Análisis_de_regresión_lineal_múltiple.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "98txNQcEGAiH"
      },
      "source": [
        "# Análisis de Regresión Lineal Múltiple"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nG05J_Gw2Skz"
      },
      "source": [
        "# Tratamiento de datos\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import os\n",
        "\n",
        "# Gráficos\n",
        "import matplotlib.pyplot as plt\n",
        "from matplotlib import style\n",
        "\n",
        "# Preprocesado y modelado\n",
        "from scipy.stats import pearsonr\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import r2_score\n",
        "from sklearn.metrics import mean_squared_error\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from scipy import stats\n",
        "#cargamos la librería de métricas\n",
        "from sklearn import metrics\n",
        "\n",
        "# Configuración matplotlib\n",
        "plt.rcParams['image.cmap'] = \"bwr\"\n",
        "plt.rcParams['savefig.bbox'] = \"tight\"\n",
        "style.use('ggplot') or plt.style.use('ggplot')\n",
        "\n",
        "# Configuración errores\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b84moHw6FjzW"
      },
      "source": [
        "## Introducción al modelo\n",
        "\n",
        "El **análisis de regresión lineal múltiple** es un método estadístico que trata de relacionar una variable frente a múltiples variables independientes mediante el ajuste de una ecuación lineal.\n",
        "\n",
        "En nuestro caso la variable a modelar o **variable respuesta** será el Ranking y el resto de variables serán las **variables independientes o predictores.**\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XNYY2LIX2rk2"
      },
      "source": [
        "# Datos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fIsU34wE2m7D",
        "outputId": "d39ee2a3-0d06-4314-c09c-775422db54b7"
      },
      "source": [
        "# Accedemos a la carpeta de google drive donde tenemos alojados los archivos\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sMZvEjIxbBDa"
      },
      "source": [
        "# para ir a la carpeta donde tenemos los datos\n",
        "os.chdir('/content/drive/MyDrive/Colab Notebooks/')"
      ],
      "execution_count": 5,
      "outputs": []
    },
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      "source": [
        "#Leemos los datos del archivo excel donde hemos recopilado todos las métricas de los 10 sitios elegidos y lo almacenamos en una variable de tipo dataframe\n",
        "dfDatos = pd.read_excel('/content/drive/MyDrive/Colab Notebooks/Datos.xlsx', header = 'infer', sheet_name='Hoja2')\n",
        "dfDatos"
      ],
      "execution_count": 6,
      "outputs": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Listado de ecommerce</th>\n",
              "      <th>Ranking</th>\n",
              "      <th>Url_amigables</th>\n",
              "      <th>Thin_content</th>\n",
              "      <th>Enlaces_rotos</th>\n",
              "      <th>Etiquetas_OK</th>\n",
              "      <th>CTR</th>\n",
              "      <th>DA</th>\n",
              "      <th>Paginas_visita</th>\n",
              "      <th>Permanencia</th>\n",
              "      <th>Rebote</th>\n",
              "      <th>Velocidad</th>\n",
              "      <th>Rendimiento</th>\n",
              "      <th>FCP</th>\n",
              "      <th>LCP</th>\n",
              "      <th>CLS</th>\n",
              "      <th>TTI</th>\n",
              "      <th>Enlaces_totales</th>\n",
              "      <th>Enlaces_follow</th>\n",
              "      <th>Enlaces_nofollow</th>\n",
              "      <th>Dominios_unicos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>bitiba.es</td>\n",
              "      <td>14</td>\n",
              "      <td>43.109756</td>\n",
              "      <td>7.317073</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>49.207317</td>\n",
              "      <td>0.12</td>\n",
              "      <td>32</td>\n",
              "      <td>6.26</td>\n",
              "      <td>301</td>\n",
              "      <td>48.07</td>\n",
              "      <td>2.5</td>\n",
              "      <td>23</td>\n",
              "      <td>2.8</td>\n",
              "      <td>10.5</td>\n",
              "      <td>0.114</td>\n",
              "      <td>12.4</td>\n",
              "      <td>151</td>\n",
              "      <td>12</td>\n",
              "      <td>139</td>\n",
              "      <td>43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>kiwoko.com</td>\n",
              "      <td>2</td>\n",
              "      <td>73.800000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>94.600000</td>\n",
              "      <td>30.38</td>\n",
              "      <td>54</td>\n",
              "      <td>4.44</td>\n",
              "      <td>172</td>\n",
              "      <td>67.48</td>\n",
              "      <td>1.8</td>\n",
              "      <td>25</td>\n",
              "      <td>3.8</td>\n",
              "      <td>12.2</td>\n",
              "      <td>0.557</td>\n",
              "      <td>13.3</td>\n",
              "      <td>798</td>\n",
              "      <td>142</td>\n",
              "      <td>656</td>\n",
              "      <td>152</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>mascoteros.com</td>\n",
              "      <td>8</td>\n",
              "      <td>99.702085</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>71.201589</td>\n",
              "      <td>0.01</td>\n",
              "      <td>48</td>\n",
              "      <td>2.10</td>\n",
              "      <td>64</td>\n",
              "      <td>71.33</td>\n",
              "      <td>2.4</td>\n",
              "      <td>38</td>\n",
              "      <td>1.9</td>\n",
              "      <td>2.7</td>\n",
              "      <td>0.030</td>\n",
              "      <td>11.6</td>\n",
              "      <td>1715</td>\n",
              "      <td>1534</td>\n",
              "      <td>181</td>\n",
              "      <td>101</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>maskokotas.com</td>\n",
