06: Statistical_Thinking_Know_your_Data_and_Business.ipynb

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    "colab": {
      "name": "06: Statistical_Thinking Know your Data and Business.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/gulabpatel/Statistics/blob/main/06%3A%20Statistical_Thinking_Know_your_Data_and_Business.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gHYtHIctP2Zn"
      },
      "source": [
        "Walkthrough video of the following code : https://www.youtube.com/watch?v=V91ayczTbJ4&list=PL3N9eeOlCrP6IjkyExZW9oZFwt-A1r0qB&index=4\n",
        "\n",
        "\n",
        "Dataset : https://www.kaggle.com/wordsforthewise/lending-club"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TnU_4f65k8K0"
      },
      "source": [
        "import warnings\n",
        "warnings.simplefilter(action='ignore', category=FutureWarning)\n",
        "warnings.simplefilter(action='ignore', category=Warning)\n",
        "\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import gzip\n",
        "import csv\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "%matplotlib inline"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4zQRvNF8flve",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eb43675e-2d59-439b-f6d7-1f8a4dd688c0"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pA0bgfiQoMG3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fbfe1631-aa76-496d-97e8-b313fadea8be"
      },
      "source": [
        "!ls -alrt '/content/drive/MyDrive/dataset'"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "total 438751\n",
            "-rw------- 1 root root  56694779 Jan  1 02:18 lc_loans.csv\n",
            "-rw------- 1 root root      3452 May  7 09:43 loan_analysis_summary.csv\n",
            "-rw------- 1 root root 392582231 May  7 12:08 accepted_2007_to_2018Q4.csv_2.gz\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OVdiNt0IflmG"
      },
      "source": [
        "loan_ddf = pd.read_csv('/content/drive/MyDrive/dataset/accepted_2007_to_2018Q4.csv_2.gz', compression='gzip', error_bad_lines=False)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H3lRWZdo02kX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "7641c4c9-2e41-4bce-b341-a5f9f14872ce"
      },
      "source": [
        "loan_ddf.shape[0]"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2260701"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AEQoMc5mW81R"
      },
      "source": [
        "# take a subset of the dataset to avoid the colab crash\n",
        "loan_df = loan_ddf[0:100000]"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W1n88zNxhTCM",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "outputId": "5d166ab7-2e42-4775-977a-0a7f067e2192"
      },
      "source": [
        "loan_df.head()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>member_id</th>\n",
              "      <th>loan_amnt</th>\n",
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              "      <th>title</th>\n",
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              "      <th>out_prncp</th>\n",
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              "      <th>total_bc_limit</th>\n",
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              "      <th>hardship_end_date</th>\n",
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              "      <th>hardship_length</th>\n",
              "      <th>hardship_dpd</th>\n",
              "      <th>hardship_loan_status</th>\n",
              "      <th>orig_projected_additional_accrued_interest</th>\n",
              "      <th>hardship_payoff_balance_amount</th>\n",
              "      <th>hardship_last_payment_amount</th>\n",
              "      <th>disbursement_method</th>\n",
              "      <th>debt_settlement_flag</th>\n",
              "      <th>debt_settlement_flag_date</th>\n",
              "      <th>settlement_status</th>\n",
              "      <th>settlement_date</th>\n",
              "      <th>settlement_amount</th>\n",
              "      <th>settlement_percentage</th>\n",
              "      <th>settlement_term</th>\n",
              "    </tr>\n",
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              "      <th>0</th>\n",
              "      <td>68407277</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3600.0</td>\n",
              "      <td>3600.0</td>\n",
              "      <td>3600.0</td>\n",
              "      <td>36 months</td>\n",
              "      <td>13.99</td>\n",
              "      <td>123.03</td>\n",
              "      <td>C</td>\n",
              "      <td>C4</td>\n",
              "      <td>leadman</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>55000.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Fully Paid</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>debt_consolidation</td>\n",
              "      <td>Debt consolidation</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>679.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>30.0</td>\n",
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              "      <td>7.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>24700.0</td>\n",
              "      <td>24700.0</td>\n",
              "      <td>24700.0</td>\n",
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              "      <td>11.99</td>\n",
              "      <td>820.28</td>\n",
              "      <td>C</td>\n",
              "      <td>C1</td>\n",
              "      <td>Engineer</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
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              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Fully Paid</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
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              "      <td>small_business</td>\n",
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              "      <td>0.0</td>\n",
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              "      <td>39475.0</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>68341763</td>\n",
              "      <td>NaN</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>60 months</td>\n",
              "      <td>10.78</td>\n",
              "      <td>432.66</td>\n",
              "      <td>B</td>\n",
              "      <td>B4</td>\n",
              "      <td>truck driver</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>63000.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Fully Paid</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>home_improvement</td>\n",
              "      <td>NaN</td>\n",
              "      <td>605xx</td>\n",
              "      <td>IL</td>\n",
              "      <td>10.78</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Aug-2000</td>\n",
              "      <td>695.0</td>\n",
              "      <td>699.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7869.0</td>\n",
              "      <td>56.2</td>\n",
              "      <td>18.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>218418.0</td>\n",
              "      <td>18696.0</td>\n",
              "      <td>6200.0</td>\n",
              "      <td>14877.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>66310712</td>\n",
              "      <td>NaN</td>\n",
              "      <td>35000.0</td>\n",
              "      <td>35000.0</td>\n",
              "      <td>35000.0</td>\n",
              "      <td>60 months</td>\n",
              "      <td>14.85</td>\n",
              "      <td>829.90</td>\n",
              "      <td>C</td>\n",
              "      <td>C5</td>\n",
              "      <td>Information Systems Officer</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>110000.0</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Current</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>debt_consolidation</td>\n",
              "      <td>Debt consolidation</td>\n",
              "      <td>076xx</td>\n",
              "      <td>NJ</td>\n",
              "      <td>17.06</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Sep-2008</td>\n",
              "      <td>785.0</td>\n",
              "      <td>789.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>13.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7802.0</td>\n",
              "      <td>11.6</td>\n",
              "      <td>17.0</td>\n",
              "      <td>w</td>\n",
              "      <td>15897.65</td>\n",
              "      <td>15897.65</td>\n",
              "      <td>...</td>\n",
              "      <td>381215.0</td>\n",
              "      <td>52226.0</td>\n",
              "      <td>62500.0</td>\n",
              "      <td>18000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>68476807</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10400.0</td>\n",
              "      <td>10400.0</td>\n",
              "      <td>10400.0</td>\n",
              "      <td>60 months</td>\n",
              "      <td>22.45</td>\n",
              "      <td>289.91</td>\n",
              "      <td>F</td>\n",
              "      <td>F1</td>\n",
              "      <td>Contract Specialist</td>\n",
              "      <td>3 years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>104433.0</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Fully Paid</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>major_purchase</td>\n",
              "      <td>Major purchase</td>\n",
              "      <td>174xx</td>\n",
              "      <td>PA</td>\n",
              "      <td>25.37</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Jun-1998</td>\n",
              "      <td>695.0</td>\n",
              "      <td>699.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21929.0</td>\n",
              "      <td>64.5</td>\n",
              "      <td>35.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>...</td>\n",
              "      <td>439570.0</td>\n",
              "      <td>95768.0</td>\n",
              "      <td>20300.0</td>\n",
              "      <td>88097.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 151 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         id  member_id  ...  settlement_percentage  settlement_term\n",
              "0  68407277        NaN  ...                    NaN              NaN\n",
              "1  68355089        NaN  ...                    NaN              NaN\n",
              "2  68341763        NaN  ...                    NaN              NaN\n",
              "3  66310712        NaN  ...                    NaN              NaN\n",
              "4  68476807        NaN  ...                    NaN              NaN\n",
              "\n",
              "[5 rows x 151 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ObAweejC07V2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "outputId": "7dbc7ea6-9bbb-4dd0-ab73-69c46ddbed31"
      },
      "source": [
        "sns.regplot(x='fico_range_low',y='int_rate',data=loan_df[:1000]) "
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa305310c90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ObrcvuZ911As",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c467c969-c37e-4698-8ef8-c6e3bd9ea8a1"
      },
      "source": [
        "loan_df['loan_status'].value_counts()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Fully Paid            70288\n",
              "Charged Off           17603\n",
              "Current               11402\n",
              "Late (31-120 days)      441\n",
              "In Grace Period         199\n",
              "Late (16-30 days)        66\n",
              "Default                   1\n",
              "Name: loan_status, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ECZdnV2wohEV"
      },
      "source": [
        "loan_int_df=loan_df[loan_df['loan_status']!='Current']\n",
        "loan_int_df=loan_int_df[loan_df['loan_status']!='Late (31-120 days)']\n",
        "loan_int_df=loan_int_df[loan_df['loan_status']!='In Grace Period']\n",
        "loan_int_df=loan_int_df[loan_df['loan_status']!='Late (16-30 days)']"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nI4nrtEAohA4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c7e66cde-2226-4d96-e34c-8c9932702a96"
      },
      "source": [
        "loan_int_df['loan_status'].value_counts()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Fully Paid     70288\n",
              "Charged Off    17603\n",
              "Default            1\n",
