL</td>\n",
       "      <td>Dollar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ZI</td>\n",
       "      <td>878675</td>\n",
       "      <td>en-ZW,sn,nr,nd</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZA,MZ,BW,ZM</td>\n",
       "      <td>716</td>\n",
       "      <td>263</td>\n",
       "      <td>13061000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>.zw</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>CS</td>\n",
       "      <td>SCG</td>\n",
       "      <td>102350.0</td>\n",
       "      <td>Belgrade</td>\n",
       "      <td>EU</td>\n",
       "      <td>RSD</td>\n",
       "      <td>Dinar</td>\n",
       "      <td>NaN</td>\n",
       "      <td>YI</td>\n",
       "      <td>8505033</td>\n",
       "      <td>cu,hu,sq,sr</td>\n",
       "      <td>Serbia and Montenegro</td>\n",
       "      <td>AL,HU,MK,RO,HR,BA,BG</td>\n",
       "      <td>891</td>\n",
       "      <td>381</td>\n",
       "      <td>10829175</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.cs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>AN</td>\n",
       "      <td>ANT</td>\n",
       "      <td>960.0</td>\n",
       "      <td>Willemstad</td>\n",
       "      <td>NaN</td>\n",
       "      <td>ANG</td>\n",
       "      <td>Guilder</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NT</td>\n",
       "      <td>8505032</td>\n",
       "      <td>nl-AN,en,es</td>\n",
       "      <td>Netherlands Antilles</td>\n",
       "      <td>GP</td>\n",
       "      <td>530</td>\n",
       "      <td>599</td>\n",
       "      <td>300000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>.an</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    alpha_2 alpha_3       area           capital continent currency_code  \\\n",
       "0        AD     AND      468.0  Andorra la Vella        EU           EUR   \n",
       "1        AE     ARE    82880.0         Abu Dhabi        AS           AED   \n",
       "2        AF     AFG   647500.0             Kabul        AS           AFN   \n",
       "3        AG     ATG      443.0        St. John's       NaN           XCD   \n",
       "4        AI     AIA      102.0        The Valley       NaN           XCD   \n",
       "..      ...     ...        ...               ...       ...           ...   \n",
       "247      ZA     ZAF  1219912.0          Pretoria        AF           ZAR   \n",
       "248      ZM     ZMB   752614.0            Lusaka        AF           ZMW   \n",
       "249      ZW     ZWE   390580.0            Harare        AF           ZWL   \n",
       "250      CS     SCG   102350.0          Belgrade        EU           RSD   \n",
       "251      AN     ANT      960.0        Willemstad       NaN           ANG   \n",
       "\n",
       "    currency_name eqivalent_fips_code fips  geoname_id  \\\n",
       "0            Euro                 NaN   AN     3041565   \n",
       "1          Dirham                 NaN   AE      290557   \n",
       "2         Afghani                 NaN   AF     1149361   \n",
       "3          Dollar                 NaN   AC     3576396   \n",
       "4          Dollar                 NaN   AV     3573511   \n",
       "..            ...                 ...  ...         ...   \n",
       "247          Rand                 NaN   SF      953987   \n",
       "248        Kwacha                 NaN   ZA      895949   \n",
       "249        Dollar                 NaN   ZI      878675   \n",
       "250         Dinar                 NaN   YI     8505033   \n",
       "251       Guilder                 NaN   NT     8505032   \n",
       "\n",
       "                                languages                   name  \\\n",
       "0                                      ca                Andorra   \n",
       "1                       ar-AE,fa,en,hi,ur   United Arab Emirates   \n",
       "2                       fa-AF,ps,uz-AF,tk            Afghanistan   \n",
       "3                                   en-AG    Antigua and Barbuda   \n",
       "4                                   en-AI               Anguilla   \n",
       "..                                    ...                    ...   \n",
       "247  zu,xh,af,nso,en-ZA,tn,st,ts,ss,ve,nr           South Africa   \n",
       "248          en-ZM,bem,loz,lun,lue,ny,toi                 Zambia   \n",
       "249                        en-ZW,sn,nr,nd               Zimbabwe   \n",
       "250                           cu,hu,sq,sr  Serbia and Montenegro   \n",
       "251                           nl-AN,en,es   Netherlands Antilles   \n",
       "\n",
       "               neighbours  numeric   phone  population postal_code_format  \\\n",
       "0                   ES,FR       20     376       84000              AD###   \n",
       "1                   SA,OM      784     971     4975593                NaN   \n",
       "2       TM,CN,IR,TJ,PK,UZ        4      93    29121286                NaN   \n",
       "3                     NaN       28  +1-268       86754                NaN   \n",
       "4                     NaN      660  +1-264       13254                NaN   \n",
       "..                    ...      ...     ...         ...                ...   \n",
       "247     ZW,SZ,MZ,BW,NA,LS      710      27    49000000               ####   \n",
       "248  ZW,TZ,MZ,CD,NA,MW,AO      894     260    13460305              #####   \n",
       "249           ZA,MZ,BW,ZM      716     263    13061000                NaN   \n",
       "250  AL,HU,MK,RO,HR,BA,BG      891     381    10829175              #####   \n",
       "251                    GP      530     599      300000                NaN   \n",
       "\n",
       "    postal_code_regex  tld  \n",
       "0    ^(?:AD)*(\\d{3})$  .ad  \n",
       "1                 NaN  .ae  \n",
       "2                 NaN  .af  \n",
       "3                 NaN  .ag  \n",
       "4                 NaN  .ai  \n",
       "..                ...  ...  \n",
       "247         ^(\\d{4})$  .za  \n",
       "248         ^(\\d{5})$  .zm  \n",
       "249               NaN  .zw  \n",
       "250         ^(\\d{5})$  .cs  \n",
       "251               NaN  .an  \n",
       "\n",
       "[252 rows x 19 columns]"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "36a7536f-87f2-4503-96cf-5012a9b609cb",
   "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>alpha_2</th>\n",
       "      <th>alpha_3</th>\n",
       "      <th>area</th>\n",
       "      <th>capital</th>\n",
       "      <th>continent</th>\n",
       "      <th>currency_code</th>\n",
       "      <th>currency_name</th>\n",
       "      <th>eqivalent_fips_code</th>\n",
       "      <th>fips</th>\n",
       "      <th>geoname_id</th>\n",
       "      <th>languages</th>\n",
       "      <th>name</th>\n",
       "      <th>neighbours</th>\n",
       "      <th>numeric</th>\n",
       "      <th>phone</th>\n",
       "      <th>population</th>\n",
       "      <th>postal_code_format</th>\n",
       "      <th>postal_code_regex</th>\n",
       "      <th>tld</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AD</td>\n",
       "      <td>AND</td>\n",
       "      <td>468.0</td>\n",
       "      <td>Andorra la Vella</td>\n",
       "      <td>EU</td>\n",
       "      <td>EUR</td>\n",
       "      <td>Euro</td>\n",
       "      <td></td>\n",
       "      <td>AN</td>\n",
       "      <td>3041565</td>\n",
       "      <td>ca</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>ES,FR</td>\n",
       "      <td>20</td>\n",
       "      <td>376</td>\n",
       "      <td>84000</td>\n",
       "      <td>AD###</td>\n",
       "      <td>^(?:AD)*(\\d{3})$</td>\n",
       "      <td>.ad</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AE</td>\n",
       "      <td>ARE</td>\n",
       "      <td>82880.0</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>AS</td>\n",
       "      <td>AED</td>\n",
       "      <td>Dirham</td>\n",
       "      <td></td>\n",
       "      <td>AE</td>\n",
       "      <td>290557</td>\n",
       "      <td>ar-AE,fa,en,hi,ur</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>SA,OM</td>\n",
       "      <td>784</td>\n",
       "      <td>971</td>\n",
       "      <td>4975593</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.ae</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF</td>\n",
       "      <td>AFG</td>\n",
       "      <td>647500.0</td>\n",
