EDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>KPI-1 Penetracion de internet cada 100 hogares por trimestre</h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>Accesos por cada 100 hogares</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>78,11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Capital Federal</td>\n",
       "      <td>122,28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Catamarca</td>\n",
       "      <td>65,33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chaco</td>\n",
       "      <td>43,86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chubut</td>\n",
       "      <td>84,38</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Año  Trimestre        Provincia Accesos por cada 100 hogares\n",
       "0  2022          3     Buenos Aires                        78,11\n",
       "1  2022          3  Capital Federal                       122,28\n",
       "2  2022          3        Catamarca                        65,33\n",
       "3  2022          3            Chaco                        43,86\n",
       "4  2022          3           Chubut                        84,38"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt = pd.read_csv('datasets/Internet_PenetracionPROV.csv')\n",
    "dt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Año                              int64\n",
      "Trimestre                        int64\n",
      "Provincia                       object\n",
      "Accesos por cada 100 hogares    object\n",
      "dtype: object \n",
      " (840, 4)\n"
     ]
    }
   ],
   "source": [
    "print(dt.dtypes,'\\n',dt.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>Accesos por cada 100 hogares</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>78.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Capital Federal</td>\n",
       "      <td>122.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Catamarca</td>\n",
       "      <td>65.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chaco</td>\n",
       "      <td>43.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chubut</td>\n",
       "      <td>84.38</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Año  Trimestre        Provincia Accesos por cada 100 hogares\n",
       "0  2022          3     Buenos Aires                        78.11\n",
       "1  2022          3  Capital Federal                       122.28\n",
       "2  2022          3        Catamarca                        65.33\n",
       "3  2022          3            Chaco                        43.86\n",
       "4  2022          3           Chubut                        84.38"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt['Accesos por cada 100 hogares'] = [x.replace(',', '.') for x in dt['Accesos por cada 100 hogares']]\n",
    "dt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Año                               int64\n",
       "Trimestre                         int64\n",
       "Provincia                        object\n",
       "Accesos por cada 100 hogares    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt['Accesos por cada 100 hogares'] = dt['Accesos por cada 100 hogares'].astype('float64')\n",
    "dt.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>Accesos por cada 100 hogares</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Año, Trimestre, Provincia, Accesos por cada 100 hogares]\n",
       "Index: []"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt[dt.duplicated()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Año                             0\n",
       "Trimestre                       0\n",
       "Provincia                       0\n",
       "Accesos por cada 100 hogares    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(dt['Accesos por cada 100 hogares'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [],
   "source": [
    "def MeanGrowthPerProv():\n",
    "    x = dt['Accesos por cada 100 hogares'].groupby(dt['Provincia']).mean().sort_values().index\n",
    "    y = dt['Accesos por cada 100 hogares'].groupby(dt['Provincia']).mean().sort_values().values\n",
    "    plt.title('Mean Access Per Prov')\n",
    "    plt.barh(x, y)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MeanGrowthPerProv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "def MeanGrowthPerYear(provincia):\n",
    "    x = dt['Accesos por cada 100 hogares'].where(dt['Provincia'] == provincia).groupby(dt['Año']).mean().index\n",
    "    y = dt['Accesos por cada 100 hogares'].where(dt['Provincia'] == provincia).groupby(dt['Año']).mean().values\n",
    "    plt.title(f'Mean Growth {provincia}')\n",
    "    plt.plot(x, y)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "MeanGrowthPerYear('Santiago Del Estero')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt.to_csv('datasets/KPI_1_Internet_PenetracionPROV.csv', index=False)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>KPI-2 Velocidad media por provincia y trimestre</h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>Mbps (Media de bajada)</th>\n",
