pandas_testing_by_kapil.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "pandas testing by_kapil.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "4M4RPtkWeaTl"
      },
      "source": [
        "import pandas as pd\r\n",
        "import numpy as np\r\n",
        "\r\n",
        "df=pd.read_csv('/content/drive/MyDrive/Colab Notebooks/test.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 787
        },
        "id": "hapPmvEtfS9E",
        "outputId": "888ab8c7-6046-41d3-e205-b6b644c9470c"
      },
      "source": [
        "df.head(25)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "        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",
              "    </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</td>\n",
              "      <td>110.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</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</td>\n",
              "      <td>126.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</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</td>\n",
              "      <td>208.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</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</td>\n",
              "      <td>100.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Urban</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</td>\n",
              "      <td>78.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>LP001054</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2165</td>\n",
              "      <td>3422</td>\n",
              "      <td>152.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>LP001055</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>2226</td>\n",
              "      <td>0</td>\n",
              "      <td>59.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>LP001056</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3881</td>\n",
              "      <td>0</td>\n",
              "      <td>147.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Rural</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>LP001059</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>NaN</td>\n",
              "      <td>13633</td>\n",
              "      <td>0</td>\n",
              "      <td>280.0</td>\n",
              "      <td>240.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>LP001067</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>2400</td>\n",
              "      <td>2400</td>\n",
              "      <td>123.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>LP001078</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3091</td>\n",
              "      <td>0</td>\n",
              "      <td>90.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>LP001082</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2185</td>\n",
              "      <td>1516</td>\n",
              "      <td>162.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>LP001083</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>3+</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>4166</td>\n",
              "      <td>0</td>\n",
              "      <td>40.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>LP001094</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12173</td>\n",
              "      <td>0</td>\n",
              "      <td>166.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>LP001096</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>4666</td>\n",
              "      <td>0</td>\n",
              "      <td>124.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>LP001099</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>5667</td>\n",
              "      <td>0</td>\n",
              "      <td>131.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>LP001105</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>4583</td>\n",
              "      <td>2916</td>\n",
              "      <td>200.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>LP001107</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>3+</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3786</td>\n",
              "      <td>333</td>\n",
              "      <td>126.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>LP001108</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>9226</td>\n",
              "      <td>7916</td>\n",
              "      <td>300.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>LP001115</td>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>1300</td>\n",
              "      <td>3470</td>\n",
              "      <td>100.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>LP001121</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>1888</td>\n",
              "      <td>1620</td>\n",
              "      <td>48.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>LP001124</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>3+</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>2083</td>\n",
              "      <td>0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>LP001128</td>\n",
              "      <td>NaN</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3909</td>\n",
              "      <td>0</td>\n",
              "      <td>101.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>LP001135</td>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3765</td>\n",
              "      <td>0</td>\n",
              "      <td>125.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>LP001149</td>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>5400</td>\n",
              "      <td>4380</td>\n",
              "      <td>290.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Loan_ID  Gender Married  ... Loan_Amount_Term Credit_History Property_Area\n",
              "0   LP001015    Male     Yes  ...            360.0            1.0         Urban\n",
              "1   LP001022    Male     Yes  ...            360.0            1.0         Urban\n",
              "2   LP001031    Male     Yes  ...            360.0            1.0         Urban\n",
