MY_OWN_EDA_ANALYSIS.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "gW3JpMqDaiBx"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "\n",
        "# Load the CSV files into pandas DataFrames\n",
        "df1 = pd.read_csv('/content/loan_sanction_test.csv')\n",
        "df2 = pd.read_csv('/content/loan_sanction_train.csv')\n",
        "\n",
        "# Concatenate the DataFrames vertically (stacking one below the other)\n",
        "combined_df = pd.concat([df1, df2], ignore_index=True)\n",
        "\n",
        "# Write the combined DataFrame to a new CSV file\n",
        "combined_df.to_csv('combined_file.csv', index=False)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df = pd.read_csv('/content/combined_file.csv')"
      ],
      "metadata": {
        "id": "YY9F6OGqcGUt"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 244
        },
        "id": "RMvsjELWdAdn",
        "outputId": "31eb2140-dcc3-4a47-f54b-6c88229060e6"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Loan_ID Gender Married Dependents     Education Self_Employed  \\\n",
              "0  LP001015   Male     Yes          0      Graduate            No   \n",
              "1  LP001022   Male     Yes          1      Graduate            No   \n",
              "2  LP001031   Male     Yes          2      Graduate            No   \n",
              "3  LP001035   Male     Yes          2      Graduate            No   \n",
              "4  LP001051   Male      No          0  Not Graduate            No   \n",
              "\n",
              "   ApplicantIncome  CoapplicantIncome  LoanAmount  Loan_Amount_Term  \\\n",
              "0             5720                0.0       110.0             360.0   \n",
              "1             3076             1500.0       126.0             360.0   \n",
              "2             5000             1800.0       208.0             360.0   \n",
              "3             2340             2546.0       100.0             360.0   \n",
              "4             3276                0.0        78.0             360.0   \n",
              "\n",
              "   Credit_History Property_Area Loan_Status  \n",
              "0             1.0         Urban         NaN  \n",
              "1             1.0         Urban         NaN  \n",
              "2             1.0         Urban         NaN  \n",
              "3             NaN         Urban         NaN  \n",
              "4             1.0         Urban         NaN  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-30e0f0ae-b950-45ec-95f7-2b43fd61b48c\" 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>Loan_ID</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Married</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>Education</th>\n",
              "      <th>Self_Employed</th>\n",
              "      <th>ApplicantIncome</th>\n",
              "      <th>CoapplicantIncome</th>\n",
              "      <th>LoanAmount</th>\n",
              "      <th>Loan_Amount_Term</th>\n",
              "      <th>Credit_History</th>\n",
              "      <th>Property_Area</th>\n",
              "      <th>Loan_Status</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>LP001015</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>5720</td>\n",
              "      <td>0.0</td>\n",
              "      <td>110.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>LP001022</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3076</td>\n",
              "      <td>1500.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>LP001031</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>5000</td>\n",
              "      <td>1800.0</td>\n",
              "      <td>208.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>LP001035</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>2340</td>\n",
              "      <td>2546.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Urban</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>LP001051</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3276</td>\n",
              "      <td>0.0</td>\n",
              "      <td>78.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>NaN</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-30e0f0ae-b950-45ec-95f7-2b43fd61b48c')\"\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",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </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-30e0f0ae-b950-45ec-95f7-2b43fd61b48c 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-30e0f0ae-b950-45ec-95f7-2b43fd61b48c');\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-71651e22-f72c-4f2a-8a60-29edd681e8fc\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-71651e22-f72c-4f2a-8a60-29edd681e8fc')\"\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-71651e22-f72c-4f2a-8a60-29edd681e8fc button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "combined_df",
              "summary": "{\n  \"name\": \"combined_df\",\n  \"rows\": 981,\n  \"fields\": [\n    {\n      \"column\": \"Loan_ID\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 981,\n        \"samples\": [\n          \"LP002361\",\n          \"LP001469\",\n          \"LP001771\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Female\",\n          \"Male\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Married\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"No\",\n          \"Yes\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Dependents\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"1\",\n          \"3+\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Education\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Not Graduate\",\n          \"Graduate\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Self_Employed\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Yes\",\n          \"No\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ApplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5695,\n        \"min\": 0,\n        \"max\": 81000,\n        \"num_unique_values\": 752,\n        \"samples\": [\n          3069,\n          5488\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CoapplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2718.7728063240784,\n        \"min\": 0.0,\n        \"max\": 41667.0,\n        \"num_unique_values\": 437,\n        \"samples\": [\n          6667.0,\n          1456.