              "      <td>6</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.050000</td>\n",
              "      <td>0.540000</td>\n",
              "      <td>65.200000</td>\n",
              "      <td>1.96</td>\n",
              "      <td>35</td>\n",
              "      <td>3.05</td>\n",
              "      <td>99</td>\n",
              "      <td>63.05</td>\n",
              "      <td>2.5</td>\n",
              "      <td>24</td>\n",
              "      <td>3.5</td>\n",
              "      <td>6.6</td>\n",
              "      <td>0.296</td>\n",
              "      <td>13.6</td>\n",
              "      <td>723</td>\n",
              "      <td>404</td>\n",
              "      <td>319</td>\n",
              "      <td>133</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>miscota.es</td>\n",
              "      <td>3</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.060000</td>\n",
              "      <td>0.870000</td>\n",
              "      <td>75.300000</td>\n",
              "      <td>9.71</td>\n",
              "      <td>43</td>\n",
              "      <td>4.05</td>\n",
              "      <td>165</td>\n",
              "      <td>56.25</td>\n",
              "      <td>2.7</td>\n",
              "      <td>31</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.4</td>\n",
              "      <td>0.134</td>\n",
              "      <td>18.1</td>\n",
              "      <td>796</td>\n",
              "      <td>51</td>\n",
              "      <td>745</td>\n",
              "      <td>74</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>nuestroperro.es</td>\n",
              "      <td>21</td>\n",
              "      <td>94.700000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>86.400000</td>\n",
              "      <td>0.08</td>\n",
              "      <td>32</td>\n",
              "      <td>1.98</td>\n",
              "      <td>241</td>\n",
              "      <td>73.87</td>\n",
              "      <td>1.9</td>\n",
              "      <td>45</td>\n",
              "      <td>3.9</td>\n",
              "      <td>6.8</td>\n",
              "      <td>0.481</td>\n",
              "      <td>6.6</td>\n",
              "      <td>216</td>\n",
              "      <td>29</td>\n",
              "      <td>187</td>\n",
              "      <td>49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>petclic.es</td>\n",
              "      <td>15</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>1.608579</td>\n",
              "      <td>5.540661</td>\n",
              "      <td>0.01</td>\n",
              "      <td>36</td>\n",
              "      <td>3.49</td>\n",
              "      <td>102</td>\n",
              "      <td>55.78</td>\n",
              "      <td>3.5</td>\n",
              "      <td>52</td>\n",
              "      <td>2.8</td>\n",
              "      <td>2.8</td>\n",
              "      <td>0.101</td>\n",
              "      <td>10.5</td>\n",
              "      <td>229</td>\n",
              "      <td>43</td>\n",
              "      <td>186</td>\n",
              "      <td>68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>tiendanimal.es</td>\n",
              "      <td>4</td>\n",
              "      <td>99.901961</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>87.205882</td>\n",
              "      <td>6.58</td>\n",
              "      <td>64</td>\n",
              "      <td>3.97</td>\n",
              "      <td>154</td>\n",
              "      <td>65.29</td>\n",
              "      <td>2.4</td>\n",
              "      <td>40</td>\n",
              "      <td>1.3</td>\n",
              "      <td>5.9</td>\n",
              "      <td>0.016</td>\n",
              "      <td>13.8</td>\n",
              "      <td>1734</td>\n",
              "      <td>247</td>\n",
              "      <td>1487</td>\n",
              "      <td>234</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>zoomalia.es</td>\n",
              "      <td>9</td>\n",
              "      <td>98.744019</td>\n",
              "      <td>0.059809</td>\n",
              "      <td>1.913876</td>\n",
              "      <td>84.090909</td>\n",
              "      <td>2.54</td>\n",
              "      <td>30</td>\n",
              "      <td>4.62</td>\n",
              "      <td>246</td>\n",
              "      <td>51.83</td>\n",
              "      <td>2.9</td>\n",
              "      <td>56</td>\n",
              "      <td>1.8</td>\n",
              "      <td>7.1</td>\n",
              "      <td>0.121</td>\n",
              "      <td>7.5</td>\n",
              "      <td>209</td>\n",
              "      <td>1</td>\n",
              "      <td>208</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>zooplus.es</td>\n",
              "      <td>1</td>\n",
              "      <td>13.800000</td>\n",
              "      <td>14.800000</td>\n",
              "      <td>2.300000</td>\n",
              "      <td>46.200000</td>\n",
              "      <td>16.17</td>\n",
              "      <td>52</td>\n",
              "      <td>5.56</td>\n",
              "      <td>276</td>\n",
              "      <td>48.94</td>\n",
              "      <td>2.2</td>\n",
              "      <td>47</td>\n",
              "      <td>2.3</td>\n",
              "      <td>9.8</td>\n",
              "      <td>0.083</td>\n",
              "      <td>8.9</td>\n",
              "      <td>587</td>\n",
              "      <td>74</td>\n",
              "      <td>513</td>\n",
              "      <td>159</td>\n",
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            "text/plain": [
              "  Listado de ecommerce  Ranking  ...  Enlaces_nofollow  Dominios_unicos\n",
              "0            bitiba.es       14  ...               139               43\n",
              "1           kiwoko.com        2  ...               656              152\n",
              "2       mascoteros.com        8  ...               181              101\n",
              "3       maskokotas.com        6  ...               319              133\n",
              "4           miscota.es        3  ...               745               74\n",