              "3   LP001035    Male     Yes  ...            360.0            NaN         Urban\n",
              "4   LP001051    Male      No  ...            360.0            1.0         Urban\n",
              "5   LP001054    Male     Yes  ...            360.0            1.0         Urban\n",
              "6   LP001055  Female      No  ...            360.0            1.0     Semiurban\n",
              "7   LP001056    Male     Yes  ...            360.0            0.0         Rural\n",
              "8   LP001059    Male     Yes  ...            240.0            1.0         Urban\n",
              "9   LP001067    Male      No  ...            360.0            1.0     Semiurban\n",
              "10  LP001078    Male      No  ...            360.0            1.0         Urban\n",
              "11  LP001082    Male     Yes  ...            360.0            1.0     Semiurban\n",
              "12  LP001083    Male      No  ...            180.0            NaN         Urban\n",
              "13  LP001094    Male     Yes  ...            360.0            0.0     Semiurban\n",
              "14  LP001096  Female      No  ...            360.0            1.0     Semiurban\n",
              "15  LP001099    Male      No  ...            360.0            1.0         Urban\n",
              "16  LP001105    Male     Yes  ...            360.0            1.0         Urban\n",
              "17  LP001107    Male     Yes  ...            360.0            1.0     Semiurban\n",
              "18  LP001108    Male     Yes  ...            360.0            1.0         Urban\n",
              "19  LP001115    Male      No  ...            180.0            1.0     Semiurban\n",
              "20  LP001121    Male     Yes  ...            360.0            1.0         Urban\n",
              "21  LP001124  Female      No  ...            180.0            1.0         Urban\n",
              "22  LP001128     NaN      No  ...            360.0            1.0         Urban\n",
              "23  LP001135  Female      No  ...            360.0            1.0         Urban\n",
              "24  LP001149    Male     Yes  ...            360.0            1.0         Urban\n",
              "\n",
              "[25 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hf62L2pRfWNb"
      },
      "source": [
        "df=df.drop(['Loan_ID' ],axis=1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "id": "ISQ34Znbgeau",
        "outputId": "da74e2a7-c8e1-4e60-d5ba-194aabc3d4ad"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\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</td>\n",
              "      <td>110.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
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              "      <td>3076</td>\n",
              "      <td>1500</td>\n",
              "      <td>126.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\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</td>\n",
              "      <td>208.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\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</td>\n",
              "      <td>100.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\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</td>\n",
              "      <td>78.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Gender Married Dependents  ... Loan_Amount_Term Credit_History  Property_Area\n",
              "0   Male     Yes          0  ...            360.0            1.0          Urban\n",
              "1   Male     Yes          1  ...            360.0            1.0          Urban\n",
              "2   Male     Yes          2  ...            360.0            1.0          Urban\n",
              "3   Male     Yes          2  ...            360.0            NaN          Urban\n",
              "4   Male      No          0  ...            360.0            1.0          Urban\n",
              "\n",
              "[5 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nPpA9TKzgpLn",
        "outputId": "2e9763a5-7729-462e-a857-1d6aa78cbbc0"
      },
      "source": [
        "# Reading data in Pandas\r\n",
        "df.columns\r\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Gender', 'Married', 'Dependents', 'Education', 'Self_Employed',\n",
              "       'ApplicantIncome', 'CoapplicantIncome', 'LoanAmount',\n",
              "       'Loan_Amount_Term', 'Credit_History', 'Property_Area'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dKUnLE0SiNjW",
        "outputId": "3e568f9b-75d4-41d2-cbc4-327f2eb2739c"
      },
      "source": [
        "df.LoanAmount.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    110.0\n",
              "1    126.0\n",
              "2    208.0\n",
              "3    100.0\n",
              "4     78.0\n",
              "Name: LoanAmount, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ilzW-LcXifG9",
        "outputId": "bfc16c97-449e-4024-97bf-707b2eb2f31f"
      },
      "source": [
        "df['LoanAmount'].head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    110.0\n",
              "1    126.0\n",
              "2    208.0\n",
              "3    100.0\n",
              "4     78.0\n",
              "Name: LoanAmount, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "id": "9-147Jp9izHf",
        "outputId": "83ff4ad6-6502-4694-a642-d4fad27747b0"
      },
      "source": [
        "df.iloc[0:5,3:8]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Education</th>\n",
              "      <th>Self_Employed</th>\n",
              "      <th>ApplicantIncome</th>\n",
              "      <th>CoapplicantIncome</th>\n",
              "      <th>LoanAmount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>5720</td>\n",
              "      <td>0</td>\n",
              "      <td>110.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3076</td>\n",
              "      <td>1500</td>\n",
              "      <td>126.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>5000</td>\n",
              "      <td>1800</td>\n",
              "      <td>208.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>2340</td>\n",