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"LoanAmount\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 77.4217431328085,\n        \"min\": 9.0,\n        \"max\": 700.0,\n        \"num_unique_values\": 232,\n        \"samples\": [\n          400.0,\n          93.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Loan_Amount_Term\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 65.10060192876894,\n        \"min\": 6.0,\n        \"max\": 480.0,\n        \"num_unique_values\": 12,\n        \"samples\": [\n          120.0,\n          36.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Credit_History\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3705534545186219,\n        \"min\": 0.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0.0,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Property_Area\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Urban\",\n          \"Semiurban\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Loan_Status\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"N\",\n          \"Y\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n"
      ],
      "metadata": {
        "id": "-t9c0zprdRiM"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x9F75Ln9fbBX",
        "outputId": "00be7072-9142-4010-e6ca-bdf9b133547d"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(981, 13)"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df.sample(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 261
        },
        "id": "4apz3Y5af489",
        "outputId": "42876486-ecdb-4160-aa62-6c0e47a7a4cc"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Loan_ID Gender Married Dependents     Education Self_Employed  \\\n",
              "546  LP001630   Male      No          0  Not Graduate            No   \n",
              "151  LP001831   Male     Yes          0      Graduate            No   \n",
              "855  LP002555   Male     Yes          2      Graduate           Yes   \n",
              "292  LP002605   Male      No          0  Not Graduate            No   \n",
              "261  LP002420   Male     Yes          0      Graduate            No   \n",
              "\n",
              "     ApplicantIncome  CoapplicantIncome  LoanAmount  Loan_Amount_Term  \\\n",
              "546             2333             1451.0       102.0             480.0   \n",
              "151             2783             1456.0       113.0             360.0   \n",
              "855             4583             2083.0       160.0             360.0   \n",
              "292             3271                0.0        90.0             360.0   \n",
              "261             2982             1550.0       110.0             360.0   \n",
              "\n",
              "     Credit_History Property_Area Loan_Status  \n",
              "546             0.0         Urban           N  \n",
              "151             1.0         Urban         NaN  \n",
              "855             1.0     Semiurban           Y  \n",
              "292             1.0         Rural         NaN  \n",
              "261             1.0     Semiurban         NaN  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-afac1874-f23e-4fea-8d63-ab9018be8d70\" 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>Loan_ID</th>\n",
              "      <th>Gender</th>\n",
              "      <th>Married</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>Education</th>\n",
              "      <th>Self_Employed</th>\n",
              "      <th>ApplicantIncome</th>\n",
              "      <th>CoapplicantIncome</th>\n",
              "      <th>LoanAmount</th>\n",
              "      <th>Loan_Amount_Term</th>\n",
              "      <th>Credit_History</th>\n",
              "      <th>Property_Area</th>\n",
              "      <th>Loan_Status</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>546</th>\n",
              "      <td>LP001630</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>2333</td>\n",
              "      <td>1451.0</td>\n",
              "      <td>102.0</td>\n",
              "      <td>480.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>N</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>151</th>\n",
              "      <td>LP001831</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>2783</td>\n",
              "      <td>1456.0</td>\n",
              "      <td>113.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>855</th>\n",
              "      <td>LP002555</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>Yes</td>\n",
              "      <td>4583</td>\n",
              "      <td>2083.0</td>\n",
              "      <td>160.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "      <td>Y</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>292</th>\n",
              "      <td>LP002605</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3271</td>\n",
              "      <td>0.0</td>\n",
              "      <td>90.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Rural</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>261</th>\n",
              "      <td>LP002420</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>2982</td>\n",
