0_Analisis_exploratorio.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jadercaro/Prediccion-colesterol/blob/main/0_Analisis_exploratorio.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Choresterol**"
      ],
      "metadata": {
        "id": "J6EDVX11cxSo"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "El conjunto de datos de enfermedades cardíacas es una colección que aborda el diagnóstico de enfermedades cardíacas mediante el análisis de varios atributos médicos. Recopilado de cuatro instituciones médicas distintas, este conjunto de datos contiene información de pacientes de diversas ubicaciones, incluidos Cleveland, Budapest, Long Beach (California) y Zurich (Suiza). Con un total de 76 atributos, se ha utilizado una selección de 14 de ellos en investigaciones anteriores. El objetivo principal de estas investigaciones ha sido predecir la el colesterol sérico en mg/dl. Es importante destacar que, aunque se han realizado estudios previos con este conjunto de datos, la mayoría de ellos se han centrado en la base de datos de Cleveland.\n",
        "\n",
        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)\n"
      ],
      "metadata": {
        "id": "JNpHGa8gushG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### **Descripción de las variables del conjunto de datos:**"
      ],
      "metadata": {
        "id": "slo9fnUKu8qj"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "| Atributo   | Descripción                                                                                   |\n",
        "|------------|-----------------------------------------------------------------------------------------------|\n",
        "| **Age**        | Edad del paciente en años.                                                                   |\n",
        "| **Sex**        | Sexo del paciente. 1 = masculino, 0 = femenino.                                             |\n",
        "| **CP**         | Tipo de dolor en el pecho.                                                                   |\n",
        "|            | - Valor 1: Angina típica.                                                                    |\n",
        "|            | - Valor 2: Angina atípica.                                                                   |\n",
        "|            | - Valor 3: Dolor no anginal.                                                                 |\n",
        "|            | - Valor 4: Asintomático.                                                                     |\n",
        "| **Trestbps**   | Presión arterial en reposo en mm Hg al ingreso al hospital.                                  |\n",
        "| **Chol**       | Colesterol sérico en mg/dl.                                                                  |\n",
        "| **FBS**        | Nivel de azúcar en sangre en ayunas. 1 = verdadero, 0 = falso.                               |\n",
        "| **Restecg**    | Resultados electrocardiográficos en reposo.                                                  |\n",
        "|            | - Valor 0: Normal.                                                                           |\n",
        "|            | - Valor 1: Con anormalidad en la onda ST-T.                                                 |\n",
        "|            | - Valor 2: Probable o definitiva hipertrofia ventricular izquierda.                          |\n",
        "| **Thalach**    | Frecuencia cardíaca máxima alcanzada.                                                        |\n",
        "| **Exang**      | Angina inducida por ejercicio. 1 = sí, 0 = no.                                               |\n",
        "| **Oldpeak**    | Depresión del segmento ST inducida por el ejercicio relativa al reposo.                       |\n",
        "| **Slope**      | La pendiente del segmento ST durante el ejercicio.                                            |\n",
        "|            | - Valor 1: Ascendente.                                                                       |\n",
        "|            | - Valor 2: Plano.                                                                            |\n",
        "|            | - Valor 3: Descendente.                                                                     |\n",
        "| **CA**         | Número de vasos principales (0-3) coloreados por fluoroscopía.                                |\n",
        "| **Thal**       | Resultados de la prueba de thalium.                                                          |\n",
        "|            | - Valor 3: Normal.                                                                           |\n",
        "|            | - Valor 6: Defecto fijo.                                                                     |\n",
        "|            | - Valor 7: Defecto reversible.                                                               |\n",
        "| **Num**        | Diagnóstico de enfermedad cardíaca (estado angiográfico).                                     |\n",
        "|            | - Valor 0: Menos del 50% de estrechamiento del diámetro en cualquier vaso importante.         |\n",
        "|            | - Valor 1: Más del 50% de estrechamiento del diámetro en cualquier vaso importante.           |\n",
        "\n"
      ],
      "metadata": {
        "id": "0BbQDJectH1S"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "------------"
      ],
      "metadata": {
        "id": "e1fAoTprlFx2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install dython"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZXcp5Gf-YNGC",
        "outputId": "3f96e942-3409-416d-f3a9-b768eb0f7162"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting dython\n",
            "  Downloading dython-0.7.5-py3-none-any.whl (26 kB)\n",
            "Requirement already satisfied: numpy>=1.23.0 in /usr/local/lib/python3.10/dist-packages (from dython) (1.25.2)\n",
            "Requirement already satisfied: pandas>=1.4.2 in /usr/local/lib/python3.10/dist-packages (from dython) (1.5.3)\n",
            "Requirement already satisfied: seaborn>=0.12.0 in /usr/local/lib/python3.10/dist-packages (from dython) (0.13.1)\n",
            "Requirement already satisfied: scipy>=1.7.1 in /usr/local/lib/python3.10/dist-packages (from dython) (1.11.4)\n",
            "Requirement already satisfied: matplotlib>=3.6.0 in /usr/local/lib/python3.10/dist-packages (from dython) (3.7.1)\n",
            "Requirement already satisfied: scikit-learn>=0.24.2 in /usr/local/lib/python3.10/dist-packages (from dython) (1.2.2)\n",
            "Requirement already satisfied: psutil>=5.9.1 in /usr/local/lib/python3.10/dist-packages (from dython) (5.9.5)\n",
            "Requirement already satisfied: contourpy>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->dython) (1.2.0)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->dython) (0.12.1)\n",
            "Requirement already satisfied: fonttools>=4.22.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->dython) (4.49.0)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->dython) (1.4.5)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->dython) (23.2)\n",
            "Requirement already satisfied: pillow>=6.2.0 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->dython) (9.4.0)\n",
            "Requirement already satisfied: pyparsing>=2.3.1 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->dython) (3.1.2)\n",