       "      <td>Kabul</td>\n",
       "      <td>AS</td>\n",
       "      <td>AFN</td>\n",
       "      <td>Afghani</td>\n",
       "      <td></td>\n",
       "      <td>AF</td>\n",
       "      <td>1149361</td>\n",
       "      <td>fa-AF,ps,uz-AF,tk</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>TM,CN,IR,TJ,PK,UZ</td>\n",
       "      <td>4</td>\n",
       "      <td>93</td>\n",
       "      <td>29121286</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.af</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AG</td>\n",
       "      <td>ATG</td>\n",
       "      <td>443.0</td>\n",
       "      <td>St. John's</td>\n",
       "      <td></td>\n",
       "      <td>XCD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>AC</td>\n",
       "      <td>3576396</td>\n",
       "      <td>en-AG</td>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td></td>\n",
       "      <td>28</td>\n",
       "      <td>+1-268</td>\n",
       "      <td>86754</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.ag</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AI</td>\n",
       "      <td>AIA</td>\n",
       "      <td>102.0</td>\n",
       "      <td>The Valley</td>\n",
       "      <td></td>\n",
       "      <td>XCD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>AV</td>\n",
       "      <td>3573511</td>\n",
       "      <td>en-AI</td>\n",
       "      <td>Anguilla</td>\n",
       "      <td></td>\n",
       "      <td>660</td>\n",
       "      <td>+1-264</td>\n",
       "      <td>13254</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.ai</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>ZA</td>\n",
       "      <td>ZAF</td>\n",
       "      <td>1219912.0</td>\n",
       "      <td>Pretoria</td>\n",
       "      <td>AF</td>\n",
       "      <td>ZAR</td>\n",
       "      <td>Rand</td>\n",
       "      <td></td>\n",
       "      <td>SF</td>\n",
       "      <td>953987</td>\n",
       "      <td>zu,xh,af,nso,en-ZA,tn,st,ts,ss,ve,nr</td>\n",
       "      <td>South Africa</td>\n",
       "      <td>ZW,SZ,MZ,BW,NA,LS</td>\n",
       "      <td>710</td>\n",
       "      <td>27</td>\n",
       "      <td>49000000</td>\n",
       "      <td>####</td>\n",
       "      <td>^(\\d{4})$</td>\n",
       "      <td>.za</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>ZM</td>\n",
       "      <td>ZMB</td>\n",
       "      <td>752614.0</td>\n",
       "      <td>Lusaka</td>\n",
       "      <td>AF</td>\n",
       "      <td>ZMW</td>\n",
       "      <td>Kwacha</td>\n",
       "      <td></td>\n",
       "      <td>ZA</td>\n",
       "      <td>895949</td>\n",
       "      <td>en-ZM,bem,loz,lun,lue,ny,toi</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>ZW,TZ,MZ,CD,NA,MW,AO</td>\n",
       "      <td>894</td>\n",
       "      <td>260</td>\n",
       "      <td>13460305</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.zm</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>249</th>\n",
       "      <td>ZW</td>\n",
       "      <td>ZWE</td>\n",
       "      <td>390580.0</td>\n",
       "      <td>Harare</td>\n",
       "      <td>AF</td>\n",
       "      <td>ZWL</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>ZI</td>\n",
       "      <td>878675</td>\n",
       "      <td>en-ZW,sn,nr,nd</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>ZA,MZ,BW,ZM</td>\n",
       "      <td>716</td>\n",
       "      <td>263</td>\n",
       "      <td>13061000</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.zw</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>CS</td>\n",
       "      <td>SCG</td>\n",
       "      <td>102350.0</td>\n",
       "      <td>Belgrade</td>\n",
       "      <td>EU</td>\n",
       "      <td>RSD</td>\n",
       "      <td>Dinar</td>\n",
       "      <td></td>\n",
       "      <td>YI</td>\n",
       "      <td>8505033</td>\n",
       "      <td>cu,hu,sq,sr</td>\n",
       "      <td>Serbia and Montenegro</td>\n",
       "      <td>AL,HU,MK,RO,HR,BA,BG</td>\n",
       "      <td>891</td>\n",
       "      <td>381</td>\n",
       "      <td>10829175</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.cs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>AN</td>\n",
       "      <td>ANT</td>\n",
       "      <td>960.0</td>\n",
       "      <td>Willemstad</td>\n",
       "      <td></td>\n",
       "      <td>ANG</td>\n",
       "      <td>Guilder</td>\n",
       "      <td></td>\n",
       "      <td>NT</td>\n",
       "      <td>8505032</td>\n",
       "      <td>nl-AN,en,es</td>\n",
       "      <td>Netherlands Antilles</td>\n",
       "      <td>GP</td>\n",
       "      <td>530</td>\n",
       "      <td>599</td>\n",
       "      <td>300000</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.an</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>252 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    alpha_2 alpha_3       area           capital continent currency_code  \\\n",
       "0        AD     AND      468.0  Andorra la Vella        EU           EUR   \n",
       "1        AE     ARE    82880.0         Abu Dhabi        AS           AED   \n",
       "2        AF     AFG   647500.0             Kabul        AS           AFN   \n",
       "3        AG     ATG      443.0        St. John's                     XCD   \n",
       "4        AI     AIA      102.0        The Valley                     XCD   \n",
       "..      ...     ...        ...               ...       ...           ...   \n",
       "247      ZA     ZAF  1219912.0          Pretoria        AF           ZAR   \n",
       "248      ZM     ZMB   752614.0            Lusaka        AF           ZMW   \n",
       "249      ZW     ZWE   390580.0            Harare        AF           ZWL   \n",
       "250      CS     SCG   102350.0          Belgrade        EU           RSD   \n",
       "251      AN     ANT      960.0        Willemstad                     ANG   \n",
       "\n",
       "    currency_name eqivalent_fips_code fips  geoname_id  \\\n",
       "0            Euro                       AN     3041565   \n",
       "1          Dirham                       AE      290557   \n",
       "2         Afghani                       AF     1149361   \n",
       "3          Dollar                       AC     3576396   \n",
       "4          Dollar                       AV     3573511   \n",
       "..            ...                 ...  ...         ...   \n",
       "247          Rand                       SF      953987   \n",
       "248        Kwacha                       ZA      895949   \n",
       "249        Dollar                       ZI      878675   \n",
       "250         Dinar                       YI     8505033   \n",
       "251       Guilder                       NT     8505032   \n",
       "\n",
       "                                languages                   name  \\\n",
       "0                                      ca                Andorra   \n",
       "1                       ar-AE,fa,en,hi,ur   United Arab Emirates   \n",
       "2                       fa-AF,ps,uz-AF,tk            Afghanistan   \n",
       "3                                   en-AG    Antigua and Barbuda   \n",
       "4                                   en-AI               Anguilla   \n",
       "..                                    ...                    ...   \n",
       "247  zu,xh,af,nso,en-ZA,tn,st,ts,ss,ve,nr           South Africa   \n",
       "248          en-ZM,bem,loz,lun,lue,ny,toi                 Zambia   \n",
       "249                        en-ZW,sn,nr,nd               Zimbabwe   \n",
       "250                           cu,hu,sq,sr  Serbia and Montenegro   \n",
       "251                           nl-AN,en,es   Netherlands Antilles   \n",
       "\n",
       "               neighbours  numeric   phone  population postal_code_format  \\\n",
       "0                   ES,FR       20     376       84000              AD###   \n",
       "1                   SA,OM      784     971     4975593                      \n",
       "2       TM,CN,IR,TJ,PK,UZ        4      93    29121286                      \n",
       "3                               28  +1-268       86754                      \n",
       "4                              660  +1-264       13254                      \n",
       "..                    ...      ...     ...         ...                ...   \n",
