Sharukh_Shaikh.ipynb

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  "metadata": {
    "colab": {
      "name": "LendingCaseStudy_SharukhShaikh.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eQMj9FSPfBEw",
        "colab_type": "text"
      },
      "source": [
        "#Table of Contents\n",
        "\n",
        "\n",
        "1.   [Data Cleaning](#Data-Cleaning)\n",
        "2.   [Univariate Analysis](#Univariate-Analysis)\n",
        "3.   [Bivariate/Multivariate Analysis](#Bivariate)\n",
        "4.   [Analysing driver variables for loan defaulters](#drivervariables)\n",
        "5.   [Conclusion](#conclusion)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9BHsFfOqf7mj",
        "colab_type": "text"
      },
      "source": [
        "#Data Cleaning <a class=\"anchor\" id=\"Data-Cleaning\"></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AbSPjaZ8fz1N",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#loading Libraries\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from scipy import stats\n",
        "from scipy.stats import norm\n",
        "\n",
        "\n",
        "\n",
        "loan_df=pd.read_csv('loan.csv',encoding = \"palmos\",low_memory=False)\n",
        "\n",
        "\n",
        "#initial Configuration\n",
        "pd.options.display.float_format = '{:.4f}'.format #set it to convert scientific noations such as 4.225108e+11 to 422510842796.00\n",
        "pd.set_option('display.max_columns', 100) # to display all the columns\n"
      ],
      "execution_count": 77,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YhwpXuHJP363",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "outputId": "bcafff61-c6ea-422a-d1fd-8001458f87bd"
      },
      "source": [
        "loan_df.info()"
      ],
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 39717 entries, 0 to 39716\n",
            "Columns: 111 entries, id to total_il_high_credit_limit\n",
            "dtypes: float64(74), int64(13), object(24)\n",
            "memory usage: 33.6+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MHqNaIJrcKW4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 695
        },
        "outputId": "b2e1e51a-d1e1-40e2-e9e4-7583f5228d52"
      },
      "source": [
        "loan_df.head()"
      ],
      "execution_count": 79,
      "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",
              "\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>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>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>total_pymnt</th>\n",
              "      <th>total_pymnt_inv</th>\n",
              "      <th>total_rec_prncp</th>\n",
              "      <th>total_rec_int</th>\n",
              "      <th>total_rec_late_fee</th>\n",
              "      <th>recoveries</th>\n",
              "      <th>collection_recovery_fee</th>\n",
              "      <th>last_pymnt_d</th>\n",
              "      <th>last_pymnt_amnt</th>\n",
              "      <th>next_pymnt_d</th>\n",
              "      <th>last_credit_pull_d</th>\n",
              "      <th>collections_12_mths_ex_med</th>\n",
              "      <th>...</th>\n",
              "      <th>open_il_12m</th>\n",
              "      <th>open_il_24m</th>\n",
              "      <th>mths_since_rcnt_il</th>\n",
              "      <th>total_bal_il</th>\n",
              "      <th>il_util</th>\n",
              "      <th>open_rv_12m</th>\n",
              "      <th>open_rv_24m</th>\n",
              "      <th>max_bal_bc</th>\n",
              "      <th>all_util</th>\n",
              "      <th>total_rev_hi_lim</th>\n",
              "      <th>inq_fi</th>\n",
              "      <th>total_cu_tl</th>\n",
              "      <th>inq_last_12m</th>\n",
              "      <th>acc_open_past_24mths</th>\n",
              "      <th>avg_cur_bal</th>\n",
              "      <th>bc_open_to_buy</th>\n",
              "      <th>bc_util</th>\n",
              "      <th>chargeoff_within_12_mths</th>\n",
              "      <th>delinq_amnt</th>\n",
              "      <th>mo_sin_old_il_acct</th>\n",
              "      <th>mo_sin_old_rev_tl_op</th>\n",
              "      <th>mo_sin_rcnt_rev_tl_op</th>\n",
              "      <th>mo_sin_rcnt_tl</th>\n",
              "      <th>mort_acc</th>\n",
              "      <th>mths_since_recent_bc</th>\n",
              "      <th>mths_since_recent_bc_dlq</th>\n",
              "      <th>mths_since_recent_inq</th>\n",
              "      <th>mths_since_recent_revol_delinq</th>\n",
              "      <th>num_accts_ever_120_pd</th>\n",
              "      <th>num_actv_bc_tl</th>\n",
              "      <th>num_actv_rev_tl</th>\n",
              "      <th>num_bc_sats</th>\n",
              "      <th>num_bc_tl</th>\n",
              "      <th>num_il_tl</th>\n",
              "      <th>num_op_rev_tl</th>\n",
              "      <th>num_rev_accts</th>\n",
              "      <th>num_rev_tl_bal_gt_0</th>\n",
              "      <th>num_sats</th>\n",
              "      <th>num_tl_120dpd_2m</th>\n",
              "      <th>num_tl_30dpd</th>\n",
              "      <th>num_tl_90g_dpd_24m</th>\n",
              "      <th>num_tl_op_past_12m</th>\n",
              "      <th>pct_tl_nvr_dlq</th>\n",
              "      <th>percent_bc_gt_75</th>\n",
              "      <th>pub_rec_bankruptcies</th>\n",
              "      <th>tax_liens</th>\n",
              "      <th>tot_hi_cred_lim</th>\n",
              "      <th>total_bal_ex_mort</th>\n",
              "      <th>total_bc_limit</th>\n",
              "      <th>total_il_high_credit_limit</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1077501</td>\n",
              "      <td>1296599</td>\n",
              "      <td>5000</td>\n",
              "      <td>5000</td>\n",
              "      <td>4975.0000</td>\n",
              "      <td>36 months</td>\n",
              "      <td>10.65%</td>\n",
              "      <td>162.8700</td>\n",
              "      <td>B</td>\n",
              "      <td>B2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>RENT</td>\n",
              "      <td>24000.0000</td>\n",
              "      <td>Verified</td>\n",
              "      <td>Dec-11</td>\n",
              "      <td>Fully Paid</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>Borrower added on 12/22/11 &gt; I need to upgra...</td>\n",
              "      <td>credit_card</td>\n",
              "      <td>Computer</td>\n",
              "      <td>860xx</td>\n",
              "      <td>AZ</td>\n",
              "      <td>27.6500</td>\n",
              "      <td>0</td>\n",
              "      <td>Jan-85</td>\n",
              "      <td>1</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>13648</td>\n",
              "      <td>83.70%</td>\n",
              "      <td>9</td>\n",
              "      <td>f</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>5863.1552</td>\n",
              "      <td>5833.8400</td>\n",
              "      <td>5000.0000</td>\n",
              "      <td>863.1600</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>Jan-15</td>\n",
              "      <td>171.6200</td>\n",
              "      <td>NaN</td>\n",
              "      <td>May-16</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>...</td>\n",
              "      <td>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>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>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>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>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1077430</td>\n",
              "      <td>1314167</td>\n",
              "      <td>2500</td>\n",
              "      <td>2500</td>\n",
              "      <td>2500.0000</td>\n",
              "      <td>60 months</td>\n",
              "      <td>15.27%</td>\n",
              "      <td>59.8300</td>\n",
              "      <td>C</td>\n",
              "      <td>C4</td>\n",
              "      <td>Ryder</td>\n",
              "      <td>&lt; 1 year</td>\n",
              "      <td>RENT</td>\n",
              "      <td>30000.0000</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>Dec-11</td>\n",
              "      <td>Charged Off</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>Borrower added on 12/22/11 &gt; I plan to use t...</td>\n",
              "      <td>car</td>\n",
              "      <td>bike</td>\n",
              "      <td>309xx</td>\n",
              "      <td>GA</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>Apr-99</td>\n",
              "      <td>5</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1687</td>\n",
              "      <td>9.40%</td>\n",
              "      <td>4</td>\n",
              "      <td>f</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>1008.7100</td>\n",
              "      <td>1008.7100</td>\n",
              "      <td>456.4600</td>\n",
              "      <td>435.1700</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>117.0800</td>\n",
              "      <td>1.1100</td>\n",
              "      <td>Apr-13</td>\n",
              "      <td>119.6600</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Sep-13</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>...</td>\n",
              "      <td>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>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>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>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>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1077175</td>\n",
              "      <td>1313524</td>\n",
              "      <td>2400</td>\n",
              "      <td>2400</td>\n",
              "      <td>2400.0000</td>\n",
              "      <td>36 months</td>\n",
              "      <td>15.96%</td>\n",
              "      <td>84.3300</td>\n",
              "      <td>C</td>\n",
              "      <td>C5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>RENT</td>\n",
              "      <td>12252.0000</td>\n",
              "      <td>Not Verified</td>\n",
              "      <td>Dec-11</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>small_business</td>\n",
              "      <td>real estate business</td>\n",
              "      <td>606xx</td>\n",
              "      <td>IL</td>\n",
              "      <td>8.7200</td>\n",
              "      <td>0</td>\n",
              "      <td>Nov-01</td>\n",
              "      <td>2</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>2956</td>\n",
              "      <td>98.50%</td>\n",
              "      <td>10</td>\n",
              "      <td>f</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>3005.6668</td>\n",
              "      <td>3005.6700</td>\n",
              "      <td>2400.0000</td>\n",
              "      <td>605.6700</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>Jun-14</td>\n",
              "      <td>649.9100</td>\n",
              "      <td>NaN</td>\n",
              "      <td>May-16</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>...</td>\n",
              "      <td>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>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>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>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>0.0000</td>\n",
              "      <td>0.0000</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>1076863</td>\n",
              "      <td>1277178</td>\n",
              "      <td>10000</td>\n",
              "      <td>10000</td>\n",
              "      <td>10000.0000</td>\n",
              "      <td>36 months</td>\n",
              "      <td>13.49%</td>\n",
              "      <td>339.3100</td>\n",
              "      <td>C</td>\n",
              "      <td>C1</td>\n",
              "      <td>AIR RESOURCES BOARD</td>\n",
              "      <td>10+ years</td>\n",
              "      <td>RENT</td>\n",
              "      <td>49200.0000</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>Dec-11</td>\n",
              "      <td>Fully Paid</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>Borrower added on 12/21/11 &gt; to pay for prop...</td>\n",
              "      <td>other</td>\n",
              "      <td>personel</td>\n",
              "      <td>917xx</td>\n",
              "      <td>CA</td>\n",
              "      <td>20.0000</td>\n",
              "      <td>0</td>\n",
              "      <td>Feb-96</td>\n",
              "      <td>1</td>\n",
              "      <td>35.0000</td>\n",
              "      <td>nan</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>5598</td>\n",
              "      <td>21%</td>\n",
              "      <td>37</td>\n",
              "      <td>f</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>12231.8900</td>\n",
              "      <td>12231.8900</td>\n",
              "      <td>10000.0000</td>\n",
              "      <td>2214.9200</td>\n",
              "      <td>16.9700</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>Jan-15</td>\n",
              "      <td>357.4800</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Apr-16</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>...</td>\n",
              "      <td>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>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>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>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>0.0000</td>\n",
              "      <td>0.0000</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>1075358</td>\n",
              "      <td>1311748</td>\n",
              "      <td>3000</td>\n",
              "      <td>3000</td>\n",
              "      <td>3000.0000</td>\n",
              "      <td>60 months</td>\n",
              "      <td>12.69%</td>\n",
              "      <td>67.7900</td>\n",
              "      <td>B</td>\n",
              "      <td>B5</td>\n",
              "      <td>University Medical Group</td>\n",
              "      <td>1 year</td>\n",
              "      <td>RENT</td>\n",
              "      <td>80000.0000</td>\n",
              "      <td>Source Verified</td>\n",
              "      <td>Dec-11</td>\n",
              "      <td>Current</td>\n",
              "      <td>n</td>\n",
              "      <td>https://lendingclub.com/browse/loanDetail.acti...</td>\n",
              "      <td>Borrower added on 12/21/11 &gt; I plan on combi...</td>\n",
              "      <td>other</td>\n",
              "      <td>Personal</td>\n",
              "      <td>972xx</td>\n",
              "      <td>OR</td>\n",
              "      <td>17.9400</td>\n",
              "      <td>0</td>\n",
              "      <td>Jan-96</td>\n",
              "      <td>0</td>\n",
              "      <td>38.0000</td>\n",
              "      <td>nan</td>\n",
              "      <td>15</td>\n",
              "      <td>0</td>\n",
              "      <td>27783</td>\n",
              "      <td>53.90%</td>\n",
              "      <td>38</td>\n",
              "      <td>f</td>\n",
              "      <td>524.0600</td>\n",
              "      <td>524.0600</td>\n",
              "      <td>3513.3300</td>\n",
              "      <td>3513.3300</td>\n",
              "      <td>2475.9400</td>\n",
              "      <td>1037.3900</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>May-16</td>\n",
              "      <td>67.7900</td>\n",
              "      <td>Jun-16</td>\n",
              "      <td>May-16</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>...</td>\n",
              "      <td>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>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>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>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>0.0000</td>\n",
              "      <td>0.0000</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 × 111 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        id  member_id  loan_amnt  funded_amnt  funded_amnt_inv        term  \\\n",
              "0  1077501    1296599       5000         5000        4975.0000   36 months   \n",
              "1  1077430    1314167       2500         2500        2500.0000   60 months   \n",
              "2  1077175    1313524       2400         2400        2400.0000   36 months   \n",
              "3  1076863    1277178      10000        10000       10000.0000   36 months   \n",
              "4  1075358    1311748       3000         3000        3000.0000   60 months   \n",
              "\n",
              "  int_rate  installment grade sub_grade                 emp_title emp_length  \\\n",
              "0   10.65%     162.8700     B        B2                       NaN  10+ years   \n",
              "1   15.27%      59.8300     C        C4                     Ryder   < 1 year   \n",
              "2   15.96%      84.3300     C        C5                       NaN  10+ years   \n",
              "3   13.49%     339.3100     C        C1       AIR RESOURCES BOARD  10+ years   \n",
              "4   12.69%      67.7900     B        B5  University Medical Group     1 year   \n",
              "\n",
              "  home_ownership  annual_inc verification_status issue_d  loan_status  \\\n",
              "0           RENT  24000.0000            Verified  Dec-11   Fully Paid   \n",
              "1           RENT  30000.0000     Source Verified  Dec-11  Charged Off   \n",
              "2           RENT  12252.0000        Not Verified  Dec-11   Fully Paid   \n",
              "3           RENT  49200.0000     Source Verified  Dec-11   Fully Paid   \n",