              "      <td>2546</td>\n",
              "      <td>100.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>3276</td>\n",
              "      <td>0</td>\n",
              "      <td>78.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Education Self_Employed  ApplicantIncome  CoapplicantIncome  LoanAmount\n",
              "0      Graduate            No             5720                  0       110.0\n",
              "1      Graduate            No             3076               1500       126.0\n",
              "2      Graduate            No             5000               1800       208.0\n",
              "3      Graduate            No             2340               2546       100.0\n",
              "4  Not Graduate            No             3276                  0        78.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "LYi09QSMjByg",
        "outputId": "c8c748fd-3ea3-467e-fbf1-a2bc69e0d5d7"
      },
      "source": [
        "df.iloc[2,4]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'No'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NLAkSuWTjQ4J",
        "outputId": "793b8d2d-7644-44cd-ae4a-1c72b8727498"
      },
      "source": [
        "df.loc[0:10,'ApplicantIncome'].mean()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4255.272727272727"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "tmu4XfoLj3m_",
        "outputId": "107f231c-c13c-4e6c-fbc5-ee2fa36bd01a"
      },
      "source": [
        "df.loc[(df['Gender']=='Female') & (df['ApplicantIncome']>7000)]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>79</th>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>7950</td>\n",
              "      <td>0</td>\n",
              "      <td>185.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>124</th>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>12500</td>\n",
              "      <td>0</td>\n",
              "      <td>300.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>12941</td>\n",
              "      <td>0</td>\n",
              "      <td>150.0</td>\n",
              "      <td>300.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>233</th>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>1</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>7600</td>\n",
              "      <td>0</td>\n",
              "      <td>92.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>284</th>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>10000</td>\n",
              "      <td>11666</td>\n",
              "      <td>460.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>302</th>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>Yes</td>\n",
              "      <td>14987</td>\n",
              "      <td>0</td>\n",
              "      <td>177.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Rural</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>315</th>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>7859</td>\n",
              "      <td>879</td>\n",
              "      <td>165.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>360</th>\n",
              "      <td>Female</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>8550</td>\n",
              "      <td>4255</td>\n",
              "      <td>96.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Gender Married Dependents  ... Loan_Amount_Term Credit_History  Property_Area\n",
              "79   Female     Yes          0  ...            360.0            1.0          Urban\n",
              "124  Female      No          0  ...            360.0            0.0          Urban\n",
              "145  Female      No          0  ...            300.0            1.0          Urban\n",
              "233  Female      No          1  ...            360.0            1.0      Semiurban\n",
              "284  Female     Yes          2  ...            360.0            1.0          Urban\n",
              "302  Female      No        NaN  ...            360.0            1.0          Rural\n",
              "315  Female     Yes          0  ...            180.0            1.0      Semiurban\n",
              "360  Female     Yes          0  ...            360.0            NaN          Urban\n",
              "\n",
              "[8 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "id": "tWS3v7ntkoCW",
        "outputId": "402356cf-dbeb-4a5a-c3aa-66032af5a591"
      },
      "source": [
        "#describing data\r\n",
        "df.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>367.000000</td>\n",
              "      <td>367.000000</td>\n",
              "      <td>362.000000</td>\n",
              "      <td>361.000000</td>\n",
              "      <td>338.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>4805.599455</td>\n",
              "      <td>1569.577657</td>\n",
              "      <td>136.132597</td>\n",
              "      <td>342.537396</td>\n",
              "      <td>0.825444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>4910.685399</td>\n",
              "      <td>2334.232099</td>\n",
              "      <td>61.366652</td>\n",
              "      <td>65.156643</td>\n",
              "      <td>0.380150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>28.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2864.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.250000</td>\n",
              "      <td>360.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>3786.000000</td>\n",
              "      <td>1025.000000</td>\n",
              "      <td>125.000000</td>\n",
              "      <td>360.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>5060.000000</td>\n",
              "      <td>2430.500000</td>\n",
              "      <td>158.000000</td>\n",
              "      <td>360.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>72529.000000</td>\n",
              "      <td>24000.000000</td>\n",
              "      <td>550.000000</td>\n",