       "247     ZW,SZ,MZ,BW,NA,LS      710      27    49000000               ####   \n",
       "248  ZW,TZ,MZ,CD,NA,MW,AO      894     260    13460305              #####   \n",
       "249           ZA,MZ,BW,ZM      716     263    13061000                      \n",
       "250  AL,HU,MK,RO,HR,BA,BG      891     381    10829175              #####   \n",
       "251                    GP      530     599      300000                      \n",
       "\n",
       "    postal_code_regex  tld  \n",
       "0    ^(?:AD)*(\\d{3})$  .ad  \n",
       "1                      .ae  \n",
       "2                      .af  \n",
       "3                      .ag  \n",
       "4                      .ai  \n",
       "..                ...  ...  \n",
       "247         ^(\\d{4})$  .za  \n",
       "248         ^(\\d{5})$  .zm  \n",
       "249                    .zw  \n",
       "250         ^(\\d{5})$  .cs  \n",
       "251                    .an  \n",
       "\n",
       "[252 rows x 19 columns]"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_espanol = df.replace(np.nan, '', regex=True)\n",
    "df_espanol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "0c60cbda-5308-4480-ae12-07624c537324",
   "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>alpha_2</th>\n",
       "      <th>alpha_3</th>\n",
       "      <th>area</th>\n",
       "      <th>capital</th>\n",
       "      <th>continent</th>\n",
       "      <th>currency_code</th>\n",
       "      <th>currency_name</th>\n",
       "      <th>eqivalent_fips_code</th>\n",
       "      <th>fips</th>\n",
       "      <th>geoname_id</th>\n",
       "      <th>languages</th>\n",
       "      <th>name</th>\n",
       "      <th>neighbours</th>\n",
       "      <th>numeric</th>\n",
       "      <th>phone</th>\n",
       "      <th>population</th>\n",
       "      <th>postal_code_format</th>\n",
       "      <th>postal_code_regex</th>\n",
       "      <th>tld</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AR</td>\n",
       "      <td>ARG</td>\n",
       "      <td>2766890.0</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>SA</td>\n",
       "      <td>ARS</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>AR</td>\n",
       "      <td>3865483</td>\n",
       "      <td>es-AR,en,it,de,fr,gn</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>CL,BO,UY,PY,BR</td>\n",
       "      <td>32</td>\n",
       "      <td>54</td>\n",
       "      <td>41343201</td>\n",
       "      <td>@####@@@</td>\n",
       "      <td>^[A-Z]?\\d{4}[A-Z]{0,3}$</td>\n",
       "      <td>.ar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>AW</td>\n",
       "      <td>ABW</td>\n",
       "      <td>193.0</td>\n",
       "      <td>Oranjestad</td>\n",
       "      <td></td>\n",
       "      <td>AWG</td>\n",
       "      <td>Guilder</td>\n",
       "      <td></td>\n",
       "      <td>AA</td>\n",
       "      <td>3577279</td>\n",
       "      <td>nl-AW,es,en</td>\n",
       "      <td>Aruba</td>\n",
       "      <td></td>\n",
       "      <td>533</td>\n",
       "      <td>297</td>\n",
       "      <td>71566</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.aw</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>BO</td>\n",
       "      <td>BOL</td>\n",
       "      <td>1098580.0</td>\n",
       "      <td>Sucre</td>\n",
       "      <td>SA</td>\n",
       "      <td>BOB</td>\n",
       "      <td>Boliviano</td>\n",
       "      <td></td>\n",
       "      <td>BL</td>\n",
       "      <td>3923057</td>\n",
       "      <td>es-BO,qu,ay</td>\n",
       "      <td>Bolivia</td>\n",
       "      <td>PE,CL,PY,BR,AR</td>\n",
       "      <td>68</td>\n",
       "      <td>591</td>\n",
       "      <td>9947418</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.bo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>BR</td>\n",
       "      <td>BRA</td>\n",
       "      <td>8511965.0</td>\n",
       "      <td>Brasilia</td>\n",
       "      <td>SA</td>\n",
       "      <td>BRL</td>\n",
       "      <td>Real</td>\n",
       "      <td></td>\n",
       "      <td>BR</td>\n",
       "      <td>3469034</td>\n",
       "      <td>pt-BR,es,en,fr</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>SR,PE,BO,UY,GY,PY,GF,VE,CO,AR</td>\n",
       "      <td>76</td>\n",
       "      <td>55</td>\n",
       "      <td>201103330</td>\n",
       "      <td>#####-###</td>\n",
       "      <td>^\\d{5}-\\d{3}$</td>\n",
       "      <td>.br</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>BZ</td>\n",
       "      <td>BLZ</td>\n",
       "      <td>22966.0</td>\n",
       "      <td>Belmopan</td>\n",
       "      <td></td>\n",
       "      <td>BZD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>BH</td>\n",
       "      <td>3582678</td>\n",
       "      <td>en-BZ,es</td>\n",
       "      <td>Belize</td>\n",
       "      <td>GT,MX</td>\n",
       "      <td>84</td>\n",
       "      <td>501</td>\n",
       "      <td>314522</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.bz</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>CL</td>\n",
       "      <td>CHL</td>\n",
       "      <td>756950.0</td>\n",
       "      <td>Santiago</td>\n",
       "      <td>SA</td>\n",
       "      <td>CLP</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>CI</td>\n",
       "      <td>3895114</td>\n",
       "      <td>es-CL</td>\n",
       "      <td>Chile</td>\n",
       "      <td>PE,BO,AR</td>\n",
       "      <td>152</td>\n",
       "      <td>56</td>\n",
       "      <td>16746491</td>\n",
       "      <td>#######</td>\n",
       "      <td>^(\\d{7})$</td>\n",
       "      <td>.cl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>CO</td>\n",
       "      <td>COL</td>\n",
       "      <td>1138910.0</td>\n",
       "      <td>Bogota</td>\n",
       "      <td>SA</td>\n",
       "      <td>COP</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>CO</td>\n",
       "      <td>3686110</td>\n",
       "      <td>es-CO</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>EC,PE,PA,BR,VE</td>\n",
       "      <td>170</td>\n",
       "      <td>57</td>\n",
       "      <td>47790000</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.co</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>CR</td>\n",
       "      <td>CRI</td>\n",
       "      <td>51100.0</td>\n",
       "      <td>San Jose</td>\n",
       "      <td></td>\n",
       "      <td>CRC</td>\n",
       "      <td>Colon</td>\n",
       "      <td></td>\n",
       "      <td>CS</td>\n",
       "      <td>3624060</td>\n",
       "      <td>es-CR,en</td>\n",
       "      <td>Costa Rica</td>\n",
       "      <td>PA,NI</td>\n",
       "      <td>188</td>\n",
       "      <td>506</td>\n",
       "      <td>4516220</td>\n",
       "      <td>####</td>\n",
       "      <td>^(\\d{4})$</td>\n",
       "      <td>.cr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>CU</td>\n",
       "      <td>CUB</td>\n",
       "      <td>110860.0</td>\n",
       "      <td>Havana</td>\n",
       "      <td></td>\n",
       "      <td>CUP</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>CU</td>\n",
       "      <td>3562981</td>\n",
       "      <td>es-CU</td>\n",
       "      <td>Cuba</td>\n",
       "      <td>US</td>\n",
       "      <td>192</td>\n",
       "      <td>53</td>\n",
       "      <td>11423000</td>\n",
       "      <td>CP #####</td>\n",
       "      <td>^(?:CP)*(\\d{5})$</td>\n",
       "      <td>.cu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>DO</td>\n",
       "      <td>DOM</td>\n",
       "      <td>48730.0</td>\n",
       "      <td>Santo Domingo</td>\n",
       "      <td></td>\n",
       "      <td>DOP</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>DR</td>\n",
       "      <td>3508796</td>\n",
       "      <td>es-DO</td>\n",
       "      <td>Dominican Republic</td>\n",
       "      <td>HT</td>\n",
       "      <td>214</td>\n",
       "      <td>+1-809 and 1-829</td>\n",
       "      <td>9823821</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.do</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>EC</td>\n",
       "      <td>ECU</td>\n",
       "      <td>283560.0</td>\n",
       "      <td>Quito</td>\n",
       "      <td>SA</td>\n",
       "      <td>USD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>EC</td>\n",
       "      <td>3658394</td>\n",
       "      <td>es-EC</td>\n",
