Taller8.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 275,
      "metadata": {
        "id": "F52V62FitXAb",
        "outputId": "096b12f4-e158-4ef6-92b2-b60818793430",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Librerias instaladas!!!\n"
          ]
        }
      ],
      "source": [
        "!pip install -q matplotlib numpy pandas seaborn scikit-learn ipython\n",
        "!pip install -q kneed\n",
        "\n",
        "print(\"Librerias instaladas!!!\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from kneed import KneeLocator\n",
        "from sklearn.datasets import make_blobs\n",
        "from sklearn.cluster import KMeans\n",
        "from sklearn.metrics import silhouette_score\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "import pandas as pd\n",
        "from sklearn.preprocessing import OrdinalEncoder"
      ],
      "metadata": {
        "id": "r5Cj3HhgtolY"
      },
      "execution_count": 276,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ruta = 'https://raw.githubusercontent.com/fmoreno4/cd-files/main/eventos_dengue_2020.csv'\n",
        "df = pd.read_csv(ruta)\n",
        "df"
      ],
      "metadata": {
        "id": "jv0VNbBFtr8g",
        "outputId": "099ec99e-e526-4ba5-a05d-6e9b9d0f0abb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 548
        }
      },
      "execution_count": 277,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        ID     fec_not  semana   año  edad_  uni_med_ sexo_  cod_pais_o  \\\n",
              "0        1  17/01/2020       1  2020     25         1     F         170   \n",
              "1        2  10/01/2020       1  2020     24         1     M         170   \n",
              "2        3  12/01/2020       1  2020     58         1     M         170   \n",
              "3        4  12/01/2020       1  2020     29         1     F         170   \n",
              "4        5  10/01/2020       1  2020     56         1     F         170   \n",
              "...    ...         ...     ...   ...    ...       ...   ...         ...   \n",
              "1257  1258   7/03/2020       9  2020     36         1     F         170   \n",
              "1258  1259  13/03/2020       9  2020     42         1     M         170   \n",
              "1259  1260   8/03/2020       9  2020      2         1     M         170   \n",
              "1260  1261  11/03/2020       9  2020     12         1     F         170   \n",
              "1261  1262   9/03/2020       9  2020     14         1     M         170   \n",
              "\n",
              "      cod_dpto_o  cod_mun_o  area_  ocupacion_       tip_ss_ cod_ase_  \\\n",
              "0             68        276      1        2411  Contributivo   EPS037   \n",
              "1             68        276      1        9997  Contributivo   EPS003   \n",
              "2             68        276      1        9999  Contributivo   EPS013   \n",
              "3             68        276      1        4121  Contributivo   EPS013   \n",
              "4             68        276      1        9210      Especial    37086   \n",
              "...          ...        ...    ...         ...           ...      ...   \n",
              "1257          68        276      1        9996  Contributivo   EPS013   \n",
              "1258          68        276      1        2145  Contributivo   EPS017   \n",
              "1259          68        276      1        9998  Contributivo   EPS013   \n",
              "1260          68        276      1        9997  Contributivo   EPS016   \n",
              "1261          68        276      1        9997  Contributivo   EPS002   \n",
              "\n",
              "      gp_discapa  gp_desplaz  gp_migrant  gp_carcela  gp_gestan  gp_calle  \\\n",
              "0              2           2           2           2          1         2   \n",
              "1              2           2           2           2          2         2   \n",
              "2              2           2           2           2          2         2   \n",
              "3              2           2           2           2          2         2   \n",
              "4              2           2           2           2          2         2   \n",
              "...          ...         ...         ...         ...        ...       ...   \n",
              "1257           2           2           2           2          2         2   \n",
              "1258           2           2           2           2          2         2   \n",
              "1259           2           2           2           2          2         2   \n",
              "1260           2           2           2           2          2         2   \n",
              "1261           2           2           2           2          2         2   \n",
              "\n",
              "      gp_psiquia  gp_vic_vio fecha_contagio inicio_sintomas  pac_hos_  \\\n",
              "0              2           2     17/01/2020      10/01/2020         2   \n",
              "1              2           2     10/01/2020       7/01/2020         2   \n",
              "2              2           2     12/01/2020       8/01/2020         2   \n",
              "3              2           2     10/01/2020       6/01/2020         2   \n",
              "4              2           2     10/01/2020       7/01/2020         1   \n",
              "...          ...         ...            ...             ...       ...   \n",
              "1257           2           2      6/03/2020       3/03/2020         2   \n",
              "1258           2           2     13/03/2020       6/03/2020         1   \n",
              "1259           2           2      8/03/2020       4/03/2020         2   \n",
              "1260           2           2     11/03/2020       5/03/2020         2   \n",
              "1261           2           2      6/03/2020       2/03/2020         1   \n",
              "\n",
              "        fec_hos_  condicion_final  fecha_defuncion fecha_nacimiento  \\\n",
              "0            NaN                1              NaN       12/11/1994   \n",
              "1            NaN                1              NaN        9/02/1995   \n",
              "2            NaN                1              NaN       19/09/1961   \n",
              "3            NaN                1              NaN        6/10/1990   \n",
              "4     10/01/2020                1              NaN       12/02/1963   \n",
              "...          ...              ...              ...              ...   \n",
              "1257         NaN                1              NaN        3/03/1984   \n",
              "1258  13/03/2020                1              NaN        3/07/1977   \n",
              "1259         NaN                1              NaN        3/08/2017   \n",
              "1260         NaN                1              NaN       16/02/2008   \n",
              "1261   6/03/2020                1              NaN       30/03/2005   \n",
              "\n",
              "      certif_defuncion  familiar_sintomas  fiebre  cefalea  dolor_retroocular  \\\n",
              "0                  NaN                  2       1        2                  1   \n",
              "1                  NaN                  2       1        1                  2   \n",
              "2                  NaN                  1       1        1                  1   \n",
              "3                  NaN                  1       1        1                  2   \n",
              "4                  NaN                  1       1        1                  2   \n",
              "...                ...                ...     ...      ...                ...   \n",
              "1257               NaN                  2       1        1                  1   \n",
              "1258               NaN                  2       1        1                  2   \n",
              "1259               NaN                  1       1        1                  1   \n",
              "1260               NaN                  2       1        1                  2   \n",
              "1261               NaN                  2       1        1                  1   \n",
              "\n",
              "      mialgias  artralgia  erupcion  dolor_abdomen  vomito  diarrea  \\\n",
              "0            1          1         1              2       2        2   \n",
              "1            1          2         2              2       2        2   \n",
              "2            1          1         1              2       2        1   \n",
              "3            2          1         1              2       2        2   \n",
              "4            1          2         2              2       1        1   \n",
              "...        ...        ...       ...            ...     ...      ...   \n",
              "1257         1          1         2              2       1        2   \n",
              "1258         1          1         2              2       2        2   \n",
              "1259         1          1         1              2       2        2   \n",
              "1260         1          2         1              2       2        2   \n",
              "1261         1          1         1              2       2        2   \n",
              "\n",
              "      somnolencia  hipotension  hepatomegalia  hemorragia_mucosa  hipotermia  \\\n",
              "0               2            2              2                  2           2   \n",
              "1               2            2              2                  2           2   \n",
              "2               2            2              2                  2           2   \n",
              "3               2            2              2                  2           2   \n",
              "4               2            2              2                  2           2   \n",
              "...           ...          ...            ...                ...         ...   \n",
              "1257            2            2              2                  1           2   \n",
              "1258            2            2              2                  2           2   \n",
              "1259            2            2              2                  2           2   \n",
              "1260            2            2              2                  2           2   \n",
              "1261            2            2              2                  2           2   \n",
              "\n",
              "      caida_plaquetas  acum_liquido  aum_hematocrito                 conducta  \\\n",
              "0                   2             2                2           1. Ambulatorio   \n",
              "1                   2             2                2           1. Ambulatorio   \n",
              "2                   2             2                2           1. Ambulatorio   \n",
              "3                   2             2                2           1. Ambulatorio   \n",
              "4                   1             2                2  2. Hospitalizacion piso   \n",
              "...               ...           ...              ...                      ...   \n",
              "1257                2             2                2           1. Ambulatorio   \n",
              "1258                1             2                1  2. Hospitalizacion piso   \n",
              "1259                2             2                2           1. Ambulatorio   \n",
              "1260                2             2                2           1. Ambulatorio   \n",
              "1261                2             2                2  2. Hospitalizacion piso   \n",
              "\n",
              "       latitud   longitud  \n",
              "0     7.076011 -73.102501  \n",
              "1     7.079495 -73.105400  \n",
              "2     7.090290 -73.091003  \n",
              "3     7.067435 -73.090958  \n",
              "4     7.066905 -73.104980  \n",
              "...        ...        ...  \n",
              "1257  7.072610 -73.099487  \n",
              "1258  7.065252 -73.103607  \n",
              "1259  7.091391 -73.103264  \n",
              "1260  7.061083 -73.097000  \n",
              "1261  7.062521 -73.080444  \n",
              "\n",
              "[1262 rows x 51 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-af58e15e-ee03-4803-aa48-cf477b58127c\" class=\"colab-df-container\">\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>fec_not</th>\n",
              "      <th>semana</th>\n",
              "      <th>año</th>\n",
              "      <th>edad_</th>\n",
              "      <th>uni_med_</th>\n",
              "      <th>sexo_</th>\n",
              "      <th>cod_pais_o</th>\n",
              "      <th>cod_dpto_o</th>\n",
              "      <th>cod_mun_o</th>\n",
              "      <th>area_</th>\n",
              "      <th>ocupacion_</th>\n",
              "      <th>tip_ss_</th>\n",
              "      <th>cod_ase_</th>\n",
              "      <th>gp_discapa</th>\n",
              "      <th>gp_desplaz</th>\n",
              "      <th>gp_migrant</th>\n",
              "      <th>gp_carcela</th>\n",
              "      <th>gp_gestan</th>\n",
              "      <th>gp_calle</th>\n",
              "      <th>gp_psiquia</th>\n",
              "      <th>gp_vic_vio</th>\n",
              "      <th>fecha_contagio</th>\n",
              "      <th>inicio_sintomas</th>\n",
              "      <th>pac_hos_</th>\n",
              "      <th>fec_hos_</th>\n",
              "      <th>condicion_final</th>\n",
              "      <th>fecha_defuncion</th>\n",
              "      <th>fecha_nacimiento</th>\n",
              "      <th>certif_defuncion</th>\n",
              "      <th>familiar_sintomas</th>\n",
              "      <th>fiebre</th>\n",
              "      <th>cefalea</th>\n",
              "      <th>dolor_retroocular</th>\n",
              "      <th>mialgias</th>\n",
              "      <th>artralgia</th>\n",
              "      <th>erupcion</th>\n",
              "      <th>dolor_abdomen</th>\n",
              "      <th>vomito</th>\n",
              "      <th>diarrea</th>\n",
              "      <th>somnolencia</th>\n",
              "      <th>hipotension</th>\n",
              "      <th>hepatomegalia</th>\n",
              "      <th>hemorragia_mucosa</th>\n",
              "      <th>hipotermia</th>\n",
              "      <th>caida_plaquetas</th>\n",
              "      <th>acum_liquido</th>\n",
              "      <th>aum_hematocrito</th>\n",
              "      <th>conducta</th>\n",
              "      <th>latitud</th>\n",