       "      <th>Unnamed: 4</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>70</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Capital Federal</td>\n",
       "      <td>101</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Catamarca</td>\n",
       "      <td>61</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chaco</td>\n",
       "      <td>53</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chubut</td>\n",
       "      <td>16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Año  Trimestre        Provincia  Mbps (Media de bajada)  Unnamed: 4  \\\n",
       "0  2022          3     Buenos Aires                      70         NaN   \n",
       "1  2022          3  Capital Federal                     101         NaN   \n",
       "2  2022          3        Catamarca                      61         NaN   \n",
       "3  2022          3            Chaco                      53         NaN   \n",
       "4  2022          3           Chubut                      16         NaN   \n",
       "\n",
       "   Unnamed: 5  \n",
       "0         NaN  \n",
       "1         NaN  \n",
       "2         NaN  \n",
       "3         NaN  \n",
       "4         NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt = pd.read_csv('datasets/historico_velocidad_internetPROV.csv')\n",
    "dt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Año                         int64\n",
      "Trimestre                   int64\n",
      "Provincia                  object\n",
      "Mbps (Media de bajada)      int64\n",
      "Unnamed: 4                float64\n",
      "Unnamed: 5                float64\n",
      "dtype: object (840, 6)\n"
     ]
    }
   ],
   "source": [
    "print(dt.dtypes, dt.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>Mbps (Media de bajada)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Capital Federal</td>\n",
       "      <td>101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Catamarca</td>\n",
       "      <td>61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chaco</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chubut</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Año  Trimestre        Provincia  Mbps (Media de bajada)\n",
       "0  2022          3     Buenos Aires                      70\n",
       "1  2022          3  Capital Federal                     101\n",
       "2  2022          3        Catamarca                      61\n",
       "3  2022          3            Chaco                      53\n",
       "4  2022          3           Chubut                      16"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt = dt.drop(columns=['Unnamed: 4', 'Unnamed: 5'])\n",
    "dt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "def meanSpeedPerProv(anio):\n",
    "    dtgp = dt.where(dt['Año'] == anio).groupby('Provincia').mean().sort_values(by='Mbps (Media de bajada)')\n",
    "    plt.barh(dtgp.index, dtgp['Mbps (Media de bajada)'])\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "meanSpeedPerProv(2015)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(dt['Mbps (Media de bajada)'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt.to_csv('datasets/KPI_2_historico_velocidad_internetPROV.csv', index=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>KPI-3 Acceso fijo por tecnologia</h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>ADSL</th>\n",
       "      <th>Cablemodem</th>\n",
       "      <th>Fibra óptica</th>\n",
       "      <th>Wireless</th>\n",
       "      <th>Otros</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>339.648</td>\n",
       "      <td>2.748.325</td>\n",
       "      <td>1.436.433</td>\n",
       "      <td>126.846</td>\n",
       "      <td>70.416</td>\n",
       "      <td>4.721.668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Capital Federal</td>\n",
       "      <td>140.791</td>\n",
       "      <td>1.240.125</td>\n",
       "      <td>129.218</td>\n",
       "      <td>5.758</td>\n",
       "      <td>31.787</td>\n",
       "      <td>1.547.679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Catamarca</td>\n",
       "      <td>10.010</td>\n",
       "      <td>10.495</td>\n",
       "      <td>46.224</td>\n",
       "      <td>1.329</td>\n",
       "      <td>2.235</td>\n",
       "      <td>70.293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chaco</td>\n",
       "      <td>27.164</td>\n",
       "      <td>61.800</td>\n",
       "      <td>44.645</td>\n",
       "      <td>8.178</td>\n",
       "      <td>2.359</td>\n",
       "      <td>144.146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chubut</td>\n",
       "      <td>45.377</td>\n",
       "      <td>72.212</td>\n",
       "      <td>9.574</td>\n",
       "      <td>29.784</td>\n",
       "      <td>8.831</td>\n",