              "Name: loan_status, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v3vqmLHkog9s",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 171
        },
        "outputId": "918f0007-3961-458d-b073-9804e82f8d5d"
      },
      "source": [
        "loan_int_df.groupby('loan_status').agg({'last_fico_range_high':'mean'})"
      ],
      "execution_count": 13,
      "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>last_fico_range_high</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>loan_status</th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Charged Off</th>\n",
              "      <td>563.817133</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Default</th>\n",
              "      <td>594.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Fully Paid</th>\n",
              "      <td>704.772294</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "             last_fico_range_high\n",
              "loan_status                      \n",
              "Charged Off            563.817133\n",
              "Default                594.000000\n",
              "Fully Paid             704.772294"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "04WtWsT7sXM6"
      },
      "source": [
        "loan_int_df['loan_status']=loan_int_df['loan_status'].replace('Charged Off','Default')\n",
        "loan_int_df['loan_status']=loan_int_df['loan_status'].replace('Fully Paid','Good')"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nuXTlwJiog6o",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ecedddba-7326-4c03-a6b6-8df095983e85"
      },
      "source": [
        "loan_int_df['loan_status'].value_counts()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Good       70288\n",
              "Default    17604\n",
              "Name: loan_status, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_rnGuy1bog33",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8e3ebcf8-03c4-44e0-cc30-9215354e7548"
      },
      "source": [
        "loan_int_df.info()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 87892 entries, 0 to 99998\n",
            "Columns: 151 entries, id to settlement_term\n",
            "dtypes: float64(113), object(38)\n",
            "memory usage: 101.9+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v1OiBkQS4izq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9f10a4cb-20b9-4dce-99b4-773a0789ba12"
      },
      "source": [
        "loan_int_df['fico_range_low'].min()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "660.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Gzdp0BsrvMzb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "590cfe5c-b31a-47c8-90a8-5bf022eb218f"
      },
      "source": [
        "loan_int_df['fico_range_low'].max()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "845.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Fjl3a2aL5o7m",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "788ecd19-7e23-4346-c362-e27de36a09e8"
      },
      "source": [
        "loan_int_df['last_fico_range_low'].min()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vLUieVdnogvO"
      },
      "source": [
        "loan_int_df['last_fico_range_low']=loan_int_df.apply(lambda x: x['fico_range_low'] if x['last_fico_range_low']==0.0 else x['last_fico_range_low'],axis=1)"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Uw4iKQz98Bz4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "30073235-155a-4e7d-ff72-418c6700ed53"
      },
      "source": [
        "loan_int_df['last_fico_range_low'].min()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "500.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qLWO-Zgx8Bb7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b1e5a319-0d6f-4256-ebb5-fc5f02484c7f"
      },
      "source": [
        "loan_int_df['last_fico_range_low'].max()"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "845.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f4LC3rP5wmOD"
      },
      "source": [
        "import math\n",
        "loan_int_df['fico_score']=loan_int_df['last_fico_range_low'].apply(lambda x: int(math.ceil(x/10))*10)"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aE68O3RP8jpk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 338
        },
        "outputId": "7819953d-0d86-45f4-c72a-0bf9a6b15105"
      },
      "source": [
        "loan_int_df.head()"
      ],
      "execution_count": 24,
      "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>id</th>\n",
              "      <th>member_id</th>\n",
              "      <th>loan_amnt</th>\n",
              "      <th>funded_amnt</th>\n",
              "      <th>funded_amnt_inv</th>\n",
              "      <th>term</th>\n",
              "      <th>int_rate</th>\n",
              "      <th>installment</th>\n",
              "      <th>grade</th>\n",
              "      <th>sub_grade</th>\n",
              "      <th>emp_title</th>\n",
              "      <th>emp_length</th>\n",
              "      <th>home_ownership</th>\n",
              "      <th>annual_inc</th>\n",
              "      <th>verification_status</th>\n",
              "      <th>issue_d</th>\n",
              "      <th>loan_status</th>\n",
              "      <th>pymnt_plan</th>\n",
              "      <th>url</th>\n",
              "      <th>desc</th>\n",
              "      <th>purpose</th>\n",
              "      <th>title</th>\n",
              "      <th>zip_code</th>\n",
              "      <th>addr_state</th>\n",
              "      <th>dti</th>\n",
              "      <th>delinq_2yrs</th>\n",
              "      <th>earliest_cr_line</th>\n",
              "      <th>fico_range_low</th>\n",
              "      <th>fico_range_high</th>\n",
              "      <th>inq_last_6mths</th>\n",
              "      <th>mths_since_last_delinq</th>\n",
              "      <th>mths_since_last_record</th>\n",
              "      <th>open_acc</th>\n",
              "      <th>pub_rec</th>\n",
              "      <th>revol_bal</th>\n",
              "      <th>revol_util</th>\n",
              "      <th>total_acc</th>\n",
              "      <th>initial_list_status</th>\n",
              "      <th>out_prncp</th>\n",
              "      <th>out_prncp_inv</th>\n",
              "      <th>...</th>\n",
              "      <th>total_bal_ex_mort</th>\n",
              "      <th>total_bc_limit</th>\n",
              "      <th>total_il_high_credit_limit</th>\n",
              "      <th>revol_bal_joint</th>\n",
              "      <th>sec_app_fico_range_low</th>\n",
              "      <th>sec_app_fico_range_high</th>\n",
              "      <th>sec_app_earliest_cr_line</th>\n",
              "      <th>sec_app_inq_last_6mths</th>\n",
              "      <th>sec_app_mort_acc</th>\n",
              "      <th>sec_app_open_acc</th>\n",
              "      <th>sec_app_revol_util</th>\n",
              "      <th>sec_app_open_act_il</th>\n",
              "      <th>sec_app_num_rev_accts</th>\n",
              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
              "      <th>sec_app_mths_since_last_major_derog</th>\n",
              "      <th>hardship_flag</th>\n",
              "      <th>hardship_type</th>\n",
              "      <th>hardship_reason</th>\n",
              "      <th>hardship_status</th>\n",
              "      <th>deferral_term</th>\n",
              "      <th>hardship_amount</th>\n",
              "      <th>hardship_start_date</th>\n",
              "      <th>hardship_end_date</th>\n",
              "      <th>payment_plan_start_date</th>\n",
              "      <th>hardship_length</th>\n",
              "      <th>hardship_dpd</th>\n",
              "      <th>hardship_loan_status</th>\n",
              "      <th>orig_projected_additional_accrued_interest</th>\n",
              "      <th>hardship_payoff_balance_amount</th>\n",
              "      <th>hardship_last_payment_amount</th>\n",
              "      <th>disbursement_method</th>\n",
              "      <th>debt_settlement_flag</th>\n",
              "      <th>debt_settlement_flag_date</th>\n",
              "      <th>settlement_status</th>\n",
              "      <th>settlement_date</th>\n",
              "      <th>settlement_amount</th>\n",
              "      <th>settlement_percentage</th>\n",
              "      <th>settlement_term</th>\n",
              "      <th>fico_score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>68407277</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3600.0</td>\n",
              "      <td>3600.0</td>\n",
              "      <td>3600.0</td>\n",
              "      <td>36 months</td>\n",
              "      <td>13.99</td>\n",
              "      <td>123.03</td>\n",
              "      <td>C</td>\n",
              "      <td>C4</td>\n",
              "      <td>leadman</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>55000.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>debt_consolidation</td>\n",
              "      <td>Debt consolidation</td>\n",
              "      <td>190xx</td>\n",
              "      <td>PA</td>\n",
              "      <td>5.91</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Aug-2003</td>\n",
              "      <td>675.0</td>\n",
              "      <td>679.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2765.0</td>\n",
              "      <td>29.7</td>\n",
              "      <td>13.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>7746.0</td>\n",
              "      <td>2400.0</td>\n",
              "      <td>13734.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>68355089</td>\n",
              "      <td>NaN</td>\n",
              "      <td>24700.0</td>\n",
              "      <td>24700.0</td>\n",
              "      <td>24700.0</td>\n",
              "      <td>36 months</td>\n",
              "      <td>11.99</td>\n",
              "      <td>820.28</td>\n",
              "      <td>C</td>\n",
              "      <td>C1</td>\n",
              "      <td>Engineer</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>small_business</td>\n",
              "      <td>Business</td>\n",
              "      <td>577xx</td>\n",
              "      <td>SD</td>\n",
              "      <td>16.06</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Dec-1999</td>\n",
              "      <td>715.0</td>\n",
              "      <td>719.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>22.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21470.0</td>\n",
              "      <td>19.2</td>\n",
              "      <td>38.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>39475.0</td>\n",
              "      <td>79300.0</td>\n",
              "      <td>24667.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>68341763</td>\n",
              "      <td>NaN</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>60 months</td>\n",
              "      <td>10.78</td>\n",
              "      <td>432.66</td>\n",
              "      <td>B</td>\n",
              "      <td>B4</td>\n",
              "      <td>truck driver</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>63000.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>home_improvement</td>\n",
              "      <td>NaN</td>\n",
              "      <td>605xx</td>\n",
              "      <td>IL</td>\n",
              "      <td>10.78</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Aug-2000</td>\n",
              "      <td>695.0</td>\n",
              "      <td>699.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7869.0</td>\n",
              "      <td>56.2</td>\n",
              "      <td>18.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>18696.0</td>\n",
              "      <td>6200.0</td>\n",
              "      <td>14877.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>68476807</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10400.0</td>\n",
              "      <td>10400.0</td>\n",
              "      <td>10400.0</td>\n",
              "      <td>60 months</td>\n",
              "      <td>22.45</td>\n",
              "      <td>289.91</td>\n",
              "      <td>F</td>\n",
              "      <td>F1</td>\n",
              "      <td>Contract Specialist</td>\n",
              "      <td>3 years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>104433.0</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>major_purchase</td>\n",
              "      <td>Major purchase</td>\n",
              "      <td>174xx</td>\n",
              "      <td>PA</td>\n",