            "Requirement already satisfied: python-dateutil>=2.7 in /usr/local/lib/python3.10/dist-packages (from matplotlib>=3.6.0->dython) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=1.4.2->dython) (2023.4)\n",
            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.24.2->dython) (1.3.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.24.2->dython) (3.3.0)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.7->matplotlib>=3.6.0->dython) (1.16.0)\n",
            "Installing collected packages: dython\n",
            "Successfully installed dython-0.7.5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Librerias utilizadas**"
      ],
      "metadata": {
        "id": "jdrewPIuvKIY"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9zrDVaHWHVMy",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2b5b4a70-ba5b-4826-f9db-6405f14b8d66"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'cholesterol'...\n",
            "remote: Enumerating objects: 22, done.\u001b[K\n",
            "remote: Counting objects: 100% (22/22), done.\u001b[K\n",
            "remote: Compressing objects: 100% (20/20), done.\u001b[K\n",
            "remote: Total 22 (delta 4), reused 0 (delta 0), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (22/22), 1.05 MiB | 9.38 MiB/s, done.\n",
            "Resolving deltas: 100% (4/4), done.\n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "from scipy.io import arff\n",
        "import matplotlib.pyplot as plt\n",
        "import warnings\n",
        "import os\n",
        "from sklearn.preprocessing import OneHotEncoder\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from dython.nominal import associations\n",
        "warnings.filterwarnings('ignore')\n",
        "!git clone https://github.com/javel3232/cholesterol.git\n",
        "os.chdir('/content/cholesterol/Data')"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Carga de los Datos**"
      ],
      "metadata": {
        "id": "EWqLOvJhvWmh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "data, meta = arff.loadarff('dataset_2190_cholesterol.arff')\n",
        "df = pd.DataFrame(data)\n",
        "df.head(10)"
      ],
      "metadata": {
        "id": "Fv5VFfg9oJxT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "fb3d6916-7e30-488f-e560-03c4a86361ec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    age   sex    cp  trestbps   fbs restecg  thalach exang  oldpeak slope  \\\n",
              "0  63.0  b'1'  b'1'     145.0  b'1'    b'2'    150.0  b'0'      2.3  b'3'   \n",
              "1  67.0  b'1'  b'4'     160.0  b'0'    b'2'    108.0  b'1'      1.5  b'2'   \n",
              "2  67.0  b'1'  b'4'     120.0  b'0'    b'2'    129.0  b'1'      2.6  b'2'   \n",
              "3  37.0  b'1'  b'3'     130.0  b'0'    b'0'    187.0  b'0'      3.5  b'3'   \n",
              "4  41.0  b'0'  b'2'     130.0  b'0'    b'2'    172.0  b'0'      1.4  b'1'   \n",
              "5  56.0  b'1'  b'2'     120.0  b'0'    b'0'    178.0  b'0'      0.8  b'1'   \n",
              "6  62.0  b'0'  b'4'     140.0  b'0'    b'2'    160.0  b'0'      3.6  b'3'   \n",
              "7  57.0  b'0'  b'4'     120.0  b'0'    b'0'    163.0  b'1'      0.6  b'1'   \n",
              "8  63.0  b'1'  b'4'     130.0  b'0'    b'2'    147.0  b'0'      1.4  b'2'   \n",
              "9  53.0  b'1'  b'4'     140.0  b'1'    b'2'    155.0  b'1'      3.1  b'3'   \n",
              "\n",
              "    ca  thal  num   chol  \n",
              "0  0.0  b'6'  0.0  233.0  \n",
              "1  3.0  b'3'  2.0  286.0  \n",
              "2  2.0  b'7'  1.0  229.0  \n",
              "3  0.0  b'3'  0.0  250.0  \n",
              "4  0.0  b'3'  0.0  204.0  \n",
              "5  0.0  b'3'  0.0  236.0  \n",
              "6  2.0  b'3'  3.0  268.0  \n",
              "7  0.0  b'3'  0.0  354.0  \n",
              "8  1.0  b'7'  2.0  254.0  \n",
              "9  0.0  b'7'  1.0  203.0  "
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>cp</th>\n",
              "      <th>trestbps</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalach</th>\n",
              "      <th>exang</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>ca</th>\n",
              "      <th>thal</th>\n",
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              "      <th>chol</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>63.0</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>145.0</td>\n",
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              "      <td>233.0</td>\n",
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              "      <th>1</th>\n",
              "      <td>67.0</td>\n",
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              "      <td>b'4'</td>\n",
              "      <td>160.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>b'2'</td>\n",
              "      <td>108.0</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>1.5</td>\n",
              "      <td>b'2'</td>\n",
              "      <td>3.0</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>2.0</td>\n",
              "      <td>286.0</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>67.0</td>\n",
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              "      <td>b'4'</td>\n",
              "      <td>120.0</td>\n",
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              "      <td>b'2'</td>\n",
              "      <td>129.0</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>2.6</td>\n",
              "      <td>b'2'</td>\n",
              "      <td>2.0</td>\n",
              "      <td>b'7'</td>\n",
              "      <td>1.0</td>\n",
              "      <td>229.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>37.0</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>130.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>187.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>3.5</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>0.0</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>0.0</td>\n",
              "      <td>250.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>41.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>b'2'</td>\n",
              "      <td>130.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>b'2'</td>\n",
              "      <td>172.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>1.4</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>0.0</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>0.0</td>\n",
              "      <td>204.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>56.0</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>b'2'</td>\n",
              "      <td>120.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>178.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>0.8</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>0.0</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>0.0</td>\n",
              "      <td>236.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>62.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>b'4'</td>\n",
              "      <td>140.0</td>\n",
              "      <td>b'0'</td>\n",
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              "      <td>160.0</td>\n",
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              "      <td>3.6</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>2.0</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>3.0</td>\n",
              "      <td>268.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>57.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>b'4'</td>\n",