              "      <td>1550.0</td>\n",
              "      <td>110.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "      <td>NaN</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-afac1874-f23e-4fea-8d63-ab9018be8d70')\"\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",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </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-afac1874-f23e-4fea-8d63-ab9018be8d70 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-afac1874-f23e-4fea-8d63-ab9018be8d70');\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-8c43aef8-abf7-4854-97dc-970f538ad9e2\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8c43aef8-abf7-4854-97dc-970f538ad9e2')\"\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-8c43aef8-abf7-4854-97dc-970f538ad9e2 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"combined_df\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Loan_ID\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"LP001831\",\n          \"LP002420\",\n          \"LP002555\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Male\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Married\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Yes\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Dependents\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"2\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Education\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Graduate\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Self_Employed\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Yes\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ApplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 850,\n        \"min\": 2333,\n        \"max\": 4583,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2783\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CoapplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 776.5960983677422,\n        \"min\": 0.0,\n        \"max\": 2083.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1456.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"LoanAmount\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 26.68332812825267,\n        \"min\": 90.0,\n        \"max\": 160.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          113.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Loan_Amount_Term\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 53.665631459994955,\n        \"min\": 360.0,\n        \"max\": 480.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          360.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Credit_History\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.44721359549995804,\n        \"min\": 0.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Property_Area\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Urban\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Loan_Status\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Y\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RUcYSyd0gE7U",
        "outputId": "348b042e-4a3b-4c46-a594-1d9f89b73bff"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 981 entries, 0 to 980\n",
            "Data columns (total 13 columns):\n",
            " #   Column             Non-Null Count  Dtype  \n",
            "---  ------             --------------  -----  \n",
            " 0   Loan_ID            981 non-null    object \n",
            " 1   Gender             957 non-null    object \n",
            " 2   Married            978 non-null    object \n",
            " 3   Dependents         956 non-null    object \n",
            " 4   Education          981 non-null    object \n",
            " 5   Self_Employed      926 non-null    object \n",
            " 6   ApplicantIncome    981 non-null    int64  \n",
            " 7   CoapplicantIncome  981 non-null    float64\n",
            " 8   LoanAmount         954 non-null    float64\n",
            " 9   Loan_Amount_Term   961 non-null    float64\n",
            " 10  Credit_History     902 non-null    float64\n",
            " 11  Property_Area      981 non-null    object \n",
            " 12  Loan_Status        614 non-null    object \n",
            "dtypes: float64(4), int64(1), object(8)\n",
            "memory usage: 99.8+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SGyqh-X9gSgH",
        "outputId": "faa42d8d-3ab5-4a3b-f7a3-a3b85b11f16a"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Loan_ID                0\n",
              "Gender                24\n",
              "Married                3\n",
              "Dependents            25\n",
              "Education              0\n",
              "Self_Employed         55\n",
              "ApplicantIncome        0\n",
              "CoapplicantIncome      0\n",
              "LoanAmount            27\n",
              "Loan_Amount_Term      20\n",
              "Credit_History        79\n",
              "Property_Area          0\n",
              "Loan_Status          367\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "QJVEwOeHgk9V",
        "outputId": "3afcfb8c-233b-4cca-962b-b9bbb9523b01"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       ApplicantIncome  CoapplicantIncome  LoanAmount  Loan_Amount_Term  \\\n",
              "count       981.000000         981.000000  954.000000        961.000000   \n",
              "mean       5179.795107        1601.916330  142.511530        342.201873   \n",
              "std        5695.104533        2718.772806   77.421743         65.100602   \n",
              "min           0.000000           0.000000    9.000000          6.000000   \n",
              "25%        2875.000000           0.000000  100.000000        360.000000   \n",
              "50%        3800.000000        1110.000000  126.000000        360.000000   \n",