              "      <th>longitud</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>17/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>25</td>\n",
              "      <td>1</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>2411</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS037</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>17/01/2020</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12/11/1994</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.076011</td>\n",
              "      <td>-73.102501</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>24</td>\n",
              "      <td>1</td>\n",
              "      <td>M</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9997</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS003</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>7/01/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>9/02/1995</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.079495</td>\n",
              "      <td>-73.105400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>12/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>58</td>\n",
              "      <td>1</td>\n",
              "      <td>M</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9999</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS013</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>12/01/2020</td>\n",
              "      <td>8/01/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>19/09/1961</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.090290</td>\n",
              "      <td>-73.091003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>12/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>29</td>\n",
              "      <td>1</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>4121</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS013</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>6/01/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6/10/1990</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.067435</td>\n",
              "      <td>-73.090958</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>56</td>\n",
              "      <td>1</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9210</td>\n",
              "      <td>Especial</td>\n",
              "      <td>37086</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>7/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12/02/1963</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2. Hospitalizacion piso</td>\n",
              "      <td>7.066905</td>\n",
              "      <td>-73.104980</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",
              "      <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",
              "      <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>1257</th>\n",
              "      <td>1258</td>\n",
              "      <td>7/03/2020</td>\n",
              "      <td>9</td>\n",
              "      <td>2020</td>\n",
              "      <td>36</td>\n",
              "      <td>1</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9996</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS013</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>6/03/2020</td>\n",
              "      <td>3/03/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3/03/1984</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.072610</td>\n",
              "      <td>-73.099487</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1258</th>\n",
              "      <td>1259</td>\n",
              "      <td>13/03/2020</td>\n",
              "      <td>9</td>\n",
              "      <td>2020</td>\n",
              "      <td>42</td>\n",
              "      <td>1</td>\n",
              "      <td>M</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>2145</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS017</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>13/03/2020</td>\n",
              "      <td>6/03/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>13/03/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3/07/1977</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2. Hospitalizacion piso</td>\n",
              "      <td>7.065252</td>\n",
              "      <td>-73.103607</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1259</th>\n",
              "      <td>1260</td>\n",
              "      <td>8/03/2020</td>\n",
              "      <td>9</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>M</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9998</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS013</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>8/03/2020</td>\n",
              "      <td>4/03/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3/08/2017</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.091391</td>\n",
              "      <td>-73.103264</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1260</th>\n",
              "      <td>1261</td>\n",
              "      <td>11/03/2020</td>\n",
              "      <td>9</td>\n",
              "      <td>2020</td>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9997</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS016</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>11/03/2020</td>\n",
              "      <td>5/03/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>16/02/2008</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.061083</td>\n",
              "      <td>-73.097000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1261</th>\n",
              "      <td>1262</td>\n",
              "      <td>9/03/2020</td>\n",
              "      <td>9</td>\n",
              "      <td>2020</td>\n",
              "      <td>14</td>\n",
              "      <td>1</td>\n",
              "      <td>M</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9997</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS002</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>6/03/2020</td>\n",
              "      <td>2/03/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>6/03/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>30/03/2005</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2. Hospitalizacion piso</td>\n",
              "      <td>7.062521</td>\n",
              "      <td>-73.080444</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1262 rows × 51 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    0% {\n",
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              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-57d68ac6-2cd6-4b85-b2d1-dd9fe56e651e button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 277
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.set_option('display.max_columns', None)\n",
        "df.head(10)"
      ],
      "metadata": {
        "id": "i4bmYJxDtu21",
        "outputId": "126a13c7-1c71-4cf2-87a6-74a7549770fd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        }
      },
      "execution_count": 278,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   ID     fec_not  semana   año  edad_  uni_med_ sexo_  cod_pais_o  \\\n",
              "0   1  17/01/2020       1  2020     25         1     F         170   \n",
              "1   2  10/01/2020       1  2020     24         1     M         170   \n",
              "2   3  12/01/2020       1  2020     58         1     M         170   \n",
              "3   4  12/01/2020       1  2020     29         1     F         170   \n",
              "4   5  10/01/2020       1  2020     56         1     F         170   \n",
              "5   6  25/01/2020       1  2020     45         1     F         170   \n",
              "6   7  16/01/2020       1  2020     46         1     F         170   \n",
              "7   8   9/01/2020       1  2020     27         1     F         170   \n",
              "8   9  15/01/2020       1  2020      8         2     F         170   \n",
              "9  10   7/01/2020       1  2020      2         1     M         170   \n",
              "\n",
              "   cod_dpto_o  cod_mun_o  area_  ocupacion_       tip_ss_ cod_ase_  \\\n",
              "0          68        276      1        2411  Contributivo   EPS037   \n",
              "1          68        276      1        9997  Contributivo   EPS003   \n",
              "2          68        276      1        9999  Contributivo   EPS013   \n",
              "3          68        276      1        4121  Contributivo   EPS013   \n",
              "4          68        276      1        9210      Especial    37086   \n",
              "5          68        276      1        5121  Contributivo   EPS016   \n",
              "6          68        276      1        7732    Subsidiado    68000   \n",
              "7          68        276      1        2221  Contributivo   EPS005   \n",
              "8          68        276      1        9999    Subsidiado    68000   \n",
              "9          68        276      1        9997  Contributivo   EPS013   \n",
              "\n",
              "   gp_discapa  gp_desplaz  gp_migrant  gp_carcela  gp_gestan  gp_calle  \\\n",
              "0           2           2           2           2          1         2   \n",
              "1           2           2           2           2          2         2   \n",
              "2           2           2           2           2          2         2   \n",
              "3           2           2           2           2          2         2   \n",
              "4           2           2           2           2          2         2   \n",
              "5           2           2           2           2          2         2   \n",
              "6           2           2           2           2          2         2   \n",
              "7           2           2           2           2          2         2   \n",
              "8           2           2           2           2          2         2   \n",
              "9           2           2           2           2          2         2   \n",
              "\n",
              "   gp_psiquia  gp_vic_vio fecha_contagio inicio_sintomas  pac_hos_  \\\n",
              "0           2           2     17/01/2020      10/01/2020         2   \n",
              "1           2           2     10/01/2020       7/01/2020         2   \n",
              "2           2           2     12/01/2020       8/01/2020         2   \n",
              "3           2           2     10/01/2020       6/01/2020         2   \n",
              "4           2           2     10/01/2020       7/01/2020         1   \n",
              "5           2           2     16/01/2020       8/01/2020         2   \n",
              "6           2           2     13/01/2020      11/01/2020         1   \n",
              "7           2           1      9/01/2020       7/01/2020         2   \n",
              "8           2           2     12/01/2020      11/01/2020         1   \n",
              "9           2           2      7/01/2020       7/01/2020         2   \n",
              "\n",
              "     fec_hos_  condicion_final  fecha_defuncion fecha_nacimiento  \\\n",
              "0         NaN                1              NaN       12/11/1994   \n",
              "1         NaN                1              NaN        9/02/1995   \n",
              "2         NaN                1              NaN       19/09/1961   \n",
              "3         NaN                1              NaN        6/10/1990   \n",
              "4  10/01/2020                1              NaN       12/02/1963   \n",
              "5         NaN                1              NaN        6/04/1974   \n",
              "6  13/01/2020                1              NaN       29/09/1973   \n",
              "7         NaN                1              NaN       10/08/1992   \n",
              "8  12/01/2020                1              NaN       17/04/2019   \n",
              "9         NaN                1              NaN        7/06/2017   \n",
              "\n",
              "   certif_defuncion  familiar_sintomas  fiebre  cefalea  dolor_retroocular  \\\n",
              "0               NaN                  2       1        2                  1   \n",
              "1               NaN                  2       1        1                  2   \n",
              "2               NaN                  1       1        1                  1   \n",
              "3               NaN                  1       1        1                  2   \n",
              "4               NaN                  1       1        1                  2   \n",
              "5               NaN                  2       1        1                  2   \n",
              "6               NaN                  2       1        1                  2   \n",
              "7               NaN                  1       1        1                  2   \n",
              "8               NaN                  2       1        2                  2   \n",
              "9               NaN                  2       1        2                  2   \n",
              "\n",
              "   mialgias  artralgia  erupcion  dolor_abdomen  vomito  diarrea  somnolencia  \\\n",
              "0         1          1         1              2       2        2            2   \n",
              "1         1          2         2              2       2        2            2   \n",
              "2         1          1         1              2       2        1            2   \n",
              "3         2          1         1              2       2        2            2   \n",
              "4         1          2         2              2       1        1            2   \n",
              "5         1          1         2              2       2        1            2   \n",
              "6         1          1         1              1       2        1            2   \n",
              "7         2          1         2              2       2        2            2   \n",
              "8         1          2         1              2       2        2            2   \n",
              "9         2          1         1              2       2        2            2   \n",
              "\n",
              "   hipotension  hepatomegalia  hemorragia_mucosa  hipotermia  caida_plaquetas  \\\n",
              "0            2              2                  2           2                2   \n",
              "1            2              2                  2           2                2   \n",
              "2            2              2                  2           2                2   \n",
              "3            2              2                  2           2                2   \n",