       "      <td>Ecuador</td>\n",
       "      <td>PE,CO</td>\n",
       "      <td>218</td>\n",
       "      <td>593</td>\n",
       "      <td>14790608</td>\n",
       "      <td>@####@</td>\n",
       "      <td>^([a-zA-Z]\\d{4}[a-zA-Z])$</td>\n",
       "      <td>.ec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>ES</td>\n",
       "      <td>ESP</td>\n",
       "      <td>504782.0</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>EU</td>\n",
       "      <td>EUR</td>\n",
       "      <td>Euro</td>\n",
       "      <td></td>\n",
       "      <td>SP</td>\n",
       "      <td>2510769</td>\n",
       "      <td>es-ES,ca,gl,eu,oc</td>\n",
       "      <td>Spain</td>\n",
       "      <td>AD,PT,GI,FR,MA</td>\n",
       "      <td>724</td>\n",
       "      <td>34</td>\n",
       "      <td>46505963</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.es</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>GI</td>\n",
       "      <td>GIB</td>\n",
       "      <td>6.5</td>\n",
       "      <td>Gibraltar</td>\n",
       "      <td>EU</td>\n",
       "      <td>GIP</td>\n",
       "      <td>Pound</td>\n",
       "      <td></td>\n",
       "      <td>GI</td>\n",
       "      <td>2411586</td>\n",
       "      <td>en-GI,es,it,pt</td>\n",
       "      <td>Gibraltar</td>\n",
       "      <td>ES</td>\n",
       "      <td>292</td>\n",
       "      <td>350</td>\n",
       "      <td>27884</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.gi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>GQ</td>\n",
       "      <td>GNQ</td>\n",
       "      <td>28051.0</td>\n",
       "      <td>Malabo</td>\n",
       "      <td>AF</td>\n",
       "      <td>XAF</td>\n",
       "      <td>Franc</td>\n",
       "      <td></td>\n",
       "      <td>EK</td>\n",
       "      <td>2309096</td>\n",
       "      <td>es-GQ,fr</td>\n",
       "      <td>Equatorial Guinea</td>\n",
       "      <td>GA,CM</td>\n",
       "      <td>226</td>\n",
       "      <td>240</td>\n",
       "      <td>1014999</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.gq</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>GT</td>\n",
       "      <td>GTM</td>\n",
       "      <td>108890.0</td>\n",
       "      <td>Guatemala City</td>\n",
       "      <td></td>\n",
       "      <td>GTQ</td>\n",
       "      <td>Quetzal</td>\n",
       "      <td></td>\n",
       "      <td>GT</td>\n",
       "      <td>3595528</td>\n",
       "      <td>es-GT</td>\n",
       "      <td>Guatemala</td>\n",
       "      <td>MX,HN,BZ,SV</td>\n",
       "      <td>320</td>\n",
       "      <td>502</td>\n",
       "      <td>13550440</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.gt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>HN</td>\n",
       "      <td>HND</td>\n",
       "      <td>112090.0</td>\n",
       "      <td>Tegucigalpa</td>\n",
       "      <td></td>\n",
       "      <td>HNL</td>\n",
       "      <td>Lempira</td>\n",
       "      <td></td>\n",
       "      <td>HO</td>\n",
       "      <td>3608932</td>\n",
       "      <td>es-HN</td>\n",
       "      <td>Honduras</td>\n",
       "      <td>GT,NI,SV</td>\n",
       "      <td>340</td>\n",
       "      <td>504</td>\n",
       "      <td>7989415</td>\n",
       "      <td>@@####</td>\n",
       "      <td>^([A-Z]{2}\\d{4})$</td>\n",
       "      <td>.hn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>MX</td>\n",
       "      <td>MEX</td>\n",
       "      <td>1972550.0</td>\n",
       "      <td>Mexico City</td>\n",
       "      <td></td>\n",
       "      <td>MXN</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>MX</td>\n",
       "      <td>3996063</td>\n",
       "      <td>es-MX</td>\n",
       "      <td>Mexico</td>\n",
       "      <td>GT,US,BZ</td>\n",
       "      <td>484</td>\n",
       "      <td>52</td>\n",
       "      <td>112468855</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.mx</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>NI</td>\n",
       "      <td>NIC</td>\n",
       "      <td>129494.0</td>\n",
       "      <td>Managua</td>\n",
       "      <td></td>\n",
       "      <td>NIO</td>\n",
       "      <td>Cordoba</td>\n",
       "      <td></td>\n",
       "      <td>NU</td>\n",
       "      <td>3617476</td>\n",
       "      <td>es-NI,en</td>\n",
       "      <td>Nicaragua</td>\n",
       "      <td>CR,HN</td>\n",
       "      <td>558</td>\n",
       "      <td>505</td>\n",
       "      <td>5995928</td>\n",
       "      <td>###-###-#</td>\n",
       "      <td>^(\\d{7})$</td>\n",
       "      <td>.ni</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>PA</td>\n",
       "      <td>PAN</td>\n",
       "      <td>78200.0</td>\n",
       "      <td>Panama City</td>\n",
       "      <td></td>\n",
       "      <td>PAB</td>\n",
       "      <td>Balboa</td>\n",
       "      <td></td>\n",
       "      <td>PM</td>\n",
       "      <td>3703430</td>\n",
       "      <td>es-PA,en</td>\n",
       "      <td>Panama</td>\n",
       "      <td>CR,CO</td>\n",
       "      <td>591</td>\n",
       "      <td>507</td>\n",
       "      <td>3410676</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.pa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>PE</td>\n",
       "      <td>PER</td>\n",
       "      <td>1285220.0</td>\n",
       "      <td>Lima</td>\n",
       "      <td>SA</td>\n",
       "      <td>PEN</td>\n",
       "      <td>Sol</td>\n",
       "      <td></td>\n",
       "      <td>PE</td>\n",
       "      <td>3932488</td>\n",
       "      <td>es-PE,qu,ay</td>\n",
       "      <td>Peru</td>\n",
       "      <td>EC,CL,BO,BR,CO</td>\n",
       "      <td>604</td>\n",
       "      <td>51</td>\n",
       "      <td>29907003</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.pe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>PR</td>\n",
       "      <td>PRI</td>\n",
       "      <td>9104.0</td>\n",
       "      <td>San Juan</td>\n",
       "      <td></td>\n",
       "      <td>USD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>RQ</td>\n",
       "      <td>4566966</td>\n",
       "      <td>en-PR,es-PR</td>\n",
       "      <td>Puerto Rico</td>\n",
       "      <td></td>\n",
       "      <td>630</td>\n",
       "      <td>+1-787 and 1-939</td>\n",
       "      <td>3916632</td>\n",
       "      <td>#####-####</td>\n",
       "      <td>^00[679]\\d{2}(?:-\\d{4})?$</td>\n",
       "      <td>.pr</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>PY</td>\n",
       "      <td>PRY</td>\n",
       "      <td>406750.0</td>\n",
       "      <td>Asuncion</td>\n",
       "      <td>SA</td>\n",
       "      <td>PYG</td>\n",
       "      <td>Guarani</td>\n",
       "      <td></td>\n",
       "      <td>PA</td>\n",
       "      <td>3437598</td>\n",
       "      <td>es-PY,gn</td>\n",
       "      <td>Paraguay</td>\n",
       "      <td>BO,BR,AR</td>\n",
       "      <td>600</td>\n",
       "      <td>595</td>\n",
       "      <td>6375830</td>\n",
       "      <td>####</td>\n",
       "      <td>^(\\d{4})$</td>\n",
       "      <td>.py</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>QA</td>\n",
       "      <td>QAT</td>\n",
       "      <td>11437.0</td>\n",
       "      <td>Doha</td>\n",
       "      <td>AS</td>\n",
       "      <td>QAR</td>\n",
       "      <td>Rial</td>\n",
       "      <td></td>\n",
       "      <td>QA</td>\n",
       "      <td>289688</td>\n",
       "      <td>ar-QA,es</td>\n",
       "      <td>Qatar</td>\n",
       "      <td>SA</td>\n",
       "      <td>634</td>\n",
       "      <td>974</td>\n",
       "      <td>840926</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.qa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>SV</td>\n",
       "      <td>SLV</td>\n",
       "      <td>21040.0</td>\n",
       "      <td>San Salvador</td>\n",
       "      <td></td>\n",
       "      <td>USD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>ES</td>\n",
       "      <td>3585968</td>\n",
       "      <td>es-SV</td>\n",
       "      <td>El Salvador</td>\n",
       "      <td>GT,HN</td>\n",
       "      <td>222</td>\n",
       "      <td>503</td>\n",
       "      <td>6052064</td>\n",
       "      <td>CP ####</td>\n",
       "      <td>^(?:CP)*(\\d{4})$</td>\n",
       "      <td>.sv</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>TT</td>\n",
       "      <td>TTO</td>\n",