              "      <td>120.0</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>b'0'</td>\n",
              "      <td>163.0</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>0.6</td>\n",
              "      <td>b'1'</td>\n",
              "      <td>0.0</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>0.0</td>\n",
              "      <td>354.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>63.0</td>\n",
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              "      <td>147.0</td>\n",
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              "      <td>254.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>53.0</td>\n",
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              "      <td>155.0</td>\n",
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              "      <td>3.1</td>\n",
              "      <td>b'3'</td>\n",
              "      <td>0.0</td>\n",
              "      <td>b'7'</td>\n",
              "      <td>1.0</td>\n",
              "      <td>203.0</td>\n",
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              "            '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-0506f7bd-5ef7-489d-9f6e-1df0c8e2b989 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 303,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 9.038662442446746,\n        \"min\": 29.0,\n        \"max\": 77.0,\n        \"num_unique_values\": 41,\n        \"samples\": [\n          61.0,\n          64.0,\n          44.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"b'0'\",\n          \"b'1'\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cp\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"b'4'\",\n          \"b'2'\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"trestbps\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 17.59974772958769,\n        \"min\": 94.0,\n        \"max\": 200.0,\n        \"num_unique_values\": 50,\n        \"samples\": [\n          124.0,\n          192.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"fbs\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"b'0'\",\n          \"b'1'\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"restecg\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"b'2'\",\n          \"b'0'\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thalach\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 22.875003276980376,\n        \"min\": 71.0,\n        \"max\": 202.0,\n        \"num_unique_values\": 91,\n        \"samples\": [\n          170.0,\n          114.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"exang\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"b'1'\",\n          \"b'0'\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"oldpeak\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.1610750220686348,\n        \"min\": 0.0,\n        \"max\": 6.2,\n        \"num_unique_values\": 40,\n        \"samples\": [\n          2.4,\n          0.2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"slope\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"b'3'\",\n          \"b'2'\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ca\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.9374383177242163,\n        \"min\": 0.0,\n        \"max\": 3.0,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          3.0,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thal\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"b'3'\",\n          \"b'?'\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"num\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.2285356879701044,\n        \"min\": 0.0,\n        \"max\": 4.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2.0,\n          4.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 51.77691754263704,\n        \"min\": 126.0,\n        \"max\": 564.0,\n        \"num_unique_values\": 152,\n        \"samples\": [\n          321.0,\n          187.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ro1wi0H92kJL",
        "outputId": "d63d67ce-d846-447c-d4c7-41f6f04b8875"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 303 entries, 0 to 302\n",
            "Data columns (total 14 columns):\n",
            " #   Column    Non-Null Count  Dtype  \n",
            "---  ------    --------------  -----  \n",
            " 0   age       303 non-null    float64\n",
            " 1   sex       303 non-null    object \n",
            " 2   cp        303 non-null    object \n",
            " 3   trestbps  303 non-null    float64\n",
            " 4   fbs       303 non-null    object \n",
            " 5   restecg   303 non-null    object \n",
            " 6   thalach   303 non-null    float64\n",
            " 7   exang     303 non-null    object \n",
            " 8   oldpeak   303 non-null    float64\n",
            " 9   slope     303 non-null    object \n",
            " 10  ca        299 non-null    float64\n",
            " 11  thal      303 non-null    object \n",
            " 12  num       303 non-null    float64\n",
            " 13  chol      303 non-null    float64\n",
            "dtypes: float64(7), object(7)\n",
            "memory usage: 33.3+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Eliminamos el valor de b que acompañaban a las variables categoricas discretas y las convertimos de tipo object a un tipo int para una mejor interpretacion de los datos**"
      ],
      "metadata": {
        "id": "CteuV8eM19Pd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "for col in df.columns:\n",
        "    if df[col].dtype == 'object':\n",
        "        df[col] = df[col].apply(lambda x: x.decode('utf-8') if isinstance(x, bytes) else x)\n",
        "        df[col] = df[col].astype(str)\n",
        "\n",
        "int_cols = ['sex', 'cp', 'fbs', 'restecg', 'exang', 'slope', 'ca', 'thal']\n",
        "for col in int_cols:\n",
        "    df[col] = pd.to_numeric(df[col], errors='coerce', downcast='integer')\n",
        "\n",
        "df.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "HPwQtqjfoNC1",
        "outputId": "6dd30194-0b3a-4992-80eb-8b1df799129f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    age  sex  cp  trestbps  fbs  restecg  thalach  exang  oldpeak  slope   ca  \\\n",
              "0  63.0    1   1     145.0    1        2    150.0      0      2.3      3  0.0   \n",
              "1  67.0    1   4     160.0    0        2    108.0      1      1.5      2  3.0   \n",
              "2  67.0    1   4     120.0    0        2    129.0      1      2.6      2  2.0   \n",
              "3  37.0    1   3     130.0    0        0    187.0      0      3.5      3  0.0   \n",
              "4  41.0    0   2     130.0    0        2    172.0      0      1.4      1  0.0   \n",
              "\n",
              "   thal  num   chol  \n",
              "0   6.0  0.0  233.0  \n",
              "1   3.0  2.0  286.0  \n",
              "2   7.0  1.0  229.0  \n",
              "3   3.0  0.0  250.0  \n",
              "4   3.0  0.0  204.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8829fff3-8a62-447f-83af-3f42a656db00\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>cp</th>\n",
              "      <th>trestbps</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalach</th>\n",
              "      <th>exang</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>ca</th>\n",
              "      <th>thal</th>\n",
              "      <th>num</th>\n",
              "      <th>chol</th>\n",
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              "  </thead>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>63.0</td>\n",