              "5      nuestroperro.es       21  ...               187               49\n",
              "6           petclic.es       15  ...               186               68\n",
              "7       tiendanimal.es        4  ...              1487              234\n",
              "8          zoomalia.es        9  ...               208               16\n",
              "9           zooplus.es        1  ...               513              159\n",
              "\n",
              "[10 rows x 21 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Eliminamos la columna del listado de ecommerce\n",
        "dfDatos = dfDatos.drop(['Listado de ecommerce'], axis=1)"
      ],
      "metadata": {
        "id": "onbhDsxhhBjp"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Obtenemos los datos estadísticos\n",
        "dfDatos.describe(include='all')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
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        "id": "t7UkKN6iD_bl",
        "outputId": "123b1c73-39c1-4248-ff18-4d2c43d55457"
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      "execution_count": 8,
      "outputs": [
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          "data": {
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Ranking</th>\n",
              "      <th>Url_amigables</th>\n",
              "      <th>Thin_content</th>\n",
              "      <th>Enlaces_rotos</th>\n",
              "      <th>Etiquetas_OK</th>\n",
              "      <th>CTR</th>\n",
              "      <th>DA</th>\n",
              "      <th>Paginas_visita</th>\n",
              "      <th>Permanencia</th>\n",
              "      <th>Rebote</th>\n",
              "      <th>Velocidad</th>\n",
              "      <th>Rendimiento</th>\n",
              "      <th>FCP</th>\n",
              "      <th>LCP</th>\n",
              "      <th>CLS</th>\n",
              "      <th>TTI</th>\n",
              "      <th>Enlaces_totales</th>\n",
              "      <th>Enlaces_follow</th>\n",
              "      <th>Enlaces_nofollow</th>\n",
              "      <th>Dominios_unicos</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.00000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.00000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.00000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>8.300000</td>\n",
              "      <td>82.375782</td>\n",
              "      <td>2.233688</td>\n",
              "      <td>0.728245</td>\n",
              "      <td>66.494636</td>\n",
              "      <td>6.756000</td>\n",
              "      <td>42.600000</td>\n",
              "      <td>3.95200</td>\n",
              "      <td>182.000000</td>\n",
              "      <td>60.189000</td>\n",
              "      <td>2.480000</td>\n",
              "      <td>38.10000</td>\n",
              "      <td>2.810000</td>\n",
              "      <td>6.880000</td>\n",
              "      <td>0.19330</td>\n",
              "      <td>11.630000</td>\n",
              "      <td>715.800000</td>\n",
              "      <td>253.700000</td>\n",
              "      <td>462.100000</td>\n",
              "      <td>102.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>6.532823</td>\n",
              "      <td>30.326034</td>\n",
              "      <td>4.974335</td>\n",
              "      <td>0.899755</td>\n",
              "      <td>26.775188</td>\n",
              "      <td>9.865049</td>\n",
              "      <td>11.500725</td>\n",
              "      <td>1.37245</td>\n",
              "      <td>80.938934</td>\n",
              "      <td>9.290939</td>\n",
              "      <td>0.489444</td>\n",
              "      <td>11.98564</td>\n",
              "      <td>0.968905</td>\n",
              "      <td>3.184965</td>\n",
              "      <td>0.18839</td>\n",
              "      <td>3.414365</td>\n",
              "      <td>589.498996</td>\n",
              "      <td>467.240136</td>\n",
              "      <td>420.450407</td>\n",
              "      <td>66.460431</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>13.800000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>5.540661</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>30.000000</td>\n",
              "      <td>1.98000</td>\n",
              "      <td>64.000000</td>\n",
              "      <td>48.070000</td>\n",
              "      <td>1.800000</td>\n",
              "      <td>23.00000</td>\n",
              "      <td>1.300000</td>\n",
              "      <td>2.700000</td>\n",
              "      <td>0.01600</td>\n",
              "      <td>6.600000</td>\n",
              "      <td>151.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>139.000000</td>\n",
              "      <td>16.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>3.250000</td>\n",
              "      <td>79.025000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>0.010000</td>\n",
              "      <td>53.205488</td>\n",
              "      <td>0.090000</td>\n",
              "      <td>32.750000</td>\n",
              "      <td>3.16000</td>\n",
              "      <td>115.000000</td>\n",
              "      <td>52.817500</td>\n",
              "      <td>2.250000</td>\n",
              "      <td>26.50000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>4.775000</td>\n",
              "      <td>0.08750</td>\n",
              "      <td>9.300000</td>\n",
              "      <td>219.250000</td>\n",
              "      <td>32.500000</td>\n",
              "      <td>186.250000</td>\n",
              "      <td>53.750000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>7.000000</td>\n",
              "      <td>99.223052</td>\n",
              "      <td>0.030000</td>\n",
              "      <td>0.275000</td>\n",
              "      <td>73.250794</td>\n",
              "      <td>2.250000</td>\n",
              "      <td>39.500000</td>\n",
              "      <td>4.01000</td>\n",
              "      <td>168.500000</td>\n",
              "      <td>59.650000</td>\n",
              "      <td>2.450000</td>\n",
              "      <td>39.00000</td>\n",
              "      <td>2.800000</td>\n",