       "      <td>5128.0</td>\n",
       "      <td>Port of Spain</td>\n",
       "      <td></td>\n",
       "      <td>TTD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>TD</td>\n",
       "      <td>3573591</td>\n",
       "      <td>en-TT,hns,fr,es,zh</td>\n",
       "      <td>Trinidad and Tobago</td>\n",
       "      <td></td>\n",
       "      <td>780</td>\n",
       "      <td>+1-868</td>\n",
       "      <td>1228691</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.tt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>US</td>\n",
       "      <td>USA</td>\n",
       "      <td>9629091.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td></td>\n",
       "      <td>USD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>US</td>\n",
       "      <td>6252001</td>\n",
       "      <td>en-US,es-US,haw,fr</td>\n",
       "      <td>United States</td>\n",
       "      <td>CA,MX,CU</td>\n",
       "      <td>840</td>\n",
       "      <td>1</td>\n",
       "      <td>310232863</td>\n",
       "      <td>#####-####</td>\n",
       "      <td>^\\d{5}(-\\d{4})?$</td>\n",
       "      <td>.us</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>UY</td>\n",
       "      <td>URY</td>\n",
       "      <td>176220.0</td>\n",
       "      <td>Montevideo</td>\n",
       "      <td>SA</td>\n",
       "      <td>UYU</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>UY</td>\n",
       "      <td>3439705</td>\n",
       "      <td>es-UY</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>BR,AR</td>\n",
       "      <td>858</td>\n",
       "      <td>598</td>\n",
       "      <td>3477000</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.uy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>VE</td>\n",
       "      <td>VEN</td>\n",
       "      <td>912050.0</td>\n",
       "      <td>Caracas</td>\n",
       "      <td>SA</td>\n",
       "      <td>VEF</td>\n",
       "      <td>Bolivar</td>\n",
       "      <td></td>\n",
       "      <td>VE</td>\n",
       "      <td>3625428</td>\n",
       "      <td>es-VE</td>\n",
       "      <td>Venezuela</td>\n",
       "      <td>GY,BR,CO</td>\n",
       "      <td>862</td>\n",
       "      <td>58</td>\n",
       "      <td>27223228</td>\n",
       "      <td>####</td>\n",
       "      <td>^(\\d{4})$</td>\n",
       "      <td>.ve</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>AN</td>\n",
       "      <td>ANT</td>\n",
       "      <td>960.0</td>\n",
       "      <td>Willemstad</td>\n",
       "      <td></td>\n",
       "      <td>ANG</td>\n",
       "      <td>Guilder</td>\n",
       "      <td></td>\n",
       "      <td>NT</td>\n",
       "      <td>8505032</td>\n",
       "      <td>nl-AN,en,es</td>\n",
       "      <td>Netherlands Antilles</td>\n",
       "      <td>GP</td>\n",
       "      <td>530</td>\n",
       "      <td>599</td>\n",
       "      <td>300000</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.an</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    alpha_2 alpha_3       area         capital continent currency_code  \\\n",
       "9        AR     ARG  2766890.0    Buenos Aires        SA           ARS   \n",
       "13       AW     ABW      193.0      Oranjestad                     AWG   \n",
       "28       BO     BOL  1098580.0           Sucre        SA           BOB   \n",
       "30       BR     BRA  8511965.0        Brasilia        SA           BRL   \n",
       "36       BZ     BLZ    22966.0        Belmopan                     BZD   \n",
       "45       CL     CHL   756950.0        Santiago        SA           CLP   \n",
       "48       CO     COL  1138910.0          Bogota        SA           COP   \n",
       "49       CR     CRI    51100.0        San Jose                     CRC   \n",
       "50       CU     CUB   110860.0          Havana                     CUP   \n",
       "60       DO     DOM    48730.0   Santo Domingo                     DOP   \n",
       "62       EC     ECU   283560.0           Quito        SA           USD   \n",
       "67       ES     ESP   504782.0          Madrid        EU           EUR   \n",
       "82       GI     GIB        6.5       Gibraltar        EU           GIP   \n",
       "87       GQ     GNQ    28051.0          Malabo        AF           XAF   \n",
       "90       GT     GTM   108890.0  Guatemala City                     GTQ   \n",
       "96       HN     HND   112090.0     Tegucigalpa                     HNL   \n",
       "157      MX     MEX  1972550.0     Mexico City                     MXN   \n",
       "165      NI     NIC   129494.0         Managua                     NIO   \n",
       "173      PA     PAN    78200.0     Panama City                     PAB   \n",
       "174      PE     PER  1285220.0            Lima        SA           PEN   \n",
       "182      PR     PRI     9104.0        San Juan                     USD   \n",
       "186      PY     PRY   406750.0        Asuncion        SA           PYG   \n",
       "187      QA     QAT    11437.0            Doha        AS           QAR   \n",
       "210      SV     SLV    21040.0    San Salvador                     USD   \n",
       "226      TT     TTO     5128.0   Port of Spain                     TTD   \n",
       "233      US     USA  9629091.0      Washington                     USD   \n",
       "234      UY     URY   176220.0      Montevideo        SA           UYU   \n",
       "238      VE     VEN   912050.0         Caracas        SA           VEF   \n",
       "251      AN     ANT      960.0      Willemstad                     ANG   \n",
       "\n",
       "    currency_name eqivalent_fips_code fips  geoname_id             languages  \\\n",
       "9            Peso                       AR     3865483  es-AR,en,it,de,fr,gn   \n",
       "13        Guilder                       AA     3577279           nl-AW,es,en   \n",
       "28      Boliviano                       BL     3923057           es-BO,qu,ay   \n",
       "30           Real                       BR     3469034        pt-BR,es,en,fr   \n",
       "36         Dollar                       BH     3582678              en-BZ,es   \n",
       "45           Peso                       CI     3895114                 es-CL   \n",
       "48           Peso                       CO     3686110                 es-CO   \n",
       "49          Colon                       CS     3624060              es-CR,en   \n",
       "50           Peso                       CU     3562981                 es-CU   \n",
       "60           Peso                       DR     3508796                 es-DO   \n",
       "62         Dollar                       EC     3658394                 es-EC   \n",
       "67           Euro                       SP     2510769     es-ES,ca,gl,eu,oc   \n",
       "82          Pound                       GI     2411586        en-GI,es,it,pt   \n",
       "87          Franc                       EK     2309096              es-GQ,fr   \n",
       "90        Quetzal                       GT     3595528                 es-GT   \n",
       "96        Lempira                       HO     3608932                 es-HN   \n",
       "157          Peso                       MX     3996063                 es-MX   \n",
       "165       Cordoba                       NU     3617476              es-NI,en   \n",
       "173        Balboa                       PM     3703430              es-PA,en   \n",
       "174           Sol                       PE     3932488           es-PE,qu,ay   \n",
       "182        Dollar                       RQ     4566966           en-PR,es-PR   \n",
       "186       Guarani                       PA     3437598              es-PY,gn   \n",
       "187          Rial                       QA      289688              ar-QA,es   \n",
       "210        Dollar                       ES     3585968                 es-SV   \n",
       "226        Dollar                       TD     3573591    en-TT,hns,fr,es,zh   \n",
       "233        Dollar                       US     6252001    en-US,es-US,haw,fr   \n",
       "234          Peso                       UY     3439705                 es-UY   \n",
       "238       Bolivar                       VE     3625428                 es-VE   \n",
       "251       Guilder                       NT     8505032           nl-AN,en,es   \n",
       "\n",