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              "      <td>145.0</td>\n",
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              "      <td>150.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>233.0</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>67.0</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>160.0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>108.0</td>\n",
              "      <td>1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>2</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>286.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>67.0</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>120.0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>129.0</td>\n",
              "      <td>1</td>\n",
              "      <td>2.6</td>\n",
              "      <td>2</td>\n",
              "      <td>2.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>229.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>37.0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>130.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>187.0</td>\n",
              "      <td>0</td>\n",
              "      <td>3.5</td>\n",
              "      <td>3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>250.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>41.0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>130.0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>172.0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>204.0</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-8829fff3-8a62-447f-83af-3f42a656db00')\"\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-8829fff3-8a62-447f-83af-3f42a656db00 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-8829fff3-8a62-447f-83af-3f42a656db00');\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-c154ae2d-2896-4ec1-b4a3-672e06765452\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c154ae2d-2896-4ec1-b4a3-672e06765452')\"\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-c154ae2d-2896-4ec1-b4a3-672e06765452 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 303,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 9.038662442446746,\n        \"min\": 29.0,\n        \"max\": 77.0,\n        \"num_unique_values\": 41,\n        \"samples\": [\n          61.0,\n          64.0,\n          44.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"int8\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cp\",\n      \"properties\": {\n        \"dtype\": \"int8\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          4,\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"trestbps\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 17.59974772958769,\n        \"min\": 94.0,\n        \"max\": 200.0,\n        \"num_unique_values\": 50,\n        \"samples\": [\n          124.0,\n          192.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"fbs\",\n      \"properties\": {\n        \"dtype\": \"int8\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"restecg\",\n      \"properties\": {\n        \"dtype\": \"int8\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          2,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thalach\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 22.875003276980376,\n        \"min\": 71.0,\n        \"max\": 202.0,\n        \"num_unique_values\": 91,\n        \"samples\": [\n          170.0,\n          114.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"exang\",\n      \"properties\": {\n        \"dtype\": \"int8\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"oldpeak\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.1610750220686348,\n        \"min\": 0.0,\n        \"max\": 6.2,\n        \"num_unique_values\": 40,\n        \"samples\": [\n          2.4,\n          0.2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"slope\",\n      \"properties\": {\n        \"dtype\": \"int8\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          3,\n          2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ca\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.9374383177242163,\n        \"min\": 0.0,\n        \"max\": 3.0,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          3.0,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thal\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.939705769378644,\n        \"min\": 3.0,\n        \"max\": 7.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          6.0,\n          3.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"num\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.2285356879701044,\n        \"min\": 0.0,\n        \"max\": 4.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2.0,\n          4.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 51.77691754263704,\n        \"min\": 126.0,\n        \"max\": 564.0,\n        \"num_unique_values\": 152,\n        \"samples\": [\n          321.0,\n          187.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Información de los datos Modificados**"
      ],
      "metadata": {
        "id": "7vZeoLBn21r5"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()\n",
        "display(df.describe())\n",
        "print(f\"Cantidad de filas en el archivo de entrenamiento:\\t{df.shape[0]}\")\n",
        "print(f\"Cantidad de columnas en el archivo de entrenamiento:\\t{df.shape[1]}\\n\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 716
        },
        "id": "5fRzvtKo28ey",
        "outputId": "730eddf8-dd1e-4fd7-d02a-7daaf34c7a13"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 303 entries, 0 to 302\n",
            "Data columns (total 14 columns):\n",
            " #   Column    Non-Null Count  Dtype  \n",
            "---  ------    --------------  -----  \n",
            " 0   age       303 non-null    float64\n",
            " 1   sex       303 non-null    int8   \n",
            " 2   cp        303 non-null    int8   \n",
            " 3   trestbps  303 non-null    float64\n",
            " 4   fbs       303 non-null    int8   \n",
            " 5   restecg   303 non-null    int8   \n",
            " 6   thalach   303 non-null    float64\n",
            " 7   exang     303 non-null    int8   \n",
            " 8   oldpeak   303 non-null    float64\n",
            " 9   slope     303 non-null    int8   \n",
            " 10  ca        299 non-null    float64\n",
            " 11  thal      301 non-null    float64\n",
            " 12  num       303 non-null    float64\n",
            " 13  chol      303 non-null    float64\n",
            "dtypes: float64(8), int8(6)\n",
            "memory usage: 20.8 KB\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "              age         sex          cp    trestbps         fbs     restecg  \\\n",
              "count  303.000000  303.000000  303.000000  303.000000  303.000000  303.000000   \n",
              "mean    54.438944    0.679868    3.158416  131.689769    0.148515    0.990099   \n",
              "std      9.038662    0.467299    0.960126   17.599748    0.356198    0.994971   \n",
              "min     29.000000    0.000000    1.000000   94.000000    0.000000    0.000000   \n",
              "25%     48.000000    0.000000    3.000000  120.000000    0.000000    0.000000   \n",
              "50%     56.000000    1.000000    3.000000  130.000000    0.000000    1.000000   \n",
              "75%     61.000000    1.000000    4.000000  140.000000    0.000000    2.000000   \n",