              "      <td>25.37</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Jun-1998</td>\n",
              "      <td>695.0</td>\n",
              "      <td>699.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21929.0</td>\n",
              "      <td>64.5</td>\n",
              "      <td>35.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>95768.0</td>\n",
              "      <td>20300.0</td>\n",
              "      <td>88097.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>68426831</td>\n",
              "      <td>NaN</td>\n",
              "      <td>11950.0</td>\n",
              "      <td>11950.0</td>\n",
              "      <td>11950.0</td>\n",
              "      <td>36 months</td>\n",
              "      <td>13.44</td>\n",
              "      <td>405.18</td>\n",
              "      <td>C</td>\n",
              "      <td>C3</td>\n",
              "      <td>Veterinary Tecnician</td>\n",
              "      <td>4 years</td>\n",
              "      <td>RENT</td>\n",
              "      <td>34000.0</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>debt_consolidation</td>\n",
              "      <td>Debt consolidation</td>\n",
              "      <td>300xx</td>\n",
              "      <td>GA</td>\n",
              "      <td>10.20</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Oct-1987</td>\n",
              "      <td>690.0</td>\n",
              "      <td>694.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>8822.0</td>\n",
              "      <td>68.4</td>\n",
              "      <td>6.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>12798.0</td>\n",
              "      <td>9400.0</td>\n",
              "      <td>4000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>760</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 152 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         id  member_id  ...  settlement_term  fico_score\n",
              "0  68407277        NaN  ...              NaN         560\n",
              "1  68355089        NaN  ...              NaN         700\n",
              "2  68341763        NaN  ...              NaN         700\n",
              "4  68476807        NaN  ...              NaN         700\n",
              "5  68426831        NaN  ...              NaN         760\n",
              "\n",
              "[5 rows x 152 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dzChx20gTfQe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "df678a4b-d849-468b-cb7f-7b3ad012d7bd"
      },
      "source": [
        "loan_int_df.isnull().sum()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                           0\n",
              "member_id                87892\n",
              "loan_amnt                    0\n",
              "funded_amnt                  0\n",
              "funded_amnt_inv              0\n",
              "                         ...  \n",
              "settlement_date          84972\n",
              "settlement_amount        84972\n",
              "settlement_percentage    84972\n",
              "settlement_term          84972\n",
              "fico_score                   0\n",
              "Length: 152, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N7MFPR5B9jTg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 194
        },
        "outputId": "effdfabf-d585-4f64-dbf7-9ec6b99174db"
      },
      "source": [
        "loan_int_df[loan_df['dti'].isnull()]"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>member_id</th>\n",
              "      <th>loan_amnt</th>\n",
              "      <th>funded_amnt</th>\n",
              "      <th>funded_amnt_inv</th>\n",
              "      <th>term</th>\n",
              "      <th>int_rate</th>\n",
              "      <th>installment</th>\n",
              "      <th>grade</th>\n",
              "      <th>sub_grade</th>\n",
              "      <th>emp_title</th>\n",
              "      <th>emp_length</th>\n",
              "      <th>home_ownership</th>\n",
              "      <th>annual_inc</th>\n",
              "      <th>verification_status</th>\n",
              "      <th>issue_d</th>\n",
              "      <th>loan_status</th>\n",
              "      <th>pymnt_plan</th>\n",
              "      <th>url</th>\n",
              "      <th>desc</th>\n",
              "      <th>purpose</th>\n",
              "      <th>title</th>\n",
              "      <th>zip_code</th>\n",
              "      <th>addr_state</th>\n",
              "      <th>dti</th>\n",
              "      <th>delinq_2yrs</th>\n",
              "      <th>earliest_cr_line</th>\n",
              "      <th>fico_range_low</th>\n",
              "      <th>fico_range_high</th>\n",
              "      <th>inq_last_6mths</th>\n",
              "      <th>mths_since_last_delinq</th>\n",
              "      <th>mths_since_last_record</th>\n",
              "      <th>open_acc</th>\n",
              "      <th>pub_rec</th>\n",
              "      <th>revol_bal</th>\n",
              "      <th>revol_util</th>\n",
              "      <th>total_acc</th>\n",
              "      <th>initial_list_status</th>\n",
              "      <th>out_prncp</th>\n",
              "      <th>out_prncp_inv</th>\n",
              "      <th>...</th>\n",
              "      <th>total_bal_ex_mort</th>\n",
              "      <th>total_bc_limit</th>\n",
              "      <th>total_il_high_credit_limit</th>\n",
              "      <th>revol_bal_joint</th>\n",
              "      <th>sec_app_fico_range_low</th>\n",
              "      <th>sec_app_fico_range_high</th>\n",
              "      <th>sec_app_earliest_cr_line</th>\n",
              "      <th>sec_app_inq_last_6mths</th>\n",
              "      <th>sec_app_mort_acc</th>\n",
              "      <th>sec_app_open_acc</th>\n",
              "      <th>sec_app_revol_util</th>\n",
              "      <th>sec_app_open_act_il</th>\n",
              "      <th>sec_app_num_rev_accts</th>\n",
              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
              "      <th>sec_app_mths_since_last_major_derog</th>\n",
              "      <th>hardship_flag</th>\n",
              "      <th>hardship_type</th>\n",
              "      <th>hardship_reason</th>\n",
              "      <th>hardship_status</th>\n",
              "      <th>deferral_term</th>\n",
              "      <th>hardship_amount</th>\n",
              "      <th>hardship_start_date</th>\n",
              "      <th>hardship_end_date</th>\n",
              "      <th>payment_plan_start_date</th>\n",
              "      <th>hardship_length</th>\n",
              "      <th>hardship_dpd</th>\n",
              "      <th>hardship_loan_status</th>\n",
              "      <th>orig_projected_additional_accrued_interest</th>\n",
              "      <th>hardship_payoff_balance_amount</th>\n",
              "      <th>hardship_last_payment_amount</th>\n",
              "      <th>disbursement_method</th>\n",
              "      <th>debt_settlement_flag</th>\n",
              "      <th>debt_settlement_flag_date</th>\n",
              "      <th>settlement_status</th>\n",
              "      <th>settlement_date</th>\n",
              "      <th>settlement_amount</th>\n",
              "      <th>settlement_percentage</th>\n",
              "      <th>settlement_term</th>\n",
              "      <th>fico_score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>18202</th>\n",
              "      <td>66415476</td>\n",
              "      <td>NaN</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>36 months</td>\n",
              "      <td>16.99</td>\n",
              "      <td>712.96</td>\n",
              "      <td>D</td>\n",
              "      <td>D3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>debt_consolidation</td>\n",
              "      <td>Debt consolidation</td>\n",
              "      <td>760xx</td>\n",
              "      <td>TX</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Jul-2001</td>\n",
              "      <td>685.0</td>\n",
              "      <td>689.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7161.0</td>\n",
              "      <td>88.4</td>\n",
              "      <td>11.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>8715.0</td>\n",
              "      <td>7200.0</td>\n",
              "      <td>3000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>65620</th>\n",
              "      <td>65199509</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3700.0</td>\n",
              "      <td>3700.0</td>\n",
              "      <td>3700.0</td>\n",
              "      <td>36 months</td>\n",
              "      <td>12.59</td>\n",
              "      <td>123.94</td>\n",
              "      <td>C</td>\n",
              "      <td>C2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Nov-2015</td>\n",
              "      <td>Default</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>credit_card</td>\n",
              "      <td>Credit card refinancing</td>\n",
              "      <td>765xx</td>\n",
              "      <td>TX</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>Aug-1978</td>\n",
              "      <td>680.0</td>\n",
              "      <td>684.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10649.0</td>\n",
              "      <td>56.9</td>\n",
              "      <td>20.0</td>\n",
              "      <td>f</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>24521.0</td>\n",
              "      <td>400.0</td>\n",
              "      <td>20167.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>540</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2 rows × 152 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "             id  member_id  ...  settlement_term  fico_score\n",
              "18202  66415476        NaN  ...              NaN         650\n",
              "65620  65199509        NaN  ...              NaN         540\n",
              "\n",
              "[2 rows x 152 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FLwOLAEGRUmI"
      },
      "source": [
        "loan_int_df['dti_final']=loan_int_df.apply(lambda x: x['dti_joint'] if pd.isnull(x['dti']) else x['dti'], axis=1)\n",
        "loan_int_df['annual_inc_final']=loan_int_df.apply(lambda x: x['annual_inc_joint'] if x['annual_inc']==0.0 else x['annual_inc'], axis=1)"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_mcTSpxt_8_m",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6085caab-42c7-4011-affa-fab849394d04"
      },
      "source": [
        "loan_int_df.isnull().sum()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id                           0\n",
              "member_id                87892\n",
              "loan_amnt                    0\n",
              "funded_amnt                  0\n",
              "funded_amnt_inv              0\n",
              "                         ...  \n",
              "settlement_percentage    84972\n",
              "settlement_term          84972\n",
              "fico_score                   0\n",
              "dti_final                    0\n",
              "annual_inc_final             0\n",
              "Length: 154, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_2LZDeLbm4Lv",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 338
        },
        "outputId": "a079b4fb-1811-4a07-c637-ef08a81f0451"
      },
      "source": [
        "loan_int_df.head()"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "    .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>id</th>\n",
              "      <th>member_id</th>\n",
              "      <th>loan_amnt</th>\n",
              "      <th>funded_amnt</th>\n",
              "      <th>funded_amnt_inv</th>\n",
              "      <th>term</th>\n",
              "      <th>int_rate</th>\n",
              "      <th>installment</th>\n",
              "      <th>grade</th>\n",
              "      <th>sub_grade</th>\n",
              "      <th>emp_title</th>\n",
              "      <th>emp_length</th>\n",
              "      <th>home_ownership</th>\n",
              "      <th>annual_inc</th>\n",
              "      <th>verification_status</th>\n",
              "      <th>issue_d</th>\n",
              "      <th>loan_status</th>\n",
              "      <th>pymnt_plan</th>\n",
              "      <th>url</th>\n",
              "      <th>desc</th>\n",
              "      <th>purpose</th>\n",
              "      <th>title</th>\n",
              "      <th>zip_code</th>\n",