       "                     name                     neighbours  numeric  \\\n",
       "9               Argentina                 CL,BO,UY,PY,BR       32   \n",
       "13                  Aruba                                     533   \n",
       "28                Bolivia                 PE,CL,PY,BR,AR       68   \n",
       "30                 Brazil  SR,PE,BO,UY,GY,PY,GF,VE,CO,AR       76   \n",
       "36                 Belize                          GT,MX       84   \n",
       "45                  Chile                       PE,BO,AR      152   \n",
       "48               Colombia                 EC,PE,PA,BR,VE      170   \n",
       "49             Costa Rica                          PA,NI      188   \n",
       "50                   Cuba                             US      192   \n",
       "60     Dominican Republic                             HT      214   \n",
       "62                Ecuador                          PE,CO      218   \n",
       "67                  Spain                 AD,PT,GI,FR,MA      724   \n",
       "82              Gibraltar                             ES      292   \n",
       "87      Equatorial Guinea                          GA,CM      226   \n",
       "90              Guatemala                    MX,HN,BZ,SV      320   \n",
       "96               Honduras                       GT,NI,SV      340   \n",
       "157                Mexico                       GT,US,BZ      484   \n",
       "165             Nicaragua                          CR,HN      558   \n",
       "173                Panama                          CR,CO      591   \n",
       "174                  Peru                 EC,CL,BO,BR,CO      604   \n",
       "182           Puerto Rico                                     630   \n",
       "186              Paraguay                       BO,BR,AR      600   \n",
       "187                 Qatar                             SA      634   \n",
       "210           El Salvador                          GT,HN      222   \n",
       "226   Trinidad and Tobago                                     780   \n",
       "233         United States                       CA,MX,CU      840   \n",
       "234               Uruguay                          BR,AR      858   \n",
       "238             Venezuela                       GY,BR,CO      862   \n",
       "251  Netherlands Antilles                             GP      530   \n",
       "\n",
       "                phone  population postal_code_format  \\\n",
       "9                  54    41343201           @####@@@   \n",
       "13                297       71566                      \n",
       "28                591     9947418                      \n",
       "30                 55   201103330          #####-###   \n",
       "36                501      314522                      \n",
       "45                 56    16746491            #######   \n",
       "48                 57    47790000                      \n",
       "49                506     4516220               ####   \n",
       "50                 53    11423000           CP #####   \n",
       "60   +1-809 and 1-829     9823821              #####   \n",
       "62                593    14790608             @####@   \n",
       "67                 34    46505963              #####   \n",
       "82                350       27884                      \n",
       "87                240     1014999                      \n",
       "90                502    13550440              #####   \n",
       "96                504     7989415             @@####   \n",
       "157                52   112468855              #####   \n",
       "165               505     5995928          ###-###-#   \n",
       "173               507     3410676                      \n",
       "174                51    29907003                      \n",
       "182  +1-787 and 1-939     3916632         #####-####   \n",
       "186               595     6375830               ####   \n",
       "187               974      840926                      \n",
       "210               503     6052064            CP ####   \n",
       "226            +1-868     1228691                      \n",
       "233                 1   310232863         #####-####   \n",
       "234               598     3477000              #####   \n",
       "238                58    27223228               ####   \n",
       "251               599      300000                      \n",
       "\n",
       "             postal_code_regex  tld  \n",
       "9      ^[A-Z]?\\d{4}[A-Z]{0,3}$  .ar  \n",
       "13                              .aw  \n",
       "28                              .bo  \n",
       "30               ^\\d{5}-\\d{3}$  .br  \n",
       "36                              .bz  \n",
       "45                   ^(\\d{7})$  .cl  \n",
       "48                              .co  \n",
       "49                   ^(\\d{4})$  .cr  \n",
       "50            ^(?:CP)*(\\d{5})$  .cu  \n",
       "60                   ^(\\d{5})$  .do  \n",
       "62   ^([a-zA-Z]\\d{4}[a-zA-Z])$  .ec  \n",
       "67                   ^(\\d{5})$  .es  \n",
       "82                              .gi  \n",
       "87                              .gq  \n",
       "90                   ^(\\d{5})$  .gt  \n",
       "96           ^([A-Z]{2}\\d{4})$  .hn  \n",
       "157                  ^(\\d{5})$  .mx  \n",
       "165                  ^(\\d{7})$  .ni  \n",
       "173                             .pa  \n",
       "174                             .pe  \n",
       "182  ^00[679]\\d{2}(?:-\\d{4})?$  .pr  \n",
       "186                  ^(\\d{4})$  .py  \n",
       "187                             .qa  \n",
       "210           ^(?:CP)*(\\d{4})$  .sv  \n",
       "226                             .tt  \n",
       "233           ^\\d{5}(-\\d{4})?$  .us  \n",
       "234                  ^(\\d{5})$  .uy  \n",
       "238                  ^(\\d{4})$  .ve  \n",
       "251                             .an  "
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_espanol = df_espanol[ df_espanol['languages'].str.contains('es') ]\n",
    "df_espanol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "1ddff927-da86-4f5e-b6ca-651288f6f970",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29, 19)"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_espanol.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "39a66d4b-71f5-466d-9144-73342b810cd3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='name'>"
      ]
     },
     "execution_count": 212,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_espanol.set_index('name')[['population','area']].plot(kind='bar',rot=65,figsize=(20,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "275f1072-cd7a-4d39-a960-68bd74369c43",
   "metadata": {},
   "source": [
    "##### Vamos a hacer detección de Outliers, (con fines educativos) en este caso definimos como limite superior (e inferior) la media más (menos) “2 veces la desviación estándar” que muchas veces es tomada como máximos de tolerancia."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "56418f8a-5442-4ae2-97ab-6a53508ed6b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "anomalies = []\n",
    " \n",
    "# Funcion ejemplo para detección de outliers\n",
    "def find_anomalies(data):\n",
    "    # Set upper and lower limit to 2 standard deviation\n",
    "    data_std = data.std()\n",
    "    data_mean = data.mean()\n",
    "    anomaly_cut_off = data_std * 1\n",
    "    lower_limit  = data_mean - anomaly_cut_off \n",
    "    upper_limit = data_mean + anomaly_cut_off\n",
    "    print(lower_limit.iloc[0])\n",
    "    print(upper_limit.iloc[0])\n",
    " \n",
    "    # Generate outliers\n",
    "    for index, row in data.iterrows():\n",
    "        outlier = row # # obtener primer columna\n",
    "        # print(outlier)\n",
    "        if (outlier.iloc[0] > upper_limit.iloc[0]) or (outlier.iloc[0] < lower_limit.iloc[0]):\n",
    "            anomalies.append(index)\n",
    "    return anomalies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "40011561-9ee2-4841-ac94-2cfc80f89128",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-35257240.59444752\n",
      "99973693.97375786\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['BRA', 'MEX', 'USA']"
      ]
     },
     "execution_count": 214,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "find_anomalies(df_espanol.set_index('alpha_3')[['population']])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72df7a9d-ec03-4aaf-b440-19f28c91a570",