       "      <td>165.778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Año Trimestre        Provincia     ADSL Cablemodem Fibra óptica  Wireless  \\\n",
       "0  2022         3     Buenos Aires  339.648  2.748.325    1.436.433   126.846   \n",
       "1  2022         3  Capital Federal  140.791  1.240.125      129.218     5.758   \n",
       "2  2022         3        Catamarca   10.010     10.495       46.224     1.329   \n",
       "3  2022         3            Chaco   27.164     61.800       44.645     8.178   \n",
       "4  2022         3           Chubut   45.377     72.212        9.574    29.784   \n",
       "\n",
       "    Otros      Total  \n",
       "0  70.416  4.721.668  \n",
       "1  31.787  1.547.679  \n",
       "2   2.235     70.293  \n",
       "3   2.359    144.146  \n",
       "4   8.831    165.778  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt = pd.read_csv('datasets/Internet_Accesos-por-tecnologiaPROV.csv')\n",
    "dt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Año              object\n",
      "Trimestre        object\n",
      "Provincia        object\n",
      "ADSL             object\n",
      "Cablemodem       object\n",
      "Fibra óptica     object\n",
      "Wireless        float64\n",
      "Otros           float64\n",
      "Total            object\n",
      "dtype: object (841, 9)\n"
     ]
    }
   ],
   "source": [
    "print(dt.dtypes, dt.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Año             0\n",
       "Trimestre       0\n",
       "Provincia       1\n",
       "ADSL            1\n",
       "Cablemodem      1\n",
       "Fibra óptica    1\n",
       "Wireless        1\n",
       "Otros           1\n",
       "Total           1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = dt.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Año              object\n",
       "Trimestre        object\n",
       "Provincia        object\n",
       "ADSL             object\n",
       "Cablemodem       object\n",
       "Fibra óptica     object\n",
       "Wireless        float64\n",
       "Otros           float64\n",
       "Total            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = dt.astype('string')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>ADSL</th>\n",
       "      <th>Cablemodem</th>\n",
       "      <th>Fibra óptica</th>\n",
       "      <th>Wireless</th>\n",
       "      <th>Otros</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>339648</td>\n",
       "      <td>2748325</td>\n",
       "      <td>1436433</td>\n",
       "      <td>126846</td>\n",
       "      <td>70416</td>\n",
       "      <td>4721668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Capital Federal</td>\n",
       "      <td>140791</td>\n",
       "      <td>1240125</td>\n",
       "      <td>129218</td>\n",
       "      <td>5758</td>\n",
       "      <td>31787</td>\n",
       "      <td>1547679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Catamarca</td>\n",
       "      <td>10010</td>\n",
       "      <td>10495</td>\n",
       "      <td>46224</td>\n",
       "      <td>1329</td>\n",
       "      <td>2235</td>\n",
       "      <td>70293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chaco</td>\n",
       "      <td>27164</td>\n",
       "      <td>61800</td>\n",
       "      <td>44645</td>\n",
       "      <td>8178</td>\n",
       "      <td>2359</td>\n",
       "      <td>144146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chubut</td>\n",
       "      <td>45377</td>\n",
       "      <td>72212</td>\n",
       "      <td>9574</td>\n",
       "      <td>29784</td>\n",
       "      <td>8831</td>\n",
       "      <td>165778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Año Trimestre        Provincia    ADSL Cablemodem Fibra óptica Wireless  \\\n",
       "0  2022         3     Buenos Aires  339648    2748325      1436433   126846   \n",
       "1  2022         3  Capital Federal  140791    1240125       129218     5758   \n",
       "2  2022         3        Catamarca   10010      10495        46224     1329   \n",
       "3  2022         3            Chaco   27164      61800        44645     8178   \n",
       "4  2022         3           Chubut   45377      72212         9574    29784   \n",
       "\n",
       "   Otros    Total  \n",
       "0  70416  4721668  \n",
       "1  31787  1547679  \n",
       "2   2235    70293  \n",
       "3   2359   144146  \n",
       "4   8831   165778  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col = ['ADSL', 'Cablemodem', 'Fibra óptica', 'Wireless', 'Otros', 'Total']\n",
    "for atrr in col:\n",
    "    dt[atrr] = [x.replace('.', '') for x in dt[atrr]]\n",
    "dt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Provincia</th>\n",
       "      <th>ADSL</th>\n",
       "      <th>Cablemodem</th>\n",
       "      <th>Fibra óptica</th>\n",
       "      <th>Wireless</th>\n",