              "      <th>addr_state</th>\n",
              "      <th>dti</th>\n",
              "      <th>delinq_2yrs</th>\n",
              "      <th>earliest_cr_line</th>\n",
              "      <th>fico_range_low</th>\n",
              "      <th>fico_range_high</th>\n",
              "      <th>inq_last_6mths</th>\n",
              "      <th>mths_since_last_delinq</th>\n",
              "      <th>mths_since_last_record</th>\n",
              "      <th>open_acc</th>\n",
              "      <th>pub_rec</th>\n",
              "      <th>revol_bal</th>\n",
              "      <th>revol_util</th>\n",
              "      <th>total_acc</th>\n",
              "      <th>initial_list_status</th>\n",
              "      <th>out_prncp</th>\n",
              "      <th>out_prncp_inv</th>\n",
              "      <th>...</th>\n",
              "      <th>total_il_high_credit_limit</th>\n",
              "      <th>revol_bal_joint</th>\n",
              "      <th>sec_app_fico_range_low</th>\n",
              "      <th>sec_app_fico_range_high</th>\n",
              "      <th>sec_app_earliest_cr_line</th>\n",
              "      <th>sec_app_inq_last_6mths</th>\n",
              "      <th>sec_app_mort_acc</th>\n",
              "      <th>sec_app_open_acc</th>\n",
              "      <th>sec_app_revol_util</th>\n",
              "      <th>sec_app_open_act_il</th>\n",
              "      <th>sec_app_num_rev_accts</th>\n",
              "      <th>sec_app_chargeoff_within_12_mths</th>\n",
              "      <th>sec_app_collections_12_mths_ex_med</th>\n",
              "      <th>sec_app_mths_since_last_major_derog</th>\n",
              "      <th>hardship_flag</th>\n",
              "      <th>hardship_type</th>\n",
              "      <th>hardship_reason</th>\n",
              "      <th>hardship_status</th>\n",
              "      <th>deferral_term</th>\n",
              "      <th>hardship_amount</th>\n",
              "      <th>hardship_start_date</th>\n",
              "      <th>hardship_end_date</th>\n",
              "      <th>payment_plan_start_date</th>\n",
              "      <th>hardship_length</th>\n",
              "      <th>hardship_dpd</th>\n",
              "      <th>hardship_loan_status</th>\n",
              "      <th>orig_projected_additional_accrued_interest</th>\n",
              "      <th>hardship_payoff_balance_amount</th>\n",
              "      <th>hardship_last_payment_amount</th>\n",
              "      <th>disbursement_method</th>\n",
              "      <th>debt_settlement_flag</th>\n",
              "      <th>debt_settlement_flag_date</th>\n",
              "      <th>settlement_status</th>\n",
              "      <th>settlement_date</th>\n",
              "      <th>settlement_amount</th>\n",
              "      <th>settlement_percentage</th>\n",
              "      <th>settlement_term</th>\n",
              "      <th>fico_score</th>\n",
              "      <th>dti_final</th>\n",
              "      <th>annual_inc_final</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>68407277</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3600.0</td>\n",
              "      <td>3600.0</td>\n",
              "      <td>3600.0</td>\n",
              "      <td>36 months</td>\n",
              "      <td>13.99</td>\n",
              "      <td>123.03</td>\n",
              "      <td>C</td>\n",
              "      <td>C4</td>\n",
              "      <td>leadman</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>55000.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>debt_consolidation</td>\n",
              "      <td>Debt consolidation</td>\n",
              "      <td>190xx</td>\n",
              "      <td>PA</td>\n",
              "      <td>5.91</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Aug-2003</td>\n",
              "      <td>675.0</td>\n",
              "      <td>679.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2765.0</td>\n",
              "      <td>29.7</td>\n",
              "      <td>13.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>13734.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>560</td>\n",
              "      <td>5.91</td>\n",
              "      <td>55000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>68355089</td>\n",
              "      <td>NaN</td>\n",
              "      <td>24700.0</td>\n",
              "      <td>24700.0</td>\n",
              "      <td>24700.0</td>\n",
              "      <td>36 months</td>\n",
              "      <td>11.99</td>\n",
              "      <td>820.28</td>\n",
              "      <td>C</td>\n",
              "      <td>C1</td>\n",
              "      <td>Engineer</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>small_business</td>\n",
              "      <td>Business</td>\n",
              "      <td>577xx</td>\n",
              "      <td>SD</td>\n",
              "      <td>16.06</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Dec-1999</td>\n",
              "      <td>715.0</td>\n",
              "      <td>719.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>22.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21470.0</td>\n",
              "      <td>19.2</td>\n",
              "      <td>38.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>24667.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>700</td>\n",
              "      <td>16.06</td>\n",
              "      <td>65000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>68341763</td>\n",
              "      <td>NaN</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>20000.0</td>\n",
              "      <td>60 months</td>\n",
              "      <td>10.78</td>\n",
              "      <td>432.66</td>\n",
              "      <td>B</td>\n",
              "      <td>B4</td>\n",
              "      <td>truck driver</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>63000.0</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>home_improvement</td>\n",
              "      <td>NaN</td>\n",
              "      <td>605xx</td>\n",
              "      <td>IL</td>\n",
              "      <td>10.78</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Aug-2000</td>\n",
              "      <td>695.0</td>\n",
              "      <td>699.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7869.0</td>\n",
              "      <td>56.2</td>\n",
              "      <td>18.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>14877.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>700</td>\n",
              "      <td>10.78</td>\n",
              "      <td>63000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>68476807</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10400.0</td>\n",
              "      <td>10400.0</td>\n",
              "      <td>10400.0</td>\n",
              "      <td>60 months</td>\n",
              "      <td>22.45</td>\n",
              "      <td>289.91</td>\n",
              "      <td>F</td>\n",
              "      <td>F1</td>\n",
              "      <td>Contract Specialist</td>\n",
              "      <td>3 years</td>\n",
              "      <td>MORTGAGE</td>\n",
              "      <td>104433.0</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>major_purchase</td>\n",
              "      <td>Major purchase</td>\n",
              "      <td>174xx</td>\n",
              "      <td>PA</td>\n",
              "      <td>25.37</td>\n",
              "      <td>1.0</td>\n",
              "      <td>Jun-1998</td>\n",
              "      <td>695.0</td>\n",
              "      <td>699.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>12.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>21929.0</td>\n",
              "      <td>64.5</td>\n",
              "      <td>35.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>88097.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>700</td>\n",
              "      <td>25.37</td>\n",
              "      <td>104433.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>68426831</td>\n",
              "      <td>NaN</td>\n",
              "      <td>11950.0</td>\n",
              "      <td>11950.0</td>\n",
              "      <td>11950.0</td>\n",
              "      <td>36 months</td>\n",
              "      <td>13.44</td>\n",
              "      <td>405.18</td>\n",
              "      <td>C</td>\n",
              "      <td>C3</td>\n",
              "      <td>Veterinary Tecnician</td>\n",
              "      <td>4 years</td>\n",
              "      <td>RENT</td>\n",
              "      <td>34000.0</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>Dec-2015</td>\n",
              "      <td>Good</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>debt_consolidation</td>\n",
              "      <td>Debt consolidation</td>\n",
              "      <td>300xx</td>\n",
              "      <td>GA</td>\n",
              "      <td>10.20</td>\n",
              "      <td>0.0</td>\n",
              "      <td>Oct-1987</td>\n",
              "      <td>690.0</td>\n",
              "      <td>694.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>8822.0</td>\n",
              "      <td>68.4</td>\n",
              "      <td>6.0</td>\n",
              "      <td>w</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>4000.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Cash</td>\n",
              "      <td>N</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>760</td>\n",
              "      <td>10.20</td>\n",
              "      <td>34000.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 154 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "         id  member_id  loan_amnt  ...  fico_score  dti_final annual_inc_final\n",
              "0  68407277        NaN     3600.0  ...         560       5.91          55000.0\n",
              "1  68355089        NaN    24700.0  ...         700      16.06          65000.0\n",
              "2  68341763        NaN    20000.0  ...         700      10.78          63000.0\n",
              "4  68476807        NaN    10400.0  ...         700      25.37         104433.0\n",
              "5  68426831        NaN    11950.0  ...         760      10.20          34000.0\n",
              "\n",
              "[5 rows x 154 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MCHxzQjjx8H6",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2c51c726-8aed-48bd-bfc3-a6adb014500c"
      },
      "source": [
        "loan_int_df['fico_score'].value_counts().sort_index()"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "500     503\n",
              "510    1122\n",
              "520    1368\n",
              "530    1531\n",
              "540    1776\n",
              "550    1773\n",
              "560    1836\n",
              "570    1792\n",
              "580    1782\n",
              "590    1586\n",
              "600    1596\n",
              "610    1668\n",
              "620    1653\n",
              "630    1808\n",
              "640    2109\n",
              "650    2582\n",
              "660    3659\n",
              "670    4687\n",
              "680    5332\n",
              "690    5666\n",
              "700    5620\n",
              "710    5492\n",
              "720    5577\n",
              "730    4736\n",
              "740    3962\n",
              "750    3319\n",
              "760    2788\n",
              "770    2459\n",
              "780    2243\n",
              "790    1867\n",
              "800    1545\n",
              "810    1153\n",
              "820     779\n",
              "830     379\n",
              "840     125\n",
              "850      19\n",
              "Name: fico_score, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EtcQ6_pH4Pmi"
      },
      "source": [
        "fico_df=loan_int_df['fico_score'].value_counts().sort_index()"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n2hx1yVy4PjW",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "517bcca6-14f2-4b56-ac3e-7e0ed9c04d67"
      },
      "source": [
        "fico_df.head()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "500     503\n",
              "510    1122\n",
              "520    1368\n",
              "530    1531\n",
              "540    1776\n",
              "Name: fico_score, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9LDolnV74PgG",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3722dbfd-f51c-4322-e51b-c934bf599580"
      },
      "source": [