              "      <td>480.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       ApplicantIncome  CoapplicantIncome  ...  Loan_Amount_Term  Credit_History\n",
              "count       367.000000         367.000000  ...        361.000000      338.000000\n",
              "mean       4805.599455        1569.577657  ...        342.537396        0.825444\n",
              "std        4910.685399        2334.232099  ...         65.156643        0.380150\n",
              "min           0.000000           0.000000  ...          6.000000        0.000000\n",
              "25%        2864.000000           0.000000  ...        360.000000        1.000000\n",
              "50%        3786.000000        1025.000000  ...        360.000000        1.000000\n",
              "75%        5060.000000        2430.500000  ...        360.000000        1.000000\n",
              "max       72529.000000       24000.000000  ...        480.000000        1.000000\n",
              "\n",
              "[8 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        },
        "id": "Wz1bczB7k9-_",
        "outputId": "aaa57a77-6865-4e2d-fe65-d2afa50a5cd2"
      },
      "source": [
        "#sorting data\r\n",
        "df.sort_values(['ApplicantIncome','LoanAmount'],ascending=[1,1]).head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>24000</td>\n",
              "      <td>148.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Rural</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>116</th>\n",
              "      <td>Female</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>1760</td>\n",
              "      <td>180.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>303</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>Yes</td>\n",
              "      <td>570</td>\n",
              "      <td>2125</td>\n",
              "      <td>68.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Rural</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>724</td>\n",
              "      <td>3510</td>\n",
              "      <td>213.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Rural</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>166</th>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>2</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>1141</td>\n",
              "      <td>2017</td>\n",
              "      <td>120.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>232</th>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>1173</td>\n",
              "      <td>1594</td>\n",
              "      <td>28.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Rural</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>1300</td>\n",
              "      <td>3470</td>\n",
              "      <td>100.0</td>\n",
              "      <td>180.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>1516</td>\n",
              "      <td>1951</td>\n",
              "      <td>35.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Semiurban</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>1516</td>\n",
              "      <td>2900</td>\n",
              "      <td>80.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Rural</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>106</th>\n",
              "      <td>NaN</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>1596</td>\n",
              "      <td>1760</td>\n",
              "      <td>119.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Urban</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Gender Married Dependents  ... Loan_Amount_Term Credit_History  Property_Area\n",
              "25     Male      No          0  ...            360.0            0.0          Rural\n",
              "116  Female      No          0  ...            360.0            1.0      Semiurban\n",
              "303     NaN     Yes          1  ...            360.0            1.0          Rural\n",
              "119    Male     Yes          2  ...            360.0            0.0          Rural\n",
              "166    Male      No          2  ...            360.0            0.0          Urban\n",
              "232    Male     Yes          0  ...            180.0            1.0          Rural\n",
              "19     Male      No          0  ...            180.0            1.0      Semiurban\n",
              "334    Male     Yes          0  ...            360.0            1.0      Semiurban\n",
              "117    Male     Yes          1  ...              NaN            0.0          Rural\n",
              "106     NaN      No          0  ...            360.0            0.0          Urban\n",
              "\n",
              "[10 rows x 11 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bWW2rEI2lnT3"
      },
      "source": [
        "#making changes to data\r\n",
        "df['TotalIncome']=df['ApplicantIncome']+df['CoapplicantIncome']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "id": "zSNZ1Ac8mX3r",
        "outputId": "a3bd4cff-ac73-44f3-c5ed-9415452a3771"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>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>TotalIncome</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\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</td>\n",
              "      <td>110.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>5720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\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</td>\n",
              "      <td>126.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>4576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\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</td>\n",
              "      <td>208.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>6800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\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</td>\n",
              "      <td>100.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Urban</td>\n",
              "      <td>4886</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\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</td>\n",