              "4           RENT  80000.0000     Source Verified  Dec-11      Current   \n",
              "\n",
              "  pymnt_plan                                                url  \\\n",
              "0          n  https://lendingclub.com/browse/loanDetail.acti...   \n",
              "1          n  https://lendingclub.com/browse/loanDetail.acti...   \n",
              "2          n  https://lendingclub.com/browse/loanDetail.acti...   \n",
              "3          n  https://lendingclub.com/browse/loanDetail.acti...   \n",
              "4          n  https://lendingclub.com/browse/loanDetail.acti...   \n",
              "\n",
              "                                                desc         purpose  \\\n",
              "0    Borrower added on 12/22/11 > I need to upgra...     credit_card   \n",
              "1    Borrower added on 12/22/11 > I plan to use t...             car   \n",
              "2                                                NaN  small_business   \n",
              "3    Borrower added on 12/21/11 > to pay for prop...           other   \n",
              "4    Borrower added on 12/21/11 > I plan on combi...           other   \n",
              "\n",
              "                  title zip_code addr_state     dti  delinq_2yrs  \\\n",
              "0              Computer    860xx         AZ 27.6500            0   \n",
              "1                  bike    309xx         GA  1.0000            0   \n",
              "2  real estate business    606xx         IL  8.7200            0   \n",
              "3              personel    917xx         CA 20.0000            0   \n",
              "4              Personal    972xx         OR 17.9400            0   \n",
              "\n",
              "  earliest_cr_line  inq_last_6mths  mths_since_last_delinq  \\\n",
              "0           Jan-85               1                     nan   \n",
              "1           Apr-99               5                     nan   \n",
              "2           Nov-01               2                     nan   \n",
              "3           Feb-96               1                 35.0000   \n",
              "4           Jan-96               0                 38.0000   \n",
              "\n",
              "   mths_since_last_record  open_acc  pub_rec  revol_bal revol_util  total_acc  \\\n",
              "0                     nan         3        0      13648     83.70%          9   \n",
              "1                     nan         3        0       1687      9.40%          4   \n",
              "2                     nan         2        0       2956     98.50%         10   \n",
              "3                     nan        10        0       5598        21%         37   \n",
              "4                     nan        15        0      27783     53.90%         38   \n",
              "\n",
              "  initial_list_status  out_prncp  out_prncp_inv  total_pymnt  total_pymnt_inv  \\\n",
              "0                   f     0.0000         0.0000    5863.1552        5833.8400   \n",
              "1                   f     0.0000         0.0000    1008.7100        1008.7100   \n",
              "2                   f     0.0000         0.0000    3005.6668        3005.6700   \n",
              "3                   f     0.0000         0.0000   12231.8900       12231.8900   \n",
              "4                   f   524.0600       524.0600    3513.3300        3513.3300   \n",
              "\n",
              "   total_rec_prncp  total_rec_int  total_rec_late_fee  recoveries  \\\n",
              "0        5000.0000       863.1600              0.0000      0.0000   \n",
              "1         456.4600       435.1700              0.0000    117.0800   \n",
              "2        2400.0000       605.6700              0.0000      0.0000   \n",
              "3       10000.0000      2214.9200             16.9700      0.0000   \n",
              "4        2475.9400      1037.3900              0.0000      0.0000   \n",
              "\n",
              "   collection_recovery_fee last_pymnt_d  last_pymnt_amnt next_pymnt_d  \\\n",
              "0                   0.0000       Jan-15         171.6200          NaN   \n",
              "1                   1.1100       Apr-13         119.6600          NaN   \n",
              "2                   0.0000       Jun-14         649.9100          NaN   \n",
              "3                   0.0000       Jan-15         357.4800          NaN   \n",
              "4                   0.0000       May-16          67.7900       Jun-16   \n",
              "\n",
              "  last_credit_pull_d  collections_12_mths_ex_med  ...  open_il_12m  \\\n",
              "0             May-16                      0.0000  ...          nan   \n",
              "1             Sep-13                      0.0000  ...          nan   \n",
              "2             May-16                      0.0000  ...          nan   \n",
              "3             Apr-16                      0.0000  ...          nan   \n",
              "4             May-16                      0.0000  ...          nan   \n",
              "\n",
              "   open_il_24m mths_since_rcnt_il  total_bal_il  il_util  open_rv_12m  \\\n",
              "0          nan                nan           nan      nan          nan   \n",
              "1          nan                nan           nan      nan          nan   \n",
              "2          nan                nan           nan      nan          nan   \n",
              "3          nan                nan           nan      nan          nan   \n",
              "4          nan                nan           nan      nan          nan   \n",
              "\n",
              "   open_rv_24m  max_bal_bc  all_util  total_rev_hi_lim  inq_fi  total_cu_tl  \\\n",
              "0          nan         nan       nan               nan     nan          nan   \n",
              "1          nan         nan       nan               nan     nan          nan   \n",
              "2          nan         nan       nan               nan     nan          nan   \n",
              "3          nan         nan       nan               nan     nan          nan   \n",
              "4          nan         nan       nan               nan     nan          nan   \n",
              "\n",
              "   inq_last_12m  acc_open_past_24mths  avg_cur_bal  bc_open_to_buy  bc_util  \\\n",
              "0           nan                   nan          nan             nan      nan   \n",
              "1           nan                   nan          nan             nan      nan   \n",
              "2           nan                   nan          nan             nan      nan   \n",
              "3           nan                   nan          nan             nan      nan   \n",
              "4           nan                   nan          nan             nan      nan   \n",
              "\n",
              "   chargeoff_within_12_mths  delinq_amnt  mo_sin_old_il_acct  \\\n",
              "0                    0.0000            0                 nan   \n",
              "1                    0.0000            0                 nan   \n",
              "2                    0.0000            0                 nan   \n",
              "3                    0.0000            0                 nan   \n",
              "4                    0.0000            0                 nan   \n",
              "\n",
              "   mo_sin_old_rev_tl_op  mo_sin_rcnt_rev_tl_op  mo_sin_rcnt_tl  mort_acc  \\\n",
              "0                   nan                    nan             nan       nan   \n",
              "1                   nan                    nan             nan       nan   \n",
              "2                   nan                    nan             nan       nan   \n",
              "3                   nan                    nan             nan       nan   \n",
              "4                   nan                    nan             nan       nan   \n",
              "\n",
              "   mths_since_recent_bc  mths_since_recent_bc_dlq  mths_since_recent_inq  \\\n",
              "0                   nan                       nan                    nan   \n",
              "1                   nan                       nan                    nan   \n",
              "2                   nan                       nan                    nan   \n",
              "3                   nan                       nan                    nan   \n",
              "4                   nan                       nan                    nan   \n",
              "\n",
              "   mths_since_recent_revol_delinq  num_accts_ever_120_pd  num_actv_bc_tl  \\\n",
              "0                             nan                    nan             nan   \n",
              "1                             nan                    nan             nan   \n",
              "2                             nan                    nan             nan   \n",
              "3                             nan                    nan             nan   \n",
              "4                             nan                    nan             nan   \n",
              "\n",
              "   num_actv_rev_tl  num_bc_sats  num_bc_tl  num_il_tl  num_op_rev_tl  \\\n",
              "0              nan          nan        nan        nan            nan   \n",
              "1              nan          nan        nan        nan            nan   \n",
              "2              nan          nan        nan        nan            nan   \n",
              "3              nan          nan        nan        nan            nan   \n",
              "4              nan          nan        nan        nan            nan   \n",
              "\n",
              "   num_rev_accts  num_rev_tl_bal_gt_0  num_sats  num_tl_120dpd_2m  \\\n",
              "0            nan                  nan       nan               nan   \n",
              "1            nan                  nan       nan               nan   \n",
              "2            nan                  nan       nan               nan   \n",
              "3            nan                  nan       nan               nan   \n",
              "4            nan                  nan       nan               nan   \n",
              "\n",
              "   num_tl_30dpd  num_tl_90g_dpd_24m  num_tl_op_past_12m  pct_tl_nvr_dlq  \\\n",
              "0           nan                 nan                 nan             nan   \n",
              "1           nan                 nan                 nan             nan   \n",
              "2           nan                 nan                 nan             nan   \n",
              "3           nan                 nan                 nan             nan   \n",
              "4           nan                 nan                 nan             nan   \n",
              "\n",
              "   percent_bc_gt_75  pub_rec_bankruptcies  tax_liens  tot_hi_cred_lim  \\\n",
              "0               nan                0.0000     0.0000              nan   \n",
              "1               nan                0.0000     0.0000              nan   \n",
              "2               nan                0.0000     0.0000              nan   \n",
              "3               nan                0.0000     0.0000              nan   \n",
              "4               nan                0.0000     0.0000              nan   \n",
              "\n",
              "   total_bal_ex_mort  total_bc_limit  total_il_high_credit_limit  \n",
              "0                nan             nan                         nan  \n",
              "1                nan             nan                         nan  \n",
              "2                nan             nan                         nan  \n",
              "3                nan             nan                         nan  \n",
              "4                nan             nan                         nan  \n",
              "\n",
              "[5 rows x 111 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L89D-wKAoaF1",
        "colab_type": "text"
      },
      "source": [
        "As there are too many columns for analysis, we will first try to reduce the number of columns so that only important columns are left for analysis"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AII4Efloaagp",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "561e9426-8bc3-4ffd-a8c1-fc99dfbc53fd"
      },
      "source": [
        "# find all the columns where the values are same for all rows\n",
        "for c in loan_df.columns:\n",
        " if len(loan_df[c].value_counts())<2:\n",
        "    print(c)\n",
        "\n",
        "#remove these columns as it as no influence on our analysis\n",
        "for c in loan_df.columns:\n",
        " if len(loan_df[c].value_counts())<2:\n",
        "    loan_df=loan_df.drop(columns=[c])\n",
        "\n",
        "loan_df.info()"
      ],
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "pymnt_plan\n",
            "initial_list_status\n",
            "collections_12_mths_ex_med\n",
            "mths_since_last_major_derog\n",
            "policy_code\n",
            "application_type\n",
            "annual_inc_joint\n",
            "dti_joint\n",
            "verification_status_joint\n",
            "acc_now_delinq\n",
            "tot_coll_amt\n",
            "tot_cur_bal\n",
            "open_acc_6m\n",
            "open_il_6m\n",
            "open_il_12m\n",
            "open_il_24m\n",
            "mths_since_rcnt_il\n",
            "total_bal_il\n",
            "il_util\n",
            "open_rv_12m\n",
            "open_rv_24m\n",
            "max_bal_bc\n",
            "all_util\n",
            "total_rev_hi_lim\n",
            "inq_fi\n",
            "total_cu_tl\n",
            "inq_last_12m\n",
            "acc_open_past_24mths\n",
            "avg_cur_bal\n",
            "bc_open_to_buy\n",
            "bc_util\n",
            "chargeoff_within_12_mths\n",
            "delinq_amnt\n",
            "mo_sin_old_il_acct\n",
            "mo_sin_old_rev_tl_op\n",
            "mo_sin_rcnt_rev_tl_op\n",
            "mo_sin_rcnt_tl\n",
            "mort_acc\n",
            "mths_since_recent_bc\n",
            "mths_since_recent_bc_dlq\n",
            "mths_since_recent_inq\n",
            "mths_since_recent_revol_delinq\n",
            "num_accts_ever_120_pd\n",
            "num_actv_bc_tl\n",
            "num_actv_rev_tl\n",
            "num_bc_sats\n",
            "num_bc_tl\n",
            "num_il_tl\n",
            "num_op_rev_tl\n",
            "num_rev_accts\n",
            "num_rev_tl_bal_gt_0\n",
            "num_sats\n",
            "num_tl_120dpd_2m\n",
            "num_tl_30dpd\n",
            "num_tl_90g_dpd_24m\n",
            "num_tl_op_past_12m\n",
            "pct_tl_nvr_dlq\n",
            "percent_bc_gt_75\n",
            "tax_liens\n",
            "tot_hi_cred_lim\n",
            "total_bal_ex_mort\n",
            "total_bc_limit\n",
            "total_il_high_credit_limit\n",
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 39717 entries, 0 to 39716\n",
            "Data columns (total 48 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   id                       39717 non-null  int64  \n",
            " 1   member_id                39717 non-null  int64  \n",
            " 2   loan_amnt                39717 non-null  int64  \n",
            " 3   funded_amnt              39717 non-null  int64  \n",
            " 4   funded_amnt_inv          39717 non-null  float64\n",
            " 5   term                     39717 non-null  object \n",
            " 6   int_rate                 39717 non-null  object \n",
            " 7   installment              39717 non-null  float64\n",
            " 8   grade                    39717 non-null  object \n",
            " 9   sub_grade                39717 non-null  object \n",
            " 10  emp_title                37258 non-null  object \n",
            " 11  emp_length               38642 non-null  object \n",
            " 12  home_ownership           39717 non-null  object \n",
            " 13  annual_inc               39717 non-null  float64\n",
            " 14  verification_status      39717 non-null  object \n",
            " 15  issue_d                  39717 non-null  object \n",
            " 16  loan_status              39717 non-null  object \n",
            " 17  url                      39717 non-null  object \n",
            " 18  desc                     26777 non-null  object \n",
            " 19  purpose                  39717 non-null  object \n",
            " 20  title                    39706 non-null  object \n",
            " 21  zip_code                 39717 non-null  object \n",
            " 22  addr_state               39717 non-null  object \n",
            " 23  dti                      39717 non-null  float64\n",
            " 24  delinq_2yrs              39717 non-null  int64  \n",
            " 25  earliest_cr_line         39717 non-null  object \n",
            " 26  inq_last_6mths           39717 non-null  int64  \n",
            " 27  mths_since_last_delinq   14035 non-null  float64\n",
            " 28  mths_since_last_record   2786 non-null   float64\n",
            " 29  open_acc                 39717 non-null  int64  \n",
            " 30  pub_rec                  39717 non-null  int64  \n",
            " 31  revol_bal                39717 non-null  int64  \n",
            " 32  revol_util               39667 non-null  object \n",
            " 33  total_acc                39717 non-null  int64  \n",
            " 34  out_prncp                39717 non-null  float64\n",