              "4            2              2                  2           2                1   \n",
              "5            2              2                  2           2                2   \n",
              "6            2              2                  2           2                2   \n",
              "7            2              2                  2           2                2   \n",
              "8            2              2                  2           2                2   \n",
              "9            2              2                  2           2                2   \n",
              "\n",
              "   acum_liquido  aum_hematocrito                 conducta   latitud   longitud  \n",
              "0             2                2           1. Ambulatorio  7.076011 -73.102501  \n",
              "1             2                2           1. Ambulatorio  7.079495 -73.105400  \n",
              "2             2                2           1. Ambulatorio  7.090290 -73.091003  \n",
              "3             2                2           1. Ambulatorio  7.067435 -73.090958  \n",
              "4             2                2  2. Hospitalizacion piso  7.066905 -73.104980  \n",
              "5             2                2           1. Ambulatorio  7.073368 -73.088821  \n",
              "6             2                2  2. Hospitalizacion piso  7.080947 -73.089188  \n",
              "7             2                2           1. Ambulatorio  7.084087 -73.085953  \n",
              "8             2                2  2. Hospitalizacion piso  7.083333 -73.102295  \n",
              "9             2                2           1. Ambulatorio  7.067431 -73.097923  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1e1ec61a-bf53-4266-a6d4-2696022db2f8\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>fec_not</th>\n",
              "      <th>semana</th>\n",
              "      <th>año</th>\n",
              "      <th>edad_</th>\n",
              "      <th>uni_med_</th>\n",
              "      <th>sexo_</th>\n",
              "      <th>cod_pais_o</th>\n",
              "      <th>cod_dpto_o</th>\n",
              "      <th>cod_mun_o</th>\n",
              "      <th>area_</th>\n",
              "      <th>ocupacion_</th>\n",
              "      <th>tip_ss_</th>\n",
              "      <th>cod_ase_</th>\n",
              "      <th>gp_discapa</th>\n",
              "      <th>gp_desplaz</th>\n",
              "      <th>gp_migrant</th>\n",
              "      <th>gp_carcela</th>\n",
              "      <th>gp_gestan</th>\n",
              "      <th>gp_calle</th>\n",
              "      <th>gp_psiquia</th>\n",
              "      <th>gp_vic_vio</th>\n",
              "      <th>fecha_contagio</th>\n",
              "      <th>inicio_sintomas</th>\n",
              "      <th>pac_hos_</th>\n",
              "      <th>fec_hos_</th>\n",
              "      <th>condicion_final</th>\n",
              "      <th>fecha_defuncion</th>\n",
              "      <th>fecha_nacimiento</th>\n",
              "      <th>certif_defuncion</th>\n",
              "      <th>familiar_sintomas</th>\n",
              "      <th>fiebre</th>\n",
              "      <th>cefalea</th>\n",
              "      <th>dolor_retroocular</th>\n",
              "      <th>mialgias</th>\n",
              "      <th>artralgia</th>\n",
              "      <th>erupcion</th>\n",
              "      <th>dolor_abdomen</th>\n",
              "      <th>vomito</th>\n",
              "      <th>diarrea</th>\n",
              "      <th>somnolencia</th>\n",
              "      <th>hipotension</th>\n",
              "      <th>hepatomegalia</th>\n",
              "      <th>hemorragia_mucosa</th>\n",
              "      <th>hipotermia</th>\n",
              "      <th>caida_plaquetas</th>\n",
              "      <th>acum_liquido</th>\n",
              "      <th>aum_hematocrito</th>\n",
              "      <th>conducta</th>\n",
              "      <th>latitud</th>\n",
              "      <th>longitud</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>17/01/2020</td>\n",
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              "      <td>1</td>\n",
              "      <td>2411</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS037</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>17/01/2020</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12/11/1994</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.076011</td>\n",
              "      <td>-73.102501</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>10/01/2020</td>\n",
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              "      <td>2020</td>\n",
              "      <td>24</td>\n",
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              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9997</td>\n",
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              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
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              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.079495</td>\n",
              "      <td>-73.105400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
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              "      <td>12/01/2020</td>\n",
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              "      <td>2020</td>\n",
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              "      <td>1</td>\n",
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              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>12/01/2020</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.090290</td>\n",
              "      <td>-73.091003</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>12/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>29</td>\n",
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              "      <td>68</td>\n",
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              "      <td>1</td>\n",
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              "      <td>Contributivo</td>\n",
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              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>6/01/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6/10/1990</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.067435</td>\n",
              "      <td>-73.090958</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>56</td>\n",
              "      <td>1</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9210</td>\n",
              "      <td>Especial</td>\n",
              "      <td>37086</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>7/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>10/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12/02/1963</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2. Hospitalizacion piso</td>\n",
              "      <td>7.066905</td>\n",
              "      <td>-73.104980</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>25/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>45</td>\n",
              "      <td>1</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>5121</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS016</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>16/01/2020</td>\n",
              "      <td>8/01/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6/04/1974</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.073368</td>\n",
              "      <td>-73.088821</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>16/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>46</td>\n",
              "      <td>1</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>7732</td>\n",
              "      <td>Subsidiado</td>\n",
              "      <td>68000</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>13/01/2020</td>\n",
              "      <td>11/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>13/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>29/09/1973</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2. Hospitalizacion piso</td>\n",
              "      <td>7.080947</td>\n",
              "      <td>-73.089188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>9/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>27</td>\n",
              "      <td>1</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>2221</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS005</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>9/01/2020</td>\n",
              "      <td>7/01/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10/08/1992</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.084087</td>\n",
              "      <td>-73.085953</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>9</td>\n",
              "      <td>15/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>8</td>\n",
              "      <td>2</td>\n",
              "      <td>F</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9999</td>\n",
              "      <td>Subsidiado</td>\n",
              "      <td>68000</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>12/01/2020</td>\n",
              "      <td>11/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>12/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>17/04/2019</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2. Hospitalizacion piso</td>\n",
              "      <td>7.083333</td>\n",
              "      <td>-73.102295</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>10</td>\n",
              "      <td>7/01/2020</td>\n",
              "      <td>1</td>\n",
              "      <td>2020</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>M</td>\n",
              "      <td>170</td>\n",
              "      <td>68</td>\n",
              "      <td>276</td>\n",
              "      <td>1</td>\n",
              "      <td>9997</td>\n",
              "      <td>Contributivo</td>\n",
              "      <td>EPS013</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>7/01/2020</td>\n",
              "      <td>7/01/2020</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7/06/2017</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1. Ambulatorio</td>\n",
              "      <td>7.067431</td>\n",
              "      <td>-73.097923</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-1e1ec61a-bf53-4266-a6d4-2696022db2f8 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-1e1ec61a-bf53-4266-a6d4-2696022db2f8');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-1a87704a-4e2b-460f-8ab6-ee945c54de34\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1a87704a-4e2b-460f-8ab6-ee945c54de34')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-1a87704a-4e2b-460f-8ab6-ee945c54de34 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 278
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.dtypes"
      ],
      "metadata": {
        "id": "FH5OjWse_hB8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5ee821fb-dd40-4cd0-a26d-1ddf1326d77d"
      },
      "execution_count": 279,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ID                     int64\n",
              "fec_not               object\n",
              "semana                 int64\n",
              "año                    int64\n",
              "edad_                  int64\n",
              "uni_med_               int64\n",
              "sexo_                 object\n",
              "cod_pais_o             int64\n",
              "cod_dpto_o             int64\n",
              "cod_mun_o              int64\n",
              "area_                  int64\n",
              "ocupacion_             int64\n",
              "tip_ss_               object\n",
              "cod_ase_              object\n",
              "gp_discapa             int64\n",
              "gp_desplaz             int64\n",
              "gp_migrant             int64\n",
              "gp_carcela             int64\n",
              "gp_gestan              int64\n",
              "gp_calle               int64\n",
              "gp_psiquia             int64\n",
              "gp_vic_vio             int64\n",
              "fecha_contagio        object\n",
              "inicio_sintomas       object\n",
              "pac_hos_               int64\n",
              "fec_hos_              object\n",
              "condicion_final        int64\n",
              "fecha_defuncion      float64\n",
              "fecha_nacimiento      object\n",
              "certif_defuncion     float64\n",
              "familiar_sintomas      int64\n",
              "fiebre                 int64\n",
              "cefalea                int64\n",
              "dolor_retroocular      int64\n",
              "mialgias               int64\n",
              "artralgia              int64\n",
              "erupcion               int64\n",
              "dolor_abdomen          int64\n",
              "vomito                 int64\n",
              "diarrea                int64\n",
              "somnolencia            int64\n",
              "hipotension            int64\n",
              "hepatomegalia          int64\n",
              "hemorragia_mucosa      int64\n",
              "hipotermia             int64\n",
              "caida_plaquetas        int64\n",
              "acum_liquido           int64\n",
              "aum_hematocrito        int64\n",
              "conducta              object\n",
              "latitud              float64\n",
              "longitud             float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 279
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def mostrar_columnas_con_nulos(dataframe):\n",
        "    # Obtener un DataFrame booleano que muestra True donde hay valores nulos\n",
        "    valores_nulos = dataframe.isnull()\n",
        "\n",
        "    # Calcular la cantidad de valores nulos en cada columna\n",
        "    cantidad_nulos = valores_nulos.sum()\n",
        "\n",
        "    # Filtrar las columnas que tienen al menos un valor nulo\n",
        "    columnas_con_nulos = cantidad_nulos[cantidad_nulos > 0]\n",
        "\n",
        "    # Mostrar las columnas con valores nulos y su cantidad\n",
        "    if not columnas_con_nulos.empty:\n",
        "        print(\"Columnas con valores nulos y su cantidad:\\n\")\n",
        "        print(columnas_con_nulos)\n",
        "    else:\n",
        "        print(\"No se encontraron valores nulos en ninguna columna.\")"
      ],
      "metadata": {
        "id": "YY4FPOU8BNhK"
      },