              "      <td>78.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>3276</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Gender Married Dependents  ... Credit_History Property_Area  TotalIncome\n",
              "0   Male     Yes          0  ...            1.0         Urban         5720\n",
              "1   Male     Yes          1  ...            1.0         Urban         4576\n",
              "2   Male     Yes          2  ...            1.0         Urban         6800\n",
              "3   Male     Yes          2  ...            NaN         Urban         4886\n",
              "4   Male      No          0  ...            1.0         Urban         3276\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3jh7LP2gmbG0"
      },
      "source": [
        "a=df.drop(['ApplicantIncome','CoapplicantIncome'], axis=1).head()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "id": "C_lr6qegm2gM",
        "outputId": "30d12b1c-68b5-4c47-f0f3-e5812609140c"
      },
      "source": [
        "a"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Gender</th>\n",
              "      <th>Married</th>\n",
              "      <th>Dependents</th>\n",
              "      <th>Education</th>\n",
              "      <th>Self_Employed</th>\n",
              "      <th>LoanAmount</th>\n",
              "      <th>Loan_Amount_Term</th>\n",
              "      <th>Credit_History</th>\n",
              "      <th>Property_Area</th>\n",
              "      <th>TotalIncome</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>0</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>110.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>5720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>1</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>126.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>4576</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>208.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>6800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Male</td>\n",
              "      <td>Yes</td>\n",
              "      <td>2</td>\n",
              "      <td>Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>100.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Urban</td>\n",
              "      <td>4886</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Male</td>\n",
              "      <td>No</td>\n",
              "      <td>0</td>\n",
              "      <td>Not Graduate</td>\n",
              "      <td>No</td>\n",
              "      <td>78.0</td>\n",
              "      <td>360.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Urban</td>\n",
              "      <td>3276</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "  Gender Married Dependents  ... Credit_History Property_Area  TotalIncome\n",
              "0   Male     Yes          0  ...            1.0         Urban         5720\n",
              "1   Male     Yes          1  ...            1.0         Urban         4576\n",
              "2   Male     Yes          2  ...            1.0         Urban         6800\n",
              "3   Male     Yes          2  ...            NaN         Urban         4886\n",
              "4   Male      No          0  ...            1.0         Urban         3276\n",
              "\n",
              "[5 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y_tM8esam-lp"
      },
      "source": [
        "df.to_csv('lodu.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YjqyscNQnaNl"
      },
      "source": [
        "# groupby function\r\n",
        "Z=df.groupby(['Gender','Married']).LoanAmount.max()\r\n",
        "X=pd.DataFrame(Z)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 106
        },
        "id": "AeIwcILZoVr_",
        "outputId": "26a53e11-f5f9-42b3-d636-0333c25d6df0"
      },
      "source": [
        "X.T"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th>Gender</th>\n",
              "      <th colspan=\"2\" halign=\"left\">Female</th>\n",
              "      <th colspan=\"2\" halign=\"left\">Male</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Married</th>\n",
              "      <th>No</th>\n",
              "      <th>Yes</th>\n",
              "      <th>No</th>\n",
              "      <th>Yes</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>LoanAmount</th>\n",
              "      <td>300.0</td>\n",
              "      <td>460.0</td>\n",
              "      <td>240.0</td>\n",
              "      <td>550.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Gender     Female          Male       \n",
              "Married        No    Yes     No    Yes\n",
              "LoanAmount  300.0  460.0  240.0  550.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 550
        },
        "id": "7Lbe7rfIpuM-",
        "outputId": "344d676d-8bb6-40c0-8a73-78ab6e14fac5"
      },
      "source": [
        "#PIVOT_TABLE\r\n",
        "c=df.pivot_table(df,index=['Gender','Married','Dependents'],aggfunc={'TotalIncome':np.mean,'LoanAmount':np.mean,})\r\n",
        "c"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>LoanAmount</th>\n",
              "      <th>TotalIncome</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Gender</th>\n",
              "      <th>Married</th>\n",
              "      <th>Dependents</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"8\" valign=\"top\">Female</th>\n",
              "      <th rowspan=\"4\" valign=\"top\">No</th>\n",
              "      <th>0</th>\n",
              "      <td>120.000000</td>\n",
              "      <td>4664.966667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>103.142857</td>\n",
              "      <td>5199.714286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>188.000000</td>\n",
              "      <td>5076.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3+</th>\n",
              "      <td>94.666667</td>\n",
              "      <td>4601.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Yes</th>\n",
              "      <th>0</th>\n",
              "      <td>128.000000</td>\n",