              "max     77.000000    1.000000    4.000000  200.000000    1.000000    2.000000   \n",
              "\n",
              "          thalach       exang     oldpeak       slope          ca        thal  \\\n",
              "count  303.000000  303.000000  303.000000  303.000000  299.000000  301.000000   \n",
              "mean   149.607261    0.326733    1.039604    1.600660    0.672241    4.734219   \n",
              "std     22.875003    0.469794    1.161075    0.616226    0.937438    1.939706   \n",
              "min     71.000000    0.000000    0.000000    1.000000    0.000000    3.000000   \n",
              "25%    133.500000    0.000000    0.000000    1.000000    0.000000    3.000000   \n",
              "50%    153.000000    0.000000    0.800000    2.000000    0.000000    3.000000   \n",
              "75%    166.000000    1.000000    1.600000    2.000000    1.000000    7.000000   \n",
              "max    202.000000    1.000000    6.200000    3.000000    3.000000    7.000000   \n",
              "\n",
              "              num        chol  \n",
              "count  303.000000  303.000000  \n",
              "mean     0.937294  246.693069  \n",
              "std      1.228536   51.776918  \n",
              "min      0.000000  126.000000  \n",
              "25%      0.000000  211.000000  \n",
              "50%      0.000000  241.000000  \n",
              "75%      2.000000  275.000000  \n",
              "max      4.000000  564.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c61b5c81-797f-429b-a913-71e974d592fe\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>sex</th>\n",
              "      <th>cp</th>\n",
              "      <th>trestbps</th>\n",
              "      <th>fbs</th>\n",
              "      <th>restecg</th>\n",
              "      <th>thalach</th>\n",
              "      <th>exang</th>\n",
              "      <th>oldpeak</th>\n",
              "      <th>slope</th>\n",
              "      <th>ca</th>\n",
              "      <th>thal</th>\n",
              "      <th>num</th>\n",
              "      <th>chol</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>299.000000</td>\n",
              "      <td>301.000000</td>\n",
              "      <td>303.000000</td>\n",
              "      <td>303.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>54.438944</td>\n",
              "      <td>0.679868</td>\n",
              "      <td>3.158416</td>\n",
              "      <td>131.689769</td>\n",
              "      <td>0.148515</td>\n",
              "      <td>0.990099</td>\n",
              "      <td>149.607261</td>\n",
              "      <td>0.326733</td>\n",
              "      <td>1.039604</td>\n",
              "      <td>1.600660</td>\n",
              "      <td>0.672241</td>\n",
              "      <td>4.734219</td>\n",
              "      <td>0.937294</td>\n",
              "      <td>246.693069</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>9.038662</td>\n",
              "      <td>0.467299</td>\n",
              "      <td>0.960126</td>\n",
              "      <td>17.599748</td>\n",
              "      <td>0.356198</td>\n",
              "      <td>0.994971</td>\n",
              "      <td>22.875003</td>\n",
              "      <td>0.469794</td>\n",
              "      <td>1.161075</td>\n",
              "      <td>0.616226</td>\n",
              "      <td>0.937438</td>\n",
              "      <td>1.939706</td>\n",
              "      <td>1.228536</td>\n",
              "      <td>51.776918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>29.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>94.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>71.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>126.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>48.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>120.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>133.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>211.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>56.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>130.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>153.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.800000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>241.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>61.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>140.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>166.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.600000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>275.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>77.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>200.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>202.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>6.200000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>564.000000</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c61b5c81-797f-429b-a913-71e974d592fe')\"\n",
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              "    </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",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "      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",
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              "\n",
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              "      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-c61b5c81-797f-429b-a913-71e974d592fe');\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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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
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              "    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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              "      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",
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              "      border-color: transparent;\n",
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              "      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-69ca439e-1678-4f23-9d0d-66c84458eebe button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"print(f\\\"Cantidad de columnas en el archivo de entrenamiento:\\\\t{df\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 92.5728159022223,\n        \"min\": 9.038662442446746,\n        \"max\": 303.0,\n        \"samples\": [\n          54.43894389438944,\n          56.0,\n          303.0\n        ],\n        \"num_unique_values\": 8,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sex\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.91803123915392,\n        \"min\": 0.0,\n        \"max\": 303.0,\n        \"samples\": [\n          0.6798679867986799,\n          1.0,\n          0.46729882777012993\n        ],\n        \"num_unique_values\": 5,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cp\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.16755832732339,\n        \"min\": 0.9601256119600138,\n        \"max\": 303.0,\n        \"samples\": [\n          303.0,\n          3.1584158415841586,\n          4.0\n        ],\n        \"num_unique_values\": 6,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"trestbps\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 82.63751582423215,\n        \"min\": 17.59974772958769,\n        \"max\": 303.0,\n        \"samples\": [\n          131.68976897689768,\n          130.0,\n          303.0\n        ],\n        \"num_unique_values\": 