      "execution_count": 280,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "mostrar_columnas_con_nulos(df)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "horI38eDBRXR",
        "outputId": "8d2f17d1-e284-4b3b-f79f-60c0f05ec6a9"
      },
      "execution_count": 281,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Columnas con valores nulos y su cantidad:\n",
            "\n",
            "cod_ase_               9\n",
            "fecha_contagio         2\n",
            "inicio_sintomas        2\n",
            "fec_hos_            1014\n",
            "fecha_defuncion     1262\n",
            "certif_defuncion    1262\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def imprimir_valores_unicos(df, max_valores=10):\n",
        "    for columna in df.columns:\n",
        "        valores_unicos = df[columna].unique()\n",
        "        if len(valores_unicos) <= max_valores:\n",
        "            print(f'Valores únicos en la columna {columna}:')\n",
        "            for valor in valores_unicos:\n",
        "                print(valor)\n",
        "        else:\n",
        "            print(f'La columna {columna} tiene más de {max_valores} valores únicos, por lo que no se imprimen.')\n",
        "        print('\\n')\n",
        "\n",
        "# Llama a la función con tu DataFrame df\n",
        "imprimir_valores_unicos(df)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EdGjGzXXKuZB",
        "outputId": "893ac090-a19b-4ee0-af77-c81776a1666f"
      },
      "execution_count": 282,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "La columna ID tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "La columna fec_not tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "La columna semana tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "Valores únicos en la columna año:\n",
            "2020\n",
            "\n",
            "\n",
            "La columna edad_ tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "Valores únicos en la columna uni_med_:\n",
            "1\n",
            "2\n",
            "4\n",
            "\n",
            "\n",
            "Valores únicos en la columna sexo_:\n",
            "F\n",
            "M\n",
            "\n",
            "\n",
            "Valores únicos en la columna cod_pais_o:\n",
            "170\n",
            "\n",
            "\n",
            "Valores únicos en la columna cod_dpto_o:\n",
            "68\n",
            "23\n",
            "20\n",
            "41\n",
            "91\n",
            "\n",
            "\n",
            "Valores únicos en la columna cod_mun_o:\n",
            "276\n",
            "1\n",
            "547\n",
            "307\n",
            "81\n",
            "206\n",
            "77\n",
            "710\n",
            "0\n",
            "\n",
            "\n",
            "Valores únicos en la columna area_:\n",
            "1\n",
            "2\n",
            "3\n",
            "\n",
            "\n",
            "La columna ocupacion_ tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "Valores únicos en la columna tip_ss_:\n",
            "Contributivo\n",
            "Especial\n",
            "Subsidiado\n",
            "Particular\n",
            "No asegurado\n",
            "\n",
            "\n",
            "La columna cod_ase_ tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "Valores únicos en la columna gp_discapa:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna gp_desplaz:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna gp_migrant:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna gp_carcela:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna gp_gestan:\n",
            "1\n",
            "2\n",
            "\n",
            "\n",
            "Valores únicos en la columna gp_calle:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna gp_psiquia:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna gp_vic_vio:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "La columna fecha_contagio tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "La columna inicio_sintomas tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "Valores únicos en la columna pac_hos_:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "La columna fec_hos_ tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "Valores únicos en la columna condicion_final:\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna fecha_defuncion:\n",
            "nan\n",
            "\n",
            "\n",
            "La columna fecha_nacimiento tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "Valores únicos en la columna certif_defuncion:\n",
            "nan\n",
            "\n",
            "\n",
            "Valores únicos en la columna familiar_sintomas:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna fiebre:\n",
            "1\n",
            "2\n",
            "\n",
            "\n",
            "Valores únicos en la columna cefalea:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna dolor_retroocular:\n",
            "1\n",
            "2\n",
            "\n",
            "\n",
            "Valores únicos en la columna mialgias:\n",
            "1\n",
            "2\n",
            "\n",
            "\n",
            "Valores únicos en la columna artralgia:\n",
            "1\n",
            "2\n",
            "\n",
            "\n",
            "Valores únicos en la columna erupcion:\n",
            "1\n",
            "2\n",
            "\n",
            "\n",
            "Valores únicos en la columna dolor_abdomen:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna vomito:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna diarrea:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna somnolencia:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna hipotension:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna hepatomegalia:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna hemorragia_mucosa:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna hipotermia:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna caida_plaquetas:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna acum_liquido:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna aum_hematocrito:\n",
            "2\n",
            "1\n",
            "\n",
            "\n",
            "Valores únicos en la columna conducta:\n",
            "1. Ambulatorio\n",
            "2. Hospitalizacion piso\n",
            "4. Observacion\n",
            "3. UCI\n",
            "\n",
            "\n",
            "La columna latitud tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n",
            "La columna longitud tiene más de 10 valores únicos, por lo que no se imprimen.\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def imprimir_valores_unicos(df, columnas):\n",
        "    for columna in columnas:\n",
        "        if columna in df.columns:\n",
        "            valores_unicos = df[columna].unique()\n",
        "            print(f'Valores únicos en la columna {columna}:')\n",
        "            for valor in valores_unicos:\n",
        "                print(valor)\n",
        "            print('\\n')\n",
        "\n",
        "# Llama a la función con tu DataFrame df y una lista de columnas específicas\n",
        "columnas_especificas = ['cod_pais_o', 'cod_dpto_o']\n",
        "imprimir_valores_unicos(df, columnas_especificas)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0xqGFRFCJ8sB",
        "outputId": "e13437c3-8ed3-45c8-c6cd-d898bf2a48a5"
      },
      "execution_count": 283,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Valores únicos en la columna cod_pais_o:\n",
            "170\n",
            "\n",
            "\n",
            "Valores únicos en la columna cod_dpto_o:\n",
            "68\n",
            "23\n",
            "20\n",
            "41\n",
            "91\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Importar librerías necesarias\n",
        "import pandas as pd\n",
        "from sklearn.preprocessing import LabelEncoder\n",
        "\n",
        "# Definir una función para codificar variables categóricas\n",
        "def encode_categorical_column(df, column_name):\n",
        "    le = LabelEncoder()\n",
        "    df[column_name] = le.fit_transform(df[column_name])\n",
        "    print(f\"Mapeo de valores textuales a numéricos para '{column_name}':\")\n",
        "    for label, numeric_value in zip(le.classes_, le.transform(le.classes_)):\n",
        "        print(f\"{label} -> {numeric_value}\")\n",
        "    print(\"\\n\")\n",
        "\n",
        "# Crear una copia del DataFrame original df\n",
        "dfClean = df.copy()\n",
        "\n",
        "# Limpieza de datos en dfClean\n",
        "# Eliminar filas con valores nulos en las columnas especificadas\n",
        "columns_with_nulls = ['cod_ase_', 'fecha_contagio', 'inicio_sintomas']\n",
        "dfClean.dropna(subset=columns_with_nulls, inplace=True)\n",
        "\n",
        "# Verificar si las columnas existen antes de eliminarlas\n",
        "columns_to_remove = ['ID', 'año', 'cod_dpto_o', 'cod_pais_o', 'semana', 'cod_mun_o', 'fec_not', 'ocupacion_', 'fec_hos_', 'fecha_defuncion', 'certif_defuncion', 'cod_ase_', 'fecha_contagio', 'inicio_sintomas', 'fecha_nacimiento', ]\n",
        "existing_columns = set(dfClean.columns)\n",
        "columns_to_remove = [col for col in columns_to_remove if col in existing_columns]\n",
        "\n",
        "if columns_to_remove:\n",
        "    dfClean.drop(columns_to_remove, axis=1, inplace=True)\n",
        "\n",
        "# Utilizar la función para codificar variables textuales\n",
        "encode_categorical_column(dfClean, 'sexo_')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vinNVEyEAZOz",
        "outputId": "a183fc72-c7c6-4f1e-acab-adc0b6da2774"
      },
      "execution_count": 284,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mapeo de valores textuales a numéricos para 'sexo_':\n",
            "F -> 0\n",
            "M -> 1\n",
            "\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Utilizar get_dummies para codificar variables textuales en one-hot\n",
        "dfClean = pd.get_dummies(dfClean, columns=['tip_ss_', 'conducta'])\n",
        "\n",
        "# Esto creará nuevas columnas para 'tip_ss_' y 'conducta' con valores numéricos únicos\n",
        "# Ahora, dfClean contiene las columnas codificadas en one-hot"
      ],
      "metadata": {
        "id": "1OJrug1UIwFy"
      },
      "execution_count": 285,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dfClean"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 478
        },
        "id": "cpma32hLAyhW",
        "outputId": "9108771f-9366-4eb3-ba14-f319c71dee20"
      },
      "execution_count": 286,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      edad_  uni_med_  sexo_  area_  gp_discapa  gp_desplaz  gp_migrant  \\\n",
              "0        25         1      0      1           2           2           2   \n",
              "1        24         1      1      1           2           2           2   \n",
              "2        58         1      1      1           2           2           2   \n",
              "3        29         1      0      1           2           2           2   \n",
              "4        56         1      0      1           2           2           2   \n",
              "...     ...       ...    ...    ...         ...         ...         ...   \n",
              "1257     36         1      0      1           2           2           2   \n",
              "1258     42         1      1      1           2           2           2   \n",
              "1259      2         1      1      1           2           2           2   \n",
              "1260     12         1      0      1           2           2           2   \n",
              "1261     14         1      1      1           2           2           2   \n",
              "\n",
              "      gp_carcela  gp_gestan  gp_calle  gp_psiquia  gp_vic_vio  pac_hos_  \\\n",
              "0              2          1         2           2           2         2   \n",
              "1              2          2         2           2           2         2   \n",
              "2              2          2         2           2           2         2   \n",
              "3              2          2         2           2           2         2   \n",
              "4              2          2         2           2           2         1   \n",
              "...          ...        ...       ...         ...         ...       ...   \n",
              "1257           2          2         2           2           2         2   \n",
              "1258           2          2         2           2           2         1   \n",
              "1259           2          2         2           2           2         2   \n",
              "1260           2          2         2           2           2         2   \n",
              "1261           2          2         2           2           2         1   \n",
              "\n",
              "      condicion_final  familiar_sintomas  fiebre  cefalea  dolor_retroocular  \\\n",
              "0                   1                  2       1        2                  1   \n",
              "1                   1                  2       1        1                  2   \n",
              "2                   1                  1       1        1                  1   \n",
              "3                   1                  1       1        1                  2   \n",
              "4                   1                  1       1        1                  2   \n",
              "...               ...                ...     ...      ...                ...   \n",
              "1257                1                  2       1        1                  1   \n",
              "1258                1                  2       1        1                  2   \n",
              "1259                1                  1       1        1                  1   \n",
              "1260                1                  2       1        1                  2   \n",
              "1261                1                  2       1        1                  1   \n",
              "\n",
              "      mialgias  artralgia  erupcion  dolor_abdomen  vomito  diarrea  \\\n",
              "0            1          1         1              2       2        2   \n",
              "1            1          2         2              2       2        2   \n",
              "2            1          1         1              2       2        1   \n",
              "3            2          1         1              2       2        2   \n",
              "4            1          2         2              2       1        1   \n",