              "      <td>5313.692308</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>130.166667</td>\n",
              "      <td>5448.500000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>218.750000</td>\n",
              "      <td>9539.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3+</th>\n",
              "      <td>101.000000</td>\n",
              "      <td>5008.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"8\" valign=\"top\">Male</th>\n",
              "      <th rowspan=\"4\" valign=\"top\">No</th>\n",
              "      <th>0</th>\n",
              "      <td>123.391304</td>\n",
              "      <td>5944.173913</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>135.600000</td>\n",
              "      <td>13073.200000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>105.750000</td>\n",
              "      <td>3656.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3+</th>\n",
              "      <td>98.500000</td>\n",
              "      <td>6266.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"4\" valign=\"top\">Yes</th>\n",
              "      <th>0</th>\n",
              "      <td>140.625000</td>\n",
              "      <td>6324.728395</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>142.000000</td>\n",
              "      <td>6263.552632</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>151.346939</td>\n",
              "      <td>6706.142857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3+</th>\n",
              "      <td>159.677419</td>\n",
              "      <td>8649.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                           LoanAmount   TotalIncome\n",
              "Gender Married Dependents                          \n",
              "Female No      0           120.000000   4664.966667\n",
              "               1           103.142857   5199.714286\n",
              "               2           188.000000   5076.000000\n",
              "               3+           94.666667   4601.333333\n",
              "       Yes     0           128.000000   5313.692308\n",
              "               1           130.166667   5448.500000\n",
              "               2           218.750000   9539.000000\n",
              "               3+          101.000000   5008.000000\n",
              "Male   No      0           123.391304   5944.173913\n",
              "               1           135.600000  13073.200000\n",
              "               2           105.750000   3656.000000\n",
              "               3+           98.500000   6266.000000\n",
              "       Yes     0           140.625000   6324.728395\n",
              "               1           142.000000   6263.552632\n",
              "               2           151.346939   6706.142857\n",
              "               3+          159.677419   8649.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 186
        },
        "id": "xSeTbBVZq-vX",
        "outputId": "d6475474-825d-4f36-b829-e8103e38aaa1"
      },
      "source": [
        "\r\n",
        "d=c.T\r\n",
        "d"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th>Gender</th>\n",
              "      <th colspan=\"8\" halign=\"left\">Female</th>\n",
              "      <th colspan=\"8\" halign=\"left\">Male</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Married</th>\n",
              "      <th colspan=\"4\" halign=\"left\">No</th>\n",
              "      <th colspan=\"4\" halign=\"left\">Yes</th>\n",
              "      <th colspan=\"4\" halign=\"left\">No</th>\n",
              "      <th colspan=\"4\" halign=\"left\">Yes</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Dependents</th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3+</th>\n",
              "      <th>0</th>\n",
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              "      <th>3+</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>LoanAmount</th>\n",
              "      <td>120.000000</td>\n",
              "      <td>103.142857</td>\n",
              "      <td>188.0</td>\n",
              "      <td>94.666667</td>\n",
              "      <td>128.000000</td>\n",
              "      <td>130.166667</td>\n",
              "      <td>218.75</td>\n",
              "      <td>101.0</td>\n",
              "      <td>123.391304</td>\n",
              "      <td>135.6</td>\n",
              "      <td>105.75</td>\n",
              "      <td>98.5</td>\n",
              "      <td>140.625000</td>\n",
              "      <td>142.000000</td>\n",
              "      <td>151.346939</td>\n",
              "      <td>159.677419</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TotalIncome</th>\n",
              "      <td>4664.966667</td>\n",
              "      <td>5199.714286</td>\n",
              "      <td>5076.0</td>\n",
              "      <td>4601.333333</td>\n",
              "      <td>5313.692308</td>\n",
              "      <td>5448.500000</td>\n",
              "      <td>9539.00</td>\n",
              "      <td>5008.0</td>\n",
              "      <td>5944.173913</td>\n",
              "      <td>13073.2</td>\n",
              "      <td>3656.00</td>\n",
              "      <td>6266.0</td>\n",
              "      <td>6324.728395</td>\n",
              "      <td>6263.552632</td>\n",
              "      <td>6706.142857</td>\n",
              "      <td>8649.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Gender            Female               ...         Male             \n",
              "Married               No               ...          Yes             \n",
              "Dependents             0            1  ...            2           3+\n",
              "LoanAmount    120.000000   103.142857  ...   151.346939   159.677419\n",
              "TotalIncome  4664.966667  5199.714286  ...  6706.142857  8649.000000\n",
              "\n",
              "[2 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 73
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "asCIhrvmrhuw"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}