              "75%        5516.000000        2365.000000  162.000000        360.000000   \n",
              "max       81000.000000       41667.000000  700.000000        480.000000   \n",
              "\n",
              "       Credit_History  \n",
              "count      902.000000  \n",
              "mean         0.835920  \n",
              "std          0.370553  \n",
              "min          0.000000  \n",
              "25%          1.000000  \n",
              "50%          1.000000  \n",
              "75%          1.000000  \n",
              "max          1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-21b87d1a-d39c-40dc-9bac-bbb1596c0e4f\" 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>ApplicantIncome</th>\n",
              "      <th>CoapplicantIncome</th>\n",
              "      <th>LoanAmount</th>\n",
              "      <th>Loan_Amount_Term</th>\n",
              "      <th>Credit_History</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>981.000000</td>\n",
              "      <td>981.000000</td>\n",
              "      <td>954.000000</td>\n",
              "      <td>961.000000</td>\n",
              "      <td>902.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>5179.795107</td>\n",
              "      <td>1601.916330</td>\n",
              "      <td>142.511530</td>\n",
              "      <td>342.201873</td>\n",
              "      <td>0.835920</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>5695.104533</td>\n",
              "      <td>2718.772806</td>\n",
              "      <td>77.421743</td>\n",
              "      <td>65.100602</td>\n",
              "      <td>0.370553</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2875.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>360.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>3800.000000</td>\n",
              "      <td>1110.000000</td>\n",
              "      <td>126.000000</td>\n",
              "      <td>360.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>5516.000000</td>\n",
              "      <td>2365.000000</td>\n",
              "      <td>162.000000</td>\n",
              "      <td>360.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>81000.000000</td>\n",
              "      <td>41667.000000</td>\n",
              "      <td>700.000000</td>\n",
              "      <td>480.000000</td>\n",
              "      <td>1.000000</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-21b87d1a-d39c-40dc-9bac-bbb1596c0e4f')\"\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",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </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-21b87d1a-d39c-40dc-9bac-bbb1596c0e4f 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-21b87d1a-d39c-40dc-9bac-bbb1596c0e4f');\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-39c0740e-8063-40d9-8e95-0f0d33908f3b\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-39c0740e-8063-40d9-8e95-0f0d33908f3b')\"\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-39c0740e-8063-40d9-8e95-0f0d33908f3b button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"combined_df\",\n  \"rows\": 8,\n  \"fields\": [\n    {\n      \"column\": \"ApplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 27503.252650502447,\n        \"min\": 0.0,\n        \"max\": 81000.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          5179.795107033639,\n          3800.0,\n          981.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CoapplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 14321.879938391894,\n        \"min\": 0.0,\n        \"max\": 41667.0,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          981.0,\n          1601.9163302636496,\n          2365.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"LoanAmount\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 345.16629967148594,\n        \"min\": 9.0,\n        \"max\": 954.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          142.51153039832286,\n          126.0,\n          954.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Loan_Amount_Term\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 289.78584049435887,\n        \"min\": 6.0,\n        \"max\": 961.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          961.0,\n          342.2018730489074,\n          480.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Credit_History\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 318.64240768957194,\n        \"min\": 0.0,\n        \"max\": 902.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.835920177383592,\n          1.0,\n          0.3705534545186219\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "combined_df.duplicated().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YPquoGG5gvfw",
        "outputId": "cb2edfbb-8189-419f-a7a1-b0309e40a017"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Loan_Amount_Term = combined_df.select_dtypes(include=['int', 'float'])\n",
        "\n",
        "categorical_features = combined_df.select_dtypes(include=['object'])"
      ],
      "metadata": {
        "id": "0evtd22khA8s"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Loan_Amount_Term"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "Hsa2kE7qiAjp",
        "outputId": "c6a581b0-9676-4291-9965-b7d4d99aa2b0"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     ApplicantIncome  CoapplicantIncome  LoanAmount  Loan_Amount_Term  \\\n",
              "0               5720                0.0       110.0             360.0   \n",
              "1               3076             1500.0       126.0             360.0   \n",
              "2               5000             1800.0       208.0             360.0   \n",