              "...        ...        ...       ...            ...     ...      ...   \n",
              "1257         1          1         2              2       1        2   \n",
              "1258         1          1         2              2       2        2   \n",
              "1259         1          1         1              2       2        2   \n",
              "1260         1          2         1              2       2        2   \n",
              "1261         1          1         1              2       2        2   \n",
              "\n",
              "      somnolencia  hipotension  hepatomegalia  hemorragia_mucosa  hipotermia  \\\n",
              "0               2            2              2                  2           2   \n",
              "1               2            2              2                  2           2   \n",
              "2               2            2              2                  2           2   \n",
              "3               2            2              2                  2           2   \n",
              "4               2            2              2                  2           2   \n",
              "...           ...          ...            ...                ...         ...   \n",
              "1257            2            2              2                  1           2   \n",
              "1258            2            2              2                  2           2   \n",
              "1259            2            2              2                  2           2   \n",
              "1260            2            2              2                  2           2   \n",
              "1261            2            2              2                  2           2   \n",
              "\n",
              "      caida_plaquetas  acum_liquido  aum_hematocrito   latitud   longitud  \\\n",
              "0                   2             2                2  7.076011 -73.102501   \n",
              "1                   2             2                2  7.079495 -73.105400   \n",
              "2                   2             2                2  7.090290 -73.091003   \n",
              "3                   2             2                2  7.067435 -73.090958   \n",
              "4                   1             2                2  7.066905 -73.104980   \n",
              "...               ...           ...              ...       ...        ...   \n",
              "1257                2             2                2  7.072610 -73.099487   \n",
              "1258                1             2                1  7.065252 -73.103607   \n",
              "1259                2             2                2  7.091391 -73.103264   \n",
              "1260                2             2                2  7.061083 -73.097000   \n",
              "1261                2             2                2  7.062521 -73.080444   \n",
              "\n",
              "      tip_ss__Contributivo  tip_ss__Especial  tip_ss__Particular  \\\n",
              "0                        1                 0                   0   \n",
              "1                        1                 0                   0   \n",
              "2                        1                 0                   0   \n",
              "3                        1                 0                   0   \n",
              "4                        0                 1                   0   \n",
              "...                    ...               ...                 ...   \n",
              "1257                     1                 0                   0   \n",
              "1258                     1                 0                   0   \n",
              "1259                     1                 0                   0   \n",
              "1260                     1                 0                   0   \n",
              "1261                     1                 0                   0   \n",
              "\n",
              "      tip_ss__Subsidiado  conducta_1. Ambulatorio  \\\n",
              "0                      0                        1   \n",
              "1                      0                        1   \n",
              "2                      0                        1   \n",
              "3                      0                        1   \n",
              "4                      0                        0   \n",
              "...                  ...                      ...   \n",
              "1257                   0                        1   \n",
              "1258                   0                        0   \n",
              "1259                   0                        1   \n",
              "1260                   0                        1   \n",
              "1261                   0                        0   \n",
              "\n",
              "      conducta_2. Hospitalizacion piso  conducta_3. UCI  \\\n",
              "0                                    0                0   \n",
              "1                                    0                0   \n",
              "2                                    0                0   \n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1251 rows × 42 columns</p>\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "      border: none;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "\n",
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              "      background-color: #434B5C;\n",
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              "      fill: #FFFFFF;\n",
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              "\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-0ef930e2-e882-4876-aed2-1ed0accef88e button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-0ef930e2-e882-4876-aed2-1ed0accef88e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
              "\n",
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              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-5657e39d-d974-4f6b-b9d8-f58bb37498b5 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 286
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "gGK34EROJudQ"
      },
      "execution_count": 286,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import StandardScaler\n",
        "\n",
        "# Seleccionar las columnas que deseas normalizar (asegúrate de que estas columnas contengan datos numéricos)\n",
        "columns_to_normalize = ['edad_', 'latitud', 'longitud']  # Reemplaza con los nombres de tus columnas\n",
        "\n",
        "# Crear un nuevo DataFrame 'df_normalized' para almacenar los datos normalizados\n",
        "df_normalized = dfClean.copy()\n",
        "\n",
        "def reemplazar_valores_uno_dos(df):\n",
        "    for columna in df.columns:\n",
        "        valores_unicos = df[columna].unique()\n",
        "        if len(valores_unicos) == 2 and 1 in valores_unicos and 2 in valores_unicos:\n",
        "            df[columna] = df[columna].replace({1: 0, 2: 1})\n",
        "\n",
        "# Llama a la función con tu DataFrame df\n",
        "reemplazar_valores_uno_dos(df_normalized)\n",
        "\n",
        "# Crear un objeto StandardScaler\n",
        "scaler = StandardScaler()\n",
        "\n",
        "# Aplicar la normalización a las columnas seleccionadas\n",
        "df_normalized[columns_to_normalize] = scaler.fit_transform(dfClean[columns_to_normalize])\n",
        "\n",
        "# Ahora, 'df_normalized' contiene las características normalizadas.\n",
        "# Puedes acceder a las primeras 5 filas de las características normalizadas de la siguiente manera:\n",
        "scaled_features = df_normalized[columns_to_normalize].head()"
      ],
      "metadata": {
        "id": "oriZFmaBGePf"
      },
      "execution_count": 287,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_normalized"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 478
        },
        "id": "-Ru4VJZlLSgJ",
        "outputId": "f64e7633-63e5-4162-8afd-f9e7d996e875"
      },
      "execution_count": 288,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         edad_  uni_med_  sexo_  area_  gp_discapa  gp_desplaz  gp_migrant  \\\n",
              "0    -0.263977         1      0      1           1           1           1   \n",
              "1    -0.312915         1      1      1           1           1           1   \n",
              "2     1.350982         1      1      1           1           1           1   \n",
              "3    -0.068224         1      0      1           1           1           1   \n",
              "4     1.253106         1      0      1           1           1           1   \n",
              "...        ...       ...    ...    ...         ...         ...         ...   \n",
              "1257  0.274343         1      0      1           1           1           1   \n",
              "1258  0.567972         1      1      1           1           1           1   \n",
              "1259 -1.389554         1      1      1           1           1           1   \n",
              "1260 -0.900172         1      0      1           1           1           1   \n",
              "1261 -0.802296         1      1      1           1           1           1   \n",
              "\n",
              "      gp_carcela  gp_gestan  gp_calle  gp_psiquia  gp_vic_vio  pac_hos_  \\\n",
              "0              1          0         1           1           1         1   \n",
              "1              1          1         1           1           1         1   \n",
              "2              1          1         1           1           1         1   \n",
              "3              1          1         1           1           1         1   \n",
              "4              1          1         1           1           1         0   \n",
              "...          ...        ...       ...         ...         ...       ...   \n",
              "1257           1          1         1           1           1         1   \n",
              "1258           1          1         1           1           1         0   \n",
              "1259           1          1         1           1           1         1   \n",
              "1260           1          1         1           1           1         1   \n",
              "1261           1          1         1           1           1         0   \n",
              "\n",
              "      condicion_final  familiar_sintomas  fiebre  cefalea  dolor_retroocular  \\\n",
              "0                   1                  1       0        1                  0   \n",
              "1                   1                  1       0        0                  1   \n",
              "2                   1                  0       0        0                  0   \n",
              "3                   1                  0       0        0                  1   \n",
              "4                   1                  0       0        0                  1   \n",
              "...               ...                ...     ...      ...                ...   \n",
              "1257                1                  1       0        0                  0   \n",
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              "1259                1                  0       0        0                  0   \n",
              "1260                1                  1       0        0                  1   \n",
              "1261                1                  1       0        0                  0   \n",
              "\n",
              "      mialgias  artralgia  erupcion  dolor_abdomen  vomito  diarrea  \\\n",
              "0            0          0         0              1       1        1   \n",
              "1            0          1         1              1       1        1   \n",
              "2            0          0         0              1       1        0   \n",
              "3            1          0         0              1       1        1   \n",
              "4            0          1         1              1       0        0   \n",
              "...        ...        ...       ...            ...     ...      ...   \n",
              "1257         0          0         1              1       0        1   \n",
              "1258         0          0         1              1       1        1   \n",
              "1259         0          0         0              1       1        1   \n",
              "1260         0          1         0              1       1        1   \n",
              "1261         0          0         0              1       1        1   \n",
              "\n",
              "      somnolencia  hipotension  hepatomegalia  hemorragia_mucosa  hipotermia  \\\n",
              "0               1            1              1                  1           1   \n",
              "1               1            1              1                  1           1   \n",
              "2               1            1              1                  1           1   \n",
              "3               1            1              1                  1           1   \n",
              "4               1            1              1                  1           1   \n",
              "...           ...          ...            ...                ...         ...   \n",
              "1257            1            1              1                  0           1   \n",
              "1258            1            1              1                  1           1   \n",
              "1259            1            1              1                  1           1   \n",
              "1260            1            1              1                  1           1   \n",
              "1261            1            1              1                  1           1   \n",
              "\n",
              "      caida_plaquetas  acum_liquido  aum_hematocrito   latitud  longitud  \\\n",
              "0                   1             1                1 -0.151960 -0.904331   \n",
              "1                   1             1                1  0.170292 -1.268275   \n",
              "2                   1             1                1  1.168671  0.538994   \n",
              "3                   1             1                1 -0.945177  0.544741   \n",
              "4                   0             1                1 -0.994174 -1.215598   \n",
              "...               ...           ...              ...       ...       ...   \n",
              "1257                1             1                1 -0.466539 -0.526019   \n",