   "metadata": {},
   "source": [
    "#### Detectamos como outliers a Brasil y a USA. Los eliminamos y graficamos ordenado por población de menor a mayor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "1542836d-2cd2-4fd6-8f68-9d9b8a2c81df",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Public\\Documents\\Wondershare\\CreatorTemp\\ipykernel_9420\\1248102128.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  df_espanol.drop([30, 157 ,233], inplace=True)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='alpha_3'>"
      ]
     },
     "execution_count": 215,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Quitemos BRA y USA por ser outlies y volvamos a graficar:\n",
    "df_espanol.drop([30, 157 ,233], inplace=True)\n",
    "df_espanol.set_index('alpha_3')[['population','area']].sort_values([\"population\"]).plot(kind='bar',rot=65,figsize=(20,10))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee780e79-a79b-47d8-add3-90011b279289",
   "metadata": {},
   "source": [
    "##### Visualización por Área"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "id": "e3b55608-113e-4884-99c6-cfbae75e072b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='alpha_3'>"
      ]
     },
     "execution_count": 216,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_espanol.set_index('alpha_3')[['area']].sort_values([\"area\"]).plot(kind='bar',rot=65,figsize=(20,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "82a6fe69-8d57-46ab-8ae8-9f92d207efee",
   "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>alpha_2</th>\n",
       "      <th>area</th>\n",
       "      <th>capital</th>\n",
       "      <th>continent</th>\n",
       "      <th>currency_code</th>\n",
       "      <th>currency_name</th>\n",
       "      <th>eqivalent_fips_code</th>\n",
       "      <th>fips</th>\n",
       "      <th>geoname_id</th>\n",
       "      <th>languages</th>\n",
       "      <th>name</th>\n",
       "      <th>neighbours</th>\n",
       "      <th>numeric</th>\n",
       "      <th>phone</th>\n",
       "      <th>population</th>\n",
       "      <th>postal_code_format</th>\n",
       "      <th>postal_code_regex</th>\n",
       "      <th>tld</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>alpha_3</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></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>ARG</th>\n",
       "      <td>AR</td>\n",
       "      <td>2766890.0</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>SA</td>\n",
       "      <td>ARS</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>AR</td>\n",
       "      <td>3865483</td>\n",
       "      <td>es-AR,en,it,de,fr,gn</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>CL,BO,UY,PY,BR</td>\n",
       "      <td>32</td>\n",
       "      <td>54</td>\n",
       "      <td>41343201</td>\n",
       "      <td>@####@@@</td>\n",
       "      <td>^[A-Z]?\\d{4}[A-Z]{0,3}$</td>\n",
       "      <td>.ar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOL</th>\n",
       "      <td>BO</td>\n",
       "      <td>1098580.0</td>\n",
       "      <td>Sucre</td>\n",
       "      <td>SA</td>\n",
       "      <td>BOB</td>\n",
       "      <td>Boliviano</td>\n",
       "      <td></td>\n",
       "      <td>BL</td>\n",
       "      <td>3923057</td>\n",
       "      <td>es-BO,qu,ay</td>\n",
       "      <td>Bolivia</td>\n",
       "      <td>PE,CL,PY,BR,AR</td>\n",
       "      <td>68</td>\n",
       "      <td>591</td>\n",
       "      <td>9947418</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.bo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHL</th>\n",
       "      <td>CL</td>\n",
       "      <td>756950.0</td>\n",
       "      <td>Santiago</td>\n",
       "      <td>SA</td>\n",
       "      <td>CLP</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>CI</td>\n",
       "      <td>3895114</td>\n",
       "      <td>es-CL</td>\n",
       "      <td>Chile</td>\n",
       "      <td>PE,BO,AR</td>\n",
       "      <td>152</td>\n",
       "      <td>56</td>\n",
       "      <td>16746491</td>\n",
       "      <td>#######</td>\n",
       "      <td>^(\\d{7})$</td>\n",
       "      <td>.cl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COL</th>\n",
       "      <td>CO</td>\n",
       "      <td>1138910.0</td>\n",
       "      <td>Bogota</td>\n",
       "      <td>SA</td>\n",
       "      <td>COP</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>CO</td>\n",
       "      <td>3686110</td>\n",
       "      <td>es-CO</td>\n",
       "      <td>Colombia</td>\n",
       "      <td>EC,PE,PA,BR,VE</td>\n",
       "      <td>170</td>\n",
       "      <td>57</td>\n",
       "      <td>47790000</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.co</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CUB</th>\n",
       "      <td>CU</td>\n",
       "      <td>110860.0</td>\n",
       "      <td>Havana</td>\n",
       "      <td></td>\n",
       "      <td>CUP</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>CU</td>\n",
       "      <td>3562981</td>\n",
       "      <td>es-CU</td>\n",
       "      <td>Cuba</td>\n",
       "      <td>US</td>\n",
       "      <td>192</td>\n",
       "      <td>53</td>\n",
       "      <td>11423000</td>\n",
       "      <td>CP #####</td>\n",
       "      <td>^(?:CP)*(\\d{5})$</td>\n",
       "      <td>.cu</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ECU</th>\n",
       "      <td>EC</td>\n",
       "      <td>283560.0</td>\n",
       "      <td>Quito</td>\n",
       "      <td>SA</td>\n",
       "      <td>USD</td>\n",
       "      <td>Dollar</td>\n",
       "      <td></td>\n",
       "      <td>EC</td>\n",
       "      <td>3658394</td>\n",
       "      <td>es-EC</td>\n",
       "      <td>Ecuador</td>\n",
       "      <td>PE,CO</td>\n",
       "      <td>218</td>\n",
       "      <td>593</td>\n",
       "      <td>14790608</td>\n",
       "      <td>@####@</td>\n",
       "      <td>^([a-zA-Z]\\d{4}[a-zA-Z])$</td>\n",
       "      <td>.ec</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ESP</th>\n",
       "      <td>ES</td>\n",
       "      <td>504782.0</td>\n",
       "      <td>Madrid</td>\n",
       "      <td>EU</td>\n",
       "      <td>EUR</td>\n",
       "      <td>Euro</td>\n",
       "      <td></td>\n",
       "      <td>SP</td>\n",
       "      <td>2510769</td>\n",
       "      <td>es-ES,ca,gl,eu,oc</td>\n",
       "      <td>Spain</td>\n",
       "      <td>AD,PT,GI,FR,MA</td>\n",
       "      <td>724</td>\n",
       "      <td>34</td>\n",
       "      <td>46505963</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.es</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HND</th>\n",
       "      <td>HN</td>\n",
       "      <td>112090.0</td>\n",
       "      <td>Tegucigalpa</td>\n",
       "      <td></td>\n",
       "      <td>HNL</td>\n",
       "      <td>Lempira</td>\n",
       "      <td></td>\n",
       "      <td>HO</td>\n",
       "      <td>3608932</td>\n",
       "      <td>es-HN</td>\n",
       "      <td>Honduras</td>\n",
       "      <td>GT,NI,SV</td>\n",
       "      <td>340</td>\n",
       "      <td>504</td>\n",
       "      <td>7989415</td>\n",
       "      <td>@@####</td>\n",
       "      <td>^([A-Z]{2}\\d{4})$</td>\n",
       "      <td>.hn</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NIC</th>\n",
       "      <td>NI</td>\n",
       "      <td>129494.0</td>\n",
       "      <td>Managua</td>\n",
       "      <td></td>\n",
       "      <td>NIO</td>\n",
       "      <td>Cordoba</td>\n",
       "      <td></td>\n",
       "      <td>NU</td>\n",
       "      <td>3617476</td>\n",
       "      <td>es-NI,en</td>\n",
       "      <td>Nicaragua</td>\n",
       "      <td>CR,HN</td>\n",
       "      <td>558</td>\n",
       "      <td>505</td>\n",
       "      <td>5995928</td>\n",
       "      <td>###-###-#</td>\n",
       "      <td>^(\\d{7})$</td>\n",
       "      <td>.ni</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PER</th>\n",
       "      <td>PE</td>\n",
       "      <td>1285220.0</td>\n",
       "      <td>Lima</td>\n",
       "      <td>SA</td>\n",
       "      <td>PEN</td>\n",
       "      <td>Sol</td>\n",
       "      <td></td>\n",
       "      <td>PE</td>\n",
       "      <td>3932488</td>\n",