8,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"fbs\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 107.0512286741478,\n        \"min\": 0.0,\n        \"max\": 303.0,\n        \"samples\": [\n          0.1485148514851485,\n          1.0,\n          0.35619787492797644\n        ],\n        \"num_unique_values\": 5,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"restecg\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.77655393236438,\n        \"min\": 0.0,\n        \"max\": 303.0,\n        \"samples\": [\n          303.0,\n          0.9900990099009901,\n          2.0\n        ],\n        \"num_unique_values\": 6,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thalach\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 83.71042641207808,\n        \"min\": 22.875003276980376,\n        \"max\": 303.0,\n        \"samples\": [\n          149.6072607260726,\n          153.0,\n          303.0\n        ],\n        \"num_unique_values\": 8,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"exang\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.9862394088184,\n        \"min\": 0.0,\n        \"max\": 303.0,\n        \"samples\": [\n          0.32673267326732675,\n          1.0,\n          0.46979446452231655\n        ],\n        \"num_unique_values\": 5,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"oldpeak\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.59952466080658,\n        \"min\": 0.0,\n        \"max\": 303.0,\n        \"samples\": [\n          303.0,\n          1.0396039603960396,\n          1.6\n        ],\n        \"num_unique_values\": 7,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"slope\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.5627986546393,\n        \"min\": 0.6162261453459619,\n        \"max\": 303.0,\n        \"samples\": [\n          303.0,\n          1.6006600660066006,\n          3.0\n        ],\n        \"num_unique_values\": 6,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ca\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 105.4337629723496,\n        \"min\": 0.0,\n        \"max\": 299.0,\n        \"samples\": [\n          299.0,\n          0.6722408026755853,\n          3.0\n        ],\n        \"num_unique_values\": 6,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thal\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 104.93809039007937,\n        \"min\": 1.939705769378644,\n        \"max\": 301.0,\n        \"samples\": [\n          4.73421926910299,\n          7.0,\n          1.939705769378644\n        ],\n        \"num_unique_values\": 5,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"num\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 106.72284943779034,\n        \"min\": 0.0,\n        \"max\": 303.0,\n        \"samples\": [\n          303.0,\n          0.9372937293729373,\n          4.0\n        ],\n        \"num_unique_values\": 6,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 150.36559430635785,\n        \"min\": 51.77691754263704,\n        \"max\": 564.0,\n        \"samples\": [\n          246.69306930693068,\n          241.0,\n          303.0\n        ],\n        \"num_unique_values\": 8,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cantidad de filas en el archivo de entrenamiento:\t303\n",
            "Cantidad de columnas en el archivo de entrenamiento:\t14\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Valores Faltantes**"
      ],
      "metadata": {
        "id": "p9wT7ZagyMPe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "display(pd.DataFrame({'Variables': df.isna().sum().index, 'Valores faltantes': df.isna().sum().values}))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "fs1Ii0CCySOt",
        "outputId": "00790391-86f8-40ff-ca1b-a13d4ca4b806"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   Variables  Valores faltantes\n",
              "0        age                  0\n",
              "1        sex                  0\n",
              "2         cp                  0\n",
              "3   trestbps                  0\n",
              "4        fbs                  0\n",
              "5    restecg                  0\n",
              "6    thalach                  0\n",
              "7      exang                  0\n",
              "8    oldpeak                  0\n",
              "9      slope                  0\n",
              "10        ca                  4\n",
              "11      thal                  2\n",
              "12       num                  0\n",
              "13      chol                  0"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-10dc2740-7853-487a-8e3b-cef9e5c70f94\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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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>Variables</th>\n",
              "      <th>Valores faltantes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>age</td>\n",
              "      <td>0</td>\n",
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              "      <th>1</th>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>cp</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
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              "      <td>trestbps</td>\n",
              "      <td>0</td>\n",
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              "      <th>4</th>\n",
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              "      <th>5</th>\n",
              "      <td>restecg</td>\n",
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              "      <th>6</th>\n",
              "      <td>thalach</td>\n",
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              "      <th>9</th>\n",
              "      <td>slope</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>ca</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>thal</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>num</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>chol</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
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              "        document.querySelector('#df-10dc2740-7853-487a-8e3b-cef9e5c70f94 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-10dc2740-7853-487a-8e3b-cef9e5c70f94');\n",
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              "          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",
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              "      --bg-color: #E8F0FE;\n",
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              "  .colab-df-quickchart:hover {\n",
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              "\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-1d40d4b4-1190-4aa0-aab0-b246ccdc1a5a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"display(pd\",\n  \"rows\": 14,\n  \"fields\": [\n    {\n      \"column\": \"Variables\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"samples\": [\n          \"slope\",\n          \"thal\",\n          \"age\"\n        ],\n        \"num_unique_values\": 14,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Valores faltantes\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 4,\n        \"samples\": [\n          0,\n          4,\n          2\n        ],\n        \"num_unique_values\": 3,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Imputación de valores faltantes en la columna \"ca\" y \"thal\" con la media**"
      ],
      "metadata": {