            " 35  out_prncp_inv            39717 non-null  float64\n",
            " 36  total_pymnt              39717 non-null  float64\n",
            " 37  total_pymnt_inv          39717 non-null  float64\n",
            " 38  total_rec_prncp          39717 non-null  float64\n",
            " 39  total_rec_int            39717 non-null  float64\n",
            " 40  total_rec_late_fee       39717 non-null  float64\n",
            " 41  recoveries               39717 non-null  float64\n",
            " 42  collection_recovery_fee  39717 non-null  float64\n",
            " 43  last_pymnt_d             39646 non-null  object \n",
            " 44  last_pymnt_amnt          39717 non-null  float64\n",
            " 45  next_pymnt_d             1140 non-null   object \n",
            " 46  last_credit_pull_d       39715 non-null  object \n",
            " 47  pub_rec_bankruptcies     39020 non-null  float64\n",
            "dtypes: float64(17), int64(10), object(21)\n",
            "memory usage: 14.5+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y-Yvke0fezY3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "e9aa8039-f165-4d75-906d-3be2097decd9"
      },
      "source": [
        "# now hecking columns with more than 90% if junk values and removing them \n",
        "for c in loan_df.columns:\n",
        "  percent=(loan_df[c].isna().sum()/len(loan_df[c]))*100\n",
        "  if percent>=90:\n",
        "    print(c,\" total junk values \",percent,\" : \",loan_df[c].isna().sum())\n",
        "    loan_df=loan_df.drop(columns=[c])\n",
        "\n",
        "#print(loan_df.info())"
      ],
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "mths_since_last_record  total junk values  92.98537150338646  :  36931\n",
            "next_pymnt_d  total junk values  97.12969257496789  :  38577\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3eC8uk-x2GlF",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "4709a94c-0b1a-4ce7-8e1d-0683904c8288"
      },
      "source": [
        "rows,cols = loan_df.shape\n",
        "len(loan_df.member_id.unique())==rows"
      ],
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uE_9igdkfPUW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#droping duplicate records\n",
        "loan_df=loan_df.drop_duplicates()\n",
        "\n",
        "\n",
        "#set id as unique id if it is unique\n",
        "rows,cols = loan_df.shape\n",
        "\n",
        "if (len(loan_df.id.unique())==rows):\n",
        "  loan_df.set_index('id', inplace=True)\n",
        "\n",
        "#removing unnecessary columns\n",
        "loan_df=loan_df.drop(columns=[\n",
        "                              'member_id',# We already have  unique ID so this one is no needed\n",
        "                              'url',# The URL does not gives any use full insight for analysis\n",
        "                              'zip_code',# This column cant be considered to decide if the loan should be approved or not                          \n",
        "                              \"emp_title\" # This column wont give direct relation to a loan defaulter\n",
        "                              ])\n",
        "\n",
        "#loan_df.info()"
      ],
      "execution_count": 83,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8vLfz35nwUF1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 731
        },
        "outputId": "b373ae63-a1e4-4663-9dfa-4643e88b5ebc"
      },
      "source": [
        "# summarise number of missing values again\n",
        "100*(loan_df.isnull().sum()/len(loan_df.index))"
      ],
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "loan_amnt                  0.0000\n",
              "funded_amnt                0.0000\n",
              "funded_amnt_inv            0.0000\n",
              "term                       0.0000\n",
              "int_rate                   0.0000\n",
              "installment                0.0000\n",
              "grade                      0.0000\n",
              "sub_grade                  0.0000\n",
              "emp_length                 2.7066\n",
              "home_ownership             0.0000\n",
              "annual_inc                 0.0000\n",
              "verification_status        0.0000\n",
              "issue_d                    0.0000\n",
              "loan_status                0.0000\n",
              "desc                      32.5805\n",
              "purpose                    0.0000\n",
              "title                      0.0277\n",
              "addr_state                 0.0000\n",
              "dti                        0.0000\n",
              "delinq_2yrs                0.0000\n",
              "earliest_cr_line           0.0000\n",
              "inq_last_6mths             0.0000\n",
              "mths_since_last_delinq    64.6625\n",
              "open_acc                   0.0000\n",
              "pub_rec                    0.0000\n",
              "revol_bal                  0.0000\n",
              "revol_util                 0.1259\n",
              "total_acc                  0.0000\n",
              "out_prncp                  0.0000\n",
              "out_prncp_inv              0.0000\n",
              "total_pymnt                0.0000\n",
              "total_pymnt_inv            0.0000\n",
              "total_rec_prncp            0.0000\n",
              "total_rec_int              0.0000\n",
              "total_rec_late_fee         0.0000\n",
              "recoveries                 0.0000\n",
              "collection_recovery_fee    0.0000\n",
              "last_pymnt_d               0.1788\n",
              "last_pymnt_amnt            0.0000\n",
              "last_credit_pull_d         0.0050\n",
              "pub_rec_bankruptcies       1.7549\n",
              "dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ft8ErJJXwaiC",
        "colab_type": "text"
      },
      "source": [
        "As you can see the columns desc and mths_since_last_delinq has lot of null values. <br>\n",
        "**desc** (Description) contains the comment the applicant had written while applying for the loan. While one can use this data to do sentiment analaysis but we dont have scope for that in our prresent scenario<br>\n",
        "**mths_since_last_delinq** contains number months passed since the person last fell into the 90 DPD group.There is an important reason we shouldn't use this column in analysis - since at the time of loan application, we will not have this data (it gets generated months after the loan has been approved), it cannot be used as a predictor of default at the time of loan approval."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QxjpeTxu-f09",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "c0767e4f-6051-4209-a399-9d30b20d114b"
      },
      "source": [
        "#rmoving those column\n",
        "loan_df= loan_df.drop(columns=['desc','mths_since_last_delinq'])\n",
        "\n",
        "# checking whether some rows have more than 3 missing values\n",
        "len(loan_df[loan_df.isnull().sum(axis=1) > 3].index)"
      ],
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SphAtdCn0DI1",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 799
        },
        "outputId": "ead4f3f4-ae50-43cf-c633-241fef9720fb"
      },
      "source": [
        "# now the data is enough sorted so that other types of cleaning can be done\n",
        "\n",
        "#converting percentage into float for interset rate\n",
        "fix=lambda x: float(x[:-1])\n",
        "loan_df.int_rate=loan_df.int_rate.apply(fix)\n",
        "\n",
        "#checking data type of columns\n",
        "loan_df.info()"
      ],
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 39717 entries, 1077501 to 87023\n",
            "Data columns (total 39 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   loan_amnt                39717 non-null  int64  \n",
            " 1   funded_amnt              39717 non-null  int64  \n",
            " 2   funded_amnt_inv          39717 non-null  float64\n",
            " 3   term                     39717 non-null  object \n",
            " 4   int_rate                 39717 non-null  float64\n",
            " 5   installment              39717 non-null  float64\n",
            " 6   grade                    39717 non-null  object \n",
            " 7   sub_grade                39717 non-null  object \n",
            " 8   emp_length               38642 non-null  object \n",
            " 9   home_ownership           39717 non-null  object \n",
            " 10  annual_inc               39717 non-null  float64\n",
            " 11  verification_status      39717 non-null  object \n",
            " 12  issue_d                  39717 non-null  object \n",
            " 13  loan_status              39717 non-null  object \n",
            " 14  purpose                  39717 non-null  object \n",
            " 15  title                    39706 non-null  object \n",
            " 16  addr_state               39717 non-null  object \n",
            " 17  dti                      39717 non-null  float64\n",
            " 18  delinq_2yrs              39717 non-null  int64  \n",
            " 19  earliest_cr_line         39717 non-null  object \n",
            " 20  inq_last_6mths           39717 non-null  int64  \n",
            " 21  open_acc                 39717 non-null  int64  \n",
            " 22  pub_rec                  39717 non-null  int64  \n",
            " 23  revol_bal                39717 non-null  int64  \n",
            " 24  revol_util               39667 non-null  object \n",
            " 25  total_acc                39717 non-null  int64  \n",
            " 26  out_prncp                39717 non-null  float64\n",
            " 27  out_prncp_inv            39717 non-null  float64\n",
            " 28  total_pymnt              39717 non-null  float64\n",
            " 29  total_pymnt_inv          39717 non-null  float64\n",
            " 30  total_rec_prncp          39717 non-null  float64\n",
            " 31  total_rec_int            39717 non-null  float64\n",
            " 32  total_rec_late_fee       39717 non-null  float64\n",
            " 33  recoveries               39717 non-null  float64\n",
            " 34  collection_recovery_fee  39717 non-null  float64\n",
            " 35  last_pymnt_d             39646 non-null  object \n",
            " 36  last_pymnt_amnt          39717 non-null  float64\n",
            " 37  last_credit_pull_d       39715 non-null  object \n",
            " 38  pub_rec_bankruptcies     39020 non-null  float64\n",
            "dtypes: float64(16), int64(8), object(15)\n",
            "memory usage: 12.1+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mzewZhcGcYXp",
        "colab_type": "text"
      },
      "source": [
        ""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gXT4VQLVHU_0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "outputId": "ef5b503d-31c0-445e-81d7-afb431c00cc4"
      },
      "source": [
        "#Employment Term : Remove 'n/a' value with '0'.\n",
        "\n",
        "print(loan_df.emp_length.unique())\n",
        "loan_df.emp_length.fillna('0',inplace=True)\n",
        "print(loan_df.emp_length.unique())\n",
        "loan_df.emp_length.value_counts()"
      ],
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "['10+ years' '< 1 year' '1 year' '3 years' '8 years' '9 years' '4 years'\n",
            " '5 years' '6 years' '2 years' '7 years' nan]\n",
            "['10+ years' '< 1 year' '1 year' '3 years' '8 years' '9 years' '4 years'\n",
            " '5 years' '6 years' '2 years' '7 years' '0']\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10+ years    8879\n",
              "< 1 year     4583\n",
              "2 years      4388\n",
              "3 years      4095\n",
              "4 years      3436\n",
              "5 years      3282\n",
              "1 year       3240\n",
              "6 years      2229\n",
              "7 years      1773\n",
              "8 years      1479\n",
              "9 years      1258\n",
              "0            1075\n",
              "Name: emp_length, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RPn6qhancv9b",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 799
        },
        "outputId": "a8a416d4-534d-4bdc-dbbf-0e33ed5127f5"
      },
      "source": [
        "#Cast all object variables to numeric\n",
        "numeric_columns = ['funded_amnt','funded_amnt_inv','installment','int_rate','annual_inc','dti']\n",
        "loan_df[numeric_columns] = loan_df[numeric_columns].apply(pd.to_numeric)\n",
        "loan_df.info()"
      ],
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 39717 entries, 1077501 to 87023\n",
            "Data columns (total 39 columns):\n",
            " #   Column                   Non-Null Count  Dtype  \n",
            "---  ------                   --------------  -----  \n",
            " 0   loan_amnt                39717 non-null  int64  \n",
            " 1   funded_amnt              39717 non-null  int64  \n",
            " 2   funded_amnt_inv          39717 non-null  float64\n",
            " 3   term                     39717 non-null  object \n",
            " 4   int_rate                 39717 non-null  float64\n",
            " 5   installment              39717 non-null  float64\n",
            " 6   grade                    39717 non-null  object \n",
            " 7   sub_grade                39717 non-null  object \n",
            " 8   emp_length               39717 non-null  object \n",
            " 9   home_ownership           39717 non-null  object \n",
            " 10  annual_inc               39717 non-null  float64\n",
            " 11  verification_status      39717 non-null  object \n",
            " 12  issue_d                  39717 non-null  object \n",
            " 13  loan_status              39717 non-null  object \n",
            " 14  purpose                  39717 non-null  object \n",
            " 15  title                    39706 non-null  object \n",
            " 16  addr_state               39717 non-null  object \n",
            " 17  dti                      39717 non-null  float64\n",
            " 18  delinq_2yrs              39717 non-null  int64  \n",
            " 19  earliest_cr_line         39717 non-null  object \n",
            " 20  inq_last_6mths           39717 non-null  int64  \n",
            " 21  open_acc                 39717 non-null  int64  \n",
            " 22  pub_rec                  39717 non-null  int64  \n",
            " 23  revol_bal                39717 non-null  int64  \n",
            " 24  revol_util               39667 non-null  object \n",
            " 25  total_acc                39717 non-null  int64  \n",
            " 26  out_prncp                39717 non-null  float64\n",
            " 27  out_prncp_inv            39717 non-null  float64\n",
            " 28  total_pymnt              39717 non-null  float64\n",
            " 29  total_pymnt_inv          39717 non-null  float64\n",
            " 30  total_rec_prncp          39717 non-null  float64\n",
            " 31  total_rec_int            39717 non-null  float64\n",
            " 32  total_rec_late_fee       39717 non-null  float64\n",
            " 33  recoveries               39717 non-null  float64\n",
            " 34  collection_recovery_fee  39717 non-null  float64\n",
            " 35  last_pymnt_d             39646 non-null  object \n",
            " 36  last_pymnt_amnt          39717 non-null  float64\n",
            " 37  last_credit_pull_d       39715 non-null  object \n",
            " 38  pub_rec_bankruptcies     39020 non-null  float64\n",
            "dtypes: float64(16), int64(8), object(15)\n",
            "memory usage: 12.1+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WOBIG3YmnUmi",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "loan_df.to_csv('./test.csv')"
      ],
      "execution_count": 89,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nzauEdD-j9op",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 697
        },
        "outputId": "06abcce1-6c3d-4e40-f7eb-314db5f71f39"
      },
      "source": [
        "\n",
        "\n",
        "#Cast all object variables to DATE\n",
        "date_columns = ['issue_d','last_pymnt_d','last_credit_pull_d','earliest_cr_line']\n",
        "loan_df[date_columns] = loan_df[date_columns].apply(lambda x:pd.to_datetime('01-'+x,format='%d-%b-%y'))\n",
        "\n",
        "#alternate method\n",
        "# import calendar\n",
        "# import datetime\n",
        "# a={v: k for k,v in enumerate(calendar.month_abbr)}\n",
        "# fix=lambda x: pd.to_datetime(datetime.datetime(int('20'+x.split('-')[1]), a[x.split('-')[0]], 1),format='%d-%b-%y')\n",
        "# fix=lambda x: pd.to_datetime('01-'+x,format='%d-%b-%y')\n",
        "\n",
        "\n",
        "loan_df.dtypes"
      ],
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "loan_amnt                           int64\n",
              "funded_amnt                         int64\n",
              "funded_amnt_inv                   float64\n",
              "term                               object\n",
              "int_rate                          float64\n",
              "installment                       float64\n",
              "grade                              object\n",
              "sub_grade                          object\n",
              "emp_length                         object\n",
              "home_ownership                     object\n",
              "annual_inc                        float64\n",
              "verification_status                object\n",