              "      <td>6.700000</td>\n",
              "      <td>0.11750</td>\n",
              "      <td>12.000000</td>\n",
              "      <td>655.000000</td>\n",
              "      <td>62.500000</td>\n",
              "      <td>263.500000</td>\n",
              "      <td>87.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>12.750000</td>\n",
              "      <td>99.975490</td>\n",
              "      <td>0.059952</td>\n",
              "      <td>1.423934</td>\n",
              "      <td>85.822727</td>\n",
              "      <td>8.927500</td>\n",
              "      <td>51.000000</td>\n",
              "      <td>4.57500</td>\n",
              "      <td>244.750000</td>\n",
              "      <td>66.932500</td>\n",
              "      <td>2.650000</td>\n",
              "      <td>46.50000</td>\n",
              "      <td>3.725000</td>\n",
              "      <td>9.125000</td>\n",
              "      <td>0.25550</td>\n",
              "      <td>13.525000</td>\n",
              "      <td>797.500000</td>\n",
              "      <td>220.750000</td>\n",
              "      <td>620.250000</td>\n",
              "      <td>147.250000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>21.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>14.800000</td>\n",
              "      <td>2.300000</td>\n",
              "      <td>94.600000</td>\n",
              "      <td>30.380000</td>\n",
              "      <td>64.000000</td>\n",
              "      <td>6.26000</td>\n",
              "      <td>301.000000</td>\n",
              "      <td>73.870000</td>\n",
              "      <td>3.500000</td>\n",
              "      <td>56.00000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>12.200000</td>\n",
              "      <td>0.55700</td>\n",
              "      <td>18.100000</td>\n",
              "      <td>1734.000000</td>\n",
              "      <td>1534.000000</td>\n",
              "      <td>1487.000000</td>\n",
              "      <td>234.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7d146b6b-33d9-4991-978a-23e785a2b972')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      display:flex;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-7d146b6b-33d9-4991-978a-23e785a2b972 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-7d146b6b-33d9-4991-978a-23e785a2b972');\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",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "         Ranking  Url_amigables  ...  Enlaces_nofollow  Dominios_unicos\n",
              "count  10.000000      10.000000  ...         10.000000        10.000000\n",
              "mean    8.300000      82.375782  ...        462.100000       102.900000\n",
              "std     6.532823      30.326034  ...        420.450407        66.460431\n",
              "min     1.000000      13.800000  ...        139.000000        16.000000\n",
              "25%     3.250000      79.025000  ...        186.250000        53.750000\n",
              "50%     7.000000      99.223052  ...        263.500000        87.500000\n",
              "75%    12.750000      99.975490  ...        620.250000       147.250000\n",
              "max    21.000000     100.000000  ...       1487.000000       234.000000\n",
              "\n",
              "[8 rows x 20 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 740
        },
        "id": "4vviTDM3XCy_",
        "outputId": "44388c87-3331-4c8b-a67f-605ad6877145"
      },
      "source": [
        "# Obtenemos la matriz de correlaciones\n",
        "np.round(dfDatos.corr(),2)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "      <th>LCP</th>\n",
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              "    <tr>\n",
              "      <th>Ranking</th>\n",
              "      <td>1.00</td>\n",
              "      <td>0.23</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.20</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>-0.67</td>\n",
              "      <td>-0.69</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>0.16</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.16</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>0.17</td>\n",
              "      <td>-0.54</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>-0.58</td>\n",
              "      <td>-0.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Url_amigables</th>\n",
              "      <td>0.23</td>\n",
              "      <td>1.00</td>\n",
              "      <td>-0.96</td>\n",
              "      <td>-0.30</td>\n",
              "      <td>0.26</td>\n",
              "      <td>-0.38</td>\n",
              "      <td>-0.14</td>\n",
              "      <td>-0.73</td>\n",
              "      <td>-0.68</td>\n",
              "      <td>0.55</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.05</td>\n",
              "      <td>-0.69</td>\n",
              "      <td>0.06</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.09</td>\n",
              "      <td>-0.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Thin_content</th>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.96</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.45</td>\n",
              "      <td>-0.35</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.66</td>\n",
              "      <td>0.62</td>\n",
              "      <td>-0.61</td>\n",
              "      <td>-0.18</td>\n",
              "      <td>0.04</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>0.49</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>-0.09</td>\n",
              "      <td>0.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Enlaces_rotos</th>\n",
              "      <td>-0.20</td>\n",
              "      <td>-0.30</td>\n",
              "      <td>0.45</td>\n",
              "      <td>1.00</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>0.03</td>\n",
              "      <td>-0.18</td>\n",
              "      <td>0.34</td>\n",
              "      <td>0.23</td>\n",
              "      <td>-0.67</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.65</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>-0.35</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>-0.35</td>\n",