        "loan_int_df[loan_int_df['loan_status']=='Default']['fico_score'].value_counts().sort_index()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "500     446\n",
              "510     967\n",
              "520    1168\n",
              "530    1261\n",
              "540    1395\n",
              "550    1384\n",
              "560    1354\n",
              "570    1254\n",
              "580    1155\n",
              "590     916\n",
              "600     810\n",
              "610     759\n",
              "620     594\n",
              "630     471\n",
              "640     405\n",
              "650     312\n",
              "660     587\n",
              "670     671\n",
              "680     549\n",
              "690     328\n",
              "700     254\n",
              "710     188\n",
              "720     138\n",
              "730      67\n",
              "740      55\n",
              "750      41\n",
              "760      24\n",
              "770      12\n",
              "780      11\n",
              "790       8\n",
              "800      12\n",
              "810       5\n",
              "820       1\n",
              "830       2\n",
              "Name: fico_score, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WnndEkP-4PdD",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "e9fb0e7f-5079-48aa-c131-f824c90ff749"
      },
      "source": [
        "loan_int_df[['fico_score','dti_final','loan_amnt','annual_inc']].groupby('fico_score').agg({'dti_final':'mean', 'loan_amnt':'mean','annual_inc':'median'})"
      ],
      "execution_count": 34,
      "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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              "    }\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>dti_final</th>\n",
              "      <th>loan_amnt</th>\n",
              "      <th>annual_inc</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fico_score</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>500</th>\n",
              "      <td>19.764672</td>\n",
              "      <td>14521.272366</td>\n",
              "      <td>60000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>510</th>\n",
              "      <td>19.998690</td>\n",
              "      <td>13642.134581</td>\n",
              "      <td>55000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>520</th>\n",
              "      <td>20.420950</td>\n",
              "      <td>13970.614035</td>\n",
              "      <td>60000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>530</th>\n",
              "      <td>20.231208</td>\n",
              "      <td>14430.519268</td>\n",
              "      <td>60000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>540</th>\n",
              "      <td>20.661875</td>\n",
              "      <td>14116.497748</td>\n",
              "      <td>60000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>550</th>\n",
              "      <td>21.079549</td>\n",
              "      <td>14750.028201</td>\n",
              "      <td>60000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>560</th>\n",
              "      <td>20.933916</td>\n",
              "      <td>14948.883442</td>\n",
              "      <td>63000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>570</th>\n",
              "      <td>20.616406</td>\n",
              "      <td>14774.930246</td>\n",
              "      <td>63000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>580</th>\n",
              "      <td>20.969136</td>\n",
              "      <td>14524.186308</td>\n",
              "      <td>62000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>590</th>\n",
              "      <td>21.274161</td>\n",
              "      <td>14508.086381</td>\n",
              "      <td>65000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>600</th>\n",
              "      <td>20.261040</td>\n",
              "      <td>13958.082707</td>\n",
              "      <td>62000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>610</th>\n",
              "      <td>20.609544</td>\n",
              "      <td>14139.868106</td>\n",
              "      <td>62000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>620</th>\n",
              "      <td>20.450272</td>\n",
              "      <td>13716.258318</td>\n",
              "      <td>60000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>630</th>\n",
              "      <td>19.653534</td>\n",
              "      <td>13284.499447</td>\n",
              "      <td>61000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>640</th>\n",
              "      <td>19.561195</td>\n",
              "      <td>12849.478426</td>\n",
              "      <td>62000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>650</th>\n",
              "      <td>19.158513</td>\n",
              "      <td>13129.337723</td>\n",
              "      <td>62000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>660</th>\n",
              "      <td>18.984299</td>\n",
              "      <td>12795.408582</td>\n",
              "      <td>62000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>670</th>\n",
              "      <td>18.936823</td>\n",
              "      <td>13182.899509</td>\n",
              "      <td>62259.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>680</th>\n",
              "      <td>19.201682</td>\n",
              "      <td>13477.344336</td>\n",
              "      <td>65000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>690</th>\n",
              "      <td>18.981340</td>\n",
              "      <td>14068.315390</td>\n",
              "      <td>65000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>700</th>\n",
              "      <td>19.186637</td>\n",
              "      <td>14198.131673</td>\n",
              "      <td>65000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>710</th>\n",
              "      <td>19.064314</td>\n",
              "      <td>14544.851602</td>\n",
              "      <td>66000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>720</th>\n",
              "      <td>18.621793</td>\n",
              "      <td>14699.825175</td>\n",
              "      <td>68000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>730</th>\n",
              "      <td>18.306978</td>\n",
              "      <td>14852.106208</td>\n",
              "      <td>68510.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>740</th>\n",
              "      <td>17.919137</td>\n",
              "      <td>14798.592882</td>\n",
              "      <td>68000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>750</th>\n",
              "      <td>17.869241</td>\n",
              "      <td>15189.432058</td>\n",
              "      <td>70000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>760</th>\n",
              "      <td>17.730165</td>\n",
              "      <td>15140.154232</td>\n",
              "      <td>70000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>770</th>\n",
              "      <td>17.292765</td>\n",
              "      <td>15316.195608</td>\n",
              "      <td>70000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>780</th>\n",
              "      <td>17.559759</td>\n",
              "      <td>15458.259028</td>\n",
              "      <td>70000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>790</th>\n",
              "      <td>16.865779</td>\n",
              "      <td>15710.980182</td>\n",
              "      <td>70000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>800</th>\n",
              "      <td>16.688032</td>\n",
              "      <td>15763.527508</td>\n",
              "      <td>70000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>810</th>\n",
              "      <td>16.477997</td>\n",
              "      <td>17034.887251</td>\n",
              "      <td>78000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>820</th>\n",
              "      <td>16.483196</td>\n",
              "      <td>17171.534018</td>\n",
              "      <td>80000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>830</th>\n",
              "      <td>16.016755</td>\n",
              "      <td>18293.073879</td>\n",
              "      <td>85000.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>840</th>\n",
              "      <td>14.748880</td>\n",
              "      <td>19029.400000</td>\n",
              "      <td>84600.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>850</th>\n",
              "      <td>17.116316</td>\n",
              "      <td>19784.210526</td>\n",
              "      <td>65000.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "            dti_final     loan_amnt  annual_inc\n",
              "fico_score                                     \n",
              "500         19.764672  14521.272366     60000.0\n",
              "510         19.998690  13642.134581     55000.0\n",
              "520         20.420950  13970.614035     60000.0\n",
              "530         20.231208  14430.519268     60000.0\n",
              "540         20.661875  14116.497748     60000.0\n",
              "550         21.079549  14750.028201     60000.0\n",
              "560         20.933916  14948.883442     63000.0\n",
              "570         20.616406  14774.930246     63000.0\n",
              "580         20.969136  14524.186308     62000.0\n",
              "590         21.274161  14508.086381     65000.0\n",
              "600         20.261040  13958.082707     62000.0\n",
              "610         20.609544  14139.868106     62000.0\n",
              "620         20.450272  13716.258318     60000.0\n",
              "630         19.653534  13284.499447     61000.0\n",
              "640         19.561195  12849.478426     62000.0\n",
              "650         19.158513  13129.337723     62000.0\n",
              "660         18.984299  12795.408582     62000.0\n",
              "670         18.936823  13182.899509     62259.0\n",
              "680         19.201682  13477.344336     65000.0\n",
              "690         18.981340  14068.315390     65000.0\n",
              "700         19.186637  14198.131673     65000.0\n",
              "710         19.064314  14544.851602     66000.0\n",
              "720         18.621793  14699.825175     68000.0\n",
              "730         18.306978  14852.106208     68510.0\n",
              "740         17.919137  14798.592882     68000.0\n",
              "750         17.869241  15189.432058     70000.0\n",
              "760         17.730165  15140.154232     70000.0\n",
              "770         17.292765  15316.195608     70000.0\n",
              "780         17.559759  15458.259028     70000.0\n",
              "790         16.865779  15710.980182     70000.0\n",
              "800         16.688032  15763.527508     70000.0\n",
              "810         16.477997  17034.887251     78000.0\n",
              "820         16.483196  17171.534018     80000.0\n",
              "830         16.016755  18293.073879     85000.0\n",
              "840         14.748880  19029.400000     84600.0\n",
              "850         17.116316  19784.210526     65000.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Uw-iQXcC4PY9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "e08c7c48-bd2d-4687-d85f-aade286398bf"
      },
      "source": [
        "loan_int_df[['fico_score','annual_inc','int_rate']].groupby('fico_score').mean()"
      ],
      "execution_count": 35,
      "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>annual_inc</th>\n",
              "      <th>int_rate</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>fico_score</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>500</th>\n",
              "      <td>65731.236044</td>\n",
              "      <td>14.553777</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>510</th>\n",
              "      <td>64011.063093</td>\n",
              "      <td>14.554608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>520</th>\n",
              "      <td>67408.905263</td>\n",
              "      <td>14.391140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>530</th>\n",
              "      <td>70423.054102</td>\n",
              "      <td>14.739523</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>540</th>\n",
              "      <td>69924.361312</td>\n",
              "      <td>14.330394</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>550</th>\n",