              "3               2340             2546.0       100.0             360.0   \n",
              "4               3276                0.0        78.0             360.0   \n",
              "..               ...                ...         ...               ...   \n",
              "976             2900                0.0        71.0             360.0   \n",
              "977             4106                0.0        40.0             180.0   \n",
              "978             8072              240.0       253.0             360.0   \n",
              "979             7583                0.0       187.0             360.0   \n",
              "980             4583                0.0       133.0             360.0   \n",
              "\n",
              "     Credit_History  \n",
              "0               1.0  \n",
              "1               1.0  \n",
              "2               1.0  \n",
              "3               NaN  \n",
              "4               1.0  \n",
              "..              ...  \n",
              "976             1.0  \n",
              "977             1.0  \n",
              "978             1.0  \n",
              "979             1.0  \n",
              "980             0.0  \n",
              "\n",
              "[981 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a3bb898a-a837-4b45-91ad-6b10e4bc1f36\" 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>ApplicantIncome</th>\n",
              "      <th>CoapplicantIncome</th>\n",
              "      <th>LoanAmount</th>\n",
              "      <th>Loan_Amount_Term</th>\n",
              "      <th>Credit_History</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>5720</td>\n",
              "      <td>0.0</td>\n",
              "      <td>110.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3076</td>\n",
              "      <td>1500.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>5000</td>\n",
              "      <td>1800.0</td>\n",
              "      <td>208.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2340</td>\n",
              "      <td>2546.0</td>\n",
              "      <td>100.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3276</td>\n",
              "      <td>0.0</td>\n",
              "      <td>78.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>976</th>\n",
              "      <td>2900</td>\n",
              "      <td>0.0</td>\n",
              "      <td>71.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>977</th>\n",
              "      <td>4106</td>\n",
              "      <td>0.0</td>\n",
              "      <td>40.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>978</th>\n",
              "      <td>8072</td>\n",
              "      <td>240.0</td>\n",
              "      <td>253.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>979</th>\n",
              "      <td>7583</td>\n",
              "      <td>0.0</td>\n",
              "      <td>187.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>980</th>\n",
              "      <td>4583</td>\n",
              "      <td>0.0</td>\n",
              "      <td>133.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>981 rows × 5 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a3bb898a-a837-4b45-91ad-6b10e4bc1f36')\"\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",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </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-a3bb898a-a837-4b45-91ad-6b10e4bc1f36 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-a3bb898a-a837-4b45-91ad-6b10e4bc1f36');\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-4da69c88-9eee-45c3-93b5-7f093272607a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-4da69c88-9eee-45c3-93b5-7f093272607a')\"\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-4da69c88-9eee-45c3-93b5-7f093272607a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_b4244fb4-6f0d-44ce-9333-7c8b7fb8694b\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('Loan_Amount_Term')\"\n",
              "            title=\"Generate code using this dataframe.\"\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",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_b4244fb4-6f0d-44ce-9333-7c8b7fb8694b button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('Loan_Amount_Term');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "Loan_Amount_Term",
              "summary": "{\n  \"name\": \"Loan_Amount_Term\",\n  \"rows\": 981,\n  \"fields\": [\n    {\n      \"column\": \"ApplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5695,\n        \"min\": 0,\n        \"max\": 81000,\n        \"num_unique_values\": 752,\n        \"samples\": [\n          3069,\n          5488,\n          5746\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CoapplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2718.7728063240784,\n        \"min\": 0.0,\n        \"max\": 41667.0,\n        \"num_unique_values\": 437,\n        \"samples\": [\n          6667.0,\n          1456.0,\n          5063.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"LoanAmount\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 77.4217431328085,\n        \"min\": 9.0,\n        \"max\": 700.0,\n        \"num_unique_values\": 232,\n        \"samples\": [\n          400.0,\n          93.0,\n          123.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Loan_Amount_Term\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 65.10060192876894,\n        \"min\": 6.0,\n        \"max\": 480.0,\n        \"num_unique_values\": 12,\n        \"samples\": [\n          120.0,\n          36.0,\n          360.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Credit_History\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3705534545186219,\n        \"min\": 0.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0.0,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Loan_Amount_Term.corr()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "hyJSZ98GiYZt",