        "id": "gSN_5GHG1EEP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "mean_ca = df['ca'].mean()\n",
        "df['ca'].fillna(mean_ca, inplace=True)\n",
        "\n",
        "mean_thal = df['thal'].mean()\n",
        "df['thal'].fillna(mean_thal, inplace=True)\n",
        "display(pd.DataFrame({'Variables': df.isna().sum().index, 'Valores faltantes': df.isna().sum().values}))"
      ],
      "metadata": {
        "id": "kl3kDTHV1Lm-",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "outputId": "a8cfbe5a-8b5e-4559-ad9d-07a26e21c796"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   Variables  Valores faltantes\n",
              "0        age                  0\n",
              "1        sex                  0\n",
              "2         cp                  0\n",
              "3   trestbps                  0\n",
              "4        fbs                  0\n",
              "5    restecg                  0\n",
              "6    thalach                  0\n",
              "7      exang                  0\n",
              "8    oldpeak                  0\n",
              "9      slope                  0\n",
              "10        ca                  0\n",
              "11      thal                  0\n",
              "12       num                  0\n",
              "13      chol                  0"
            ],
            "text/html": [
              "\n",
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              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
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              "</style>\n",
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              "  <thead>\n",
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              "      <th>Valores faltantes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
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              "      <td>cp</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>trestbps</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>fbs</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>restecg</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>thalach</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>oldpeak</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>slope</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>ca</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>thal</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>num</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>chol</td>\n",
              "      <td>0</td>\n",
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              "  </tbody>\n",
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              "\n",
              "    .colab-df-buttons div {\n",
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              "  </style>\n",
              "\n",
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              "        document.querySelector('#df-5da36586-2b3b-4290-960e-aa41aa8626aa 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-5da36586-2b3b-4290-960e-aa41aa8626aa');\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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              "        element.appendChild(docLink);\n",
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              "\n",
              "\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-cfcb97ff-e3bc-4240-a880-ffb720d75fa0 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"display(pd\",\n  \"rows\": 14,\n  \"fields\": [\n    {\n      \"column\": \"Variables\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 14,\n        \"samples\": [\n          \"slope\",\n          \"thal\",\n          \"age\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Valores faltantes\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Matriz de dispersiones**"
      ],
      "metadata": {
        "id": "rqqwEDWqUwzV"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sns.set(style='whitegrid', context='notebook')\n",
        "cols=['age','trestbps','thalach','oldpeak','chol']\n",
        "sns.pairplot(df[cols] , height=2, palette='viridis')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "6Ui5UCtzC1KF",
        "outputId": "174e68b1-5142-42b5-d490-736b5a2758f8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x1000 with 30 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Distribución de las variables en el conjunto de datos**"
      ],
      "metadata": {
        "id": "ZaadE4gaZUul"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "![Skewness](https://www.biologyforlife.com/uploads/2/2/3/9/22392738/c101b0da6ea1a0dab31f80d9963b0368_orig.png\n",
        ")"
      ],
      "metadata": {
        "id": "rP6xpypKZ05Q"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(8,6))\n",
        "plt.title(\"Distribución de las variables en el conjunto de datos \")\n",
        "for i, col in enumerate(cols, 1):\n",
        "    plt.subplot(3, 2, i)\n",
        "    plt.title(f\"Distribución de los datos de {col}\")\n",
        "    sns.histplot(df[col], kde=True)\n",
        "    plt.tight_layout()\n",
        "    plt.plot()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 601
        },
        "id": "aCw4LqPgYE6d",
        "outputId": "c9053641-57c1-42d6-dc1c-4c038a8f42f8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 5 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def pie_chart_for_variables(df, variables):\n",
        "    num_variables = len(variables)\n",
        "    fig, axs = plt.subplots((num_variables + 2) // 3, 3, figsize=(10, 5 * ((num_variables + 2) // 3)))\n",
        "\n",
        "    for i, var in enumerate(variables):\n",
        "        counts = df[var].value_counts()\n",
        "        ax = axs[i // 3, i % 3]\n",
        "        ax.pie(counts, labels=counts.index, autopct='%1.1f%%')\n",
        "        ax.set_title(f'Distribución de {var}')\n",
        "\n",
        "    if num_variables % 3 != 0:\n",
        "        for j in range(num_variables % 3, 3):\n",
        "            fig.delaxes(axs[num_variables // 3, j])\n",
        "\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "variables_cat = ['sex', 'cp', 'fbs', 'restecg', 'exang', 'slope', 'thal', 'num']\n",
        "pie_chart_for_variables(df, variables_cat)\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "jj0Rd1T5_4YA",
        "outputId": "6841ba63-ac8f-4c8c-ff75-9a65ec8c7d69"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x1500 with 8 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Box plots**"
      ],
      "metadata": {
        "id": "6L1jFjaPb1gn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_boxplots(df, variables, figsize=(12, 10)):\n",
        "\n",
        "    num_variables = len(variables)\n",
        "    num_cols = 3\n",
        "    num_rows = (num_variables - 1) // num_cols + 1\n",
        "\n",
        "    plt.figure(figsize=figsize)\n",
        "\n",
        "    sns.set(style=\"whitegrid\")\n",
        "\n",
        "    for i, var in enumerate(variables, 1):\n",
        "        plt.subplot(num_rows, num_cols, i)\n",
        "        plt.boxplot(x=df[var], showmeans=True, meanline=True, patch_artist=True, boxprops=dict(facecolor='lightblue'))\n",
        "        plt.title(var)\n",
        "        plt.ylabel('Frequency')\n",
        "\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "\n",
        "variables_num = ['age','thalach', 'chol', 'trestbps', 'oldpeak']\n",
        "plot_boxplots(df, variables_num)\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "AOXWapWRz98R",