              "      <td>71161.031117</td>\n",
              "      <td>14.185601</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>560</th>\n",
              "      <td>72395.414303</td>\n",
              "      <td>13.975790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>570</th>\n",
              "      <td>71695.992824</td>\n",
              "      <td>13.910469</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>580</th>\n",
              "      <td>72305.214422</td>\n",
              "      <td>13.869080</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>590</th>\n",
              "      <td>72961.390820</td>\n",
              "      <td>13.789206</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>600</th>\n",
              "      <td>74036.281566</td>\n",
              "      <td>13.621096</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>610</th>\n",
              "      <td>71004.060845</td>\n",
              "      <td>13.762794</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>620</th>\n",
              "      <td>70281.199764</td>\n",
              "      <td>13.570544</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>630</th>\n",
              "      <td>72281.689635</td>\n",
              "      <td>13.138402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>640</th>\n",
              "      <td>73202.308279</td>\n",
              "      <td>13.014822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>650</th>\n",
              "      <td>79348.101139</td>\n",
              "      <td>12.805085</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>660</th>\n",
              "      <td>75443.385078</td>\n",
              "      <td>12.925832</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>670</th>\n",
              "      <td>74368.659729</td>\n",
              "      <td>12.819413</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>680</th>\n",
              "      <td>75754.514850</td>\n",
              "      <td>12.432793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>690</th>\n",
              "      <td>80397.471207</td>\n",
              "      <td>11.999603</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>700</th>\n",
              "      <td>78795.693584</td>\n",
              "      <td>11.753854</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>710</th>\n",
              "      <td>78940.525643</td>\n",
              "      <td>11.485169</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>720</th>\n",
              "      <td>81585.784305</td>\n",
              "      <td>11.126794</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>730</th>\n",
              "      <td>81994.094662</td>\n",
              "      <td>10.844850</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>740</th>\n",
              "      <td>79536.547590</td>\n",
              "      <td>10.568523</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>750</th>\n",
              "      <td>83705.293920</td>\n",
              "      <td>10.309822</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>760</th>\n",
              "      <td>80881.407618</td>\n",
              "      <td>10.028533</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>770</th>\n",
              "      <td>80552.777218</td>\n",
              "      <td>9.869597</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>780</th>\n",
              "      <td>81221.465332</td>\n",
              "      <td>9.508903</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>790</th>\n",
              "      <td>84756.460568</td>\n",
              "      <td>9.224178</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>800</th>\n",
              "      <td>87061.088816</td>\n",
              "      <td>8.850259</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>810</th>\n",
              "      <td>92708.077337</td>\n",
              "      <td>8.530069</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>820</th>\n",
              "      <td>92888.068203</td>\n",
              "      <td>8.181733</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>830</th>\n",
              "      <td>96970.189974</td>\n",
              "      <td>7.658997</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>840</th>\n",
              "      <td>91735.324000</td>\n",
              "      <td>7.168240</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>850</th>\n",
              "      <td>68263.157895</td>\n",
              "      <td>7.440526</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              annual_inc   int_rate\n",
              "fico_score                         \n",
              "500         65731.236044  14.553777\n",
              "510         64011.063093  14.554608\n",
              "520         67408.905263  14.391140\n",
              "530         70423.054102  14.739523\n",
              "540         69924.361312  14.330394\n",
              "550         71161.031117  14.185601\n",
              "560         72395.414303  13.975790\n",
              "570         71695.992824  13.910469\n",
              "580         72305.214422  13.869080\n",
              "590         72961.390820  13.789206\n",
              "600         74036.281566  13.621096\n",
              "610         71004.060845  13.762794\n",
              "620         70281.199764  13.570544\n",
              "630         72281.689635  13.138402\n",
              "640         73202.308279  13.014822\n",
              "650         79348.101139  12.805085\n",
              "660         75443.385078  12.925832\n",
              "670         74368.659729  12.819413\n",
              "680         75754.514850  12.432793\n",
              "690         80397.471207  11.999603\n",
              "700         78795.693584  11.753854\n",
              "710         78940.525643  11.485169\n",
              "720         81585.784305  11.126794\n",
              "730         81994.094662  10.844850\n",
              "740         79536.547590  10.568523\n",
              "750         83705.293920  10.309822\n",
              "760         80881.407618  10.028533\n",
              "770         80552.777218   9.869597\n",
              "780         81221.465332   9.508903\n",
              "790         84756.460568   9.224178\n",
              "800         87061.088816   8.850259\n",
              "810         92708.077337   8.530069\n",
              "820         92888.068203   8.181733\n",
              "830         96970.189974   7.658997\n",
              "840         91735.324000   7.168240\n",
              "850         68263.157895   7.440526"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Bzlq17sLbpCG"
      },
      "source": [
        "fico_df=pd.concat([fico_df,pd.DataFrame(loan_int_df[loan_int_df['loan_status']=='Default']['fico_score'].value_counts().sort_index()),pd.DataFrame(loan_int_df[['fico_score','dti_final','loan_amnt','annual_inc']].groupby('fico_score').agg({'dti_final':'mean', 'loan_amnt':'mean','annual_inc':'median'})),pd.DataFrame(loan_int_df[['fico_score','annual_inc','int_rate']].groupby('fico_score').mean())], ignore_index=True, axis=1)"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-vAC-xDSbo_J",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        },
        "outputId": "d0859c32-41ee-4a6c-bc4d-c0692862cbe3"
      },
      "source": [
        "fico_df.head()"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>0</th>\n",
              "      <th>1</th>\n",
              "      <th>2</th>\n",
              "      <th>3</th>\n",
              "      <th>4</th>\n",
              "      <th>5</th>\n",
              "      <th>6</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>500</th>\n",
              "      <td>503</td>\n",
              "      <td>446.0</td>\n",
              "      <td>19.764672</td>\n",
              "      <td>14521.272366</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>65731.236044</td>\n",
              "      <td>14.553777</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>510</th>\n",
              "      <td>1122</td>\n",
              "      <td>967.0</td>\n",
              "      <td>19.998690</td>\n",
              "      <td>13642.134581</td>\n",
              "      <td>55000.0</td>\n",
              "      <td>64011.063093</td>\n",
              "      <td>14.554608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>520</th>\n",
              "      <td>1368</td>\n",
              "      <td>1168.0</td>\n",
              "      <td>20.420950</td>\n",
              "      <td>13970.614035</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>67408.905263</td>\n",
              "      <td>14.391140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>530</th>\n",
              "      <td>1531</td>\n",
              "      <td>1261.0</td>\n",
              "      <td>20.231208</td>\n",
              "      <td>14430.519268</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>70423.054102</td>\n",
              "      <td>14.739523</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>540</th>\n",
              "      <td>1776</td>\n",
              "      <td>1395.0</td>\n",
              "      <td>20.661875</td>\n",
              "      <td>14116.497748</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>69924.361312</td>\n",
              "      <td>14.330394</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        0       1          2             3        4             5          6\n",
              "500   503   446.0  19.764672  14521.272366  60000.0  65731.236044  14.553777\n",
              "510  1122   967.0  19.998690  13642.134581  55000.0  64011.063093  14.554608\n",
              "520  1368  1168.0  20.420950  13970.614035  60000.0  67408.905263  14.391140\n",
              "530  1531  1261.0  20.231208  14430.519268  60000.0  70423.054102  14.739523\n",
              "540  1776  1395.0  20.661875  14116.497748  60000.0  69924.361312  14.330394"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dSjuT0BZrxFu"
      },
      "source": [
        "fico_df=fico_df.reset_index()"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9naqeV9krTxv"
      },
      "source": [
        "fico_df.columns = ['fico_score','loan_total','default_total','dti','avg_loan_amnt','median_annual_inc','avg_annual_inc','int_rate']"
      ],
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gKonnt2wrTlx",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 222
        },
        "outputId": "1bfedfb3-ecc5-440a-cbcb-c8563add0ebe"
      },
      "source": [
        "fico_df.head()"
      ],
      "execution_count": 40,
      "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",
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              "\n",
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              "\n",
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              "        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>fico_score</th>\n",
              "      <th>loan_total</th>\n",
              "      <th>default_total</th>\n",
              "      <th>dti</th>\n",
              "      <th>avg_loan_amnt</th>\n",
              "      <th>median_annual_inc</th>\n",
              "      <th>avg_annual_inc</th>\n",
              "      <th>int_rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>500</td>\n",
              "      <td>503</td>\n",
              "      <td>446.0</td>\n",
              "      <td>19.764672</td>\n",
              "      <td>14521.272366</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>65731.236044</td>\n",
              "      <td>14.553777</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>510</td>\n",
              "      <td>1122</td>\n",
              "      <td>967.0</td>\n",
              "      <td>19.998690</td>\n",
              "      <td>13642.134581</td>\n",
              "      <td>55000.0</td>\n",
              "      <td>64011.063093</td>\n",
              "      <td>14.554608</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>520</td>\n",
              "      <td>1368</td>\n",
              "      <td>1168.0</td>\n",
              "      <td>20.420950</td>\n",
              "      <td>13970.614035</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>67408.905263</td>\n",
              "      <td>14.391140</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>530</td>\n",
              "      <td>1531</td>\n",