              "      <td>-0.19</td>\n",
              "      <td>-0.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Etiquetas_OK</th>\n",
              "      <td>-0.26</td>\n",
              "      <td>0.26</td>\n",
              "      <td>-0.35</td>\n",
              "      <td>-0.48</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.28</td>\n",
              "      <td>-0.19</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.52</td>\n",
              "      <td>-0.68</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CTR</th>\n",
              "      <td>-0.67</td>\n",
              "      <td>-0.38</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.33</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.34</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.02</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>0.26</td>\n",
              "      <td>0.63</td>\n",
              "      <td>0.45</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0.48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DA</th>\n",
              "      <td>-0.69</td>\n",
              "      <td>-0.14</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.18</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.58</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>0.25</td>\n",
              "      <td>-0.37</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>0.10</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.78</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.82</td>\n",
              "      <td>0.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Paginas_visita</th>\n",
              "      <td>-0.34</td>\n",
              "      <td>-0.73</td>\n",
              "      <td>0.66</td>\n",
              "      <td>0.34</td>\n",
              "      <td>-0.19</td>\n",
              "      <td>0.34</td>\n",
              "      <td>0.06</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.68</td>\n",
              "      <td>-0.84</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>0.65</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>0.11</td>\n",
              "      <td>-0.33</td>\n",
              "      <td>-0.53</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Permanencia</th>\n",
              "      <td>0.16</td>\n",
              "      <td>-0.68</td>\n",
              "      <td>0.62</td>\n",
              "      <td>0.23</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>0.68</td>\n",
              "      <td>1.00</td>\n",
              "      <td>-0.53</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.68</td>\n",
              "      <td>0.09</td>\n",
              "      <td>-0.40</td>\n",
              "      <td>-0.59</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Rebote</th>\n",
              "      <td>0.17</td>\n",
              "      <td>0.55</td>\n",
              "      <td>-0.61</td>\n",
              "      <td>-0.67</td>\n",
              "      <td>0.52</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.25</td>\n",
              "      <td>-0.84</td>\n",
              "      <td>-0.53</td>\n",
              "      <td>1.00</td>\n",
              "      <td>-0.49</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>0.20</td>\n",
              "      <td>-0.25</td>\n",
              "      <td>0.48</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Velocidad</th>\n",
              "      <td>0.19</td>\n",
              "      <td>0.32</td>\n",
              "      <td>-0.18</td>\n",
              "      <td>0.50</td>\n",
              "      <td>-0.68</td>\n",
              "      <td>-0.52</td>\n",
              "      <td>-0.37</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>-0.49</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.41</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>-0.61</td>\n",
              "      <td>-0.59</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.10</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>-0.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Rendimiento</th>\n",
              "      <td>0.26</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.65</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>-0.15</td>\n",
              "      <td>0.10</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>0.41</td>\n",
              "      <td>1.00</td>\n",
              "      <td>-0.47</td>\n",
              "      <td>-0.38</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>-0.68</td>\n",
              "      <td>-0.19</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>-0.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FCP</th>\n",
              "      <td>0.16</td>\n",
              "      <td>0.05</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>-0.22</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.26</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>-0.17</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.20</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>-0.47</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.74</td>\n",
              "      <td>0.25</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>-0.25</td>\n",
              "      <td>-0.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LCP</th>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.69</td>\n",
              "      <td>0.49</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>0.28</td>\n",
              "      <td>0.63</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.65</td>\n",
              "      <td>0.68</td>\n",
              "      <td>-0.25</td>\n",
              "      <td>-0.61</td>\n",
              "      <td>-0.38</td>\n",
              "      <td>0.20</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.49</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>-0.45</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CLS</th>\n",
              "      <td>0.17</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>-0.35</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0.45</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>-0.24</td>\n",