              "issue_d                    datetime64[ns]\n",
              "loan_status                        object\n",
              "purpose                            object\n",
              "title                              object\n",
              "addr_state                         object\n",
              "dti                               float64\n",
              "delinq_2yrs                         int64\n",
              "earliest_cr_line           datetime64[ns]\n",
              "inq_last_6mths                      int64\n",
              "open_acc                            int64\n",
              "pub_rec                             int64\n",
              "revol_bal                           int64\n",
              "revol_util                         object\n",
              "total_acc                           int64\n",
              "out_prncp                         float64\n",
              "out_prncp_inv                     float64\n",
              "total_pymnt                       float64\n",
              "total_pymnt_inv                   float64\n",
              "total_rec_prncp                   float64\n",
              "total_rec_int                     float64\n",
              "total_rec_late_fee                float64\n",
              "recoveries                        float64\n",
              "collection_recovery_fee           float64\n",
              "last_pymnt_d               datetime64[ns]\n",
              "last_pymnt_amnt                   float64\n",
              "last_credit_pull_d         datetime64[ns]\n",
              "pub_rec_bankruptcies              float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-4NlCpkbOAhd",
        "colab_type": "text"
      },
      "source": [
        "# Univariate Analysis <a class=\"anchor\" id=\"Univariate-Analysis\"></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "It6I6TQL34Q2",
        "colab_type": "text"
      },
      "source": [
        "As now the data is cleaned enough so we can begin with analysis "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D4Ks2y2P3a64",
        "colab_type": "text"
      },
      "source": [
        "## Numeric/Continues Analysis"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UxQ8j5x2chh5",
        "colab_type": "text"
      },
      "source": [
        "### Analysing Verification Status"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mhj6L-nE3-Tk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 453
        },
        "outputId": "0fd28ca5-38d9-46c2-8235-958f4def093a"
      },
      "source": [
        "print(loan_df.verification_status.value_counts())\n",
        "\n",
        "#after checking the column in dictionary it seems like the value Verified and Source Verified has the same meaning \n",
        "#hence replacing the value Source Verified with Verified\n",
        "loan_df[\"verification_status\"] = loan_df[\"verification_status\"].replace(\"Source Verified\",\"Verified\")\n",
        "\n",
        "\n",
        "\n",
        "loan_df.verification_status.value_counts().plot.bar(figsize=(5,5))"
      ],
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Not Verified       16921\n",
            "Verified           12809\n",
            "Source Verified     9987\n",
            "Name: verification_status, dtype: int64\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f92b768fa20>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 91
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 360x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KMt9PIPyYN3c",
        "colab_type": "text"
      },
      "source": [
        "**Insight:** Most of the accepted loan applicants have their source verified"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ld_JHieZcntC",
        "colab_type": "text"
      },
      "source": [
        "### Analysing loan status"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0wdrdP6q7i6t",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 592
        },
        "outputId": "44a85a91-33c4-4b8f-d3a8-3eab42387ac4"
      },
      "source": [
        "loan_df.loan_status.value_counts().plot.pie(figsize=(10,10))"
      ],
      "execution_count": 92,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f92b768fa90>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 92
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Myk41jYHYZWh",
        "colab_type": "text"
      },
      "source": [
        "**Insight:** Most of the loan applicants have fully paid their loan amount"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BGd8hFleYZFp",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 446
        },
        "outputId": "20fe8682-f1a2-4d4f-a2c2-b469371fc9e4"
      },
      "source": [
        "loan_df.loan_amnt.plot.box(figsize=(7,7))"
      ],
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f92b82eb320>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 93
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 504x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JgXZxGoXY5A7",
        "colab_type": "text"
      },
      "source": [
        "**Insight:** Most of the loan amount is distributed between 5k to 15k"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HPl3CyBXcsPa",
        "colab_type": "text"
      },
      "source": [
        "### Analysing loan interest rate"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jKqZcwHhfUmM",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 706
        },
        "outputId": "22ae715d-9637-4afc-e0eb-119536ae6130"
      },
      "source": [
        "plt.figure(figsize=(7,7))\n",
        "sns.distplot(loan_df.int_rate)\n",
        "#loan_df.int_rate.plot.hist(figsize=(7,7))\n",
        "plt.show()\n",
        "sns.boxplot(loan_df.int_rate)\n",
        "plt.show()"
      ],
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 504x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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5PKyJrc9/uPuwJJnZOZK+oeTZ9F/MbIOkc8rcxiQ95e6XT3JeoG44Z4zp4FUl/w9ZrUbC+1L65uCrKtzXHyVdaGaXS8n711pz/tcXgBhjWtgsaWe1F/BKufvflLzx9z4l78H7eMnV35P0rfQ0SIuSUG9MX/jbLamWn+4A6o4X8AAgAJ4ZA0AAvICHacXMHpN09rjNn3L3vc2YB6gXTlMAQACcpgCAAIgxAARAjAEgAGIMAAH8EzVPS43t4yAGAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kX19YAY5mJzk",
        "colab_type": "text"
      },
      "source": [
        "**Insight:** most of the interest rate is distributed approximately between 9% to 14%\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4mECS1bmcvse",
        "colab_type": "text"
      },
      "source": [
        "### Analysing annual income of all the applicants"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-bgLpFVx2AVA",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 440
        },
        "outputId": "596530bb-2f90-4ac5-bdff-81bba003b3f8"
      },
      "source": [
        "plt.figure(figsize=(7,7))\n",
        "# g=sns.distplot(loan_df.annual_inc)\n",
        "# g.set(ylabel='Annual Income    ( 1 Unit = 1M )')\n",
        "# plt.show()\n",
        "# s=sns.scatterplot(data=loan_df.annual_inc) \n",
        "loan_df.annual_inc.plot.box()\n",
        "plt.show()"
      ],
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 504x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "V8RU8PyW6Mcx",
        "colab_type": "text"
      },
      "source": [
        "As you can see there are few outliers (above 1.8 ) .Probably removing those outliers would provide safe analysys "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JNoNovVg7zZ3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 170
        },
        "outputId": "ea5dfc28-aebb-42ed-c9a6-b4c293da4411"
      },
      "source": [
        "loan_df.annual_inc.describe()"
      ],
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count     39717.0000\n",
              "mean      68968.9264\n",
              "std       63793.7658\n",
              "min        4000.0000\n",
              "25%       40404.0000\n",
              "50%       59000.0000\n",
              "75%       82300.0000\n",
              "max     6000000.0000\n",
              "Name: annual_inc, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 96
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W_YLzf1P6sG3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 721
        },
        "outputId": "691586aa-e494-4a51-b8ec-4891138f475a"
      },
      "source": [
        "limit=loan_df.annual_inc.quantile(0.98)\n",
        "print(limit)\n",
        "loan_df=loan_df[loan_df.annual_inc<=limit]\n",
        "g=sns.scatterplot(data=loan_df.annual_inc)\n",
        "g.set(ylabel='Annual Income')\n",
        "plt.show()\n",
        "plt.figure(figsize=(7,7))\n",
        "sns.boxplot(loan_df.annual_inc)\n",
        "plt.show()"
      ],
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "187000.0\n"
          ],
          "name": "stdout"
        },
        {
          "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"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 504x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e8x7LUMn-iMv",
        "colab_type": "text"
      },
      "source": [
        "Now the distribution is comparitively better <br>\n",
        "**Insight:** There were few outliers which are removed and most of the applicants have annual income between 40K to 80K"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WOupzNRLD2hM",
        "colab_type": "text"
      },
      "source": [
        "## Categorical Anaysis"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "A_PxpvUNcO0V",
        "colab_type": "text"
      },
      "source": [
        "### Analysing loan purpose"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nmEpndCMEdig",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 272
        },
        "outputId": "01d0efed-c3d6-416b-aa5a-c6137d1e54fa"
      },
      "source": [
        "loan_df.purpose.value_counts()  #.plot.bar()"
      ],
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "debt_consolidation    18356\n",
              "credit_card            5041\n",
              "other                  3913\n",
              "home_improvement       2835\n",
              "major_purchase         2143\n",
              "small_business         1771\n",
              "car                    1529\n",
              "wedding                 929\n",
              "medical                 671\n",
              "moving                  573\n",
              "vacation                378\n",
              "house                   367\n",
              "educational             319\n",
              "renewable_energy         98\n",
              "Name: purpose, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lYPefJEHEUW2",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 593
        },
        "outputId": "6d7123b5-9bc8-4683-b922-7db34e9fa296"
      },
      "source": [
        "plt.figure(figsize=(20,12))\n",
        "data=loan_df.purpose.value_counts()\n",
        "g=sns.barplot(x=data.index, y=data)\n",
        "g.set_title('Purpose Analysis',fontsize =25)\n",
        "g.set_xlabel(\"purpose\",fontsize=30,size=20)\n",
        "g.set_ylabel(\"count\",fontsize=20)\n",
        "plt.show()"
      ],
      "execution_count": 99,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x864 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mZqoW7T_IHVN",
        "colab_type": "text"
      },
      "source": [
        "**Insight:** Most of the applicants have took loan for payng their other loans (Debt Consolidation)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rIc6Jl84cXwQ",
        "colab_type": "text"
      },
      "source": [
        "### Analysing grades"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f57Qi6LzKtkG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 596
        },
        "outputId": "0049e4b3-bd73-447c-9ed6-b1e61f351ac4"
      },
      "source": [
        "plt.figure(figsize=(20,12))\n",
        "data=loan_df.grade.value_counts()\n",
        "g=sns.barplot(x=data.index, y=data,)\n",
        "g.set_title('Grade Analysis',fontsize =25)\n",
        "g.set_xlabel(\"Grade\",fontsize=30,size=20)\n",
        "g.set_ylabel(\"count\",fontsize=20)\n",
        "plt.show()"
      ],
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x864 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7vx8UhnwXCM5",
        "colab_type": "text"
      },
      "source": [
        "**Insight:** Most of the applicants have been assigned as grade B"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ag9RGFPQcb_Q",
        "colab_type": "text"
      },
      "source": [
        "### Analysing loan allocation as per the employment term"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dT0CHw8AFSpg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 639
        },
        "outputId": "f6e0ee2e-394b-448b-9c0c-1d7607622fe8"
      },
      "source": [
        "pv=pd.pivot_table(loan_df,values='loan_amnt',columns='emp_length',aggfunc='sum')\n",
        "plt.figure(figsize=(10,10))\n",
        "g=sns.barplot(data=pv)\n",
        "g.set_title('Loan allocation as per employment term',fontsize =25)\n",
        "g.set_xlabel(\"Employement term\",fontsize=30,size=20)\n",
        "g.set_ylabel(\"Loan Allocation\",fontsize=20)\n",
        "plt.show()"
      ],
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NzfIaDBmGtGJ",
        "colab_type": "text"
      },
      "source": [
        "**Insight:** Most of the loan amount is allocated to applicants having 10+ years of employment term.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_Pgrunh9XPda",
        "colab_type": "text"
      },
      "source": [
        "# Bivariate/Multivariate Analysis <a class=\"anchor\" id=\"Bivariate\"></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TbwOd2TyeTfV",
        "colab_type": "text"
      },
      "source": [
        "### Purpose of Loan vs Loan Amount by Loan Status"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aEjCNayAXlge",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 819
        },
        "outputId": "0ac67ffb-fbf2-49af-c30a-25d79027c966"
      },
      "source": [
        "plt.figure(figsize=(23,20))\n",
        "sns.boxplot(data =loan_df, x='purpose', y='loan_amnt', hue ='loan_status')\n",
        "plt.title('Purpose of Loan vs Loan Amount by Loan Status')\n",
        "plt.show()"
      ],
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1656x1440 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U72pWVbpehVa",
        "colab_type": "text"
      },
      "source": [
        "### Correlation Matrix : All Continuos(Numeric) Variables"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P2Rf2LvreskC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 348
        },
        "outputId": "09b26b10-655b-40cb-b512-7b678dfbfd53"
      },
      "source": [
        "# picking relevent (contineous variable) fields to check if they are corelated , \n",
        "col_for_corr = ['loan_amnt', 'funded_amnt', 'funded_amnt_inv','int_rate',\n",
        "                'installment','annual_inc', 'dti', 'out_prncp', 'out_prncp_inv',\n",
        "                'loan_amt_inc_ratio']\n",
        "loan_correlation = loan_df.filter(col_for_corr).corr()\n",
        "loan_correlation"
      ],
      "execution_count": 103,
      "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>loan_amnt</th>\n",
              "      <th>funded_amnt</th>\n",
              "      <th>funded_amnt_inv</th>\n",
              "      <th>int_rate</th>\n",
              "      <th>installment</th>\n",
              "      <th>annual_inc</th>\n",
              "      <th>dti</th>\n",
              "      <th>out_prncp</th>\n",
              "      <th>out_prncp_inv</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>loan_amnt</th>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9816</td>\n",
              "      <td>0.9397</td>\n",
              "      <td>0.3041</td>\n",
              "      <td>0.9297</td>\n",
              "      <td>0.4160</td>\n",
              "      <td>0.0812</td>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1967</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>funded_amnt</th>\n",
              "      <td>0.9816</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9580</td>\n",
              "      <td>0.3081</td>\n",
              "      <td>0.9556</td>\n",
              "      <td>0.4113</td>\n",
              "      <td>0.0810</td>\n",
              "      <td>0.1991</td>\n",
              "      <td>0.1988</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>funded_amnt_inv</th>\n",
              "      <td>0.9397</td>\n",
              "      <td>0.9580</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.3024</td>\n",
              "      <td>0.9037</td>\n",
              "      <td>0.3946</td>\n",
              "      <td>0.0891</td>\n",
              "      <td>0.2078</td>\n",
              "      <td>0.2078</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>int_rate</th>\n",
              "      <td>0.3041</td>\n",
              "      <td>0.3081</td>\n",
              "      <td>0.3024</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.2787</td>\n",
              "      <td>0.0697</td>\n",
              "      <td>0.1138</td>\n",
              "      <td>0.1339</td>\n",
              "      <td>0.1340</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>installment</th>\n",
              "      <td>0.9297</td>\n",
              "      <td>0.9556</td>\n",
              "      <td>0.9037</td>\n",
              "      <td>0.2787</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.4124</td>\n",