              "      <td>1261.0</td>\n",
              "      <td>20.231208</td>\n",
              "      <td>14430.519268</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>70423.054102</td>\n",
              "      <td>14.739523</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>540</td>\n",
              "      <td>1776</td>\n",
              "      <td>1395.0</td>\n",
              "      <td>20.661875</td>\n",
              "      <td>14116.497748</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>69924.361312</td>\n",
              "      <td>14.330394</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   fico_score  loan_total  ...  avg_annual_inc   int_rate\n",
              "0         500         503  ...    65731.236044  14.553777\n",
              "1         510        1122  ...    64011.063093  14.554608\n",
              "2         520        1368  ...    67408.905263  14.391140\n",
              "3         530        1531  ...    70423.054102  14.739523\n",
              "4         540        1776  ...    69924.361312  14.330394\n",
              "\n",
              "[5 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "foDi8qUrsEe5"
      },
      "source": [
        "fico_df['default_rate']=(fico_df.default_total/fico_df.default_total.sum())*100\n",
        "fico_df['actual_default_rate']=(fico_df.default_total/fico_df.loan_total.sum())*100"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9VQ88BzmsFDj",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 682
        },
        "outputId": "2d706f39-7ed7-4682-b253-4bfb39bda747"
      },
      "source": [
        "fico_df.head(20)"
      ],
      "execution_count": 42,
      "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",
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              "\n",
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              "    }\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>fico_score</th>\n",
              "      <th>loan_total</th>\n",
              "      <th>default_total</th>\n",
              "      <th>dti</th>\n",
              "      <th>avg_loan_amnt</th>\n",
              "      <th>median_annual_inc</th>\n",
              "      <th>avg_annual_inc</th>\n",
              "      <th>int_rate</th>\n",
              "      <th>default_rate</th>\n",
              "      <th>actual_default_rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>500</td>\n",
              "      <td>503</td>\n",
              "      <td>446.0</td>\n",
              "      <td>19.764672</td>\n",
              "      <td>14521.272366</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>65731.236044</td>\n",
              "      <td>14.553777</td>\n",
              "      <td>2.533515</td>\n",
              "      <td>0.507441</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>510</td>\n",
              "      <td>1122</td>\n",
              "      <td>967.0</td>\n",
              "      <td>19.998690</td>\n",
              "      <td>13642.134581</td>\n",
              "      <td>55000.0</td>\n",
              "      <td>64011.063093</td>\n",
              "      <td>14.554608</td>\n",
              "      <td>5.493070</td>\n",
              "      <td>1.100214</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>520</td>\n",
              "      <td>1368</td>\n",
              "      <td>1168.0</td>\n",
              "      <td>20.420950</td>\n",
              "      <td>13970.614035</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>67408.905263</td>\n",
              "      <td>14.391140</td>\n",
              "      <td>6.634856</td>\n",
              "      <td>1.328904</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>530</td>\n",
              "      <td>1531</td>\n",
              "      <td>1261.0</td>\n",
              "      <td>20.231208</td>\n",
              "      <td>14430.519268</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>70423.054102</td>\n",
              "      <td>14.739523</td>\n",
              "      <td>7.163145</td>\n",
              "      <td>1.434715</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>540</td>\n",
              "      <td>1776</td>\n",
              "      <td>1395.0</td>\n",
              "      <td>20.661875</td>\n",
              "      <td>14116.497748</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>69924.361312</td>\n",
              "      <td>14.330394</td>\n",
              "      <td>7.924335</td>\n",
              "      <td>1.587175</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>550</td>\n",
              "      <td>1773</td>\n",
              "      <td>1384.0</td>\n",
              "      <td>21.079549</td>\n",
              "      <td>14750.028201</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>71161.031117</td>\n",
              "      <td>14.185601</td>\n",
              "      <td>7.861850</td>\n",
              "      <td>1.574660</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>560</td>\n",
              "      <td>1836</td>\n",
              "      <td>1354.0</td>\n",
              "      <td>20.933916</td>\n",
              "      <td>14948.883442</td>\n",
              "      <td>63000.0</td>\n",
              "      <td>72395.414303</td>\n",
              "      <td>13.975790</td>\n",
              "      <td>7.691434</td>\n",
              "      <td>1.540527</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>570</td>\n",
              "      <td>1792</td>\n",
              "      <td>1254.0</td>\n",
              "      <td>20.616406</td>\n",
              "      <td>14774.930246</td>\n",
              "      <td>63000.0</td>\n",
              "      <td>71695.992824</td>\n",
              "      <td>13.910469</td>\n",
              "      <td>7.123381</td>\n",
              "      <td>1.426751</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>580</td>\n",
              "      <td>1782</td>\n",
              "      <td>1155.0</td>\n",
              "      <td>20.969136</td>\n",
              "      <td>14524.186308</td>\n",
              "      <td>62000.0</td>\n",
              "      <td>72305.214422</td>\n",
              "      <td>13.869080</td>\n",
              "      <td>6.561009</td>\n",
              "      <td>1.314113</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>590</td>\n",
              "      <td>1586</td>\n",
              "      <td>916.0</td>\n",
              "      <td>21.274161</td>\n",
              "      <td>14508.086381</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>72961.390820</td>\n",
              "      <td>13.789206</td>\n",
              "      <td>5.203363</td>\n",
              "      <td>1.042188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>600</td>\n",
              "      <td>1596</td>\n",
              "      <td>810.0</td>\n",
              "      <td>20.261040</td>\n",
              "      <td>13958.082707</td>\n",
              "      <td>62000.0</td>\n",
              "      <td>74036.281566</td>\n",
              "      <td>13.621096</td>\n",
              "      <td>4.601227</td>\n",
              "      <td>0.921586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>610</td>\n",
              "      <td>1668</td>\n",
              "      <td>759.0</td>\n",
              "      <td>20.609544</td>\n",
              "      <td>14139.868106</td>\n",
              "      <td>62000.0</td>\n",
              "      <td>71004.060845</td>\n",
              "      <td>13.762794</td>\n",
              "      <td>4.311520</td>\n",
              "      <td>0.863560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>620</td>\n",
              "      <td>1653</td>\n",
              "      <td>594.0</td>\n",
              "      <td>20.450272</td>\n",
              "      <td>13716.258318</td>\n",
              "      <td>60000.0</td>\n",
              "      <td>70281.199764</td>\n",
              "      <td>13.570544</td>\n",
              "      <td>3.374233</td>\n",
              "      <td>0.675829</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>630</td>\n",
              "      <td>1808</td>\n",
              "      <td>471.0</td>\n",
              "      <td>19.653534</td>\n",
              "      <td>13284.499447</td>\n",
              "      <td>61000.0</td>\n",
              "      <td>72281.689635</td>\n",
              "      <td>13.138402</td>\n",
              "      <td>2.675528</td>\n",
              "      <td>0.535885</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>640</td>\n",
              "      <td>2109</td>\n",
              "      <td>405.0</td>\n",
              "      <td>19.561195</td>\n",
              "      <td>12849.478426</td>\n",
              "      <td>62000.0</td>\n",
              "      <td>73202.308279</td>\n",
              "      <td>13.014822</td>\n",
              "      <td>2.300613</td>\n",
              "      <td>0.460793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>650</td>\n",
              "      <td>2582</td>\n",
              "      <td>312.0</td>\n",
              "      <td>19.158513</td>\n",
              "      <td>13129.337723</td>\n",
              "      <td>62000.0</td>\n",
              "      <td>79348.101139</td>\n",
              "      <td>12.805085</td>\n",
              "      <td>1.772324</td>\n",
              "      <td>0.354981</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>660</td>\n",
              "      <td>3659</td>\n",
              "      <td>587.0</td>\n",
              "      <td>18.984299</td>\n",
              "      <td>12795.408582</td>\n",
              "      <td>62000.0</td>\n",
              "      <td>75443.385078</td>\n",
              "      <td>12.925832</td>\n",
              "      <td>3.334469</td>\n",
              "      <td>0.667865</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>670</td>\n",
              "      <td>4687</td>\n",
              "      <td>671.0</td>\n",
              "      <td>18.936823</td>\n",
              "      <td>13182.899509</td>\n",
              "      <td>62259.0</td>\n",
              "      <td>74368.659729</td>\n",
              "      <td>12.819413</td>\n",
              "      <td>3.811634</td>\n",
              "      <td>0.763437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>680</td>\n",
              "      <td>5332</td>\n",
              "      <td>549.0</td>\n",
              "      <td>19.201682</td>\n",
              "      <td>13477.344336</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>75754.514850</td>\n",
              "      <td>12.432793</td>\n",
              "      <td>3.118609</td>\n",
              "      <td>0.624630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>690</td>\n",
              "      <td>5666</td>\n",
              "      <td>328.0</td>\n",
              "      <td>18.981340</td>\n",
              "      <td>14068.315390</td>\n",
              "      <td>65000.0</td>\n",
              "      <td>80397.471207</td>\n",
              "      <td>11.999603</td>\n",
              "      <td>1.863213</td>\n",
              "      <td>0.373185</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    fico_score  loan_total  ...  default_rate  actual_default_rate\n",
              "0          500         503  ...      2.533515             0.507441\n",
              "1          510        1122  ...      5.493070             1.100214\n",
              "2          520        1368  ...      6.634856             1.328904\n",
              "3          530        1531  ...      7.163145             1.434715\n",
              "4          540        1776  ...      7.924335             1.587175\n",
              "5          550        1773  ...      7.861850             1.574660\n",
              "6          560        1836  ...      7.691434             1.540527\n",
              "7          570        1792  ...      7.123381             1.426751\n",
              "8          580        1782  ...      6.561009             1.314113\n",
              "9          590        1586  ...      5.203363             1.042188\n",
              "10         600        1596  ...      4.601227             0.921586\n",
              "11         610        1668  ...      4.311520             0.863560\n",
              "12         620        1653  ...      3.374233             0.675829\n",
              "13         630        1808  ...      2.675528             0.535885\n",
              "14         640        2109  ...      2.300613             0.460793\n",