              "      <td>0.09</td>\n",
              "      <td>0.48</td>\n",
              "      <td>-0.59</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>0.74</td>\n",
              "      <td>0.49</td>\n",
              "      <td>1.00</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>-0.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TTI</th>\n",
              "      <td>-0.54</td>\n",
              "      <td>0.19</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.34</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.11</td>\n",
              "      <td>-0.40</td>\n",
              "      <td>-0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>-0.68</td>\n",
              "      <td>0.25</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.44</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Enlaces_totales</th>\n",
              "      <td>-0.52</td>\n",
              "      <td>0.27</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.41</td>\n",
              "      <td>0.37</td>\n",
              "      <td>0.12</td>\n",
              "      <td>0.78</td>\n",
              "      <td>-0.33</td>\n",
              "      <td>-0.59</td>\n",
              "      <td>0.50</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.19</td>\n",
              "      <td>-0.43</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>0.44</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.71</td>\n",
              "      <td>0.62</td>\n",
              "      <td>0.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Enlaces_follow</th>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.26</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>-0.35</td>\n",
              "      <td>0.11</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>0.25</td>\n",
              "      <td>-0.53</td>\n",
              "      <td>-0.64</td>\n",
              "      <td>0.50</td>\n",
              "      <td>-0.10</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>-0.32</td>\n",
              "      <td>-0.45</td>\n",
              "      <td>-0.26</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.71</td>\n",
              "      <td>1.00</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>0.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Enlaces_nofollow</th>\n",
              "      <td>-0.58</td>\n",
              "      <td>0.09</td>\n",
              "      <td>-0.09</td>\n",
              "      <td>-0.19</td>\n",
              "      <td>0.39</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0.82</td>\n",
              "      <td>0.12</td>\n",
              "      <td>-0.11</td>\n",
              "      <td>0.14</td>\n",
              "      <td>-0.21</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>-0.25</td>\n",
              "      <td>0.05</td>\n",
              "      <td>-0.16</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.62</td>\n",
              "      <td>-0.12</td>\n",
              "      <td>1.00</td>\n",
              "      <td>0.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dominios_unicos</th>\n",
              "      <td>-0.64</td>\n",
              "      <td>-0.13</td>\n",
              "      <td>0.13</td>\n",
              "      <td>-0.19</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.48</td>\n",
              "      <td>0.90</td>\n",
              "      <td>0.02</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>0.26</td>\n",
              "      <td>-0.37</td>\n",
              "      <td>-0.23</td>\n",
              "      <td>-0.28</td>\n",
              "      <td>0.15</td>\n",
              "      <td>-0.07</td>\n",
              "      <td>0.35</td>\n",
              "      <td>0.70</td>\n",
              "      <td>0.17</td>\n",
              "      <td>0.80</td>\n",
              "      <td>1.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ed8a43c6-04e0-4627-9874-032587842fca')\"\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 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
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              "    }\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",
              "    [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",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-ed8a43c6-04e0-4627-9874-032587842fca');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "                  Ranking  Url_amigables  ...  Enlaces_nofollow  Dominios_unicos\n",
              "Ranking              1.00           0.23  ...             -0.58            -0.64\n",
              "Url_amigables        0.23           1.00  ...              0.09            -0.13\n",
              "Thin_content        -0.23          -0.96  ...             -0.09             0.13\n",
              "Enlaces_rotos       -0.20          -0.30  ...             -0.19            -0.19\n",
              "Etiquetas_OK        -0.26           0.26  ...              0.39             0.20\n",
              "CTR                 -0.67          -0.38  ...              0.41             0.48\n",
              "DA                  -0.69          -0.14  ...              0.82             0.90\n",
              "Paginas_visita      -0.34          -0.73  ...              0.12             0.02\n",
              "Permanencia          0.16          -0.68  ...             -0.11            -0.28\n",
              "Rebote               0.17           0.55  ...              0.14             0.26\n",
              "Velocidad            0.19           0.32  ...             -0.21            -0.37\n",
              "Rendimiento          0.26           0.11  ...             -0.12            -0.23\n",
              "FCP                  0.16           0.05  ...             -0.25            -0.28\n",
              "LCP                 -0.23          -0.69  ...              0.05             0.15\n",
              "CLS                  0.17           0.06  ...             -0.16            -0.07\n",
              "TTI                 -0.54           0.19  ...              0.50             0.35\n",