       "      <th>Otros</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>339648</td>\n",
       "      <td>2748325</td>\n",
       "      <td>1436433</td>\n",
       "      <td>126846</td>\n",
       "      <td>70416</td>\n",
       "      <td>4721668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Capital Federal</td>\n",
       "      <td>140791</td>\n",
       "      <td>1240125</td>\n",
       "      <td>129218</td>\n",
       "      <td>5758</td>\n",
       "      <td>31787</td>\n",
       "      <td>1547679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Catamarca</td>\n",
       "      <td>10010</td>\n",
       "      <td>10495</td>\n",
       "      <td>46224</td>\n",
       "      <td>1329</td>\n",
       "      <td>2235</td>\n",
       "      <td>70293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chaco</td>\n",
       "      <td>27164</td>\n",
       "      <td>61800</td>\n",
       "      <td>44645</td>\n",
       "      <td>8178</td>\n",
       "      <td>2359</td>\n",
       "      <td>144146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>Chubut</td>\n",
       "      <td>45377</td>\n",
       "      <td>72212</td>\n",
       "      <td>9574</td>\n",
       "      <td>29784</td>\n",
       "      <td>8831</td>\n",
       "      <td>165778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Año Trimestre        Provincia    ADSL Cablemodem Fibra óptica Wireless  \\\n",
       "0  2022         3     Buenos Aires  339648    2748325      1436433   126846   \n",
       "1  2022         3  Capital Federal  140791    1240125       129218     5758   \n",
       "2  2022         3        Catamarca   10010      10495        46224     1329   \n",
       "3  2022         3            Chaco   27164      61800        44645     8178   \n",
       "4  2022         3           Chubut   45377      72212         9574    29784   \n",
       "\n",
       "   Otros    Total  \n",
       "0  70416  4721668  \n",
       "1  31787  1547679  \n",
       "2   2235    70293  \n",
       "3   2359   144146  \n",
       "4   8831   165778  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt = dt.drop(dt[dt['Año'] == '2019 *'].index)\n",
    "dt.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "col = {'Año':'int64','Trimestre':'int32','ADSL':'int64','Cablemodem':'int64','Fibra óptica':'int64','Wireless':'int64','Otros':'int64','Total':'int64'}\n",
    "dt = dt.astype(col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Año              int64\n",
       "Trimestre        int32\n",
       "Provincia       string\n",
       "ADSL             int64\n",
       "Cablemodem       int64\n",
       "Fibra óptica     int64\n",
       "Wireless         int64\n",
       "Otros            int64\n",
       "Total            int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4396850.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt['ADSL'].where(dt['Año']==2022).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = dt[['ADSL', 'Cablemodem', 'Fibra óptica', 'Wireless', 'Otros']].where((dt['Año']==2022) & (dt['Trimestre']==3)).sum(skipna=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "def accessAmountPerTecnology(anio, trimestre):\n",
    "    suma = dt[['ADSL', 'Cablemodem', 'Fibra óptica', 'Wireless', 'Otros']].where((dt['Año']==2022) & (dt['Trimestre']==3)).sum(skipna=True)\n",
    "    plt.title(f'Cantidad de accesos por tecnologia {anio} trim {trimestre}')\n",
    "    plt.bar(['ADSL', 'Cablemodem', 'Fibra óptica', 'Wireless', 'Otros'], suma )\n",
    "    plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "accessAmountPerTecnology(2021,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "dt.to_csv('datasets/KPI_3_Internet_Accesos-por-tecnologiaPROV.csv', index=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>KPI-4 Ingresos</h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Ingresos (miles de pesos)</th>\n",
       "      <th>Periodo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022</td>\n",
       "      <td>3</td>\n",
       "      <td>67.055.930</td>\n",
       "      <td>Jul-Sept 2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022</td>\n",
       "      <td>2</td>\n",
       "      <td>60.335.724</td>\n",
       "      <td>Abr-Jun 2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022</td>\n",
       "      <td>1</td>\n",
       "      <td>55.589.997</td>\n",
       "      <td>Ene-Mar 2022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>4</td>\n",
       "      <td>45.467.887</td>\n",
       "      <td>Oct-Dic 2021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021</td>\n",
       "      <td>3</td>\n",
       "      <td>42.999.944</td>\n",
       "      <td>Jul-Sept 2021</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Año  Trimestre Ingresos (miles de pesos)        Periodo\n",
       "0  2022          3                67.055.930  Jul-Sept 2022\n",
       "1  2022          2                60.335.724   Abr-Jun 2022\n",