              "15         650        2582  ...      1.772324             0.354981\n",
              "16         660        3659  ...      3.334469             0.667865\n",
              "17         670        4687  ...      3.811634             0.763437\n",
              "18         680        5332  ...      3.118609             0.624630\n",
              "19         690        5666  ...      1.863213             0.373185\n",
              "\n",
              "[20 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QnJEG4LpnB5g",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 314
        },
        "outputId": "778730d6-ac97-40dd-e56e-3143ae507c02"
      },
      "source": [
        "fico_df.describe()"
      ],
      "execution_count": 43,
      "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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              "        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>fico_score</th>\n",
              "      <th>loan_total</th>\n",
              "      <th>default_total</th>\n",
              "      <th>dti</th>\n",
              "      <th>avg_loan_amnt</th>\n",
              "      <th>median_annual_inc</th>\n",
              "      <th>avg_annual_inc</th>\n",
              "      <th>int_rate</th>\n",
              "      <th>default_rate</th>\n",
              "      <th>actual_default_rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>36.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>34.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>36.000000</td>\n",
              "      <td>34.000000</td>\n",
              "      <td>34.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>675.000000</td>\n",
              "      <td>2441.444444</td>\n",
              "      <td>517.764706</td>\n",
              "      <td>18.880460</td>\n",
              "      <td>14882.605749</td>\n",
              "      <td>66093.583333</td>\n",
              "      <td>77381.424779</td>\n",
              "      <td>11.803889</td>\n",
              "      <td>2.941176</td>\n",
              "      <td>0.589092</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>105.356538</td>\n",
              "      <td>1663.572188</td>\n",
              "      <td>486.646350</td>\n",
              "      <td>1.664874</td>\n",
              "      <td>1616.845570</td>\n",
              "      <td>6870.100641</td>\n",
              "      <td>8026.320257</td>\n",
              "      <td>2.338604</td>\n",
              "      <td>2.764408</td>\n",
              "      <td>0.553687</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>500.000000</td>\n",
              "      <td>19.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>14.748880</td>\n",
              "      <td>12795.408582</td>\n",
              "      <td>55000.000000</td>\n",
              "      <td>64011.063093</td>\n",
              "      <td>7.168240</td>\n",
              "      <td>0.005681</td>\n",
              "      <td>0.001138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>587.500000</td>\n",
              "      <td>1541.500000</td>\n",
              "      <td>44.500000</td>\n",
              "      <td>17.687564</td>\n",
              "      <td>13967.481203</td>\n",
              "      <td>62000.000000</td>\n",
              "      <td>71562.252397</td>\n",
              "      <td>9.988799</td>\n",
              "      <td>0.252783</td>\n",
              "      <td>0.050630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>675.000000</td>\n",
              "      <td>1800.000000</td>\n",
              "      <td>425.500000</td>\n",
              "      <td>19.111413</td>\n",
              "      <td>14534.518955</td>\n",
              "      <td>65000.000000</td>\n",
              "      <td>75598.949964</td>\n",
              "      <td>12.618939</td>\n",
              "      <td>2.417064</td>\n",
              "      <td>0.484117</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>762.500000</td>\n",
              "      <td>3404.000000</td>\n",
              "      <td>889.500000</td>\n",
              "      <td>20.301018</td>\n",
              "      <td>15221.122945</td>\n",
              "      <td>70000.000000</td>\n",
              "      <td>81312.545075</td>\n",
              "      <td>13.809174</td>\n",
              "      <td>5.052829</td>\n",
              "      <td>1.012038</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>850.000000</td>\n",
              "      <td>5666.000000</td>\n",
              "      <td>1395.000000</td>\n",
              "      <td>21.274161</td>\n",
              "      <td>19784.210526</td>\n",
              "      <td>85000.000000</td>\n",
              "      <td>96970.189974</td>\n",
              "      <td>14.739523</td>\n",
              "      <td>7.924335</td>\n",
              "      <td>1.587175</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       fico_score   loan_total  ...  default_rate  actual_default_rate\n",
              "count   36.000000    36.000000  ...     34.000000            34.000000\n",
              "mean   675.000000  2441.444444  ...      2.941176             0.589092\n",
              "std    105.356538  1663.572188  ...      2.764408             0.553687\n",
              "min    500.000000    19.000000  ...      0.005681             0.001138\n",
              "25%    587.500000  1541.500000  ...      0.252783             0.050630\n",
              "50%    675.000000  1800.000000  ...      2.417064             0.484117\n",
              "75%    762.500000  3404.000000  ...      5.052829             1.012038\n",
              "max    850.000000  5666.000000  ...      7.924335             1.587175\n",
              "\n",
              "[8 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nQCnwkefEleE"
      },
      "source": [
        "fico_df.to_csv('loan_analysis_summary.csv')"
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hVpwoIfaowLt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 375
        },
        "outputId": "7797bce3-4bf6-4924-98c8-3460d1aa6250"
      },
      "source": [
        "fico_df.corr()"
      ],
      "execution_count": 45,
      "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>fico_score</th>\n",
              "      <th>loan_total</th>\n",
              "      <th>default_total</th>\n",
              "      <th>dti</th>\n",
              "      <th>avg_loan_amnt</th>\n",
              "      <th>median_annual_inc</th>\n",
              "      <th>avg_annual_inc</th>\n",
              "      <th>int_rate</th>\n",
              "      <th>default_rate</th>\n",
              "      <th>actual_default_rate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>fico_score</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.071474</td>\n",
              "      <td>-0.884677</td>\n",
              "      <td>-0.919147</td>\n",
              "      <td>0.680018</td>\n",
              "      <td>0.828385</td>\n",
              "      <td>0.824738</td>\n",
              "      <td>-0.975022</td>\n",
              "      <td>-0.884677</td>\n",
              "      <td>-0.884677</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>loan_total</th>\n",
              "      <td>0.071474</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.280431</td>\n",
              "      <td>0.097083</td>\n",
              "      <td>-0.472674</td>\n",
              "      <td>-0.148343</td>\n",
              "      <td>0.057189</td>\n",
              "      <td>0.091839</td>\n",
              "      <td>-0.280431</td>\n",
              "      <td>-0.280431</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>default_total</th>\n",
              "      <td>-0.884677</td>\n",
              "      <td>-0.280431</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.872398</td>\n",
              "      <td>-0.418804</td>\n",
              "      <td>-0.699679</td>\n",
              "      <td>-0.763114</td>\n",
              "      <td>0.857459</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dti</th>\n",
              "      <td>-0.919147</td>\n",
              "      <td>0.097083</td>\n",
              "      <td>0.872398</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.715443</td>\n",
              "      <td>-0.861145</td>\n",
              "      <td>-0.827226</td>\n",
              "      <td>0.954075</td>\n",
              "      <td>0.872398</td>\n",
              "      <td>0.872398</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>avg_loan_amnt</th>\n",
              "      <td>0.680018</td>\n",
              "      <td>-0.472674</td>\n",
              "      <td>-0.418804</td>\n",
              "      <td>-0.715443</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.754054</td>\n",
              "      <td>0.550918</td>\n",
              "      <td>-0.801464</td>\n",
              "      <td>-0.418804</td>\n",
              "      <td>-0.418804</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>median_annual_inc</th>\n",
              "      <td>0.828385</td>\n",
              "      <td>-0.148343</td>\n",
              "      <td>-0.699679</td>\n",
              "      <td>-0.861145</td>\n",
              "      <td>0.754054</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.931928</td>\n",
              "      <td>-0.874371</td>\n",
              "      <td>-0.699679</td>\n",
              "      <td>-0.699679</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>avg_annual_inc</th>\n",
              "      <td>0.824738</td>\n",
              "      <td>0.057189</td>\n",
              "      <td>-0.763114</td>\n",
              "      <td>-0.827226</td>\n",
              "      <td>0.550918</td>\n",
              "      <td>0.931928</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.822662</td>\n",
              "      <td>-0.763114</td>\n",
              "      <td>-0.763114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>int_rate</th>\n",
              "      <td>-0.975022</td>\n",
              "      <td>0.091839</td>\n",
              "      <td>0.857459</td>\n",
              "      <td>0.954075</td>\n",
              "      <td>-0.801464</td>\n",
              "      <td>-0.874371</td>\n",
              "      <td>-0.822662</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.857459</td>\n",
              "      <td>0.857459</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>default_rate</th>\n",
              "      <td>-0.884677</td>\n",
              "      <td>-0.280431</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.872398</td>\n",
              "      <td>-0.418804</td>\n",
              "      <td>-0.699679</td>\n",
              "      <td>-0.763114</td>\n",
              "      <td>0.857459</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>actual_default_rate</th>\n",
              "      <td>-0.884677</td>\n",
              "      <td>-0.280431</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.872398</td>\n",
              "      <td>-0.418804</td>\n",
              "      <td>-0.699679</td>\n",
              "      <td>-0.763114</td>\n",
              "      <td>0.857459</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     fico_score  loan_total  ...  default_rate  actual_default_rate\n",
              "fico_score             1.000000    0.071474  ...     -0.884677            -0.884677\n",
              "loan_total             0.071474    1.000000  ...     -0.280431            -0.280431\n",
              "default_total         -0.884677   -0.280431  ...      1.000000             1.000000\n",
              "dti                   -0.919147    0.097083  ...      0.872398             0.872398\n",
              "avg_loan_amnt          0.680018   -0.472674  ...     -0.418804            -0.418804\n",
              "median_annual_inc      0.828385   -0.148343  ...     -0.699679            -0.699679\n",
              "avg_annual_inc         0.824738    0.057189  ...     -0.763114            -0.763114\n",
              "int_rate              -0.975022    0.091839  ...      0.857459             0.857459\n",
              "default_rate          -0.884677   -0.280431  ...      1.000000             1.000000\n",
              "actual_default_rate   -0.884677   -0.280431  ...      1.000000             1.000000\n",
              "\n",
              "[10 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7aW-NYQnQHP7"
      },
      "source": [
        "-------------------------"
      ]
    }
  ]
}