              "Enlaces_totales     -0.52           0.27  ...              0.62             0.70\n",
              "Enlaces_follow      -0.12           0.26  ...             -0.12             0.17\n",
              "Enlaces_nofollow    -0.58           0.09  ...              1.00             0.80\n",
              "Dominios_unicos     -0.64          -0.13  ...              0.80             1.00\n",
              "\n",
              "[20 rows x 20 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 690
        },
        "id": "aA2eRHriXSA7",
        "outputId": "eca5eb1b-377c-4fd2-902f-c9de48950b4a"
      },
      "source": [
        "# Visualizamos las correlaciones como un mapa de calor\n",
        "plt.figure(figsize = (20,20))\n",
        "sns.heatmap(dfDatos.corr(),cmap='coolwarm', annot=True)\n",
        "plt.savefig('/content/drive/MyDrive/Colab Notebooks/matrix_scatter.png', dpi=300)\n",
        "plt.show()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1440 with 2 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ddlqVeKmMf4F"
      },
      "source": [
        "Observando la matriz de correlaciones entre todas las métricas que hemos obtenido vemos que hay seis métricas que tienen una fuerte correlación con el ránking que son, el CTR, la autoridad del dominio, el tiempo de interactividad, los enlaces totales, los enlaces no follow y la cantidad de dominios únicos que apuntan a cada uno de los sitios web analizados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XSquPk4OQVhS"
      },
      "source": [
        "# En primer lugar separamos la variable respuesta de las variables predictoras descartando aquellas que no tienen influencia en el ranking\n",
        "# guardamos en X todos los datos de las variables predictoras elegidas\n",
        "X = dfDatos.drop(columns = ['Ranking', 'Url_amigables', 'Thin_content', 'Etiquetas_OK', 'Paginas_visita', 'Permanencia',\t'Rebote', 'Enlaces_rotos', 'Velocidad', 'Rendimiento', 'FCP', 'LCP', 'TTI','CLS', 'Enlaces_follow'])\n",
        "# en Y guardaremos el ranking\n",
        "Y = dfDatos['Ranking']"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualizamos los datos\n",
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "XzDKXWK5ykmy",
        "outputId": "7b923672-d823-4931-acc6-2b1e997fda06"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-7dde2e65-b749-4921-b94f-54205d611f90\">\n",
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              "      <th>CTR</th>\n",
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              "      <td>0.12</td>\n",
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              "      <th>1</th>\n",
              "      <td>30.38</td>\n",
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              "      <td>0.08</td>\n",
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              "\n",
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              "      background-color: #434B5C;\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-7dde2e65-b749-4921-b94f-54205d611f90 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-7dde2e65-b749-4921-b94f-54205d611f90');\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",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     CTR  DA  Enlaces_totales  Enlaces_nofollow  Dominios_unicos\n",
              "0   0.12  32              151               139               43\n",
              "1  30.38  54              798               656              152\n",
              "2   0.01  48             1715               181              101\n",
              "3   1.96  35              723               319              133\n",
              "4   9.71  43              796               745               74\n",
              "5   0.08  32              216               187               49\n",
              "6   0.01  36              229               186               68\n",
              "7   6.58  64             1734              1487              234\n",
              "8   2.54  30              209               208               16\n",
              "9  16.17  52              587               513              159"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Normalizamos los datos de las variables predictoras\n",
        "scaler = MinMaxScaler() \n",
        "scaled_values = scaler.fit_transform(X) \n",
        "X.loc[:,:] = scaled_values\n",
        "\n",
        "# Y visualizamos\n",
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "lAVaPtD9GUIR",
        "outputId": "839f5bb8-b93a-445b-ea1a-c6c7e0d59067"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "\n",
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              "      <th>CTR</th>\n",
              "      <th>DA</th>\n",
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              "      <td>0.133531</td>\n",
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              "      <td>0.449555</td>\n",
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              "      <td>0.035608</td>\n",
              "      <td>0.151376</td>\n",
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              "      <td>0.034866</td>\n",
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              "      <td>1.000000</td>\n",
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              "      <td>0.051187</td>\n",
              "      <td>0.000000</td>\n",
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              "      <th>9</th>\n",
              "      <td>0.532104</td>\n",
              "      <td>0.647059</td>\n",
              "      <td>0.275426</td>\n",
              "      <td>0.277448</td>\n",
              "      <td>0.655963</td>\n",
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              "  </style>\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-9ce705f7-69ec-4ec3-9ca9-0e0b53cde89a');\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",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        CTR        DA  Enlaces_totales  Enlaces_nofollow  Dominios_unicos\n",
              "0  0.003622  0.058824         0.000000          0.000000         0.123853\n",
              "1  1.000000  0.705882         0.408718          0.383531         0.623853\n",