       "      <td>es-PE,qu,ay</td>\n",
       "      <td>Peru</td>\n",
       "      <td>EC,CL,BO,BR,CO</td>\n",
       "      <td>604</td>\n",
       "      <td>51</td>\n",
       "      <td>29907003</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>.pe</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PRY</th>\n",
       "      <td>PY</td>\n",
       "      <td>406750.0</td>\n",
       "      <td>Asuncion</td>\n",
       "      <td>SA</td>\n",
       "      <td>PYG</td>\n",
       "      <td>Guarani</td>\n",
       "      <td></td>\n",
       "      <td>PA</td>\n",
       "      <td>3437598</td>\n",
       "      <td>es-PY,gn</td>\n",
       "      <td>Paraguay</td>\n",
       "      <td>BO,BR,AR</td>\n",
       "      <td>600</td>\n",
       "      <td>595</td>\n",
       "      <td>6375830</td>\n",
       "      <td>####</td>\n",
       "      <td>^(\\d{4})$</td>\n",
       "      <td>.py</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>URY</th>\n",
       "      <td>UY</td>\n",
       "      <td>176220.0</td>\n",
       "      <td>Montevideo</td>\n",
       "      <td>SA</td>\n",
       "      <td>UYU</td>\n",
       "      <td>Peso</td>\n",
       "      <td></td>\n",
       "      <td>UY</td>\n",
       "      <td>3439705</td>\n",
       "      <td>es-UY</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>BR,AR</td>\n",
       "      <td>858</td>\n",
       "      <td>598</td>\n",
       "      <td>3477000</td>\n",
       "      <td>#####</td>\n",
       "      <td>^(\\d{5})$</td>\n",
       "      <td>.uy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VEN</th>\n",
       "      <td>VE</td>\n",
       "      <td>912050.0</td>\n",
       "      <td>Caracas</td>\n",
       "      <td>SA</td>\n",
       "      <td>VEF</td>\n",
       "      <td>Bolivar</td>\n",
       "      <td></td>\n",
       "      <td>VE</td>\n",
       "      <td>3625428</td>\n",
       "      <td>es-VE</td>\n",
       "      <td>Venezuela</td>\n",
       "      <td>GY,BR,CO</td>\n",
       "      <td>862</td>\n",
       "      <td>58</td>\n",
       "      <td>27223228</td>\n",
       "      <td>####</td>\n",
       "      <td>^(\\d{4})$</td>\n",
       "      <td>.ve</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        alpha_2       area       capital continent currency_code  \\\n",
       "alpha_3                                                            \n",
       "ARG          AR  2766890.0  Buenos Aires        SA           ARS   \n",
       "BOL          BO  1098580.0         Sucre        SA           BOB   \n",
       "CHL          CL   756950.0      Santiago        SA           CLP   \n",
       "COL          CO  1138910.0        Bogota        SA           COP   \n",
       "CUB          CU   110860.0        Havana                     CUP   \n",
       "ECU          EC   283560.0         Quito        SA           USD   \n",
       "ESP          ES   504782.0        Madrid        EU           EUR   \n",
       "HND          HN   112090.0   Tegucigalpa                     HNL   \n",
       "NIC          NI   129494.0       Managua                     NIO   \n",
       "PER          PE  1285220.0          Lima        SA           PEN   \n",
       "PRY          PY   406750.0      Asuncion        SA           PYG   \n",
       "URY          UY   176220.0    Montevideo        SA           UYU   \n",
       "VEN          VE   912050.0       Caracas        SA           VEF   \n",
       "\n",
       "        currency_name eqivalent_fips_code fips  geoname_id  \\\n",
       "alpha_3                                                      \n",
       "ARG              Peso                       AR     3865483   \n",
       "BOL         Boliviano                       BL     3923057   \n",
       "CHL              Peso                       CI     3895114   \n",
       "COL              Peso                       CO     3686110   \n",
       "CUB              Peso                       CU     3562981   \n",
       "ECU            Dollar                       EC     3658394   \n",
       "ESP              Euro                       SP     2510769   \n",
       "HND           Lempira                       HO     3608932   \n",
       "NIC           Cordoba                       NU     3617476   \n",
       "PER               Sol                       PE     3932488   \n",
       "PRY           Guarani                       PA     3437598   \n",
       "URY              Peso                       UY     3439705   \n",
       "VEN           Bolivar                       VE     3625428   \n",
       "\n",
       "                    languages       name      neighbours  numeric phone  \\\n",
       "alpha_3                                                                   \n",
       "ARG      es-AR,en,it,de,fr,gn  Argentina  CL,BO,UY,PY,BR       32    54   \n",
       "BOL               es-BO,qu,ay    Bolivia  PE,CL,PY,BR,AR       68   591   \n",
       "CHL                     es-CL      Chile        PE,BO,AR      152    56   \n",
       "COL                     es-CO   Colombia  EC,PE,PA,BR,VE      170    57   \n",
       "CUB                     es-CU       Cuba              US      192    53   \n",
       "ECU                     es-EC    Ecuador           PE,CO      218   593   \n",
       "ESP         es-ES,ca,gl,eu,oc      Spain  AD,PT,GI,FR,MA      724    34   \n",
       "HND                     es-HN   Honduras        GT,NI,SV      340   504   \n",
       "NIC                  es-NI,en  Nicaragua           CR,HN      558   505   \n",
       "PER               es-PE,qu,ay       Peru  EC,CL,BO,BR,CO      604    51   \n",
       "PRY                  es-PY,gn   Paraguay        BO,BR,AR      600   595   \n",
       "URY                     es-UY    Uruguay           BR,AR      858   598   \n",
       "VEN                     es-VE  Venezuela        GY,BR,CO      862    58   \n",
       "\n",
       "         population postal_code_format          postal_code_regex  tld  \n",
       "alpha_3                                                                 \n",
       "ARG        41343201           @####@@@    ^[A-Z]?\\d{4}[A-Z]{0,3}$  .ar  \n",
       "BOL         9947418                                                .bo  \n",
       "CHL        16746491            #######                  ^(\\d{7})$  .cl  \n",
       "COL        47790000                                                .co  \n",
       "CUB        11423000           CP #####           ^(?:CP)*(\\d{5})$  .cu  \n",
       "ECU        14790608             @####@  ^([a-zA-Z]\\d{4}[a-zA-Z])$  .ec  \n",
       "ESP        46505963              #####                  ^(\\d{5})$  .es  \n",
       "HND         7989415             @@####          ^([A-Z]{2}\\d{4})$  .hn  \n",
       "NIC         5995928          ###-###-#                  ^(\\d{7})$  .ni  \n",
       "PER        29907003                                                .pe  \n",
       "PRY         6375830               ####                  ^(\\d{4})$  .py  \n",
       "URY         3477000              #####                  ^(\\d{5})$  .uy  \n",
       "VEN        27223228               ####                  ^(\\d{4})$  .ve  "
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# En este caso, podriamos quitar por \"lo bajo\", area menor a 110.000 km2:\n",
    "df_2 = df_espanol.set_index('alpha_3')\n",
    "df_2 = df_2[df_2['area'] > 110000]\n",
    "df_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "id": "b974e5ee-e51e-4a37-8706-37d30f6bf79d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13, 18)"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "id": "03472a68-d3ca-4051-bedd-b83d6fbbd971",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='alpha_3'>"
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_2[['area']].sort_values([\"area\"]).plot(kind='bar',rot=65,figsize=(20,10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7da9fc70-754e-4be3-90b0-a01b9deb843b",
   "metadata": {},
   "outputs": [],
   "source": [
    "for, while"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed83ae4b-e361-4b10-a370-414d48ce4798",
   "metadata": {},
   "outputs": [],
   "source": [
    "i = 1\n",
    "while(i < 1000){\n",
    "    num = i * 2\n",
    "    i = 1 + 1\n",
    "    print(num)\n",
    "}"
   ]
  }
 ],
 "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": "3.11.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}