       "2  2022          1                55.589.997   Ene-Mar 2022\n",
       "3  2021          4                45.467.887   Oct-Dic 2021\n",
       "4  2021          3                42.999.944  Jul-Sept 2021"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rev = pd.read_csv('datasets/Internet_IngresosTRIM.csv')\n",
    "rev.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 35 entries, 0 to 34\n",
      "Data columns (total 4 columns):\n",
      " #   Column                     Non-Null Count  Dtype \n",
      "---  ------                     --------------  ----- \n",
      " 0   Año                        35 non-null     int64 \n",
      " 1   Trimestre                  35 non-null     int64 \n",
      " 2   Ingresos (miles de pesos)  35 non-null     object\n",
      " 3   Periodo                    35 non-null     object\n",
      "dtypes: int64(2), object(2)\n",
      "memory usage: 1.2+ KB\n"
     ]
    }
   ],
   "source": [
    "rev.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>years</th>\n",
       "      <th>meanUSD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>94</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   years  meanUSD\n",
       "0   2018       37\n",
       "1   2019       48\n",
       "2   2020       70\n",
       "3   2021       94\n",
       "4   2022      131"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "usdcot = pd.DataFrame({'years':[2018,2019,2020,2021,2022], 'meanUSD':[37,48,70,94,131]})\n",
    "usdcot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "rev['Ingresos (miles de pesos)'] = [x.replace('.','') for x in rev['Ingresos (miles de pesos)']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Año</th>\n",
       "      <th>Trimestre</th>\n",
       "      <th>Ingresos (miles de pesos)</th>\n",
       "      <th>Periodo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>33539703</td>\n",
       "      <td>Oct-Dic 2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2020</td>\n",
       "      <td>3</td>\n",
       "      <td>31997445</td>\n",
       "      <td>Jul-Sept 2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020</td>\n",
       "      <td>2</td>\n",
       "      <td>32102476</td>\n",
       "      <td>Abr-Jun 2020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>29946216</td>\n",
       "      <td>Ene-Mar 2020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Año  Trimestre Ingresos (miles de pesos)        Periodo\n",
       "7   2020          4                  33539703   Oct-Dic 2020\n",
       "8   2020          3                  31997445  Jul-Sept 2020\n",
       "9   2020          2                  32102476   Abr-Jun 2020\n",
       "10  2020          1                  29946216   Ene-Mar 2020"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rev[rev['Año'] == 2020]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Año                           int64\n",
       "Trimestre                     int64\n",
       "Ingresos (miles de pesos)     int64\n",
       "Periodo                      object\n",
       "dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rev['Ingresos (miles de pesos)'] = rev['Ingresos (miles de pesos)'].astype('int64')\n",
    "rev.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "tab = rev['Ingresos (miles de pesos)'].groupby(rev['Año']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>Año</th>\n",
       "      <th>ingresospesos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [Año, ingresospesos]\n",
       "Index: []"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dftab = pd.DataFrame(columns=['Año', 'ingresospesos'])\n",
    "dftab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>Año</th>\n",
       "      <th>ingresospesos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>3.420987e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>5.027204e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>6.716877e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017</td>\n",
       "      <td>9.917993e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>1.488490e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019</td>\n",
       "      <td>2.169313e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020</td>\n",
       "      <td>3.189646e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2021</td>\n",
       "      <td>4.084597e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2022</td>\n",
       "      <td>6.099388e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Año  ingresospesos\n",
       "0  2014   3.420987e+06\n",
       "1  2015   5.027204e+06\n",
       "2  2016   6.716877e+06\n",
       "3  2017   9.917993e+06\n",
       "4  2018   1.488490e+07\n",
       "5  2019   2.169313e+07\n",
       "6  2020   3.189646e+07\n",
       "7  2021   4.084597e+07\n",
       "8  2022   6.099388e+07"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dftab['Año'] = tab.index\n",