              "2  0.000000  0.529412         0.987997          0.031157         0.389908\n",
              "3  0.064208  0.147059         0.361339          0.133531         0.536697\n",
              "4  0.319394  0.382353         0.407454          0.449555         0.266055\n",
              "5  0.002305  0.058824         0.041061          0.035608         0.151376\n",
              "6  0.000000  0.176471         0.049274          0.034866         0.238532\n",
              "7  0.216332  1.000000         1.000000          1.000000         1.000000\n",
              "8  0.083306  0.000000         0.036639          0.051187         0.000000\n",
              "9  0.532104  0.647059         0.275426          0.277448         0.655963"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wy_tGThNSmqd",
        "outputId": "fe3b97be-c28d-45ee-c7f3-0b5ca9cba8ea"
      },
      "source": [
        "# Visualizamos los datos de Y para comprobar que se ha realizado\n",
        "Y"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    14\n",
              "1     2\n",
              "2     8\n",
              "3     6\n",
              "4     3\n",
              "5    21\n",
              "6    15\n",
              "7     4\n",
              "8     9\n",
              "9     1\n",
              "Name: Ranking, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fb0Hti5bSyXs"
      },
      "source": [
        "# Creamos dos conjuntos, uno para entrenamiento (80%) y otro para test(20%)\n",
        "X_train, X_test, Y_train, Y_test = train_test_split(X, Y.values.reshape(-1,1), test_size= 0.2, random_state = 123)"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y0-tJ6_hTSS8",
        "outputId": "5eb98621-a085-4091-8169-a6392a0ec379"
      },
      "source": [
        "# Visualizamos que se ha realizado correctamente\n",
        "print(X_train.shape)\n",
        "print(X_test.shape)\n",
        "print(Y_train.shape)\n",
        "print(Y_test.shape)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(8, 5)\n",
            "(2, 5)\n",
            "(8, 1)\n",
            "(2, 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aOfFNC3Bvliu"
      },
      "source": [
        "# Cargamos el modelo\n",
        "modelo = LinearRegression()\n",
        "#Entrenamos\n",
        "modelo.fit(X_train,Y_train)\n",
        "# Predecimos en el entrenamiento\n",
        "predY_in = modelo.predict(X_train)\n",
        "# Predecimos en el test\n",
        "predY_out = modelo.predict(X_test)"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x6pvTDrsHLi8",
        "outputId": "e3b7c2d7-d7ea-4a02-88dc-354386cae36f"
      },
      "source": [
        "# Intercept\n",
        "modelo.intercept_"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([15.86448846])"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J_dHnSqUHMq9",
        "outputId": "aa8b9aca-cef4-4e2b-8e1a-1e48ba50effe"
      },
      "source": [
        "# Coeficientes, reflejan el impacto de cada una de las variables sobre el ranking\n",
        "modelo.coef_"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[-12.00944601,   7.73828103,  -7.22583921,   2.67968799,\n",
              "        -12.72503449]])"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1akn1oZUHqiO",
        "outputId": "1443bc4d-7f55-4a08-e54e-6fe9fe1eb736"
      },
      "source": [
        "# Calculamos el coeficiente de determinación (R^2):\n",
        "modelo.score(X,Y)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.6059701099208674"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GlgY6DEcNFzI"
      },
      "source": [
        "El modelo con todos los predictores introducidos tiene un R2 de 0.6059, es decir, es capaz de explicar el 60.59% de la variabilidad observada en el ranking."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cfoKARkzvvji",
        "outputId": "fd70da1c-0645-4d9f-fd5b-2e6249cfca2b"
      },
      "source": [
        "print('El error MSE de entrenamiento es: ' + str(metrics.mean_squared_error(Y_train, predY_in)))\n",
        "print('El error MSE de test es : ' + str(metrics.mean_squared_error(Y_test, predY_out)))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "El error MSE de entrenamiento es: 12.970509103111388\n",
            "El error MSE de test es : 23.79140397725188\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3SajkJU9ycYc"
      },
      "source": [
        "Introducimos un valor en el modelo para que haga una predicción del ranking. Para el dominio lucasylola.es tenemos los siguientes datos:\n",
        "- **CTR:** 3.375\n",
        "- **DA:** 26\n",
        "- **Enlaces totales:** 176\n",
        "- **Enlaces no follow:** 71\n",
        "- **Dominios únicos:** 59\n",
        "- **Ranking:** 10"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Debemos normalizar estos datos de entrada para introducirlos en el modelo para realizar la predicción, ya que el modelo ha sido entrenado con datos normalizados:\n",
        "\n",
        "- **CTR:** 0.1039\n",
        "- **DA:** 0\n",
        "- **Enlaces totales:** 0.015\n",
        "- **Enlaces no follow:** 0\n",
        "- **Dominios únicos:** 0.1972\n",
        "- **Ranking:** 10\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "cGAQH5cONki3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Tenemos que normalizar los datos antes de introducirlos en el modelo para hacer la predicción\n",
        "X_nuevo = np.array([0.1039, 0, 0.015, 0, 0.1972]).reshape(1,-1)\n",
        "X_nuevo"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h_JK6kFpE5NG",
        "outputId": "104dae73-b5a9-4b30-82e1-120e1c83ecc0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.1039, 0.    , 0.015 , 0.    , 0.1972]])"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WEbL8D3ixolL",
        "outputId": "c182f268-0cf9-487d-869b-d8ca32a57e17"
      },
      "source": [
        "Y_pred_nuevo = modelo.predict(X_nuevo)\n",
        "print('La predicción de ranking para lucasylola.es es:',np.round(Y_pred_nuevo[0,0],3))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "La predicción de ranking para lucasylola.es es: 11.999\n"
          ]
        }
      ]
    }
  ]
}