              "      <td>0.0695</td>\n",
              "      <td>0.1283</td>\n",
              "      <td>0.1282</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>annual_inc</th>\n",
              "      <td>0.4160</td>\n",
              "      <td>0.4113</td>\n",
              "      <td>0.3946</td>\n",
              "      <td>0.0697</td>\n",
              "      <td>0.4124</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>-0.0974</td>\n",
              "      <td>0.0668</td>\n",
              "      <td>0.0666</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dti</th>\n",
              "      <td>0.0812</td>\n",
              "      <td>0.0810</td>\n",
              "      <td>0.0891</td>\n",
              "      <td>0.1138</td>\n",
              "      <td>0.0695</td>\n",
              "      <td>-0.0974</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.0375</td>\n",
              "      <td>0.0374</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>out_prncp</th>\n",
              "      <td>0.1970</td>\n",
              "      <td>0.1991</td>\n",
              "      <td>0.2078</td>\n",
              "      <td>0.1339</td>\n",
              "      <td>0.1283</td>\n",
              "      <td>0.0668</td>\n",
              "      <td>0.0375</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>0.9998</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>out_prncp_inv</th>\n",
              "      <td>0.1967</td>\n",
              "      <td>0.1988</td>\n",
              "      <td>0.2078</td>\n",
              "      <td>0.1340</td>\n",
              "      <td>0.1282</td>\n",
              "      <td>0.0666</td>\n",
              "      <td>0.0374</td>\n",
              "      <td>0.9998</td>\n",
              "      <td>1.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                 loan_amnt  funded_amnt  funded_amnt_inv  int_rate  \\\n",
              "loan_amnt           1.0000       0.9816           0.9397    0.3041   \n",
              "funded_amnt         0.9816       1.0000           0.9580    0.3081   \n",
              "funded_amnt_inv     0.9397       0.9580           1.0000    0.3024   \n",
              "int_rate            0.3041       0.3081           0.3024    1.0000   \n",
              "installment         0.9297       0.9556           0.9037    0.2787   \n",
              "annual_inc          0.4160       0.4113           0.3946    0.0697   \n",
              "dti                 0.0812       0.0810           0.0891    0.1138   \n",
              "out_prncp           0.1970       0.1991           0.2078    0.1339   \n",
              "out_prncp_inv       0.1967       0.1988           0.2078    0.1340   \n",
              "\n",
              "                 installment  annual_inc     dti  out_prncp  out_prncp_inv  \n",
              "loan_amnt             0.9297      0.4160  0.0812     0.1970         0.1967  \n",
              "funded_amnt           0.9556      0.4113  0.0810     0.1991         0.1988  \n",
              "funded_amnt_inv       0.9037      0.3946  0.0891     0.2078         0.2078  \n",
              "int_rate              0.2787      0.0697  0.1138     0.1339         0.1340  \n",
              "installment           1.0000      0.4124  0.0695     0.1283         0.1282  \n",
              "annual_inc            0.4124      1.0000 -0.0974     0.0668         0.0666  \n",
              "dti                   0.0695     -0.0974  1.0000     0.0375         0.0374  \n",
              "out_prncp             0.1283      0.0668  0.0375     1.0000         0.9998  \n",
              "out_prncp_inv         0.1282      0.0666  0.0374     0.9998         1.0000  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 103
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mtuZIvLVe2gz",
        "colab_type": "text"
      },
      "source": [
        "### Heatmap of the correlation matrix"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2eQ12HuzfMb7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 618
        },
        "outputId": "604156a8-59ab-42a3-ea40-e8f213f46f7b"
      },
      "source": [
        "f, ax = plt.subplots(figsize=(14, 9))\n",
        "sns.heatmap(loan_correlation, \n",
        "            xticklabels=loan_correlation.columns.values,\n",
        "            yticklabels=loan_correlation.columns.values,annot= True)\n",
        "plt.show()"
      ],
      "execution_count": 104,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1008x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r1LuNdsfAHXB",
        "colab_type": "text"
      },
      "source": [
        "**Insight:** \n",
        "\n",
        "> From the heat map it is very clear that **annual income and Debt to Income (dti) is negatively corelated**. It makes sense becuase more income means less debt ration\n",
        "\n",
        "> It is also clear that **annual income and loan amount is positively corelated**. Becuase the more income an applicant has the more there is chance to pay off the loan.\n",
        "\n",
        "> One more factor to consider is **Intrest rate and loan amount is positively corelated**. The more the amount of the loan is the greater the interest would be.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NXEI6rycEk5m",
        "colab_type": "text"
      },
      "source": [
        "### Employment Length vs Loan Amount for different pupose of Loan"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HvxDguphC4v3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 905
        },
        "outputId": "f2156486-9251-4fac-82d6-5c116f8f68a8"
      },
      "source": [
        "# As there are few unrecognized categories such as other and none, we shall remove it.\n",
        "\n",
        "loan_df=loan_df[~loan_df.home_ownership.isin(['OTHER','NONE'])]\n",
        "plt.figure(figsize=(20,20))\n",
        "# as there is no estimator for count, using a lambda expression to achive this\n",
        "sns.barplot(y='emp_length', x='loan_amnt',hue=\"purpose\", data=loan_df,estimator=lambda x: len(x) )\n",
        "plt.show()"
      ],
      "execution_count": 105,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x1440 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NV6EiYif9Lo0",
        "colab_type": "text"
      },
      "source": [
        "# Analysing driver variables for loan defaulters <a class=\"anchor\" id=\"drivervariables\"></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Jh5R2Twe9W0S",
        "colab_type": "text"
      },
      "source": [
        "**Charge off**\n",
        "> By defination it means the business that gave you the loan, typically a Credit card company or retailer, has written off the amount owed as uncollectable, closed your account, and declared it a loss. \n",
        "<br>\n",
        "so basically Charged off applicants are the loan defaulters\n",
        "\n",
        "> To get the probability of getting a charged off applicant we can use a simple formula as below\n",
        "\n",
        "`Probability of Charged Off= No. of applicants who is charged off / total no. of applicants `\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3aJqM-LxM_QK",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Defining a function to provide us summary matrix with given column as parameter\n",
        "def summarytab(df,col):\n",
        "    '''\n",
        "    df : Dataframe\n",
        "    col: Column Name\n",
        "    '''\n",
        "    summarytab = pd.crosstab(df[col], df['loan_status'],margins=True)\n",
        "    summarytab['Probability_Charged Off'] = round((summarytab['Charged Off']/summarytab['All']),3)\n",
        "    summarytab = summarytab[0:-1]\n",
        "    return summarytab"
      ],
      "execution_count": 106,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SjPBhIpKNo4R",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Line bar chart for Probability of charge off\n",
        "def prob_chart(df,col,stacked= True,showtable=False):\n",
        "    # get dataframe from summarytab function\n",
        "    plotCrosstab = summarytab(df,col)\n",
        "    \n",
        "    if showtable:\n",
        "      display(plotCrosstab)\n",
        "\n",
        "    linePlot = plotCrosstab[['Probability_Charged Off']]      \n",
        "    barPlot =  plotCrosstab.iloc[:,0:2]\n",
        "    ax = linePlot.plot(figsize=(15,8), marker='o',color = 'b')\n",
        "    ax2 = barPlot.plot(kind='bar',ax = ax,rot=1,secondary_y=True,stacked=stacked)\n",
        "    ax.set_title(df[col].name.title()+' vs Probability Charge Off',fontsize=20,weight=\"bold\")\n",
        "    ax.set_xlabel(df[col].name.title(),fontsize=14)  \n",
        "    ax.set_ylabel('Probability of Charged off',color = 'b',fontsize=14)\n",
        "    ax2.set_ylabel('Number of Applicants',color = 'g',fontsize=14)\n",
        "    plt.show()"
      ],
      "execution_count": 107,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oK0hvsgyltl3",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Get slots arranged\n",
        "def slots(df,col):\n",
        "  labels = ['Very Low', 'Low', 'Medium', 'High', 'Very High']\n",
        "  qnty=list(round(df[col].quantile([0,0.2,0.4,0.6,0.8,1])))\n",
        "  for x in range(len(labels)):\n",
        "    labels[x]=labels[x]+\" \"+\"(.aprx \"+str(qnty[x])+\")\"\n",
        "  return labels;"
      ],
      "execution_count": 108,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WnuHpWXpnJcH",
        "colab_type": "text"
      },
      "source": [
        "### understanding the impact of Grades on loan defualter"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "feuuSAUglbZZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "d94dbf65-1f6c-4e19-e805-a10409ee3c74"
      },
      "source": [
        "prob_chart(loan_df,\"grade\",showtable=True)\n",
        "prob_chart(loan_df,\"sub_grade\")"
      ],
      "execution_count": 109,
      "outputs": [
        {
          "output_type": "display_data",
          "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>loan_status</th>\n",
              "      <th>Charged Off</th>\n",
              "      <th>Current</th>\n",
              "      <th>Fully Paid</th>\n",
              "      <th>All</th>\n",
              "      <th>Probability_Charged Off</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>grade</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>A</th>\n",
              "      <td>598</td>\n",
              "      <td>40</td>\n",
              "      <td>9282</td>\n",
              "      <td>9920</td>\n",
              "      <td>0.0600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>B</th>\n",
              "      <td>1399</td>\n",
              "      <td>341</td>\n",
              "      <td>10020</td>\n",
              "      <td>11760</td>\n",
              "      <td>0.1190</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>C</th>\n",
              "      <td>1336</td>\n",
              "      <td>261</td>\n",
              "      <td>6324</td>\n",
              "      <td>7921</td>\n",
              "      <td>0.1690</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>D</th>\n",
              "      <td>1100</td>\n",
              "      <td>216</td>\n",
              "      <td>3861</td>\n",
              "      <td>5177</td>\n",
              "      <td>0.2120</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>E</th>\n",
              "      <td>695</td>\n",
              "      <td>173</td>\n",
              "      <td>1877</td>\n",
              "      <td>2745</td>\n",
              "      <td>0.2530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F</th>\n",
              "      <td>307</td>\n",
              "      <td>69</td>\n",
              "      <td>626</td>\n",
              "      <td>1002</td>\n",
              "      <td>0.3060</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>G</th>\n",
              "      <td>97</td>\n",
              "      <td>16</td>\n",
              "      <td>187</td>\n",
              "      <td>300</td>\n",
              "      <td>0.3230</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "loan_status  Charged Off  Current  Fully Paid    All  Probability_Charged Off\n",
              "grade                                                                        \n",
              "A                    598       40        9282   9920                   0.0600\n",
              "B                   1399      341       10020  11760                   0.1190\n",
              "C                   1336      261        6324   7921                   0.1690\n",
              "D                   1100      216        3861   5177                   0.2120\n",
              "E                    695      173        1877   2745                   0.2530\n",
              "F                    307       69         626   1002                   0.3060\n",
              "G                     97       16         187    300                   0.3230"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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xvmy+Vh0jtDE/wn7Vs3HuvUDzHLxHwWP75aDPWb5Hof3aksGK14HtDUIrH4eO6RRW/1kGx+0C4vPgMzEim+dbARyXST8zbDPsNZkdqJsdVhfHkfdeTdlaRnh9w6/rd6BsLr+z/TnyfsORtn7ZvJbMXp/we+OmbCm3+cmozQy/n2H7ZXSf2u3Al4HnG8OOy859ajP9zGfQn0GkX5k6o218pPcvs9c5p6+NNm3atBWkTcOPRaRAc35uZiz+Fh2f4LOKicBB4Bf8H5YvAn/GzwvMafsb8AvNfIQP5PYBC/AZwNczOe6P0HF/xy/ichCfORpO+mxnpGMn4OevvoDPnu3Fr+r7O37I49/xWcU5ObyWOfg/pIMiZdt2AbfhF29agX8dk/DXvhafoWrh/AJUBYJz7kugEf5+qwn4oCkJv1jPf4CezrmrXebzBx/Grwi9CJ813Imfa9zGOZcQOFeuPhMRXIj/PKzHfz5+wr/nHUOfn2PGObcCvxjYQnz/s/L3sOeTnXMHIu6Z9bkn4Bcruhc/z/Zn/PUn4kceTMHPU56am/bD3I4PPL/DZ1B/wg+nPgf/GTkqzrnH8SMvlpK26NJb+PvNBt/DHWHHbcTfOmsoPpDcjv+Op3zHpgA3AXfmsD9j8D+6PIL/b9/v+O/BH/j/lozF/2gxILfvn4hIYWTOuWj3QURERKLIzCrhb/OUMjc83mV866Viw8zKubT51MHyU/FDjFNu7TXWOXdr+H4iIpI/NKdWRESkmDKzTvi5rwNIC2g/V0Cb6iEzOwd4F39rqsP4ee+DSAtok/AZeBERiRIFtSIiIsXXrLDnieRwSGwRZ/j53G0zqN8H3OicW51/XRIRkXAKakVERGQXsAR4yDm3LNqdKUDeB07Gr1ZcE6iAn6v7LX5BuJedc99Hr3siIgKaUysiIiIiIiKFmFY/FhERERERkUKryA4/LlGihCtXrly0uyEiIiIiIhIV+/btc865Ip/ILLJBbbly5di7d2+0uyEiIiIiIhIVZnbEbcmKoiIftYuIiIiIiEjRpaBWRERERERECi0FtSIiIiIiIlJoFdk5tZEcOnSIzZs3c+DAgWh3RYqwsmXLUqtWLUqVKhXtroiIiIiIFHnFKqjdvHkzlSpVIjY2FjOLdnekCHLOsX37djZv3kydOnWi3R0RERERkSKvWA0/PnDgANWqVVNAK8eMmVGtWjWNBhARERERySfFKqgFFNDKMafPmIiIiIhI/il2Qa2IiIiIiIgUHQpqC6GKFStG7dyzZ89m/vz5ebafiIiIiIjI0VBQKzmioFZERERERAoSBbWFmHOOu+++m8aNGxMXF8fUqVMB2LNnD+effz7NmzcnLi6O9957D4BNmzbRoEEDBgwYQKNGjejSpQv79+/PsP3nn3+ehg0b0qRJE3r37s2mTZsYO3Yszz33HPHx8XzxxRf85z//oU2bNjRr1ozOnTuzbdu2iPv169ePadOmpbadkm3eunUrHTt2JD4+nsaNG/PFF18cw1dMRERERESKmmJ1S5+i5p133iEhIYHly5fz22+/0apVKzp27EiNGjWYPn06xx13HL/99htnnXUW3bt3B+Dbb7/lzTffZPz48Vx55ZW8/fbbXHPNNRHbHzVqFN999x1lypRh586dVKlShYEDB1KxYkXuuusuAHbs2MGCBQswM1599VWefPJJnnnmmSP2mzBhQsRzvPHGG3Tt2pUHHniAw4cPs2/fvmPwSomIiIiISFGloLYQmzt3Ln369CEmJoaaNWtyzjnnsGjRIi688ELuv/9+5syZQ4kSJdiyZQvbtm0DoE6dOsTHxwPQokULNm3alGH7TZo0oW/fvvTo0YMePXpE3Gfz5s1cddVVbN26lYMHD+b43qytWrXixhtv5NChQ/To0SO1byIiIiIiItmh4cdF0OTJk/n1119ZsmQJCQkJ1KxZM/W+qWXKlEndLyYmhqSkpAzb+eCDDxg0aBBLly6lVatWEfcdMmQIgwcPZsWKFbzyyisZ3p+1ZMmSJCcnA5CcnMzBgwcB6NixI3PmzOHkk0+mX79+vP7667m+bhERERERyRkze83MfjGzlYGyqWaWENo2mVlCqDzWzPYH6sYGjmlhZivMbL2ZPW/5eJ9LBbWFWIcOHZg6dSqHDx/m119/Zc6cObRu3Zpdu3ZxwgknUKpUKWbNmsX333+f47aTk5P58ccfOffcc3niiSfYtWsXe/bsoVKlSuzevTt1v127dnHyyScDMGnSpNTy8P1iY2NZsmQJADNmzODQoUMAfP/999SsWZMBAwZw0003sXTp0ly9FiIiIiIikisTgW7BAufcVc65eOdcPPA28E6gekNKnXNuYKD8ZWAAUC+0pWvzWFJQW4j17NmTJk2a0LRpU8477zyefPJJTjzxRPr27cvixYuJi4vj9ddf58wzz8xx24cPH+aaa64hLi6OZs2acfvtt1OlShUuvfRSpk+fnroA1IgRI+jVqxctWrSgevXqqceH7zdgwAA+//xzmjZtypdffkmFChUAv0py06ZNadasGVOnTmXo0KF59vqIiIiIiKSYPBliY6FECf/v5MnR7lHB4JybA/weqS6Ubb0SeDOzNszsT8BxzrkFzjkHvA5Enr94DJg/Z9FToUIFt3fv3nRl33zzDQ0aNIhSj6Q40WdNREREpOCYPBluvhmCa5KWLw/jxkHfvtHr17FmZgeBFYGicc65cRH2iwXed841DivvCDzrnGsZ2G8VsA74A3jQOfeFmbUERjnnOof26wDc65y7JK+vKRItFCUiIiIiIkWKc7B5MyxcCF99Bc8/D4mJ6ffZtw8eeKBoB7VAUkpAmkt9SJ+l3Qqc6pzbbmYtgHfNrNFR9TAPKKgVBg0axLx589KVDR06lBtuuCFKPSrARlTO1m5FJkc7Yle0eyAiIiKSpT/+gMWL04LYhQth61ZfV7o0hNYoPcIPP+RfHwsbMysJXAa0SClzziUCiaHHS8xsA3AGsAWoFTi8VqgsXyioFcaMGRPtLoiIiIiIZEtSEqxc6QPXlO2bb3x2FuCMM+D886FNG781aQL160OktVNPPTV/+17IdAbWOOc2pxSYWQ3gd+fcYTM7Db8g1Ebn3O9m9oeZnQUsBK4DXsivjiqoFRERERGRAsk5n01Nyb4uXAhLlsD+/b6+enUfuF51lf+3VSs4/vgj23nsschzah97LH+uoyAzszeBTkB1M9sMDHfOTQB6c+QCUR2Bh83sEJAMDHTOpSwydRt+JeVywEehLV8oqBURERERkQJh1y5YtCj9MOJt23xdmTLQvDnccgu0bu2D2Dp1IDt3Q02ZN/vAAz5IPvVUH9AW8fm02eKc65NBeb8IZW/jb/ETaf/FQONIdceagloREREREcl3hw7BihXphxGvWZNWf+aZ0LVr2jDiuDg/Pza3+vZVEFtUKagVEREREZFjyjnYtCl9BnbpUjhwwNefcIIPXPv2TRtGXKVKVLsshUiJaHegIDsWN2iOiYkhPj6exo0b06tXL/YFB/ZnYeLEiQwePDhH56tYsWLE8oceeoiZM2cC0KlTJxYvXgzARRddxM6dO9m5cycvvfRSjs4V9NVXX9GxY0fq169Ps2bNuOmmm9i3bx8jRozg6aefznW7eSE2NpbffvvtiPJdu3Zx3XXXcfrpp1O3bl2uu+46du1KW/337rvvzs9uioiIiBRaO3bAJ5/AI4/ApZdCzZpw2mnQpw+8/LIfMnzbbTBlCnz3Hfz8M8yYAQ8+CBdcoIBWckZBbQZSbtD8/ff+l6Xvv/fPjzawLVeuHAkJCaxcuZLSpUszduzYdPVJSUlHd4Jsevjhh+ncufMR5R9++CFVqlQ5qqB227Zt9OrViyeeeIK1a9eybNkyunXrxu7du4+22xw+fPio28hI//79Oe2001i/fj0bNmygTp063HTTTan148YdcZ9qERERkWLv4EE/D3bMGLjuOr/S8PHH+6HDw4fDhg1w8cU+mF261N9+Z+5ceOYZv8BTbGz25sWKZKTYDj++4w5ISMi4fsGCyDdo7t8fxo+PfEx8PIwenf0+dOjQga+//prZs2fzt7/9japVq7JmzRq+/vprbr31VhYvXkzJkiV59tlnOffccwH48ccf6dSpE1u2bOGaa65h+PDhAPTo0YMff/yRAwcOMHToUG6++ebU89x555188sknnHjiiUyZMoUaNWrQr18/LrnkEq644op0fYqNjWXx4sUMGzaMDRs2EB8fzwUXXMC2bdu47LLL6NGjBwB9+/blyiuv5M9//vMR1zVmzBiuv/562rZtm1oWPM/q1avp1KkTP/zwA3fccQe33357ptdQsWJFbrnlFmbOnMmYMWNYu3YtTzzxBFWqVKFp06aUKVOGF198kV9//ZWBAwfyQ+iGY6NHj6Zdu3Zs376dPn36sGXLFtq2bYtLWe89YP369SxZsoSpU6emlj300EOcfvrpbNiwgTvvvJM9e/YAkTPfIiIiIsWBc7BxY/phxMuWpf3dfOKJfvjw9df7f1u2hMqVo9tnKfqKbVCblfCANqvynEpKSuKjjz6iW7duACxdupSVK1dSp04dnnnmGcyMFStWsGbNGrp06