              "1258                0             1                0 -1.147075 -1.043204   \n",
              "1259                1             1                1  1.270458 -1.000104   \n",
              "1260                1             1                1 -1.532614 -0.213794   \n",
              "1261                1             1                1 -1.399647  1.864516   \n",
              "\n",
              "      tip_ss__Contributivo  tip_ss__Especial  tip_ss__Particular  \\\n",
              "0                        1                 0                   0   \n",
              "1                        1                 0                   0   \n",
              "2                        1                 0                   0   \n",
              "3                        1                 0                   0   \n",
              "4                        0                 1                   0   \n",
              "...                    ...               ...                 ...   \n",
              "1257                     1                 0                   0   \n",
              "1258                     1                 0                   0   \n",
              "1259                     1                 0                   0   \n",
              "1260                     1                 0                   0   \n",
              "1261                     1                 0                   0   \n",
              "\n",
              "      tip_ss__Subsidiado  conducta_1. Ambulatorio  \\\n",
              "0                      0                        1   \n",
              "1                      0                        1   \n",
              "2                      0                        1   \n",
              "3                      0                        1   \n",
              "4                      0                        0   \n",
              "...                  ...                      ...   \n",
              "1257                   0                        1   \n",
              "1258                   0                        0   \n",
              "1259                   0                        1   \n",
              "1260                   0                        1   \n",
              "1261                   0                        0   \n",
              "\n",
              "      conducta_2. Hospitalizacion piso  conducta_3. UCI  \\\n",
              "0                                    0                0   \n",
              "1                                    0                0   \n",
              "2                                    0                0   \n",
              "3                                    0                0   \n",
              "4                                    1                0   \n",
              "...                                ...              ...   \n",
              "1257                                 0                0   \n",
              "1258                                 1                0   \n",
              "1259                                 0                0   \n",
              "1260                                 0                0   \n",
              "1261                                 1                0   \n",
              "\n",
              "      conducta_4. Observacion  \n",
              "0                           0  \n",
              "1                           0  \n",
              "2                           0  \n",
              "3                           0  \n",
              "4                           0  \n",
              "...                       ...  \n",
              "1257                        0  \n",
              "1258                        0  \n",
              "1259                        0  \n",
              "1260                        0  \n",
              "1261                        0  \n",
              "\n",
              "[1251 rows x 42 columns]"
            ],
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              "      <th></th>\n",
              "      <th>edad_</th>\n",
              "      <th>uni_med_</th>\n",
              "      <th>sexo_</th>\n",
              "      <th>area_</th>\n",
              "      <th>gp_discapa</th>\n",
              "      <th>gp_desplaz</th>\n",
              "      <th>gp_migrant</th>\n",
              "      <th>gp_carcela</th>\n",
              "      <th>gp_gestan</th>\n",
              "      <th>gp_calle</th>\n",
              "      <th>gp_psiquia</th>\n",
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              "      <th>fiebre</th>\n",
              "      <th>cefalea</th>\n",
              "      <th>dolor_retroocular</th>\n",
              "      <th>mialgias</th>\n",
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              "      <th>dolor_abdomen</th>\n",
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              "      <th>conducta_3. UCI</th>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.151960</td>\n",
              "      <td>-0.904331</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-0.312915</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.170292</td>\n",
              "      <td>-1.268275</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.350982</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.168671</td>\n",
              "      <td>0.538994</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.068224</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.945177</td>\n",
              "      <td>0.544741</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.253106</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.994174</td>\n",
              "      <td>-1.215598</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <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",
              "      <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>1257</th>\n",
              "      <td>0.274343</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.466539</td>\n",
              "      <td>-0.526019</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1258</th>\n",
              "      <td>0.567972</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>-1.147075</td>\n",
              "      <td>-1.043204</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1259</th>\n",
              "      <td>-1.389554</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.270458</td>\n",
              "      <td>-1.000104</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1260</th>\n",
              "      <td>-0.900172</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-1.532614</td>\n",
              "      <td>-0.213794</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1261</th>\n",
              "      <td>-0.802296</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-1.399647</td>\n",
              "      <td>1.864516</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1251 rows × 42 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8c16f90c-8e40-4d0d-bd30-f6b498938b5b')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "        document.querySelector('#df-8c16f90c-8e40-4d0d-bd30-f6b498938b5b button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        const element = document.querySelector('#df-8c16f90c-8e40-4d0d-bd30-f6b498938b5b');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-c4ca685b-2531-41c0-be1b-a3ef1fa207ca\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c4ca685b-2531-41c0-be1b-a3ef1fa207ca')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-c4ca685b-2531-41c0-be1b-a3ef1fa207ca button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 288
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans\n",
        "from kneed import KneeLocator\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Aplicar el código K-Means al DataFrame normalizado df_normalized\n",
        "\n",
        "kmeans_kwargs = {\n",
        "    \"init\": \"random\",\n",
        "    \"n_init\": 10,\n",
        "    \"max_iter\": 300,\n",
        "    \"random_state\": 42,\n",
        "}\n",
        "\n",
        "sse = []\n",
        "for k in range(1, 11):\n",
        "    kmeans = KMeans(n_clusters=k, **kmeans_kwargs)\n",
        "    kmeans.fit(df_normalized)  # Usar el DataFrame normalizado df_normalized en lugar de scaled_features\n",
        "    sse.append(kmeans.inertia_)\n",
        "\n",
        "# Trazar la gráfica del codo\n",
        "plt.style.use(\"fivethirtyeight\")\n",
        "plt.plot(range(1, 11), sse)\n",
        "plt.xticks(range(1, 11))\n",
        "plt.xlabel(\"Number of Clusters\")\n",
        "plt.ylabel(\"SSE\")\n",
        "plt.show()\n",
        "\n",
        "# Encontrar el codo (elbow) utilizando la biblioteca KneeLocator\n",
        "kl = KneeLocator(range(1, 11), sse, curve=\"convex\", direction=\"decreasing\")\n",
        "\n",
        "# Obtener el número óptimo de clusters (elbow)\n",
        "optimal_k = kl.elbow\n",
        "print(\"Número óptimo de clusters (elbow):\", optimal_k)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 496
        },
        "id": "TyJulZJHOkK8",
        "outputId": "e319c607-d8fe-40d7-bc24-28285fe4d22a"
      },
      "execution_count": 289,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Número óptimo de clusters (elbow): 4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans\n",
        "from sklearn.metrics import silhouette_score\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "silhouette_coefficients = []\n",
        "\n",
        "# Aquí se inicia con 2 clústeres\n",
        "for k in range(2, 11):\n",
        "    kmeans = KMeans(n_clusters=k, **kmeans_kwargs)\n",
        "    kmeans.fit(df_normalized)  # Usar el DataFrame normalizado df_normalized en lugar de scaled_features\n",
        "    score = silhouette_score(df_normalized, kmeans.labels_)  # Calcular el coeficiente de silueta\n",
        "    silhouette_coefficients.append(score)\n",
        "\n",
        "# Encontrar el número óptimo de clusters basado en el coeficiente de silueta\n",
        "optimal_k = silhouette_coefficients.index(max(silhouette_coefficients)) + 2  # Sumar 2 para compensar el inicio desde k=2\n",
        "\n",
        "# Trazar la gráfica del coeficiente de silueta\n",
        "plt.style.use(\"fivethirtyeight\")\n",
        "plt.plot(range(2, 11), silhouette_coefficients)\n",
        "plt.xticks(range(2, 11))\n",
        "plt.xlabel(\"Number of Clusters\")\n",
        "plt.ylabel(\"Silhouette Coefficient\")\n",
        "plt.show()\n",
        "\n",
        "print(\"Número óptimo de clusters (según el coeficiente de silueta):\", optimal_k)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 496
        },
        "id": "Ly-Lv13nOyDS",
        "outputId": "66ebc150-e0e6-4872-aa1a-7600f02d1214"
      },
      "execution_count": 290,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Número óptimo de clusters (según el coeficiente de silueta): 3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import KMeans\n",
        "\n",
        "# Suponiendo que 'df_normalized' contiene tus datos normalizados y que deseas realizar la clustering en estas características\n",
        "# Crear un objeto KMeans con 4 clusters\n",
        "kmeans = KMeans(n_clusters=4)\n",
        "\n",
        "# Realizar el clustering en tus datos normalizados y obtener las etiquetas de cluster para cada fila\n",
        "df_normalized['cluster'] = kmeans.fit_predict(df_normalized[columns_to_normalize])\n",
        "\n",
        "# Ahora, el DataFrame 'df_normalized' contiene una nueva columna llamada 'cluster' que contiene las etiquetas de cluster para cada fila.\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zhiHsViwP39N",
        "outputId": "4963509f-87fb-4041-9d24-0d17f35d47f1"
      },
      "execution_count": 291,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/sklearn/cluster/_kmeans.py:870: FutureWarning: The default value of `n_init` will change from 10 to 'auto' in 1.4. Set the value of `n_init` explicitly to suppress the warning\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_normalized"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 478
        },
        "id": "moiNQI5nQqZz",
        "outputId": "5bad5ec3-0c98-4c97-e9fc-ae078eb5daa3"
      },
      "execution_count": 292,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         edad_  uni_med_  sexo_  area_  gp_discapa  gp_desplaz  gp_migrant  \\\n",
              "0    -0.263977         1      0      1           1           1           1   \n",
              "1    -0.312915         1      1      1           1           1           1   \n",
              "2     1.350982         1      1      1           1           1           1   \n",
              "3    -0.068224         1      0      1           1           1           1   \n",
              "4     1.253106         1      0      1           1           1           1   \n",
              "...        ...       ...    ...    ...         ...         ...         ...   \n",
              "1257  0.274343         1      0      1           1           1           1   \n",
              "1258  0.567972         1      1      1           1           1           1   \n",
              "1259 -1.389554         1      1      1           1           1           1   \n",
              "1260 -0.900172         1      0      1           1           1           1   \n",
              "1261 -0.802296         1      1      1           1           1           1   \n",
              "\n",
              "      gp_carcela  gp_gestan  gp_calle  gp_psiquia  gp_vic_vio  pac_hos_  \\\n",
              "0              1          0         1           1           1         1   \n",
              "1              1          1         1           1           1         1   \n",
              "2              1          1         1           1           1         1   \n",
              "3              1          1         1           1           1         1   \n",
              "4              1          1         1           1           1         0   \n",
              "...          ...        ...       ...         ...         ...       ...   \n",
              "1257           1          1         1           1           1         1   \n",
              "1258           1          1         1           1           1         0   \n",
              "1259           1          1         1           1           1         1   \n",
              "1260           1          1         1           1           1         1   \n",
              "1261           1          1         1           1           1         0   \n",
              "\n",
              "      condicion_final  familiar_sintomas  fiebre  cefalea  dolor_retroocular  \\\n",