    "dftab['ingresospesos'] = tab.values\n",
    "dftab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "newtab = usdcot.merge(dftab, left_on=usdcot['years'], right_on=dftab['Año'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
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       "        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>key_0</th>\n",
       "      <th>years</th>\n",
       "      <th>meanUSD</th>\n",
       "      <th>Año</th>\n",
       "      <th>ingresospesos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>37</td>\n",
       "      <td>2018</td>\n",
       "      <td>1.488490e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>2019</td>\n",
       "      <td>48</td>\n",
       "      <td>2019</td>\n",
       "      <td>2.169313e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>2020</td>\n",
       "      <td>70</td>\n",
       "      <td>2020</td>\n",
       "      <td>3.189646e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>2021</td>\n",
       "      <td>94</td>\n",
       "      <td>2021</td>\n",
       "      <td>4.084597e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>2022</td>\n",
       "      <td>131</td>\n",
       "      <td>2022</td>\n",
       "      <td>6.099388e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   key_0  years  meanUSD   Año  ingresospesos\n",
       "0   2018   2018       37  2018   1.488490e+07\n",
       "1   2019   2019       48  2019   2.169313e+07\n",
       "2   2020   2020       70  2020   3.189646e+07\n",
       "3   2021   2021       94  2021   4.084597e+07\n",
       "4   2022   2022      131  2022   6.099388e+07"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newtab.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "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>key_0</th>\n",
       "      <th>years</th>\n",
       "      <th>meanUSD</th>\n",
       "      <th>Año</th>\n",
       "      <th>ingresospesos</th>\n",
       "      <th>ingresosUSD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018</td>\n",
       "      <td>2018</td>\n",
       "      <td>37</td>\n",
       "      <td>2018</td>\n",
       "      <td>1.488490e+07</td>\n",
       "      <td>4.022946e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019</td>\n",
       "      <td>2019</td>\n",
       "      <td>48</td>\n",
       "      <td>2019</td>\n",
       "      <td>2.169313e+07</td>\n",
       "      <td>4.519403e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020</td>\n",
       "      <td>2020</td>\n",
       "      <td>70</td>\n",
       "      <td>2020</td>\n",
       "      <td>3.189646e+07</td>\n",
       "      <td>4.556637e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021</td>\n",
       "      <td>2021</td>\n",
       "      <td>94</td>\n",
       "      <td>2021</td>\n",
       "      <td>4.084597e+07</td>\n",
       "      <td>4.345316e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022</td>\n",
       "      <td>2022</td>\n",
       "      <td>131</td>\n",
       "      <td>2022</td>\n",
       "      <td>6.099388e+07</td>\n",
       "      <td>4.656022e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   key_0  years  meanUSD   Año  ingresospesos   ingresosUSD\n",
       "0   2018   2018       37  2018   1.488490e+07  4.022946e+08\n",
       "1   2019   2019       48  2019   2.169313e+07  4.519403e+08\n",
       "2   2020   2020       70  2020   3.189646e+07  4.556637e+08\n",
       "3   2021   2021       94  2021   4.084597e+07  4.345316e+08\n",
       "4   2022   2022      131  2022   6.099388e+07  4.656022e+08"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newtab['ingresosUSD'] = (newtab['ingresospesos']*1000)/newtab['meanUSD']\n",
    "newtab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(newtab['years'], newtab['ingresospesos'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(newtab['years'], newtab['ingresosUSD'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "newtab.to_csv('datasets/KPI_4_ingresos.csv', index=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h4>Mapa de conectividad</h4>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Provincia</th>\n",
       "      <th>Partido</th>\n",
       "      <th>Localidad</th>\n",
       "      <th>Poblacion</th>\n",
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       "      <th>0</th>\n",
       "      <td>BUENOS AIRES</td>\n",
       "      <td>Bahía Blanca</td>\n",
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       "      <td>BUENOS AIRES</td>\n",
       "      <td>Bahía Blanca</td>\n",
       "      <td>Villa Espora</td>\n",
       "      <td>0</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>BUENOS AIRES</td>\n",
       "      <td>Balcarce</td>\n",
       "      <td>Balcarce</td>\n",
       "      <td>38376</td>\n",
       "      <td>SI</td>\n",
       "      <td>SI</td>\n",
       "      <td>SI</td>\n",