cK6desAP6x35cqVlC9fnlatWnHxxRfTsmVLXnvtNY4//nj2799Pq1atuPzyy6lWrRp79+6lZcuWPPfcczz88MOMHDmSF198Mcv+jRo1ipUrV5IQivw///xznnvuOXr06MGuXbuYP38+kyZNinjsypUruf766zNse82aNcyaNYvdu3dTv359br31VkqVKpXpNbRp04ZnnnmGn376iWuuuYalS5dSqVIlzjvvPJo2bQrA0KFDufPOO2nfvj0//PADXbt25ZtvvmHkyJG0b9+ehx56iA8++IAJEyYc0afVq1cTHx9PTExMalnKUPFVq1YxY8aMDIdyi4iIiBRVv/+eFrx+9ZXfUmZxlS8PLVrAkCFpqxGfcoqyrpL/im1Qm1VGNTY28g2aa9eG2bNzf979+/cTHx8P+Ext//79mT9/Pq1bt6ZOnToAzJ07lyFDhgBw5plnUrt27dSg9oILLqBatWoAXHbZZcydO5eWLVvy/PPPM336dMBnc7/99luqVatGiRIluOqqqwC45ppruOyyy3LV73POOYfbbruNX3/9lbfffpvLL7+ckiVz9/G5+OKLKVOmDGXKlOGEE05g27Zt1KpVK8NriImJ4fLLLwd8UH/OOedwfOgGZL169Up9bWbOnMnq1atTz/PHH3+wZ88e5syZwzvvvJN67qpVq+aq3yIiIiJFWWIiLF+efjXi9et9nRk0bAjdu/vgtXVraNwYcvnnoEie0scwA8fqBs0pc2rDVahQIVvHW9hPX2bG7NmzmTlzJl9++SXly5enU6dOHEhZSi6L43Piuuuu41//+hdTpkzhH//4R4b7NWrUiCVLlkQcmgxQpkyZ1McxMTEkJSVleg1ly5ZNl0HNSHJyMgsWLKBs2bI5vDJo2LAhCQkJJCcnU6JEidT2EhISaNiwYY7bExERESnInPMBa3AYcUKCnx8LcNJJPnjt3z9tGHGlStHts0hGtFBUBvr2hXHjfGbWzP87blz+3NuqQ4cOTA6tSLVu3Tp++OEH6tevD8Cnn37K77//zv79+3n33Xdp164du3btomrVqpQvX541a9awYMGC1LaSk5OZNm0aAG+88Qbt27fPVh8qVap0xMJO/fr1Y3QoxZ1ZoDd48GAmTZrEwoULU8veeecdtqXcOTuCzK4hqFWrVnz++efs2LGDpKQk3n477d7PXbp04YUXXkh9nvLjQceOHXnjjTcA+Oijj9ixY8cR7Z5++uk0a9aMRx99NLXs0UcfpXnz5px++ukZ9ltERESkMPjtN/jwQ79wU7duUK0anHEGXHstvPYalCvn15yZNg1+/BG2bIF33oFhw+DccxXQSsGmTG0monWD5ttuu41bb72VuLg4SpYsycSJE1Ozm61bt+byyy9n8+bNXHPNNbRs2ZK4uDjGjh1LgwYNqF+/PmeddVZqWxUqVOCrr77i0Ucf5YQTTki3EFJmqlWrRrt27WjcuDEXXnghTz31FDVr1qRBgwapi0VlpGbNmkyZMoW77rqLX375hRIlSgJhupIAACAASURBVNCxY8fU+cORdOvWLcNrCDr55JO5//77ad26NccffzxnnnkmlUOrDzz//PMMGjSIJk2akJSURMeOHRk7dizDhw+nT58+NGrUiLPPPptTTz01YtsTJkxgyJAh1K1bF4C2bdtGnH8rIiIiUpAdOOAXb0rJwC5c6Bd3An+rykaN4PLLfQa2TRs/rDgbg+JECiyLtBJsUVChQgW3d+/edGXffPMNDRo0iFKPCr99+/YRFxfH0qVLUwPJaNizZw8VK1YkKSmJnj17cuONN9KzZ8/8OfmIYrZ834hdWe8jIiIiUZOcDN9+mxa8fvWVnxd76JCvr1UrbRGnNm38wk5a+7L4MLN9zrnszXMsxJSplWyZOXMm/fv3584774xqQAswYsQIZs6cyYEDB+jSpUuWmWMRERGRouLXX9Mv5LRoEezc6esqVoRWreCvf00LZE86Kbr9FckPytRKrn388cfce++96crq1KmTuoJxkaRMrYiIiOST/fth6dL0w4g3bfJ1MTF+9eGUDGybNnDmmRpGLOkpUyuSha5du9K1a9dod0NERESk0EtOhrVr069G/PXXkJTk60891WdfBw3yAWzz5pDNm2eIFHkKakVERERE8tnPP6fPwC5aBH/84euOO84PI77nHh/Itm4Nf/pTdPsrUpApqBUREREROYb27YMlS9IHsT/84OtiYqBJE7j6ap+Bbd3aDyMuoRtvimSbgloRERERkTxy+DCsWZN+NeIVK3w5QGwsnHUWDB3qg9hmzaB8+ah2WaTQ029A+eznn3+md+/e1K1blxYtWnDRRRexbt06Zs+ezSWXXBLVvvXr149p06YdUe6c49FHH6VevXqcccYZnHvuuaxatSq1/q233qJBgwace+65APTp04cmTZrw3HPPHdHW6NGjef311yOef+zYsRnWpZg4cSKDBw+OWPf444+nPj548CAdO3YkKWUiioiIiMgx8NNP8O67cN99cN55ULWqX8Cpf3+YOhVq1PB1M2b4IcfffefL//IXaNdOAa1IXijWmdrYYR/kaXubRl2cab1zjp49e3L99dczZcoUAJYvX862bduO+txJSUmULHls3s4xY8Ywf/58li9fTvny5fnkk0/o3r07q1atomzZskyYMIHx48fTvn17fv75ZxYtWsT69esj9vG1115j6dKlEesGDhx4VP18/PHHuf/++wEoXbo0559/PlOnTqVv375H1a6IiIgUD5MnwwMP+KHBp54Kjz0GwT8j9uw5chjx5s2+rmRJaNoUrr02bRjxGWdoGLFIfijWQW1+mzVrFqVKlUoXvDVt2hSA2bNns2fPHq644gpWrlxJixYt+Ne//oWZ8fDDD/Of//yH/fv3c/bZZ/PKK69gZnTq1In4+Hjmzp1Lnz596NixI/3796dEiRJccMEFfPTRR6xcuZLDhw8zbNgwZs+eTWJiIoMGDeKWW27BOceQIUP49NNPOeWUUyhdunTEfj/xxBN8/vnnlA/9lNilSxfOPvtsJk+ezJYtW5g7dy79+/ene/fufPzxx2zZsoX4+HheeOEFOnTokNrOZ599RvPmzVOD7/D+7969m4oVK3LXXXexaNGiiNcC8NNPP9GtWzc2bNhAz549efLJJxk2bBj79+8nPj6eRo0aMXnyZHr06MF9992noFZERESyNHky3Hyzn/8K8P33cNNNMGuWD0wXLoSVK/0qxQCnnQbt26fdTqdZMyhbNnr9FynOFNTmo5RgNSPLli1j1apVnHTSSbRr14558+bRvn17Bg8ezEMPPQTAtddey/vvv8+ll14K+GG2ixcvBqBx48aMHz+etm3bMmzYsNR2J0yYQOXKlVm0aBGJiYm0a9eOLl26sGzZMtauXcvq1avZtm0bDRs25MYbb0zXpz/++IO9e/dy2mmnpStv2bIlq1at4tlnn+Wzzz7j6aefpmXLlgwaNIhLLrmEhISEI65v3rx5R1x/sP8jRoxILb/hhhsiXgtAQkICy5Yto0yZMtSvX58hQ4YwatQoXnzxxXTnbdy4MYsWLcrw9RYRERFJ8cADaQFtigMHYMIEP6S4dWvo0SNtNeIaNaLTTxE5kgZEFCCtW7emVq1alChRgvj4eDaF7q49a9Ys2rRpQ1xcHJ999lm6+axXXXUVADt37mT37t20bdsWgKuvvjp1n08++YTXX3+d+Ph42rRpw/bt2/n222+ZM2cOffr0ISYmhpNOOonzzjvvmF7f1q1bqRH2f4CU/gdldi0A559/PpUrV6Zs2bI0bNiQ77//PuL5YmJiKF26NLt3786jKxAREZGiKmU14nBmsH07/Pe/MHIkXHyxAlqRgkZBbT5q1KgRS5YsybC+TJkyqY9jYmJISkriwIED3HbbbUybNo0VK1YwYMAADhw4kLpfhWzcdds5xwsvvEBCQgIJCQl89913dOnSJVt9Pu6446hQoQIbN25MV75kyRIaNWqUrTZSlCtXLl3fIXv9DxfpdcpIYmIiZTUWSERERDLgHLzySsb1p57qA1sRKbgU1Oaj8847j8TERMaNG5da9vXXX/PFF19keExKEFi9enX27NkTcXVigCpVqlCpUiUWLlwIkLoQFUDXrl15+eWXOXToEADr1q1j7969dOzYkalTp3L48GG2bt3KrFmzIrZ99913c/vtt7N//34AZs6cydy5c4/IoGalQYMGEReQysm1ZKZUqVKp1wiwfft2qlevTqlSpXLUTxERESkevv8eLrgABg6EBg2gXLn09eXL+8WiRKRgU1Cbj8yM6dOnM3PmTOrWrUujRo247777OPHEEzM8pkqVKgwYMIDGjRvTtWtXWrVqleG+EyZMYMCAAcTHx7N3714qV64MwE033UTDhg1p3rw5jRs35pZbbiEpKYmePXtSr149GjZsyHXXXZc63DfckCFDaNWqFXFxcdSvX59HHnmE9957j3Lh/+XPwoUXXsicOXOytW9G15KZm2++mSZNmqQuDDVr1iwuvjjzFalFRESk+EnJzjZu7BeAGjvWLwI1fjzUru0zs7Vrw7hx6Vc/FpGCyZxz0e7DMVGhQgW3d+/edGXffPMNDRo0iFKPjr09e/ZQsWJFAEaNGsXWrVv5+9//HuVepZeyWnG9evUy3S8vruWyyy5j1KhRnHHGGbnu7xFGZB1cFykjdkW7ByIiInlq0ya/qvH//gfnnw+vvgqxsdHulcixYWb7nHM5n+9XyGj14yLkgw8+4P/+7/9ISkqidu3aTJw4MdpdOkJKgJpVUHu013Lw4EF69OiRtwGtiIiIFFop2dm77/bPx471t/DRfFmRwi9fM7Vm1g34OxADvOqcGxVWPxAYBBwG9gA3O+dWh+ruA/qH6m53zn2c2bmKY6ZW8oEytSIiIoXOpk3Qvz989hl07uyzs7VrR7tXIsdeccnU5tucWjOLAcYAFwINgT5m1jBstzecc3HOuXjgSeDZ0LENgd5AI6Ab8FKoPRERERGRiJzzGdm4OPjqK//4k08U0IoUNfm5UFRrYL1zbqNz7iAwBfhzcAfn3B+BpxWAlDTyn4EpzrlE59x3wPpQeyIiIiIiR9i0yWdlb70VzjrLLwR1yy0abixSFOVnUHsy8GPg+eZQWTpmNsjMNuAztbfn8NibzWyxmS3O7N6lIiIiIlI0JSenz86+8oqysyJFXYFbKMo5NwYYY2ZXAw8C1+fg2HHAOPBzao9ND0WkSNJ8aRGRQk9zZ0WKp/zM1G4BTgk8rxUqy8gUoEcujy2wfv75Z3r37k3dunVp0aIFF110EevWrcvXPsyePZv58+dnWP/uu+/y8MMPR6ybMWMGo0aNilgXbP+SSy6JWDd69Gj27duX+rxz587s2LEjG70WERERiSw5GV5+2d93VtlZkeInPzO1i4B6ZlYHH5D2Bq4O7mBm9Zxz34aeXgykPJ4BvGFmzwInAfWAr466R3mdmcki8+Gco2fPnlx//fVMmTIFgOXLl7Nt27Zs33rm8OHDxMTEZPg8O2bPnk3FihU5++yzI9Y/+eSTzJgx44jypKQkunfvTvfu3XN0vqDRo0dzzTXXUL58eQCuvfZaXnrpJR544IFctykiIiLFl7KzIpJvmVrnXBIwGPgY+Ab4t3NulZk9bGYpUdJgM1tlZgnAXwgNPXbOrQL+DawG/gsMcs4dzq++55VZs2ZRqlQpBg4cmFrWtGlTOnTocER2c/Dgwan3Zo2NjeXee++lefPmvPXWW0c8/+STT2jbti3NmzenV69e7NmzJ/W44cOH07x5c+Li4lizZg2bNm1i7NixPPfcc8THx/PFF1+k6+O6desoU6YM1atXB6Bfv34MHDiQNm3acM899zBx4kQGDx4MwIYNGzjrrLOIi4vjwQcfpGLFiqnt7NmzhyuuuIIzzzyTvn374pzj+eef56effuLcc8/l3HPPBaB79+68+eabef9ii4iISJGm7KyIpMjP4cc45z50zp3hnKvrnHssVPaQc25G6PFQ51wj51y8c+7cUDCbcuxjoePqO+c+ys9+55WVK1fSokWLXB1brVo1li5dSu/evdM979y5M48++igzZ85k6dKltGzZkmeffTb1uOrVq7N06VJuvfVWnn76aWJjYxk4cCB33nknCQkJdOjQId155s2bR/PmzdOVbd68mfnz56drF2Do0KEMHTqUFStWUKtWrXR1y5YtY/To0axevZqNGzcyb948br/9dk466SRmzZrFrFmzAKhatSqJiYls3749V6+LiIiIFD/ffQcXXAC33QZnn+1XNr75Zq1sLFJc5WtQK7l31VVXRXy+YMECVq9eTbt27YiPj2fSpEl8//33qftddtllALRo0YJNmzZleZ6tW7dSo0aNdGW9evWKOMT5yy+/pFevXgBcfXW6keS0bt2aWrVqUaJECeLj4zM99wknnMBPP/2UZd9ERESkeEvJzsbFwaJFMG4cfPyxsrMixV2BW/24KGvUqBHTpk2LWFeyZEmSk5NTnx84cCBdfYUKFSI+d85xwQUXZDiEt0yZMgDExMSQndsclStXjl270s8NDj93dqScNzvnPnDgAOXKlcvxOURERKT4+O47P3d21iyfpX31VTj11Gj3SkQKAmVq89F5551HYmIi48aNSy37+uuv+eKLL6hduzarV68mMTGRnTt38r///S9bbZ511lnMmzeP9evXA7B3794sV1OuVKkSu3fvjljXoEGD1Layc+63334bIHXhq6yEn9s5x88//0xsbGy2jhcREZHiJZidXbw4LTurgFZEUiiozUdmxvTp05k5cyZ169alUaNG3HfffZx44omccsopXHnllTRu3Jgrr7ySZs2aZavNGjVqMHHiRPr06UOTJk1o27Yta9asyfSYSy+9lOnTp0dcKKpjx44sW7YM57K+ze/o0aN59tlnadKkCevXr6dy5axXk7755pvp1q1b6kJRS5Ys4ayzzqJkSQ0aEBERkfS++86vaBycOztggObOikh6lp3gpTCqUKGC27t3b7qyb775hgYNGkSpR4XH0KFDufTSS+ncuXOm++3bt49y5cphZkyZMoU333yT9957L8fn6t69O+eff/7RdDn/5PVtoAq6LG5TVaTovRURKTCSk2HsWLjnHihRAp55Bm66ScGsSE6Z2T7nXM7nEhYySo/JEe6//34WLlyY5X5Llixh8ODBOOeoUqUKr732Wo7P1bhx48IT0IqIiMgxp7mzIpJTCmrlCDVr1qR79+5Z7tehQweWL19+VOcaMGDAUR0vIiIiRUN4dnbcOGVnRSR7FNSKiIiISFQpOysiR6PYLRRVVOcQi4iIiBQ2ycnw0ktpKxuPH6+VjUUk54pVUFu2bFm2b9+uwFZEREQkylJWNh40CNq18ysba7ixiORGsRp+XKtWLTZv3syvv/4a7a5IIaW1s0VERI5Oyn1n773Xz50dP94PPVYwKyK5VayC2lKlSlGnTp1od0NERESkWPruO7jxRpg9G7p08QGthhqLyNEqVsOPRURERCT/JSfDmDF+7uySJT6Y/e9/FdCKSN4oVplaEREREclfwexs167+Vj0KZkUkLylTKyIiIiJ5LpidXbrU36bno48U0IoUNGb2mpn9YmYrA2UjzGyLmSWEtosCdfeZ2XozW2tmXQPl3UJl681sWH5eg4JaEREREclTGzfC+efD4MHQvr1f2ViLQYkUWBOBbhHKn3POxYe2DwHMrCHQG2gUOuYlM4sxsxhgDHAh0BDoE9o3XyioFREREZE8kZKdbdIkfXb2lFOi3TMRyYhzbg7wezZ3/zMwxTmX6Jz7DlgPtA5t651zG51zB4EpoX3zhYJaERERETlqys6KFDmDzezr0PDkqqGyk4EfA/tsDpVlVJ4vFNSKiIiISK4pOytSoJU0s8WB7eZsHvcyUBeIB7YCzxyzHuYBrX4sIiIiIrmycaNf2fjzz/3KxuPHK5gVKWCSnHMtc3qQc25bymMzGw+8H3q6BQh+y2uFysik/JhTplZEREREciQ5GV580a9svGyZsrMiRY2Z/SnwtCeQsjLyDKC3mZUxszpAPeArYBFQz8zqmFlp/GJSM/Krv8rUioiIiEi2KTsrUrSY2ZtAJ6C6mW0GhgOdzCwecMAm4BYA59wqM/s3sBpIAgY55w6H2hkMfAzEAK8551bl1zUoqBURERGRLCUnw0svwb33QsmSMGEC3HCDFoISKeycc30iFE/IZP/HgMcilH8IfJiHXcs2BbUiIiIikqlgdrZbNxg3TtlZESk4NKdWRERERCIKnzs7YQJ8+KECWhEpWJSpFREREZEjbNjg7zOr7KyIFHTK1IqIiIhIquRkeOEFf9/ZZcvgtdeUnRWRgk2ZWhEREREBjszOjh8PtWpFu1ciIplTplZERESkmMsoO6uAVkQKA2VqRURERIqxDRv8ysZz5ig7KyKFkzK1IiIiIsVQMDubkKDsrIgUXsrUioiIiBQzwezshRf6lY0VzIpIYaVMrYiIiEgxEczOLl/us7MffKCAVkQKN2VqRURERIoBZWdFpKhSplZERESkCEtOhuefV3ZWRIouZWpFREREiqj163129osv4KKL4JVXFMyKSNGjTK2IiIhIERPMzn79NfzjH/D++wpoRaRoUqZWREREpAgJz86OGwcnnxztXomIHDvK1IqIiIgUARllZxXQikhRp0ytiIiISCGn7KyIFGfK1IqIiIgUUsnJ8Pe/p2VnJ05UdlZEih9lakVEREQKIWVnRUQ8BbUiORB74I1odyFfbYp2B0RE5AjJyfDCC3DffVC6tM/OXncdmEW7ZyIi0aGgVkRERKSQUHZWRORImlMrIiIiUsBp7qyISMaUqRUREREpwNavhxtugLlz4eKL4ZVXFMyKiAQpUysiIiJSAAWzsytW+Ozsf/6jgFZEJJwytSIiIiIFjLKzIiLZp0ytiIiISAGh7KyISM4pUysiIiJSAHz7rV/ZWNlZEZGcUaZWREREJIqSk2H0aGjaFFauhEmTlJ0VEckJZWpFREREoiQ8OztuHJx0UrR7JSJSuChTKyIiIpLPMsrOKqAVEck5ZWpFRERE8pGysyIieUuZWhEREZF8cPhw+uzs668rOysikheUqRURERE5xr791t93dt48uOQSv7KxglkRkbyhTK2IiIjIMXL4MDz3nL/v7KpVPjs7Y4YCWhGRvKRMrYgIEHvgjWh3IV9tinYHRIoBZWdFRPKHMrUiIiIieUjZWRGR/KVMrYiIiEgeWbfOr2w8bx5ceqnPzv7pT9HulYhI0aZMrYiIiMhRSsnONm2alp197z0FtCIi+UGZWhERKfpGVI52D/LXiF3R7kGxouysiEh0KVMrIiIikgOTJ0NsLJQoAccfD40aKTsrIhJNytSKiIiIZNPkyXDzzbBvn3++YwfExMCjj8K110a3byIixZUytSIiIiLZNGxYWkCb4vBheOqp6PRHRESUqRURERHJ0s6d8OyzsHlz5Poffsjf/oiISJp8zdSaWTczW2tm681sWIT6v5jZajP72sz+Z2a1A3WHzSwhtM3Iz36LiIhI8bR7Nzz2GNSpA488AuXLR97v1FPzt18iIpIm34JaM4sBxgAXAg2BPmbWMGy3ZUBL51wTYBrwZKBuv3MuPrR1z5dOi4iISLG0fz888wycdho8+CB07AgJCTBu3JGBbfnyPvAVEZHoyDCoNaOjWZ4OT24NrHfObXTOHQSmAH8O7uCcm+WcS5mpsgColYfnFxEREclUYiKMGQN168Jdd0Hz5rBwoV/VuGlT6NvXB7a1a4OZ/3fcOF8uIiLRkVmmdhZwPIAZG82odpTnOhn4MfB8c6gsI/2BjwLPy5rZYjNbYGY9Ih1gZjeH9lmclJR0lN0VERGR4uLQIZgwAc44AwYPhtNPh88/h48/htat0+/bty9s2gTJyf5fBbQiItGVWSZ2B1AH+AWIJX+HKl8DtATOCRTXds5tMbPTgM/MbIVzbkPwOOfcOGAcQIUKFVx+9VdEREQKp8OHYcoUGDEC1q/3Aeyrr0Lnzj4TKyIiBV9mQe3bwOdmbAUcsNiMw5F2dI7TsnGuLcApgee1QmXpmFln4AHgHOdcYto53JbQvxvNbDbQDNgQfryIiIhIVpKTYfp0eOghWL3aDy2eMQMuuUTBrIhIYZNZUDsQmAHUA54F/gHsPopzLQLqmVkdfDDbG7g6uIOZNQNeAbo5534JlFcF9jnnEs2sOtCO9ItIiYiIiGTJOfjwQ/jb32DZMmjQAP79b7j8ciiRr/eEEBGRvJJZUNsB+Ng5PjCjKfCMc7kPap1zSWY2GPgYiAFec86tMrOHgcXOuRnAU0BF4C3zP5P+EFrpuAHwipkl44dBj3LOrc5tX0RERKR4cQ4++8yvZLxggV/V+J//hD59ICYm2r0TEZGjkVlQOwv4E35O7TlA6aM9mXPuQ+DDsLKHAo87Z3DcfCDuaM8vIiIixc/cuT4zO3s2nHKKX624Xz8oVSraPRMRiT4zew24BPjFOdc4VPYUcClwED/l8wbn3E4ziwW+AdaGDl/gnBsYOqYFMBEoh4/5hjrn8mWdo8wG2qQsFAX5vFCUiIiIyNFavBguvBA6dIA1a+CFF+Dbb2HAAAW0IiIBE4FuYWWfAo2dc02AdcB9gboNzrn40DYwUP4yMAA/fbVehDaPmfxcKEpERETkmFuxwmdm33sPqlWDp56C226D8uWj3TMRkYLHOTcnlIENln0SeLoAuCKzNszsT8BxzrkFoeevAz1If4vWYyY/F4oSEREROWbWrvW35pk6FY47Dh55BIYOhUqVot0zEZGoKWlmiwPPx4Vug5oTNwJTA8/rmNky4A/gQefcF8DJwObAPptDZfkiw6DWORzwAUBeLBQlIiIicixs3AgPP+wXfipXDu6/H/76V6haNdo9ExGJuiTnXMvcHmxmDwBJwORQ0VbgVOfc9tAc2nfNrFEe9POoZJapTeUcNwCYURY4HT8ceYNzHDiGfRMRERHJ0ObN8OijMGEClCwJd94J994LNWpEu2ciIoWfmfXDLyB1fsqCT865RCAx9HiJmW0AzsDfsrVW4PBaobJ8ka3Fn8woacZT+MWjlgMrgB1mPGmGlloQERGRfLNtG9xxB5x+Orz2GtxyC2zYAE8/rYBWRCQvmFk34B6gu3NuX6C8hpnFhB6fhp+qutE5txX4w8zOMn9v1uuA9/Krv9nK1AJPAn3w82znhso6AP+HD4zvyvuuiYiIiKTZvt0v+vTCC5CY6G/L87e/Qe3a0e6ZiEjhZWZvAp2A6ma2GRiOX+24DPCpj1FTb93TEXjYzA4BycBA59zvoaZuI+2WPh+RT4tEQfaD2quBG51Ld4/ZDWb8CryKgloRERE5Rnbtgueeg2efhT174OqrYfhwqFcv2j0TESn8nHN9IhRPyGDft/F3yYlUtxhonIddy7bsBrWV8TfdDbcBqJJ33RERERHx9u71Wdknn4QdO+Dyy2HkSGgU9SVJRETkaNlIqwHghrtfQ8/jgKuAVW64ezMnbWVrTi1+Hu3tEcqHAgk5OaGIiIhIZg4cgNGj4bTT4L774OyzYckSmDZNAa2ISBHyb+BSABtp1YE5QE9grI20v+akoewGtfcA15ux1oxJoW0tcA1wd05OKCIiIhLJwYMwdqxfAOrOOyEuDubPh/ffh+bNo907ERHJY02ABaHHVwDr3XDXCL/I1C05aShbQa1zzMEv1TwNqBja3gLqO5e6cJSIiIhIjiUlwcSJUL8+3HorxMbCrFkwcya0bRvt3omIyDFSDtgTetwZmBF6vBQ4JScNZXdOLc7xE/BAThoXERERyUhyMkydCiNGwLp10LKlz9R26QJ+sU0RESnCvgUus5H2NtAFeCpUXhPYmZOGsjv8WERERCRPOAfTp0PTpn4l4zJl4N134auvoGtXBbQiIsXESOAJYBOwwA13C0PlXYFlOWlIQa2IiIjkC+fgo4+gVSu47DI4dAimTIGEBPjznxXMiogUJ264ewc4FWgJdAtUzQT+kpO2FNSKiIjIMTdrFrRvDxddBNu3+zm0K1fCVVdBCf01IiJS7NhIewjY7Ya7ZW64Sw5UfQ1cmZO29L8REREROWbmz4fzz4fzzoPvv/dzZteuheuvh5LZXtlDRESKoOH4BYjDlQ/VZZuCWhEREclzS5fCxRdDu3Y+Izt6NKxfD7fcAqVLR7t3IiJSABjgIpQ3A37PSUMZ/kZqxqwMTnIE5zgvJycVERGRomnlShg+HN55B6pWhVGjYPBgqFAh2j0TEZGCwEbabnyc6YCNNtKCMWcMUBYYm5M2Mxv4szKs8b7Az0DKqlStgT8B/8rJCUVERKToWbcORo6EN9+ESpX8bXruuAMqV452z0REpIAZjM/Svoa/ZeyuQN1BYJMb7r7MSYMZBrXOMSTlsRnPAZOAoc6lZW/NGB3qkIiIiBRDmzbBI4/ApEn+1jz33gt3IRoW1AAAIABJREFU3QXVqkW7ZyIiUhC54W4SgI2074D5brg7dLRtZneJhuuAtsGANuQlYAEw9Gg7IiIiIoXHli3w+OMwfrxfvXjIEBg2DGrWjHbPRESkMHDD3ecANtJOAk4gbL0nN9wtzW5b2Q1qDYgD1oWVx2X3RCIiIlL4/fKLnyf70ktw+DAMGAD33w+1akW7ZyIiUpjYSGuGn8p6JkeO/nX4KbDZkt2g9jXgVTPq4TOzAGcB9wD/yO7JREREpHD6/Xd4+un/Z+/Ow+SoqsaPfw/BEIzsqGyRPQr4KiCyyL4K+gqCIKgsssoPgiv71gwQX0A2QUSCIKACsikRIjsIqGBCQBCiEJYAYd8xJECS8/ujKqQzTibdmc50uuf7eZ55pupW1a0T28xwcu89F846CyZOhN13h2OPheWXb3ZkkqQWNQx4BtgXeI4aixR3pdak9lDgJYppxj8u254HTgJOm92XS5KkudtbbxXb8Zx2Grz9NuyyS1Hd+JOfbHZkkqQWtyqwRlay82zgutWU1GYyFTgFOCWCBcu2t3r6ckmSNHeaMAHOOQdOPrkYpd1++6K68f+48EiS1BgPAUvw30tc61brSC0AEawFrAhcV54PBN7NZHJPA5EkSc03aRIMG1YUgXrxRdhmGzj+eFhrrWZHJklqM0cCp0RHHE2R4M5QBTkr+VqtHdWU1EbwceBair1pE1gZeAI4HZiE1Y8lSWpp778Pv/pVsT3Ps8/CJpvA1VfD+us3OzJJUpu6pfx+EzOupw3mUKGoM4AXgcWAp6varwTOrvVlkiRp7jJlCvz2t8XU4ieegPXWK/ac3WyzZkcmSWpzmzaqo1qT2s2BzTN5PWYstvw48IlGBSNJknrH1Klw1VVF0ad//QvWWAOuv76YbhydN1aQJKnBpu1T2wi1JrXzA+910f5RiunHkiSpBWTCH/8IxxwDDz4Iq61WTDPefnuTWUlS74uOWIpioLR/dXtW8s5a+6g1qb0T+DbFYl6AjKAfcBhwa60vkyRJzZEJN91UJLMjR8JKKxXTjnfeGfrVvGpJkqTGKJPZS4GNKNbQTltLO03Nv53mqfG+Q4F9I7gZmI9ib9pHgPWBI2p9mSRJ6n133gkbbwxbb11UNL7gAhgzBr75TRNaSVLTnAlModiv9h1gQ2AnYAywdT0d1ZTUZvII8D/AXymqUw2gKBK1RiaP1/NCSZLUO+65B7bcskhox44t9p199FHYay+Yt65N/SRJariNgcOykv+iGKF9OSt5DcVs4BPq6ajmX2mZvABU6ulckiT1vvvvh2OPheuug49+FE4/HfbfH+afv9mRSZL0gfmBV8rj14CPAY9SzAj+TD0d1bpP7UYzuZQUhaIez6TmzXElSdKcs+aasPDC8OMfw0EHwUc+0uyIJEn6L/8CPgU8BTwA7B8d8QxwIDC+no5qHam9g+mLdqfVRqw+nxrBcGC3TCbUE4AkSWqsY4+FH/ygSGwlSZpL/RRYojw+HrgB+AbwLrBHPR3VWijqyxQLdncFViq/dgUeBr5Wfq0OnFTPyyVJUuN1dJjQSpLmblnJ32YlLyqPRwPLAZ8HPpGVvLKevmodqT0R+F7mDNv3PBHBy8DJmXwuginA2cBB9QQgSdKcttykS5sdQq96qtkBSJI0C9ER/YF5spKTALKS7wCjoyMGREf0z0q+V2tftY7UrkrX85rHl9cAHmL68LEkSZIkSTNzJXBAF+37A1fU01GtSe0jwFERzDetoTw+srwGMAh4oZ6XS5IkSZL6pPUptovt7GbgC/V0VOv04wOAPwLjI/hn2fZpYCrwv+X5CsDP63m5JEmSJKlP+jAwuYv2qcAC9XRUU1Kbyb0RLE9RHOqTZfOlwKWZ/Ke855J6XixJkiRJ6rMepKh2XOnU/k34YCC1JrNMaiP4EPAMsHkm59XTuSRJkiRJXTgeuDY6YiXgtrJtc2AnYPt6OprlmtpM3gfeZ/q+tJIkSZIkzbas5AjgK8CywFnl1yeAbbOS19XTV61ras8Gjohgz8wu5z1LkiRJklSzrOQNwA097afWpHZDYGOmF4qaMEMwybY9DUSSJEmSpHrVmtS+Alw9JwORJEmSJLWv6Ii3gBWykq9ER7xNN0tcs5IL1tpvrdWP96y1Q0mSJEmSunAQ8HZ5PKRRndY6UitJkiRJ0mzLSl7c1XFP1ZzURrAnxT5CnwD6zxBcskKjApIkSZIkqVY1JbURHAIcAZwHbAT8HFipPD51jkUnSZIkSWoLs1pHW63ha2qBfYH9MrkqgiHAzzJ5IoJjKPYVkiRJkiSpOw1bR1ut1qR2GeDv5fFEYFrWfFnZvm+D45IkSZIktZFGrqOtVmtS+wKwOPA0MA5YD3iAYgpyTcPHkiRJkiRVi47YDFi1PH0kK3lbvX3UmtTeBmwLjAYuAM6I4OvAmsAV9b5UkiRJktR3RUcsD1wNfAZ4rmxeKjriIeBrWcknau2r1qR2P2AegEx+EcHrwPplEOfV+jJJkiRJkigGS98GVshKPg0QHfEJ4GLgl8BmtXZUU1KbyVRgatX574Df1RGwJEmSJEnTrAesOy2hBchKPh0d8QPgb/V0NE+tN0bw4Qi+EMFXI9ih+queF0qSJEmS5g4RcWFEvBQR/6xqWzQibo6Ix8rvi5TtERFnRcTYiHgwItasemaP8v7HImKPGl79NDB/F+0DgGfq+TPUuk/tFhSVjhfr4nIC/ep5qSRJkiRprnAR8DPgkqq2w4FbM/OkiDi8PD8M2AZYufxaBzgXWCciFgUqwFoU+eF9ETE8M1/v5r0/As6KjvguMLJ8bm3gzPJazWpdU/tT4HrgyMwPFvFKkiRJklpYZt4ZEct1at4O2KQ8vhi4gyKp3Q64JDMTuCciFo6IJct7b87M1wAi4mZga4qB0Zm5DJgP+AvTl7rOA0wBfhsdMT3GSi74X09XqTWpXQ7Y1oRWkiRJktrexzPz+fL4BeDj5fHSzDg1+NmybWbt3RnSgDiB2pPavwCfBB5v1IslSZIkSXPUvBExqup8WGYOq6eDzMyIyAbHRVby4kb1NdOkNoI1q05/AZwawVLAQ8D7MwSUjG5UQJIkSZKkhpicmWvNxnMvRsSSmfl8Ob34pbJ9PDCo6r5lyrbxTJ+uPK39jlm9JDpiAPBNYNWy6RHgsqzkxHqC7W6kdhTFYt2oausqq7dQlCRJkiS1j+HAHsBJ5fdrq9qHRMTlFIWi3iwT3xuBH0+rkgxsBRzR3QuiI9YErqOogPxQ2bwXMDQ64stZyZoHTrtLapevtRNJkiRJUuuJiMsoRlkXj4hnKaoYnwRcERF7A+OAr5e3jwC+BIwF3gH2BMjM1yLiBIoqxgDHTysa1Y1hwN3AnlnJCQDREQOBC8trNY8wzzSpzWRcrZ3UKiK2pqik3A/4ZWae1On6D4F9gMnAy8BemTmuvLYHcHR564mZjZuDLUlqX2+80ewIJEmae2XmN2ZyafMu7k3gwJn0cyFFQlqr1YDdpyW0AFnJCdERx1PMGq7ZPN1djGC9CEZG8F8llCNYKIK/R7B2LS+KiH7AORR7G60KfCMiVu102/3AWpn5GeAq4JTy2Wn7Hq1DsXdRpWpoW5Kk//Luu3D66bDiis2ORJIkdeFfwFJdtC8JPFpPR7OqfvxD4OpM3up8IZM3I7gKOJjpw9HdWRsYm5lPAJTzsLejWAxc9pm3V91/D7BrefxF6t/3SJLUB02ZApdeCsccA+PGwVZbwb+bHZQkSersaOCscmT2nrJt3bL98OiIRafdmJXupzJ3O1JLMY/5um6ujwA+P8twC/XuXbQ38Kd6no2I/SJiVESMmjx5co1hSZLaQSbccAOsuSbsvjssthjcfDPceGOzI5MkSV34I/Ap4FKKrWMfL49XpShM9TLwSvm9W7MaqV0SmNDN9XfKexoqInalSKg3rue5cs+lYQADBw5s+F5KkqS508iRcNhhcPvtsMIKcNll8PWvwzyz+qdbSZLULJs2qqNZJbUvUWTPT87k+ipM37NoVma2p9EMImIL4Chg48x8t+rZTTo9e0eN75UktamxY+Goo+CKK2DxxeGss+A734H+/ZsdmSRJ6k5W8s8zuxYdsVJWcmytfc0qqb0ZOCaCGzKZYeQzgnmAI8t7ajESWDkilqdIUneh2Gi3qs9YAzgP2Dozq5Pluvc9kiS1rxdfhBNOgPPOKxLYY46Bgw+GBf+rrKEkSWoF0REDgB2BfYENKHbMqcmsktqhwGhgZAQ/oahQBcUI7SHAisDutbwoMydHxBCKBLUfcGFmPhxRlGzOzOHAT4CPAFdGBMDTmbntbO57JElqM2+/XVQ0PvVUmDgR9tsPjj0Wllii2ZFJkqTZER2xJkU9pW8A7wK/B46rp49uk9pMnohgC+AiikrD00Zrg6Jq8ZaZPF7ryzJzBEVxqeq2Y6uOt+jm2Xr3PZIktYn334fzz4eODnjpJdhxRxg6FAYPbnZkkiSpXtERCwHfAvYBVqYoDLUAsEFW8pHunu3KrEZqyWQU8OkIVi9fGMCjmTxQ78skSapHJlx5ZbFuduxY2HhjGD4c1lmn2ZFJkqTZER3xa+CrwL3AT4GrspIToiN2nt0+Z5nUTlMmsSaykqRecfvtcOihMGoUfPrTcP31sM02UKxOkSRJLeobwMnAqVnJ1xvRYc1JrSRJveEf/4DDDy/2nB00CC66CHbdFfrVXC5CkiTNxb5OsYb22eiIm4BLgOt60qE7+EmS5grjxsHuu8Maa8C998JPfgKPPgp77GFCK0lSu8hKXpOV/DLwSYqixKcCL1DkpmtER/1zskxqJUlN9eqr8KMfFUWfrrgCDjkEHn+82KJnwIBmRydJkuaErOSzWckTspIrAjsDVwK/BJ6Pjji3nr5mmtRGcGEEC5THG0U4VVmS1DjvvAMnnQQrrghnnllMMX7sMTj5ZFhkkVk/L0mS2kNW8pas5C7AUsD/AV+o5/nuEtVdgSOBt4HbgSWBl2YzTkmSAJg8GS6+GCoVGD8evvIV+PGPi2JQkiSp7yoLR/20/KpZd0ntU8BBEdxEsY3PehF0WZ0qkzvreakkqe/JLLbjOeIIGDMG1l0XLrsMNtyw2ZFJkqRW1l1SewjFnOYjgAR+P5P7ErCEhyRppv7yFzjssOL7Jz8J11wDX/2q2/NIkqSem+ma2kyuzeSjwKIUI7WrAR/t4utjvRCnJKkFjRlTJK8bbFAUfzrvPPjnP2H77U1oJUlSY8yy+nEmbwCbAo9l8mpXX3M+TElSKxk/Hvbdt1gne9ttcOKJMHYs7LcfzGvZQUmS+qToiAujIxYojzeKjmjIfxXU1Ekmf45gvgh2B1almHL8CHBpJu82IhBJUut74w045ZSimvHkyfDd78JRR8Hiizc7MkmSNBeYI8WIa0pqI1gV+BOwEPBQ2bwvcFwEW2cypqeBSJJa17vvws9/XozIvvYafOtbcMIJsPzyzY5MkiTNRZ4CDoqOmF6MuCO6LkZcyZqLEdc63PtT4AFgt0zeAohgQeA3wJnAF2t9oSSpfUydCpdeCkcfDePGwVZbFXvPrrFGsyOTJElzoTlSjLjWpHZ94PPTElqATN6K4CjgnlpfJklqD5lw441w+OHwj3/AmmvCL38JW2zR7MgkSdLcKit5LXBtdMTCwGsUxYh7Z/oxMAlYuIv2hcprkqQ+YtSoYnue226DFVYo9pr9+tdhnlmWHpQkSYKs5BvREUUx4kpO7ml/tSa1fwTOj2Bfpo/MrgecBwzvaRCSpLnf2LFF0acrrigKP511FnznO9C/f7MjkyRJrSYr+efoiPmiI/67GHEl6ypGXOu/q38PeAy4i2JkdhLwZ+BR4Pv1vFCS1FpeegmGDIFVVoHrroNjjin2nD3oIBNaSZI0e6IjVqXIJ08H1gHWBc4AHo2OWKWevmrd0ucNYLsIVgKmvWBMJmPreZkkqXX85z9w2mlw6qkwcWKxx+yxx8ISSzQ7MqmT4xZqdgS957g3mx2BJDXK9GLElSyKEXfEbBUjrmuz2zKJNZGVpDb2/vtw/vnQ0VGM0u64IwwdCoMHNzsySZLURopixGVCC5CVfCs6ou5ixHUltZKk9pUJV10FRx5ZrJ/daCMYPhzWWafZkUmSpDbUsGLEJrWSJG6/vahoPHIkfPrTcP31sM02ENHsyCRJUpsqihF3RI+LEbsBgyT1YQ8+CF/6Emy2GbzwAlx0ETzwQNFmQitJkuaghhUjdqRWkvqgceOKKsa/+Q0svDD85CdFheMBA5odmSRJ6guykkUx4o6YsRhxJeuu4VRTUhvBA8Avgd9m8nq9L5EkzV0GDy5GYg85BA4/HBZZpNkRSZKkvqhMYntUjLjW6cfXA4cCz0VwWQSb9+SlkqTm2nVXeOwxOPlkE1pJktTaakpqMzkKWBbYAegHXB/BkxEcG8En5mSAkqTGu+ACGDSo2VFIkiT1XM2FojLJTP6UydeBpYBhwJHAExHcGMHWcypISZIkSZK6UnehqAjWBfYCdgaeA34FLAlcFcEvM+urVCVJkiRJ6juiI+YF9gP+kJV8rqf91TRSG8HHIjg4goeBOyg2yd0xkxUyOSGTA4AtgX16GpAkSZIkqX1lJScDPwE+1Ij+ah2pfZaiItUFwMWZvNLFPQ8DIxsRlCRJkiSprd0DrAmM62lHtSa1m2dyV3c3ZPIWsGlPA5IkSZIktb3zgdOiI5YF7gMmVF/MSo6utaNak9qOCHbI5I3qxggWBP6QyWa1vlCSJEmS1OddWn4/vYtrSbHrTk1qTWo3Bvp30T4A2LDWl0mSJEmSBCzfqI66TWojWHPaIfCZCF6rutwP+CIwvlHBSJIkSZLaX1ayx2tpp5nVSO0oiqHfBG7q4vpE4KBGBSNJkiRJ6huiI7YBDgRWAL6YlXwmOmIf4Mms5K219jOrpHZ5ilHaJ4C1gZerrr0HvJTJlLoilyRJkiT1adER3wJ+AfwS2Jzp2/v0Aw4Fak5qu92nNpNxmTyVyTyZjCrPp309b0IrSZIkSZoNhwL7ZiV/AEyuar8HWL2ejmY6UhvBDsAfM3m/PJ6pTK6p56WSJEmSpD5tZeBvXbT/B1iwno66m358FbAE8FJ5PDN1lVuWJEmSJPV5zwGDgc4FozYCHq+no5kmtZnTpyZXH0uSJEmS1EPDgLPKwlAAg6IjNgROAY6rp6Na96mVJEmSJKkhspKnREcsBNwMDABuB94FTs1KnlNPX7NaU1tbQK6plSRJkiTVISt5VHTEUGBViiLGj2Ql/1NvP7NaU1tTLLimVpIkSZJaSkR8EvhdVdMKwLHAwsC+TN/S9cjMHFE+cwSwNzAF+G5m3tjDMBKYVB7P1u46Na2plSRJkiS1l8z8N+X2ORHRDxgP/B7YEzgjM0+tvj8iVgV2AVYDlgJuiYjBmVl3MhodMR9wMvAdoD8QwLvREcOAw7KSk7p7vpqJqyRJkiRpc+DxzOxcjbjadsDlmfluZj4JjAXWns33nQvsCOxDsb3PSuXx9sDP6+nIfWolSZIkqT3NGxGjqs6HZeawmdy7C3BZ1fmQiNgdGAX8KDNfB5YG7qm659mybXbsBOyQlby5qu2J6IiXgKuBvWrtyH1qJUmSJKk9Tc7MtWZ1U0T0B7YFjiibzgVOoMj1TgBOo44ks0YTKKY7dzYemFhPRzOdfpzJPJm8VHU8sy8TWkmSJElqXdsAozPzRYDMfDEzp2TmVOB8pk8xHg8MqnpuGbpOTGtxNlCJjph/WkN5fEx5rWbuUytJkiRJfds3qJp6HBFLZubz5en2wD/L4+HApRFxOkWhqJWBv9f6kuiI4Z2aNgHGR0c8WJ7/D0WOOrCe4GtOaiNYE/g+xR5CAGOAMzIZXc8LJUmSJElzh4gYCGxJUYV4mlMiYnWK6cdPTbuWmQ9HxBXAI8Bk4MA6Kx+/2un86k7nT9bR1wdqSmoj+BZwCXAbMKJsXhf4ewTfzuQ3s/NySZIkSVLzZOYEYLFObbt1c/9QYOhsvauSe87Oc7NS60jtUOCYTH5c3RjBEcCJYFIrSZIkSep9tSa1HwWu6KL9SoqFvJIkSZIk1SQ6YhHgOGBT4GN0KmKclfxYrX3VmtTeTrGId2yn9k2AP9f6MkmSJEmSKJa3rgZcDLxIsX53tsw0qY1gh6rTPwH/F8FaTN9sd11gB4rsWpIkSZKkWm0CbJyV7HHh4e5Gaq/qom2/8qva2cDPexqIJEmSJKnPeJxOU45n10w7yWSeGr/6NSIQSZIkSVKf8T3g/6IjPhsd0aOcsuZ9aiVJkiRJapCxwPzAaIDoiBkuZiVrTnRrTmojWATYBvgE0H+GFybH19qPJM1NpkyBc85pdhSSemK5SZc2O4Re81SzA5CkxrkMWAj4LnOqUFS1CNYFrgfepdjeZzywZHn+FJjUSmo9DzwA++0HI0fCsoc1OxpJkqQ+ZS1g7azkP3vaUa0Lc38C/BZYGpgEbEYxYjsKOLmnQUhSb5owAQ45BNZaC55+Gi6/vNkRSZIk9TmPAAs2oqNapx9/Btg7k4xgCjBfJk9EcBhwKUXCK0lzvREj4IADYNy4YpT2pJNgkUXgsPubHZkkSVKfcjRwenTE0cBDwPvVF7OSr9XaUa1J7XtVxy8CywJjgP8AS9X6MklqlhdegO99D664AlZZBe66CzbYoNlRSZIk9Vkjyu83MeN62ijPG14oajTweeBR4A7gxAg+DuwKPFjryySpt02dCuefD4cdBpMmwQknwKGHQv/+s35WkiRJc8ymjeqo1qT2KGCB8vho4BLgbIokd89GBSNJjfTww8UU47/+FTbdFH7xCxg8uNlRSZIkKSv550b1VVNSm8moquOXKbb2qVtEbA38lGIo+ZeZeVKn6xsBZ1Ks4d0lM6+qujaFYq41wNOZue3sxCCp/U2cCEOHwimnwIILwkUXwe67Q8QsH5UkSVIviI5Ys7vrWcnRtfZV8z61ABGsCKxSnj6SyRO1Pxv9gHOALYFngZERMTwzH6m67Wng28DBXXQxMTNXrydeSX3PrbfC/vvD2LFFInvaabD44s2OSpIkSZ2Molg7Wz3sUL22trFraiNYDLgA2BaY+kFzcB2wVyav1tDN2sDYzHyifPhyYDuKUs4AZOZT5bWpXXUgSTPz8stw8MFwySWw0kpwyy2w+ebNjkqSJEkzsXyn8w8Ba1AsfT2ino5qHan9JbASsCFwb9m2DnAucD6wQw19LA08U3X+bNlHrQZExChgMnBSZv6hjmcltalMuPjiIqF96y04+mg46igYMKDZkUmSJGlmspLjumgeGx3xJlAB/lRrX7UmtV8ENs/kb1Vtf4ngO8Attb6sh5bNzPERsQJwW0Q8lJmPV98QEfsB+wH0t7Sp1PYefbSYanz77bD++nDeebDaas2OSpIkST3wJFDXstNak9qXgQldtL8DNU09BhgPDKo6X6Zsq0lmji+/PxERd1AMTT/e6Z5hwDCAgQMHZuc+JLWH996Dk08uikENGFAks/vsA/PM0+zIJEmSVIvoiEU7NwFLAscB/66nr1qT2uOBMyPYLbNIRCNYGjitvFaLkcDKEbE8RTK7C/DNWh6MiEWAdzLz3YhYHFgfOKXG90pqI3ffXWzTM2YM7LwznHkmLLFEs6OSJElSnV5hxsJQUCS2zwA719PRTJPaCB7q9JLlgaciPhhdXRqYBHyMYs1ttzJzckQMAW6kqGR1YWY+HBHHA6Myc3hEfB74PbAI8JWI6MjM1SgqLp9XFpCah2JN7SMzeVVzHbdQsyPoXce92ewI1Ee8/jocdhicfz4suyyMGAHbzNbmYpIkSZoLbNrpfCrFDOGxWcnJ9XTU3UjtVd1cmy2ZOQIY0ant2KrjkRTTkjs/91fgfxodj6S5Xyb87nfw/e/DK68UBaGOOw4GDmx2ZJIkSZpdWck/N6qvmSa1mXQ06iWSNDuefBIOOABuuAE+//ni++ruVi1JktSyulhL26Ws5Gu19lnrmtoigGAzYFWKackPZ3JHPc9LUi3efx/OOKMYke3XD846q0hu+9W8BbckSZLmUl2tpe0sqSNXrenGsijU74HPAc+VzUtFMArYPvODNknqkb//HfbdFx58EL76VTj7bFjmvxYlSJIkqUV1XktbbWvge0DD1tRWOwuYAqyUyZMAEawA/Ka8tmM9L5Wkzt56C446Cs45B5ZaCq65BrbfvtlRSZIkqZG6WksbHbEG8BNgQ+A84IR6+qw1qd0S2GRaQguQyRMRfBe4tZ4XSlJnv/89HHQQPPccDBkCJ54ICy7Y7KgkSZI0J0VHLA8MBXYCrgFWzUo+Xm8/9ayp7Wre86zmQkvSTD3zTJHMXnstfPazxejs2ms3OypJkiTNSdERiwHHAvsDfwG+kJUcObv9zVPjfbcCZ0cw6INAgk8AZ+JIraQ6TZlSFH9adVW46SY45RQYOdKEVpIkqd1FRxwFPA5sDGyXldysJwkt1D5S+11gOPBExPRCUcBDwDd6EkC7WW7Spc0OoVc91ewA1HIeeAD2269IYrfeGn7+c1h++WZHJUmSpF5yAjAReBY4IDrigK5uykpuW2uHtSa1rwJrA5sAnyrbxmRyS60vktS3TZhQbNFzxhmw+OJw2WWw884Q0ezIJEmS1IsuocHLWGeZ1EbQD3gT+GwmNwM3NzIASe1vxIhin9lx44pR2pNOgkUWaXZUkiRJ6m1ZyW83us9ZrqnNZAowDujf6JdLam8vvFCMxn75y/DhD8Ndd8F555nQSpIkqXFqLRR1AnBSBIvPyWAktYepU4vk9VOfKiobn3BCsZZ2gw2aHZkkSZLaTa1rag8GlgfGR/AsMKH6YiafaXRgklrTww8XU4z/+lfYdFP4xS9g8OBmRyVJkqR2VWtSezXuSSupGxMnwtChxfY8Cy4IF10Eu+9uIShJkiTNWTUltZkcN4fjkNTCbr0V9t8fxo4tEtnTTisZlVHQAAAWDklEQVQqHEuSJElzWrdraiP4cATnRDA+gpciuNR1tZKmefll2GMP2GKL4vyWW+Dii01oJUmS1HtmVSiqA/g2cD1wObAlcO4cjknSXC6zmF68yirFfrNHHw0PPQSbb97syCRJktTXzGr68Q7A3plcDhDBb4C/RNCv3OpHUh/z6KPFVOPbb4f11y+qHK+2WrOjkiRJUl81q5HaQcBd004y+TswGVhqTgYlae7z3nvF1jyf+QyMHl1UNb7zThNaSZIkNdesRmr7Ae91aptcw3OS2sjddxfb9IwZAzvvDGeeCUss0eyoJEmSpFknpwH8JoJ3q9oGAOdH8M60hky2nRPBSWqu11+Hww6D88+HZZeFESNgm22aHZUkSZI03ayS2ou7aPvNnAhE0txnlVXglVfg4IPhuONg4MBmRyRJkiTNqNukNpM9eysQSXOfQYPghhtg9dWbHYkkSZLUNdfGSpqpe+6Bfv2aHYUkSZI0c7OqfiypDzOhlSRJ0tzOpFaSJEmS1LJMaiVJkiRJLcukVpIkSZL6qIh4KiIeiogHImJU2bZoRNwcEY+V3xcp2yMizoqIsRHxYESs2dzoCya1kiRJktS3bZqZq2fmWuX54cCtmbkycGt5DrANsHL5tR9wbq9H2gWTWkmSJElSte2Ai8vji4GvVrVfkoV7gIUjYslmBFjNpFaSJEmS+q4EboqI+yJiv7Lt45n5fHn8AvDx8nhp4JmqZ58t25rKfWolSZIkqT3NO22dbGlYZg7rdM8GmTk+Ij4G3BwR/6q+mJkZETnHI+0Bk1pJkiRJak+Tq9bJdikzx5ffX4qI3wNrAy9GxJKZ+Xw5vfil8vbxwKCqx5cp25rK6ceSJEmS1AdFxMCIWGDaMbAV8E9gOLBHedsewLXl8XBg97IK8rrAm1XTlJvGkVpJkiRJ6ps+Dvw+IqDIDS/NzBsiYiRwRUTsDYwDvl7ePwL4EjAWeAfYs/dD/m8mtZIkSZLUB2XmE8Bnu2h/Fdi8i/YEDuyF0Ori9GNJkiRJUssyqZUkSZIktSyTWkmSJElSyzKplSRJkiS1LJNaSZIkSVLLMqmVJEmSJLUsk1pJkiRJUssyqZUkSZIktSyTWkmSJElSyzKplSRJkiS1LJNaSZIkSVLLMqmVJEmSJLUsk1pJkiRJUssyqZUkSZIktSyTWkmSJElSyzKplSRJkiS1LJNaSZIkSVLLMqmVJEmSJLUsk1pJkiRJUssyqZUkSZIktSyTWkmSJElSyzKplSRJkiS1LJNaSZIkSVLLMqmVJEmSJLWseZsdgCRJktSl4xZqdgS967g3mx2B1JIcqZUkSZIktSyTWqlGt97a7AgkSZIkdWZSK83C5Mlw7LGw5ZbNjkSSJElSZ66plboxfjx885tw552w555wW7MDkiRJkjQDR2qlmRgxAlZfHe67Dy65BC68sNkRSZIkSeqsV5PaiNg6Iv4dEWMj4vAurm8UEaMjYnJE7Njp2h4R8Vj5tUfvRa2+5v334ZBD4MtfhqWWKpLa3XZrdlSSJEmSutJr048joh9wDrAl8CwwMiKGZ+YjVbc9DXwbOLjTs4sCFWAtIIH7ymdf743Y1Xc89RTssgvcey/8v/8Hp50G88/f7KgkSZIkzUxvjtSuDYzNzCcy8z3gcmC76hsy86nMfBCY2unZLwI3Z+ZrZSJ7M7B1bwStvuOaa2CNNWDMGLjiCvj5z01oJUmSpLldbya1SwPPVJ0/W7bN6Welbk2aBAcdBF/7Gqy0Etx/P+y0U7OjkiRJklSLtioUFRH7RcSoiBg1efLkZoejFvDYY/CFL8DPfgY/+AH85S+wwgrNjkqSJElSrXozqR0PDKo6X6Zsa9izmTksM9fKzLXmndfditS9yy6DNdeEceNg+HA4/XTo37/ZUUmSJEmqR28mtSOBlSNi+YjoD+wCDK/x2RuBrSJikYhYBNiqbJPq9s47sO++xf6zn/0sPPAAfOUrzY5KkiRJ0uzotaQ2MycDQyiS0THAFZn5cEQcHxHbAkTE5yPiWWAn4LyIeLh89jXgBIrEeCRwfNkm1eXhh2HtteGCC+DII+GOO2DQoFk+JkmSJGku1atzdDNzBDCiU9uxVccjKaYWd/XshcCFczRAta1M+NWvYMgQWGABuOEG2GqrZkclSZIkqafaqlCU1JW334bddoO994b11iumG5vQSpIkSe3BpFZt7YEH4HOfK4pCHX883HQTLLlks6OSJEmS1CiWCFZbyoRzz4Uf/hAWWwxuuw023rjZUUmSpHosN+nSZofQq55qdgBSi3KkVm3njTdgp53gwANhs82K0VoTWkmSJKk9mdSqrfz977DGGnDttXDKKXDddfDRjzY7KkmSJElzikmt2sLUqXDaabD++sXU47vugkMOgXn8f7gkSZLU1lxTq5b3yivw7W/D9dfD9tsXe9Auskizo5IkSZLUGxzHUku76y5YfXW4+WY4+2y4+moTWkmSJKkvMalVS5oyBYYOhU02gfnnh7/9DYYMgYhmRyZJkiSpNzn9WC3nhRdgt93glltgl13gvPNgwQWbHZUkSZKkZjCpVUu55RbYdVd48004/3zYe29HZyVJkqS+zOnHagmTJ8Mxx8BWW8Gii8LIkbDPPia0kiRJUl9nUqu53rPPwmabwYknwp57Fgntpz/d7KgkSZKk1hYRgyLi9oh4JCIejojvle3HRcT4iHig/PpS1TNHRMTYiPh3RHyxedFP5/RjzdWuvx722AMmTYJf/7qYeixJkiSpISYDP8rM0RGxAHBfRNxcXjsjM0+tvjkiVgV2AVYDlgJuiYjBmTmlV6PuxJFazZXeew8OPhj+939hmWVg9GgTWkmSJKmRMvP5zBxdHr8NjAGW7uaR7YDLM/PdzHwSGAusPecj7Z5JreY6Tz4JG24Ip50GBxwA99wDgwc3OypJkiSp5cwbEaOqvvab2Y0RsRywBnBv2TQkIh6MiAsjYpGybWngmarHnqX7JLhXOP1Yc5Wrry4qGmfClVfCjjs2OyJJkiSpZU3OzLVmdVNEfAS4Gvh+Zr4VEecCJwBZfj8N2GuORtoDjtRqrjBpEgwZUiSxgwfD/feb0EqSJElzWkR8iCKh/W1mXgOQmS9m5pTMnAqcz/QpxuOBQVWPL1O2NZVJrZru0UdhvfXgnHPghz+Eu++GFVZodlSSJElSe4uIAC4AxmTm6VXtS1bdtj3wz/J4OLBLRMwXEcsDKwN/7614Z8bpx2qq3/4W9t8f+veHP/6xKAwlSZIkqVesD+wGPBQRD5RtRwLfiIjVKaYfPwV8ByAzH46IK4BHKConH9jsysdgUqsmmTABvvtduPBC2GADuPRSGDRo1s9JkiRJaozMvBuILi6N6OaZocDQORbUbHD6sXrdww/D2mvDr34FRx0Ft99uQitJkiRp9jhSq16TWYzMHnQQLLAA3HgjbLlls6OSJEmS1MocqVWvePtt2HVX2Gcf+MIX4B//MKGVJEmS1HMmtZrj7r8f1lwTLr8cTjyxGKFdYolmRyVJkiSpHZjUao7JLLbpWXddmDixWDt71FHQr1+zI5MkSZLULkxqNUe8/jp87WswZAhssQU88ABstFGzo5IkSZLUbkxq1XD33ANrrFHsO3vqqcX3xRdvdlSSJEmS2pFJrRpm6tQiid1wQ4iAu++GH/0I5vH/ZZIkSZLmELf0UUO88grssQeMGAE77AAXXAALL9zsqCRJkiS1O8fQ1GN33gmf/SzccktRGOqqq0xoJUmSJPUOk1r1yIknwqabwsCBxVraAw4oph5LkiRJUm8wqVWPHHMM7LIL3HdfURxKkiRJknqTa2rVIxdcAHvu6eisJEmSpOYwqVWP7LVXsyOQJEmS1Jc5/ViSJEmS1LJMaiVJkiRJLcukVpIkSZLUskxqJUmSJEkty6RWkiRJktSyTGolSZIkSS3LpFaSJEmS1LJMaiVJkiRJLcukVpIkSZLUskxqJUmSJEkty6RWkiRJktSyTGolSZIkSS3LpFaSJEmS1LLmbXYAkiRJkvqg4xZqdgS967g3mx1B23KkVpIkSZLUskxqJUmSJEkty6RWkiRJktSyXFMrSZIkqdctN+nSZofQq55qdgBtzJFaSZIkSVLLMqmVJEmSJLUsk1pJkiRJUssyqZUkSZIktSyTWkmSJElSyzKplSRJkiS1LJNaSZIkSVLLMqmVJEmSJLUsk1pJkiRJUssyqZUkSZIktSyTWkmSJElSyzKplSRJkiS1LJNaSZIkSVLL6tWkNiK2joh/R8TYiDi8i+vzRcTvyuv3RsRyZftyETExIh4ov37Rm3FLkiRJkuZO8/bWiyKiH3AOsCXwLDAyIoZn5iNVt+0NvJ6ZK0XELsDJwM7ltcczc/XeileSJEmSNPfrzZHatYGxmflEZr4HXA5s1+me7YCLy+OrgM0jInoxRkmSJElSC+nNpHZp4Jmq82fLti7vyczJwJvAYuW15SPi/oj4c0RsOKeDlSRJkiTN/Xpt+nEPPQ98IjNfjYjPAX+IiNUy863qmyJiP2A/gP79+zchTEmSJElSb+rNkdrxwKCq82XKti7viYh5gYWAVzPz3cx8FSAz7wMeBwZ3fkFmDsvMtTJzrXnnbZV8XZIkSZKaY1bFfFtBbya1I4GVI2L5iOgP7AIM73TPcGCP8nhH4LbMzIj4aFloiohYAVgZeKKX4pYkSZKktlNVzHcbYFXgGxGxanOjql+vDWdm5uSIGALcCPQDLszMhyPieGBUZg4HLgB+HRFjgdcoEl+AjYDjI+J9YCqwf2a+1luxS5IkSVIb+qCYL0BETCvm+0i3T81lenWObmaOAEZ0aju26ngSsFMXz10NXD3HA5QkSZKkvqOrYr7rNCmW2RaZ2ewY5oiImApMbHYcvWheYHKzg9Ac4+fbvvxs25ufb3vz821ffrbtrS99vvMDo6vOh2XmsGknEbEjsHVm7lOe7wask5lDejfMnmnbakqZ2ZvrhZsuIkZl5lrNjkNzhp9v+/KzbW9+vu3Nz7d9+dm2Nz/fGdRSzHeu16cSP0mSJEnSB2op5jvXa9uRWkmSJEnSzM2smG+Tw6qbSW37GDbrW9TC/Hzbl59te/PzbW9+vu3Lz7a9+flW6aqYb6tp20JRkiRJkqT250htG4iIeYABmflOs2NR40REUEwD6UfxD1CTmhySGiwiPgTMR1HfYGpm/qfJIakBqv7uzkvx2U7KzKnNjUqN0sXnOzkz32tuVGqUTp9vZGZf2kmj7ZVrRvtTfMYA/8nMKU0MSQ1ioagWVya0PwJei4iPNjseNUaZ7EwB7gRGAX+KiDWaG5UaKSI+DVxP8fneBPwiIj7e3KjUU1V/d+8C7gNuA/ZvalBqmE4/m+8BbgG+1dSg1DBd/O79Q0Qs2Nyo1CgRsRpFAaT7KH7vXgls0dSg1DBOP25xEbEQcAXwPnB3Zp7U5JDUABExLzA+Mz9enu8E7JuZW0VEpH9xW1qZvP4JqGTmH8u2TwHzZuY/mxqceqSLv7ufAC4Cbs3Moc2MTT3X+fNVe/HzbV9Vv3ePzczryrZPAJtk5iVNDU4N4Uht6/sYsBzwA2A3+GDqjFpbUk6NiYiFgSWAxwFMaNvCRsBzmfnHiOgHkJn/MqFtC0n5uzUi+mXm0xSzaQ4q2/z53NqqfzYPjIiPlKN7ag+dP9/5mxyPGmdjin+wuK7q9+7TJrTtwzW1Laz8F8UtgGuAJ4AXI+LT/odxW0hg0Yi4B1icYv3Hls0NSY1QJjUrAqMBXMvTdj5IastjgGeAeSJigGvjW171z+YBwATgBOCGpkalRpn2+d5L8Xt3NLB3c0NST5W/d1cA7ofi925EDKSoaTE1M99oZnxqDJPa1jYfsB0wFPgIxdqtPSlGBdTaEngzM9cFiIgNgT8AqzQ1KvVYZmZETMGfv+2qOqmdZjLF522xqNY3w89mtZ1pn+86zQ5EjVP1e/dDABExADgTWAeYBKzdxPDUIP5HVWtbFNic4l+f5gGC4j+eTGrbQ/U0xdHAIhHxYatct4UxFEsGZhAR82bm5CbEo8YKgKqKx6sAb1sht204hby9BRSjey73aSuPAD8EKGfM7BsRi1AUjVIbcE1ta9sOOCczB2fmSpm5IvB0RDhNtcWVv0inrcsbAKwOTDShbRs3AQMjYp+IGBARC0fERvivxS2v89/diBgM/Bg4uamBqSG6+HwHlj+j1QaqP18T2rZzM/DhiPhORMxfFlodDLzd5LjUII7UtrYdgOOnnZTb+/wO2IriL69a28CIGEXxC/Z93DaibWTmexHxVYrpT4cC7wCPAt9vamBqlGl/d+ejmNr2i8y8oMkxqXGqfzZPpdiaq9LckNRALhNoQ1W/d88ADgZeAt6gHL1V63NLH0mSJElSy3L6sSRJkiSpZZnUSpIkSZJalkmtJEmSJKllmdRKkiRJklqWSa0kSZIkqWWZ1EqS1EQR8bOIuKPZcUiS1KpMaiVJqhIRH4+IMyLisYiYFBEvRcRfI+KgiPhIs+OTJEkzmrfZAUiSNLeIiOWAvwBvAccADwITgdWAfYBXgUu7eK5/Zr7Xa4FKkqQPOFIrSdJ05wJTgbUy8/LMfCQzn8zM6zLzq8BlABGREXFgRFwTEROAH0dEv4i4ICKejIiJ5UjvoRHxwe/a8p5TI+L18utMoF91AFE4NCIeL/t5KCJ27cX/DSRJaikmtZIkARGxGPBF4JzMnNDVPZmZVacVYATwP8A5FL9TxwNfB1YBjgKOBPaseuZHwL7Ad4D1KBLab3V6zYnA3sCBwKrA/wHnRcSXe/DHkySpbcWMv58lSeqbImId4B5gh8z8fVX7s8DC5elvMnP/iEjgZ5l50Cz6PIli1HeL8vw5iqR5aHk+D/Av4LnM3CQiBgKvAFtl5l1V/ZwJDM7MLzXqzytJUrtwTa0kSd3bkGJEdRgwoKp9VOcbI2J/irW3ywLzAx8CxpXXFgKWBP427f7MnBoR9wKDyqZVy3fcUCbO03wIeKoxfxxJktqLSa0kSYWxQAKfqm7MzCcBIuKdTvfPMEU5InYGzgQOBv5KUWzqQGD7OmKYtizoK8DTna69X0c/kiT1GSa1kiQBmflqRNwEDImIszPzP3V2sQFwb2b+bFpDRKxY1f+bEfE8sC5wW3k9gLWB58vbHgHeBZbNzNtm/08jSVLfYVIrSdJ0B1Bs6XNfRBwH/AOYDHwO+CxwUzfPPgp8OyK2oRj13QXYGHi96p6fAkdExKPAQ+X7lqRMajPz7Yg4FTi1THjvBD5CkQhPzcxhDfpzSpLUNiwUJUlSlYhYAjgC+DLFWtf3gTHANRTFod4u17vulJlXVT3Xn2JLoB2AAK6mWE+7V2YuV94zL/ATpldE/jXFPzCvkpmblPcEMAT4f8CKFNOYHwBOycyb59gfXJKkFmVSK0mSJElqWe5TK0mSJElqWSa1kiRJkqSWZVIrSZIkSWpZJrWSJEmSpJZlUitJkiRJalkmtZIkSZKklmVSK0mSJElqWSa1kiRJkqSWZVIrSZL0/zcKRsEoGAWjYMgCAKlQiVqDtcBbAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hktNVRFgm80D",
        "colab_type": "text"
      },
      "source": [
        "**Insight:**\n",
        "> Grade A to G, probability that person will be Defaulter, is increasing"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SjuYOqDnnq4J",
        "colab_type": "text"
      },
      "source": [
        "### understanding the impact of Annual Income on loan defualter"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VhWAR27RmT6B",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 739
        },
        "outputId": "5979426b-e0d8-441f-cb3f-221357097f88"
      },
      "source": [
        "loan_df['annual_inc_level'] = pd.qcut(loan_df['annual_inc'],q=5, labels=slots(loan_df,'annual_inc'))\n",
        "prob_chart(loan_df,\"annual_inc_level\",showtable=True)"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "display_data",
          "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>loan_status</th>\n",
              "      <th>Charged Off</th>\n",
              "      <th>Current</th>\n",
              "      <th>Fully Paid</th>\n",
              "      <th>All</th>\n",
              "      <th>Probability_Charged Off</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>annual_inc_level</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Very Low (.aprx 4000.0)</th>\n",
              "      <td>1408</td>\n",
              "      <td>135</td>\n",
              "      <td>6269</td>\n",
              "      <td>7812</td>\n",
              "      <td>0.1800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Low (.aprx 37000.0)</th>\n",
              "      <td>1198</td>\n",
              "      <td>220</td>\n",
              "      <td>6474</td>\n",
              "      <td>7892</td>\n",
              "      <td>0.1520</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Medium (.aprx 50000.0)</th>\n",
              "      <td>1152</td>\n",
              "      <td>234</td>\n",
              "      <td>6530</td>\n",
              "      <td>7916</td>\n",
              "      <td>0.1460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>High (.aprx 65000.0)</th>\n",
              "      <td>937</td>\n",
              "      <td>246</td>\n",
              "      <td>6257</td>\n",
              "      <td>7440</td>\n",
              "      <td>0.1260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Very High (.aprx 87613.0)</th>\n",
              "      <td>837</td>\n",
              "      <td>281</td>\n",
              "      <td>6647</td>\n",
              "      <td>7765</td>\n",
              "      <td>0.1080</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "loan_status                Charged Off  Current  Fully Paid   All  \\\n",
              "annual_inc_level                                                    \n",
              "Very Low (.aprx 4000.0)           1408      135        6269  7812   \n",
              "Low (.aprx 37000.0)               1198      220        6474  7892   \n",
              "Medium (.aprx 50000.0)            1152      234        6530  7916   \n",
              "High (.aprx 65000.0)               937      246        6257  7440   \n",
              "Very High (.aprx 87613.0)          837      281        6647  7765   \n",
              "\n",
              "loan_status                Probability_Charged Off  \n",
              "annual_inc_level                                    \n",
              "Very Low (.aprx 4000.0)                     0.1800  \n",
              "Low (.aprx 37000.0)                         0.1520  \n",
              "Medium (.aprx 50000.0)                      0.1460  \n",
              "High (.aprx 65000.0)                        0.1260  \n",
              "Very High (.aprx 87613.0)                   0.1080  "
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e5MsQO1WZkGZ",
        "colab_type": "text"
      },
      "source": [
        "**Insight:**\n",
        "> Annual income is one of the important factor to consider if a loan applicant will default or not <br>\n",
        "Higher the income the lower is the prbability of getting charged off"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Cf2EToTOZYLB",
        "colab_type": "text"
      },
      "source": [
        "### understanding the impact of Interest rate on loan defualter"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_sx7cQ0WZXrc",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 736
        },
        "outputId": "bba44efa-465a-4355-94e3-edb327955a07"
      },
      "source": [