              "0                   1                  1       0        1                  0   \n",
              "1                   1                  1       0        0                  1   \n",
              "2                   1                  0       0        0                  0   \n",
              "3                   1                  0       0        0                  1   \n",
              "4                   1                  0       0        0                  1   \n",
              "...               ...                ...     ...      ...                ...   \n",
              "1257                1                  1       0        0                  0   \n",
              "1258                1                  1       0        0                  1   \n",
              "1259                1                  0       0        0                  0   \n",
              "1260                1                  1       0        0                  1   \n",
              "1261                1                  1       0        0                  0   \n",
              "\n",
              "      mialgias  artralgia  erupcion  dolor_abdomen  vomito  diarrea  \\\n",
              "0            0          0         0              1       1        1   \n",
              "1            0          1         1              1       1        1   \n",
              "2            0          0         0              1       1        0   \n",
              "3            1          0         0              1       1        1   \n",
              "4            0          1         1              1       0        0   \n",
              "...        ...        ...       ...            ...     ...      ...   \n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.270458</td>\n",
              "      <td>-1.000104</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>1260</th>\n",
              "      <td>-0.900172</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-1.532614</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1261</th>\n",
              "      <td>-0.802296</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-1.399647</td>\n",
              "      <td>1.864516</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1251 rows × 43 columns</p>\n",
              "</div>\n",
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              "\n",
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              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
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              "        document.querySelector('#df-f647819d-85d8-43d0-83cb-1035c2d4a338 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f647819d-85d8-43d0-83cb-1035c2d4a338');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
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              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "    30% {\n",
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              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-4eb5a6a1-93c0-4e0e-887b-77afe3ab3efb button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 292
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Suponiendo que ya has realizado el clustering y tienes la columna 'cluster' en 'df_normalized'\n",
        "\n",
        "# Crear DataFrames separados para cada cluster\n",
        "cluster_dataframes = [df_normalized[df_normalized['cluster'] == i].copy() for i in range(4)]\n"
      ],
      "metadata": {
        "id": "XzJJBascRDkJ"
      },
      "execution_count": 293,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Dataset con filas de cluster 0:\")\n",
        "cluster_dataframes[0].head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "763DzGn2RO2A",
        "outputId": "ee96085b-7cef-4778-8d1f-d5caf69f14f1"
      },
      "execution_count": 294,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset con filas de cluster 0:\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       edad_  uni_med_  sexo_  area_  gp_discapa  gp_desplaz  gp_migrant  \\\n",
              "3  -0.068224         1      0      1           1           1           1   \n",
              "5   0.714786         1      0      1           1           1           1   \n",
              "11 -0.998049         1      0      1           1           1           1   \n",
              "13 -0.655482         1      0      1           1           1           0   \n",
              "14 -0.557605         1      1      1           1           1           1   \n",
              "\n",
              "    gp_carcela  gp_gestan  gp_calle  gp_psiquia  gp_vic_vio  pac_hos_  \\\n",
              "3            1          1         1           1           1         1   \n",
              "5            1          1         1           1           1         1   \n",
              "11           1          1         1           1           1         0   \n",
              "13           1          1         1           1           1         0   \n",
              "14           1          1         1           1           1         1   \n",
              "\n",
              "    condicion_final  familiar_sintomas  fiebre  cefalea  dolor_retroocular  \\\n",
              "3                 1                  0       0        0                  1   \n",
              "5                 1                  1       0        0                  1   \n",
              "11                1                  1       0        0                  0   \n",
              "13                1                  1       0        1                  1   \n",
              "14                1                  1       0        0                  0   \n",
              "\n",
              "    mialgias  artralgia  erupcion  dolor_abdomen  vomito  diarrea  \\\n",
              "3          1          0         0              1       1        1   \n",
              "5          0          0         1              1       1        0   \n",
              "11         0          0         0              0       0        1   \n",
              "13         0          0         0              1       1        1   \n",
              "14         0          1         1              1       1        1   \n",
              "\n",
              "    somnolencia  hipotension  hepatomegalia  hemorragia_mucosa  hipotermia  \\\n",
              "3             1            1              1                  1           1   \n",
              "5             1            1              1                  1           1   \n",
              "11            1            1              1                  1           1   \n",
              "13            1            1              1                  1           1   \n",
              "14            1            1              1                  1           1   \n",
              "\n",
              "    caida_plaquetas  acum_liquido  aum_hematocrito   latitud  longitud  \\\n",
              "3                 1             1                1 -0.945177  0.544741   \n",
              "5                 1             1                1 -0.396417  0.812910   \n",
              "11                0             0                0 -1.410496  0.648177   \n",
              "13                1             1                1 -1.167495  2.240912   \n",
              "14                1             1                1 -0.432360  0.774600   \n",
              "\n",
              "    tip_ss__Contributivo  tip_ss__Especial  tip_ss__Particular  \\\n",
              "3                      1                 0                   0   \n",
              "5                      1                 0                   0   \n",
              "11                     1                 0                   0   \n",
              "13                     0                 0                   0   \n",
              "14                     1                 0                   0   \n",
              "\n",
              "    tip_ss__Subsidiado  conducta_1. Ambulatorio  \\\n",
              "3                    0                        1   \n",
              "5                    0                        1   \n",
              "11                   0                        0   \n",
              "13                   1                        0   \n",
              "14                   0                        1   \n",
              "\n",
              "    conducta_2. Hospitalizacion piso  conducta_3. UCI  \\\n",
              "3                                  0                0   \n",
              "5                                  0                0   \n",
              "11                                 1                0   \n",
              "13                                 1                0   \n",
              "14                                 0                0   \n",
              "\n",
              "    conducta_4. Observacion  cluster  \n",
              "3                         0        0  \n",
              "5                         0        0  \n",
              "11                        0        0  \n",
              "13                        0        0  \n",
              "14                        0        0  "
            ],
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              "\n",
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              "      <th></th>\n",
              "      <th>edad_</th>\n",
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              "      <th>cefalea</th>\n",
              "      <th>dolor_retroocular</th>\n",
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              "      <th>hipotension</th>\n",
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              "      <th>conducta_3. UCI</th>\n",
              "      <th>conducta_4. Observacion</th>\n",
              "      <th>cluster</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.945177</td>\n",
              "      <td>0.544741</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>0.714786</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.396417</td>\n",
              "      <td>0.812910</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>-0.998049</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-1.410496</td>\n",
              "      <td>0.648177</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>-0.655482</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-1.167495</td>\n",
              "      <td>2.240912</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>-0.557605</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.432360</td>\n",
              "      <td>0.774600</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f6023c72-49f6-4692-95ab-96ce937c33a5')\"\n",
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              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f6023c72-49f6-4692-95ab-96ce937c33a5 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f6023c72-49f6-4692-95ab-96ce937c33a5');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-38ab21bf-4e76-4dd4-859c-cbbcb99b9645\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-38ab21bf-4e76-4dd4-859c-cbbcb99b9645')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-38ab21bf-4e76-4dd4-859c-cbbcb99b9645 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 294
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Dataset con filas de cluster 1:\")\n",
        "cluster_dataframes[1].head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "FytdHv6-RUCQ",
        "outputId": "df13f886-ccf5-42e1-97ae-49f02dcbc715"
      },
      "execution_count": 295,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset con filas de cluster 1:\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       edad_  uni_med_  sexo_  area_  gp_discapa  gp_desplaz  gp_migrant  \\\n",
              "2   1.350982         1      1      1           1           1           1   \n",
              "4   1.253106         1      0      1           1           1           1   \n",
              "6   0.763725         1      0      1           1           1           1   \n",
              "17  2.036117         1      0      2           1           1           1   \n",
              "29  1.546735         1      0      1           1           1           1   \n",
              "\n",
              "    gp_carcela  gp_gestan  gp_calle  gp_psiquia  gp_vic_vio  pac_hos_  \\\n",
              "2            1          1         1           1           1         1   \n",
              "4            1          1         1           1           1         0   \n",
              "6            1          1         1           1           1         0   \n",
              "17           1          1         1           1           1         1   \n",
              "29           1          1         1           1           1         1   \n",
              "\n",
              "    condicion_final  familiar_sintomas  fiebre  cefalea  dolor_retroocular  \\\n",
              "2                 1                  0       0        0                  0   \n",
              "4                 1                  0       0        0                  1   \n",
              "6                 1                  1       0        0                  1   \n",
              "17                1                  1       0        0                  0   \n",
              "29                1                  1       0        0                  0   \n",
              "\n",
              "    mialgias  artralgia  erupcion  dolor_abdomen  vomito  diarrea  \\\n",
              "2          0          0         0              1       1        0   \n",
              "4          0          1         1              1       0        0   \n",
              "6          0          0         0              0       1        0   \n",
              "17         0          0         1              1       1        1   \n",
              "29         0          0         0              1       1        1   \n",
              "\n",
              "    somnolencia  hipotension  hepatomegalia  hemorragia_mucosa  hipotermia  \\\n",
              "2             1            1              1                  1           1   \n",
              "4             1            1              1                  1           1   \n",
              "6             1            1              1                  1           1   \n",
              "17            1            1              1                  1           1   \n",
              "29            1            1              1                  1           1   \n",
              "\n",