       "      <td>SI</td>\n",
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       "      <td>SI</td>\n",
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       "      <td>Balcarce</td>\n",
       "      <td>Los Pinos</td>\n",
       "      <td>337</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>SI</td>\n",
       "      <td>SI</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>6063020.0</td>\n",
       "      <td>-37,9412057603</td>\n",
       "      <td>-58,3225920150442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BUENOS AIRES</td>\n",
       "      <td>Balcarce</td>\n",
       "      <td>Napaleofú</td>\n",
       "      <td>374</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>--</td>\n",
       "      <td>SI</td>\n",
       "      <td>--</td>\n",
       "      <td>SI</td>\n",
       "      <td>SI</td>\n",
       "      <td>SI</td>\n",
       "      <td>SI</td>\n",
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      "text/plain": [
       "      Provincia       Partido      Localidad  Poblacion ADSL CABLEMODEM  \\\n",
       "0  BUENOS AIRES  Bahía Blanca  Villa Bordeau          0   --         --   \n",
       "1  BUENOS AIRES  Bahía Blanca   Villa Espora          0   --         --   \n",
       "2  BUENOS AIRES      Balcarce       Balcarce      38376   SI         SI   \n",
       "3  BUENOS AIRES      Balcarce      Los Pinos        337   --         --   \n",
       "4  BUENOS AIRES      Balcarce      Napaleofú        374   --         --   \n",
       "\n",
       "  DIALUP FIBRAOPTICA SATELITAL WIRELESS TELEFONIAFIJA  3G  4G       link  \\\n",
       "0     --          --        --       --            --  SI  SI  6056020.0   \n",
       "1     --          --        --       --            --  --  --  6056020.0   \n",
       "2     SI          SI        --       SI            SI  SI  SI  6063010.0   \n",
       "3     --          --        --       SI            SI  --  --  6063020.0   \n",
       "4     --          SI        --       SI            SI  SI  SI  6063030.0   \n",
       "\n",
       "             Latitud           Longitud  \n",
       "0  -38,6472605094596  -62,3200223419024  \n",
       "1  -38,7765069529222  -62,1851833537179  \n",
       "2  -37,8482779294345  -58,2551665841248  \n",
       "3     -37,9412057603  -58,3225920150442  \n",
       "4  -37,6254980210026  -58,7461862359423  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mp = pd.read_csv('datasets/mapaconectividad_fijo&movil.csv')\n",
    "mp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4312 entries, 0 to 4311\n",
      "Data columns (total 16 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Provincia      4312 non-null   object \n",
      " 1   Partido        4312 non-null   object \n",
      " 2   Localidad      4312 non-null   object \n",
      " 3   Poblacion      4312 non-null   int64  \n",
      " 4   ADSL           4312 non-null   object \n",
      " 5   CABLEMODEM     4312 non-null   object \n",
      " 6   DIALUP         4312 non-null   object \n",
      " 7   FIBRAOPTICA    4312 non-null   object \n",
      " 8   SATELITAL      4312 non-null   object \n",
      " 9   WIRELESS       4312 non-null   object \n",
      " 10  TELEFONIAFIJA  4312 non-null   object \n",
      " 11  3G             4312 non-null   object \n",
      " 12  4G             4312 non-null   object \n",
      " 13  link           4300 non-null   float64\n",
      " 14  Latitud        4312 non-null   object \n",
      " 15  Longitud       4312 non-null   object \n",
      "dtypes: float64(1), int64(1), object(14)\n",
      "memory usage: 539.1+ KB\n"
     ]
    }
   ],
   "source": [
    "mp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "atrr = ['ADSL', 'CABLEMODEM', 'DIALUP', 'FIBRAOPTICA','SATELITAL','WIRELESS','TELEFONIAFIJA','3G','4G']\n",
    "for x in atrr:\n",
    "   mp[x] = mp[x].map({'SI':True,'--':False})\n",
    "   mp[x] = mp[x].astype('bool')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>Balcarce</td>\n",
       "      <td>38376</td>\n",
       "      <td>True</td>\n",
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       "      <th>3</th>\n",
       "      <td>BUENOS AIRES</td>\n",
       "      <td>Balcarce</td>\n",
       "      <td>Los Pinos</td>\n",
       "      <td>337</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>6063020.0</td>\n",
       "      <td>-37,9412057603</td>\n",
       "      <td>-58,3225920150442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>BUENOS AIRES</td>\n",
       "      <td>Balcarce</td>\n",
       "      <td>Napaleofú</td>\n",
       "      <td>374</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
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      ],
      "text/plain": [
       "      Provincia       Partido      Localidad  Poblacion   ADSL  CABLEMODEM  \\\n",
       "0  BUENOS AIRES  Bahía Blanca  Villa Bordeau          0  False       False   \n",