        "outputId": "56f07584-e569-4728-e84e-0fbf83666ee5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x1000 with 5 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###**Mapa de calor de correlación**"
      ],
      "metadata": {
        "id": "vb_ifh8cAyNx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Mapa de Calor de Correlación\n",
        "plt.figure(figsize=(12, 8))\n",
        "correlation_matrix = df[variables_num].corr()\n",
        "sns.heatmap(correlation_matrix, annot=True, cmap=\"viridis\", fmt=\".2f\")\n",
        "plt.title(\"Mapa de Calor de Correlación\")\n",
        "plt.show()\n",
        "display(pd.DataFrame(correlation_matrix))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 893
        },
        "id": "461OIiwlApj1",
        "outputId": "bc5ad898-c6fe-42f9-d5a3-6ad322ca2baf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 2 Axes>"
            ],
            "image/png": 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              "               age   thalach      chol  trestbps   oldpeak\n",
              "age       1.000000 -0.393806  0.208950  0.284946  0.203805\n",
              "thalach  -0.393806  1.000000 -0.003432 -0.045351 -0.343085\n",
              "chol      0.208950 -0.003432  1.000000  0.130120  0.046564\n",
              "trestbps  0.284946 -0.045351  0.130120  1.000000  0.189171\n",
              "oldpeak   0.203805 -0.343085  0.046564  0.189171  1.000000"
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              "      <td>1.000000</td>\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",
              "    }\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-0cff4dc4-4f4e-4dc2-8aa8-9196aa5ec97c 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-0cff4dc4-4f4e-4dc2-8aa8-9196aa5ec97c');\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-fc7ae72c-f3f2-4349-a36b-4f6c6902ec2c\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fc7ae72c-f3f2-4349-a36b-4f6c6902ec2c')\"\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-fc7ae72c-f3f2-4349-a36b-4f6c6902ec2c button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"display(pd\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4953395790114183,\n        \"min\": -0.39380580598682063,\n        \"max\": 1.0,\n        \"samples\": [\n          -0.39380580598682063,\n          0.2038054813870624,\n          0.2089502699467822\n        ],\n        \"num_unique_values\": 5,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"thalach\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.562510431897285,\n        \"min\": -0.39380580598682063,\n        \"max\": 1.0,\n        \"samples\": [\n          1.0,\n          -0.3430853918479222,\n          -0.0034318315180257605\n        ],\n        \"num_unique_values\": 5,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"chol\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.41251505134347694,\n        \"min\": -0.0034318315180257605,\n        \"max\": 1.0,\n        \"samples\": [\n          -0.0034318315180257605,\n          0.04656398918044737,\n          1.0\n        ],\n        \"num_unique_values\": 5,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"trestbps\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.40309508539090155,\n        \"min\": -0.045350879358343546,\n        \"max\": 1.0,\n        \"samples\": [\n          -0.045350879358343546,\n          0.1891709707903293,\n          0.13012010849269198\n        ],\n        \"num_unique_values\": 5,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"oldpeak\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.48906936790752087,\n        \"min\": -0.3430853918479222,\n        \"max\": 1.0,\n        \"samples\": [\n          -0.3430853918479222,\n          1.0,\n          0.04656398918044737\n        ],\n        \"num_unique_values\": 5,\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "* La edad (age) tiene una correlación positiva moderada con la presión sanguínea en reposo (trestbps) y el pico anterior al ejercicio (oldpeak).\n",
        "\n",
        "* La frecuencia cardíaca máxima alcanzada durante el ejercicio (thalach) tiene una correlación negativa moderada con la edad y una correlación negativa fuerte con el pico anterior al ejercicio (oldpeak).\n",
        "\n",
        "* El colesterol (chol) tiene una correlación positiva débil con la edad y una correlación débil con la presión sanguínea en reposo (trestbps)."
      ],
      "metadata": {
        "id": "wmUVorIeLocl"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Podemos ver que algunas de nuestras características tienen valores atípicos, estas características son:\n",
        "\n",
        "**-trestbps**\n",
        "\n",
        "**-oldpeak**\n",
        "\n",
        "**-chol**"
      ],
      "metadata": {
        "id": "AEVNMabBfky5"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Transformación de datos"
      ],
      "metadata": {
        "id": "uUTKg8L7UagV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Codificación de variables catégoricas\n",
        "Aplicamos one hot enconding"
      ],
      "metadata": {
        "id": "vPPr665hUfFz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "variables_codificar = ['cp','restecg','slope','thal','num']\n",
        "\n",
        "encoder = OneHotEncoder(sparse=False)\n",
        "\n",
        "# Ajustar y transformar las columnas categóricas\n",
        "encoded_data = encoder.fit_transform(df[variables_codificar])\n",
        "\n",
        "# Crear un DataFrame con las columnas codificadas\n",
        "encoded_df = pd.DataFrame(encoded_data, columns=encoder.get_feature_names_out(variables_codificar))\n",
        "\n",
        "# Concatenar el DataFrame original con el DataFrame codificado\n",
        "final_df = pd.concat([df, encoded_df], axis=1)\n",
        "\n",
        "#Eliminamos las columnas ya codificadas\n",
        "final_df = final_df.drop(columns=variables_codificar)"
      ],
      "metadata": {
        "id": "t4a7_Ln4UdPJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Escalamiento de variables númericas"
      ],
      "metadata": {
        "id": "T0FSc2t4WKrU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "variables_continuas = ['age','trestbps','thalach','oldpeak','chol']\n",
        "\n",
        "# Crea un objeto StandardScaler\n",
        "scaler = StandardScaler()\n",
        "\n",
        "# Ajusta el scaler a las columnas seleccionadas y luego transforma las columnas\n",
        "columnas_escaladas = scaler.fit_transform(final_df[variables_continuas])\n",
        "\n",
        "# Reemplaza las columnas originales con las columnas escaladas\n",
        "final_df[variables_continuas] = columnas_escaladas"
      ],
      "metadata": {
        "id": "NhjFb5j4V7u5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "variables_continuas = ['age','trestbps','thalach','oldpeak','chol']\n",
        "variables_nominales = [col for col in df.columns if col not in variables_continuas]\n",
        "result = associations(df, nominal_columns=variables_nominales,numerical_columns=variables_continuas, annot=False, cmap='viridis')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 478
        },
        "id": "TV5ci43jX2QP",
        "outputId": "f414cea5-1b8f-4c2c-bca3-7520e897e265"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "final_df.to_csv('regresion_preprocesado.csv',index=False)"
      ],
      "metadata": {
        "id": "Di3n7mNpXFa1"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}