              "    caida_plaquetas  acum_liquido  aum_hematocrito   latitud  longitud  \\\n",
              "2                 1             1                1  1.168671  0.538994   \n",
              "4                 0             1                1 -0.994174 -1.215598   \n",
              "6                 1             1                1  0.304582  0.766939   \n",
              "17                1             1                1 -0.435844  0.662543   \n",
              "29                1             1                1  0.307846 -0.917739   \n",
              "\n",
              "    tip_ss__Contributivo  tip_ss__Especial  tip_ss__Particular  \\\n",
              "2                      1                 0                   0   \n",
              "4                      0                 1                   0   \n",
              "6                      0                 0                   0   \n",
              "17                     0                 0                   1   \n",
              "29                     1                 0                   0   \n",
              "\n",
              "    tip_ss__Subsidiado  conducta_1. Ambulatorio  \\\n",
              "2                    0                        1   \n",
              "4                    0                        0   \n",
              "6                    1                        0   \n",
              "17                   0                        1   \n",
              "29                   0                        1   \n",
              "\n",
              "    conducta_2. Hospitalizacion piso  conducta_3. UCI  \\\n",
              "2                                  0                0   \n",
              "4                                  1                0   \n",
              "6                                  1                0   \n",
              "17                                 0                0   \n",
              "29                                 0                0   \n",
              "\n",
              "    conducta_4. Observacion  cluster  \n",
              "2                         0        1  \n",
              "4                         0        1  \n",
              "6                         0        1  \n",
              "17                        0        1  \n",
              "29                        0        1  "
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>edad_</th>\n",
              "      <th>uni_med_</th>\n",
              "      <th>sexo_</th>\n",
              "      <th>area_</th>\n",
              "      <th>gp_discapa</th>\n",
              "      <th>gp_desplaz</th>\n",
              "      <th>gp_migrant</th>\n",
              "      <th>gp_carcela</th>\n",
              "      <th>gp_gestan</th>\n",
              "      <th>gp_calle</th>\n",
              "      <th>gp_psiquia</th>\n",
              "      <th>gp_vic_vio</th>\n",
              "      <th>pac_hos_</th>\n",
              "      <th>condicion_final</th>\n",
              "      <th>familiar_sintomas</th>\n",
              "      <th>fiebre</th>\n",
              "      <th>cefalea</th>\n",
              "      <th>dolor_retroocular</th>\n",
              "      <th>mialgias</th>\n",
              "      <th>artralgia</th>\n",
              "      <th>erupcion</th>\n",
              "      <th>dolor_abdomen</th>\n",
              "      <th>vomito</th>\n",
              "      <th>diarrea</th>\n",
              "      <th>somnolencia</th>\n",
              "      <th>hipotension</th>\n",
              "      <th>hepatomegalia</th>\n",
              "      <th>hemorragia_mucosa</th>\n",
              "      <th>hipotermia</th>\n",
              "      <th>caida_plaquetas</th>\n",
              "      <th>acum_liquido</th>\n",
              "      <th>aum_hematocrito</th>\n",
              "      <th>latitud</th>\n",
              "      <th>longitud</th>\n",
              "      <th>tip_ss__Contributivo</th>\n",
              "      <th>tip_ss__Especial</th>\n",
              "      <th>tip_ss__Particular</th>\n",
              "      <th>tip_ss__Subsidiado</th>\n",
              "      <th>conducta_1. Ambulatorio</th>\n",
              "      <th>conducta_2. Hospitalizacion piso</th>\n",
              "      <th>conducta_3. UCI</th>\n",
              "      <th>conducta_4. Observacion</th>\n",
              "      <th>cluster</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.350982</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.168671</td>\n",
              "      <td>0.538994</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.253106</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.994174</td>\n",
              "      <td>-1.215598</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>0.763725</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.304582</td>\n",
              "      <td>0.766939</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2.036117</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>-0.435844</td>\n",
              "      <td>0.662543</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>1.546735</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.307846</td>\n",
              "      <td>-0.917739</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c9fa0ef2-2ca4-4875-8dc8-948494d61328')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-c9fa0ef2-2ca4-4875-8dc8-948494d61328 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-c9fa0ef2-2ca4-4875-8dc8-948494d61328');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-5de566d8-acc6-4f29-83a0-472c864397ff\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5de566d8-acc6-4f29-83a0-472c864397ff')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-5de566d8-acc6-4f29-83a0-472c864397ff button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 295
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Dataset con filas de cluster 2:\")\n",
        "cluster_dataframes[2].head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "FYge9vkvRVLI",
        "outputId": "c75a9cb9-5592-4abd-d54b-177db0992e49"
      },
      "execution_count": 296,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset con filas de cluster 2:\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       edad_  uni_med_  sexo_  area_  gp_discapa  gp_desplaz  gp_migrant  \\\n",
              "0  -0.263977         1      0      1           1           1           1   \n",
              "1  -0.312915         1      1      1           1           1           1   \n",
              "8  -1.095925         2      0      1           1           1           1   \n",
              "9  -1.389554         1      1      1           1           1           1   \n",
              "15  0.225405         1      1      1           1           1           1   \n",
              "\n",
              "    gp_carcela  gp_gestan  gp_calle  gp_psiquia  gp_vic_vio  pac_hos_  \\\n",
              "0            1          0         1           1           1         1   \n",
              "1            1          1         1           1           1         1   \n",
              "8            1          1         1           1           1         0   \n",
              "9            1          1         1           1           1         1   \n",
              "15           1          1         1           1           1         1   \n",
              "\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a01c7ca5-56e7-4702-b492-66d5ecd4d244 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 296
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Dataset con filas de cluster 3:\")\n",
        "cluster_dataframes[3].head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        },
        "id": "2wEZXeegRWDw",
        "outputId": "96b267fb-c2a7-4473-aaf5-860a786bc284"
      },
      "execution_count": 297,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset con filas de cluster 3:\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       edad_  uni_med_  sexo_  area_  gp_discapa  gp_desplaz  gp_migrant  \\\n",
              "7  -0.166100         1      0      1           1           1           1   \n",
              "10 -0.802296         1      1      1           1           1           1   \n",
              "12 -1.046987         1      1      1           1           1           1   \n",
              "21 -1.095925         1      0      1           1           1           1   \n",
              "22 -1.046987         2      1      1           1           1           1   \n",
              "\n",
              "    gp_carcela  gp_gestan  gp_calle  gp_psiquia  gp_vic_vio  pac_hos_  \\\n",
              "7            1          1         1           1           0         1   \n",
              "10           1          1         1           1           1         1   \n",
              "12           1          1         1           1           1         0   \n",
              "21           1          1         1           1           1         0   \n",
              "22           1          1         1           1           1         1   \n",
              "\n",
              "    condicion_final  familiar_sintomas  fiebre  cefalea  dolor_retroocular  \\\n",
              "7                 1                  0       0        0                  1   \n",
              "10                1                  0       0        0                  1   \n",
              "12                1                  1       0        0                  1   \n",
              "21                1                  1       0        0                  1   \n",
              "22                1                  1       0        1                  1   \n",
              "\n",
              "    mialgias  artralgia  erupcion  dolor_abdomen  vomito  diarrea  \\\n",
              "7          1          0         1              1       1        1   \n",
              "10         0          0         1              1       0        0   \n",
              "12         0          1         1              0       0        0   \n",
              "21         0          1         1              0       0        1   \n",
              "22         0          1         0              1       1        1   \n",
              "\n",
              "    somnolencia  hipotension  hepatomegalia  hemorragia_mucosa  hipotermia  \\\n",
              "7             1            1              1                  1           1   \n",
              "10            1            1              1                  1           1   \n",
              "12            1            1              1                  1           1   \n",
              "21            1            1              1                  1           1   \n",
              "22            1            1              1                  1           1   \n",
              "\n",
              "    caida_plaquetas  acum_liquido  aum_hematocrito   latitud  longitud  \\\n",
              "7                 1             1                1  0.594949  1.173023   \n",
              "10                1             1                1  1.259653 -0.684048   \n",
              "12                1             1                1  0.802228  0.764065   \n",
              "21                1             1                1  0.857708 -0.541345   \n",
              "22                1             1                1  1.136432  0.083107   \n",
              "\n",
              "    tip_ss__Contributivo  tip_ss__Especial  tip_ss__Particular  \\\n",
              "7                      1                 0                   0   \n",
              "10                     0                 0                   0   \n",
              "12                     1                 0                   0   \n",
              "21                     1                 0                   0   \n",
              "22                     1                 0                   0   \n",
              "\n",
              "    tip_ss__Subsidiado  conducta_1. Ambulatorio  \\\n",
              "7                    0                        1   \n",
              "10                   1                        1   \n",
              "12                   0                        0   \n",
              "21                   0                        0   \n",
              "22                   0                        1   \n",
              "\n",
              "    conducta_2. Hospitalizacion piso  conducta_3. UCI  \\\n",
              "7                                  0                0   \n",
              "10                                 0                0   \n",
              "12                                 1                0   \n",
              "21                                 0                0   \n",
              "22                                 0                0   \n",
              "\n",
              "    conducta_4. Observacion  cluster  \n",
              "7                         0        3  \n",
              "10                        0        3  \n",
              "12                        0        3  \n",
              "21                        1        3  \n",
              "22                        0        3  "
            ],
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              "\n",
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              "      <th>tip_ss__Subsidiado</th>\n",
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              "      <th>conducta_2. Hospitalizacion piso</th>\n",
              "      <th>conducta_3. UCI</th>\n",
              "      <th>conducta_4. Observacion</th>\n",
              "      <th>cluster</th>\n",
              "    </tr>\n",
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              "      <th>7</th>\n",
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              "      <td>1</td>\n",
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              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1.136432</td>\n",
              "      <td>0.083107</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>3</td>\n",
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              "  </tbody>\n",
              "</table>\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "    .colab-df-buttons div {\n",
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              "      buttonEl.style.display =\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
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              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-6bad0f35-be35-4855-80c2-f70c40a42179 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 297
        }
      ]
    }
  ]
}