       "1  BUENOS AIRES  Bahía Blanca   Villa Espora          0  False       False   \n",
       "2  BUENOS AIRES      Balcarce       Balcarce      38376   True        True   \n",
       "3  BUENOS AIRES      Balcarce      Los Pinos        337  False       False   \n",
       "4  BUENOS AIRES      Balcarce      Napaleofú        374  False       False   \n",
       "\n",
       "   DIALUP  FIBRAOPTICA  SATELITAL  WIRELESS  TELEFONIAFIJA     3G     4G  \\\n",
       "0   False        False      False     False          False   True   True   \n",
       "1   False        False      False     False          False  False  False   \n",
       "2    True         True      False      True           True   True   True   \n",
       "3   False        False      False      True           True  False  False   \n",
       "4   False         True      False      True           True   True   True   \n",
       "\n",
       "        link            Latitud           Longitud  \n",
       "0  6056020.0  -38,6472605094596  -62,3200223419024  \n",
       "1  6056020.0  -38,7765069529222  -62,1851833537179  \n",
       "2  6063010.0  -37,8482779294345  -58,2551665841248  \n",
       "3  6063020.0     -37,9412057603  -58,3225920150442  \n",
       "4  6063030.0  -37,6254980210026  -58,7461862359423  "
      ]
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     "execution_count": 65,
     "metadata": {},
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    }
   ],
   "source": [
    "mp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4312 entries, 0 to 4311\n",
      "Data columns (total 16 columns):\n",
      " #   Column         Non-Null Count  Dtype  \n",
      "---  ------         --------------  -----  \n",
      " 0   Provincia      4312 non-null   object \n",
      " 1   Partido        4312 non-null   object \n",
      " 2   Localidad      4312 non-null   object \n",
      " 3   Poblacion      4312 non-null   int64  \n",
      " 4   ADSL           4312 non-null   bool   \n",
      " 5   CABLEMODEM     4312 non-null   bool   \n",
      " 6   DIALUP         4312 non-null   bool   \n",
      " 7   FIBRAOPTICA    4312 non-null   bool   \n",
      " 8   SATELITAL      4312 non-null   bool   \n",
      " 9   WIRELESS       4312 non-null   bool   \n",
      " 10  TELEFONIAFIJA  4312 non-null   bool   \n",
      " 11  3G             4312 non-null   bool   \n",
      " 12  4G             4312 non-null   bool   \n",
      " 13  link           4300 non-null   float64\n",
      " 14  Latitud        4312 non-null   object \n",
      " 15  Longitud       4312 non-null   object \n",
      "dtypes: bool(9), float64(1), int64(1), object(5)\n",
      "memory usage: 273.8+ KB\n"
     ]
    }
   ],
   "source": [
    "mp.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_9368/3553150430.py:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
      "  correl = mp.corr()\n"
     ]
    }
   ],
   "source": [
    "correl = mp.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1170x827 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "sns.heatmap(correl, annot=True)\n",
    "sns.set(rc={'figure.figsize':(15,15)})"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<p>Poblaciones mas pequeñas acceden a mas internet movil que fijo.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Provincia\n",
       "TIERRA DEL FUEGO         125823\n",
       "SANTA CRUZ               268436\n",
       "LA PAMPA                 302570\n",
       "LA RIOJA                 319248\n",
       "CATAMARCA                343343\n",
       "SAN LUIS                 410669\n",
       "FORMOSA                  452714\n",
       "CHUBUT                   490554\n",
       "NEUQUEN                  522527\n",
       "RIO NEGRO                597058\n",
       "JUJUY                    628141\n",
       "SAN JUAN                 631000\n",
       "SANTIAGO DEL ESTERO      671932\n",
       "MISIONES                 836097\n",
       "CORRIENTES               857994\n",
       "CHACO                    927414\n",
       "SALTA                   1117163\n",
       "ENTRE RIOS              1119919\n",
       "TUCUMAN                 1210114\n",
       "MENDOZA                 1654993\n",
       "CABA                    2890151\n",
       "SANTA FE                3055611\n",
       "CORDOBA                 3139606\n",
       "BUENOS AIRES           14911542\n",
       "Name: Poblacion, dtype: int64"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mp['Poblacion'].groupby(mp['Provincia']).sum().sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x1500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(mp['Poblacion'].groupby(mp['Provincia']).sum().sort_values().index, mp['Poblacion'].groupby(mp['Provincia']).sum().sort_values().values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "mp.to_csv('datasets/K_mapaconectividad_fija_movil.csv', index=False)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}