        "outputId": "a925229b-4d90-4849-deb4-5239b0658f2b"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   ApplicantIncome  CoapplicantIncome  LoanAmount  \\\n",
              "ApplicantIncome           1.000000          -0.114247    0.551811   \n",
              "CoapplicantIncome        -0.114247           1.000000    0.179228   \n",
              "LoanAmount                0.551811           0.179228    1.000000   \n",
              "Loan_Amount_Term         -0.023089          -0.043860    0.055636   \n",
              "Credit_History            0.023378          -0.027253   -0.008235   \n",
              "\n",
              "                   Loan_Amount_Term  Credit_History  \n",
              "ApplicantIncome           -0.023089        0.023378  \n",
              "CoapplicantIncome         -0.043860       -0.027253  \n",
              "LoanAmount                 0.055636       -0.008235  \n",
              "Loan_Amount_Term           1.000000       -0.020439  \n",
              "Credit_History            -0.020439        1.000000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c58b1f73-7cad-45ef-8650-43f035fd7486\" 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>ApplicantIncome</th>\n",
              "      <th>CoapplicantIncome</th>\n",
              "      <th>LoanAmount</th>\n",
              "      <th>Loan_Amount_Term</th>\n",
              "      <th>Credit_History</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>ApplicantIncome</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.114247</td>\n",
              "      <td>0.551811</td>\n",
              "      <td>-0.023089</td>\n",
              "      <td>0.023378</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CoapplicantIncome</th>\n",
              "      <td>-0.114247</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.179228</td>\n",
              "      <td>-0.043860</td>\n",
              "      <td>-0.027253</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LoanAmount</th>\n",
              "      <td>0.551811</td>\n",
              "      <td>0.179228</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.055636</td>\n",
              "      <td>-0.008235</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Loan_Amount_Term</th>\n",
              "      <td>-0.023089</td>\n",
              "      <td>-0.043860</td>\n",
              "      <td>0.055636</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.020439</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Credit_History</th>\n",
              "      <td>0.023378</td>\n",
              "      <td>-0.027253</td>\n",
              "      <td>-0.008235</td>\n",
              "      <td>-0.020439</td>\n",
              "      <td>1.000000</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-c58b1f73-7cad-45ef-8650-43f035fd7486')\"\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",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </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-c58b1f73-7cad-45ef-8650-43f035fd7486 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-c58b1f73-7cad-45ef-8650-43f035fd7486');\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-0bf3a3f6-de50-44a8-8e88-2be742470f37\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-0bf3a3f6-de50-44a8-8e88-2be742470f37')\"\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-0bf3a3f6-de50-44a8-8e88-2be742470f37 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"Loan_Amount_Term\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"ApplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.475695125581242,\n        \"min\": -0.11424717433574819,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          -0.11424717433574819,\n          0.023378126883895452,\n          0.5518108565650456\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"CoapplicantIncome\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4610549724029645,\n        \"min\": -0.11424717433574819,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1.0,\n          -0.027252600987999934,\n          0.17922799333033052\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"LoanAmount\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.4204791730872866,\n        \"min\": -0.008234591317408292,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.17922799333033052,\n          -0.008234591317408292,\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Loan_Amount_Term\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.45234649071775784,\n        \"min\": -0.043860129753574506,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          -0.043860129753574506,\n          -0.020439325088262475,\n          0.05563629551481618\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Credit_History\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.45127106384090093,\n        \"min\": -0.027252600987999934,\n        \"max\": 1.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          -0.027252600987999934,\n          1.0,\n          -0.008234591317408292\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "correlation_matrix = Loan_Amount_Term.corr()"
      ],
      "metadata": {
        "id": "c_2jSgGTiYTV"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(8, 6))\n",
        "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n",
        "plt.title('Correlation Heatmap of Numerical Features')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 666
        },
        "id": "qsNC-hiCivUM",
        "outputId": "ffbcfe7d-3e47-405f-b8ab-c546da409575"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}