        "loan_df['int_rate_level'] = pd.qcut(loan_df['int_rate'],q=5, labels=slots(loan_df,'int_rate'))\n",
        "prob_chart(loan_df,\"int_rate_level\",showtable=True)"
      ],
      "execution_count": 111,
      "outputs": [
        {
          "output_type": "display_data",
          "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>loan_status</th>\n",
              "      <th>Charged Off</th>\n",
              "      <th>Current</th>\n",
              "      <th>Fully Paid</th>\n",
              "      <th>All</th>\n",
              "      <th>Probability_Charged Off</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>int_rate_level</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Very Low (.aprx 5.0)</th>\n",
              "      <td>426</td>\n",
              "      <td>15</td>\n",
              "      <td>7475</td>\n",
              "      <td>7916</td>\n",
              "      <td>0.0540</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Low (.aprx 8.0)</th>\n",
              "      <td>841</td>\n",
              "      <td>159</td>\n",
              "      <td>7292</td>\n",
              "      <td>8292</td>\n",
              "      <td>0.1010</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Medium (.aprx 11.0)</th>\n",
              "      <td>1027</td>\n",
              "      <td>209</td>\n",
              "      <td>5926</td>\n",
              "      <td>7162</td>\n",
              "      <td>0.1430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>High (.aprx 13.0)</th>\n",
              "      <td>1316</td>\n",
              "      <td>230</td>\n",
              "      <td>6161</td>\n",
              "      <td>7707</td>\n",
              "      <td>0.1710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Very High (.aprx 15.0)</th>\n",
              "      <td>1922</td>\n",
              "      <td>503</td>\n",
              "      <td>5323</td>\n",
              "      <td>7748</td>\n",
              "      <td>0.2480</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "loan_status             Charged Off  Current  Fully Paid   All  \\\n",
              "int_rate_level                                                   \n",
              "Very Low (.aprx 5.0)            426       15        7475  7916   \n",
              "Low (.aprx 8.0)                 841      159        7292  8292   \n",
              "Medium (.aprx 11.0)            1027      209        5926  7162   \n",
              "High (.aprx 13.0)              1316      230        6161  7707   \n",
              "Very High (.aprx 15.0)         1922      503        5323  7748   \n",
              "\n",
              "loan_status             Probability_Charged Off  \n",
              "int_rate_level                                   \n",
              "Very Low (.aprx 5.0)                     0.0540  \n",
              "Low (.aprx 8.0)                          0.1010  \n",
              "Medium (.aprx 11.0)                      0.1430  \n",
              "High (.aprx 13.0)                        0.1710  \n",
              "Very High (.aprx 15.0)                   0.2480  "
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZOwOUwOGqNMQ",
        "colab_type": "text"
      },
      "source": [
        "**Insight:**\n",
        "> The heigher the interest rate is the more there is a chance that an applicant will default the loan. The probability of defaulting loan is heighest at 15% interest"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IYA2hEriq6fR",
        "colab_type": "text"
      },
      "source": [
        "### understanding the impact of Loan Amount on defualter"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jNkGa3zZqo_C",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 739
        },
        "outputId": "2f42cd9e-cbf7-4344-c68e-eec6c0c66147"
      },
      "source": [
        "loan_df['loan_amnt_level'] = pd.qcut(loan_df['loan_amnt'],q=5, labels=slots(loan_df,'loan_amnt'))\n",
        "prob_chart(loan_df,\"loan_amnt_level\",showtable=True)"
      ],
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "display_data",
          "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>loan_status</th>\n",
              "      <th>Charged Off</th>\n",
              "      <th>Current</th>\n",
              "      <th>Fully Paid</th>\n",
              "      <th>All</th>\n",
              "      <th>Probability_Charged Off</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>loan_amnt_level</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Very Low (.aprx 500.0)</th>\n",
              "      <td>1308</td>\n",
              "      <td>96</td>\n",
              "      <td>8079</td>\n",
              "      <td>9483</td>\n",
              "      <td>0.1380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Low (.aprx 5000.0)</th>\n",
              "      <td>746</td>\n",
              "      <td>86</td>\n",
              "      <td>5278</td>\n",
              "      <td>6110</td>\n",
              "      <td>0.1220</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Medium (.aprx 7800.0)</th>\n",
              "      <td>1007</td>\n",
              "      <td>86</td>\n",
              "      <td>6610</td>\n",
              "      <td>7703</td>\n",
              "      <td>0.1310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>High (.aprx 11300.0)</th>\n",
              "      <td>1103</td>\n",
              "      <td>339</td>\n",
              "      <td>6429</td>\n",
              "      <td>7871</td>\n",
              "      <td>0.1400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Very High (.aprx 16000.0)</th>\n",
              "      <td>1368</td>\n",
              "      <td>509</td>\n",
              "      <td>5781</td>\n",
              "      <td>7658</td>\n",
              "      <td>0.1790</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "loan_status                Charged Off  Current  Fully Paid   All  \\\n",
              "loan_amnt_level                                                     \n",
              "Very Low (.aprx 500.0)            1308       96        8079  9483   \n",
              "Low (.aprx 5000.0)                 746       86        5278  6110   \n",
              "Medium (.aprx 7800.0)             1007       86        6610  7703   \n",
              "High (.aprx 11300.0)              1103      339        6429  7871   \n",
              "Very High (.aprx 16000.0)         1368      509        5781  7658   \n",
              "\n",
              "loan_status                Probability_Charged Off  \n",
              "loan_amnt_level                                     \n",
              "Very Low (.aprx 500.0)                      0.1380  \n",
              "Low (.aprx 5000.0)                          0.1220  \n",
              "Medium (.aprx 7800.0)                       0.1310  \n",
              "High (.aprx 11300.0)                        0.1400  \n",
              "Very High (.aprx 16000.0)                   0.1790  "
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2UuFSiuiskf2",
        "colab_type": "text"
      },
      "source": [
        "**Insight:**\n",
        "> As the loan amount is increasing the probability of getting charged off is also increasing."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lYUt6EczvJ6S",
        "colab_type": "text"
      },
      "source": [
        "### understanding the impact of region/state on  being a loan defualter"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cQJaQw-Qu49E",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "598f4421-f6b7-4d54-f26b-3d82dee16798"
      },
      "source": [
        "# Removing  Address state those having vary small value, which will impact the Probability Analysis\n",
        "\n",
        "filter_states = loan_df.addr_state.value_counts()\n",
        "filter_states = filter_states[(filter_states < 10)]\n",
        "\n",
        "loan_filter_states = loan_df.drop(labels = loan_df[loan_df.addr_state.isin(filter_states.index)].index)\n",
        "prob_chart(loan_filter_states,\"addr_state\",True,True)"
      ],
      "execution_count": 113,
      "outputs": [
        {
          "output_type": "display_data",
          "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>loan_status</th>\n",
              "      <th>Charged Off</th>\n",
              "      <th>Current</th>\n",
              "      <th>Fully Paid</th>\n",
              "      <th>All</th>\n",
              "      <th>Probability_Charged Off</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>addr_state</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>AK</th>\n",
              "      <td>14</td>\n",
              "      <td>2</td>\n",
              "      <td>62</td>\n",
              "      <td>78</td>\n",
              "      <td>0.1790</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AL</th>\n",
              "      <td>54</td>\n",
              "      <td>17</td>\n",
              "      <td>378</td>\n",
              "      <td>449</td>\n",
              "      <td>0.1200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AR</th>\n",
              "      <td>25</td>\n",
              "      <td>10</td>\n",
              "      <td>203</td>\n",
              "      <td>238</td>\n",
              "      <td>0.1050</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AZ</th>\n",
              "      <td>118</td>\n",
              "      <td>29</td>\n",
              "      <td>709</td>\n",
              "      <td>856</td>\n",
              "      <td>0.1380</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CA</th>\n",
              "      <td>1104</td>\n",
              "      <td>149</td>\n",
              "      <td>5682</td>\n",
              "      <td>6935</td>\n",
              "      <td>0.1590</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CO</th>\n",
              "      <td>95</td>\n",
              "      <td>26</td>\n",
              "      <td>652</td>\n",
              "      <td>773</td>\n",
              "      <td>0.1230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CT</th>\n",
              "      <td>94</td>\n",
              "      <td>24</td>\n",
              "      <td>602</td>\n",
              "      <td>720</td>\n",
              "      <td>0.1310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DC</th>\n",
              "      <td>15</td>\n",
              "      <td>3</td>\n",
              "      <td>190</td>\n",
              "      <td>208</td>\n",
              "      <td>0.0720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DE</th>\n",
              "      <td>12</td>\n",
              "      <td>1</td>\n",
              "      <td>99</td>\n",
              "      <td>112</td>\n",
              "      <td>0.1070</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FL</th>\n",
              "      <td>495</td>\n",
              "      <td>85</td>\n",
              "      <td>2231</td>\n",
              "      <td>2811</td>\n",
              "      <td>0.1760</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GA</th>\n",
              "      <td>213</td>\n",
              "      <td>38</td>\n",
              "      <td>1118</td>\n",
              "      <td>1369</td>\n",
              "      <td>0.1560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HI</th>\n",
              "      <td>28</td>\n",
              "      <td>7</td>\n",
              "      <td>138</td>\n",
              "      <td>173</td>\n",
              "      <td>0.1620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>IL</th>\n",
              "      <td>194</td>\n",
              "      <td>47</td>\n",
              "      <td>1245</td>\n",
              "      <td>1486</td>\n",
              "      <td>0.1310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KS</th>\n",
              "      <td>31</td>\n",
              "      <td>16</td>\n",
              "      <td>218</td>\n",
              "      <td>265</td>\n",
              "      <td>0.1170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>KY</th>\n",
              "      <td>45</td>\n",
              "      <td>12</td>\n",
              "      <td>266</td>\n",
              "      <td>323</td>\n",
              "      <td>0.1390</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LA</th>\n",
              "      <td>52</td>\n",
              "      <td>9</td>\n",
              "      <td>363</td>\n",
              "      <td>424</td>\n",
              "      <td>0.1230</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MA</th>\n",
              "      <td>153</td>\n",
              "      <td>42</td>\n",
              "      <td>1100</td>\n",
              "      <td>1295</td>\n",
              "      <td>0.1180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MD</th>\n",
              "      <td>160</td>\n",
              "      <td>26</td>\n",
              "      <td>838</td>\n",
              "      <td>1024</td>\n",
              "      <td>0.1560</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MI</th>\n",
              "      <td>102</td>\n",
              "      <td>16</td>\n",
              "      <td>593</td>\n",
              "      <td>711</td>\n",
              "      <td>0.1430</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MN</th>\n",
              "      <td>81</td>\n",
              "      <td>10</td>\n",
              "      <td>517</td>\n",
              "      <td>608</td>\n",
              "      <td>0.1330</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MO</th>\n",
              "      <td>113</td>\n",
              "      <td>16</td>\n",
              "      <td>549</td>\n",
              "      <td>678</td>\n",
              "      <td>0.1670</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MS</th>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>16</td>\n",
              "      <td>18</td>\n",
              "      <td>0.1110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MT</th>\n",
              "      <td>11</td>\n",
              "      <td>2</td>\n",
              "      <td>71</td>\n",
              "      <td>84</td>\n",
              "      <td>0.1310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NC</th>\n",
              "      <td>114</td>\n",
              "      <td>38</td>\n",
              "      <td>622</td>\n",
              "      <td>774</td>\n",
              "      <td>0.1470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NH</th>\n",
              "      <td>25</td>\n",
              "      <td>5</td>\n",
              "      <td>138</td>\n",
              "      <td>168</td>\n",
              "      <td>0.1490</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NJ</th>\n",
              "      <td>274</td>\n",
              "      <td>57</td>\n",
              "      <td>1458</td>\n",
              "      <td>1789</td>\n",
              "      <td>0.1530</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NM</th>\n",
              "      <td>30</td>\n",
              "      <td>5</td>\n",
              "      <td>149</td>\n",
              "      <td>184</td>\n",
              "      <td>0.1630</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NV</th>\n",
              "      <td>106</td>\n",
              "      <td>17</td>\n",
              "      <td>366</td>\n",
              "      <td>489</td>\n",
              "      <td>0.2170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NY</th>\n",
              "      <td>485</td>\n",
              "      <td>109</td>\n",
              "      <td>3108</td>\n",
              "      <td>3702</td>\n",
              "      <td>0.1310</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OH</th>\n",
              "      <td>152</td>\n",
              "      <td>44</td>\n",
              "      <td>1012</td>\n",
              "      <td>1208</td>\n",
              "      <td>0.1260</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OK</th>\n",
              "      <td>40</td>\n",
              "      <td>12</td>\n",
              "      <td>244</td>\n",
              "      <td>296</td>\n",
              "      <td>0.1350</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>OR</th>\n",
              "      <td>71</td>\n",
              "      <td>16</td>\n",
              "      <td>362</td>\n",
              "      <td>449</td>\n",
              "      <td>0.1580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PA</th>\n",
              "      <td>177</td>\n",
              "      <td>49</td>\n",
              "      <td>1270</td>\n",
              "      <td>1496</td>\n",
              "      <td>0.1180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RI</th>\n",
              "      <td>24</td>\n",
              "      <td>4</td>\n",
              "      <td>164</td>\n",
              "      <td>192</td>\n",
              "      <td>0.1250</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SC</th>\n",
              "      <td>65</td>\n",
              "      <td>13</td>\n",
              "      <td>381</td>\n",
              "      <td>459</td>\n",
              "      <td>0.1420</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SD</th>\n",
              "      <td>12</td>\n",
              "      <td>2</td>\n",
              "      <td>50</td>\n",
              "      <td>64</td>\n",
              "      <td>0.1880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TN</th>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>15</td>\n",
              "      <td>17</td>\n",
              "      <td>0.1180</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TX</th>\n",
              "      <td>306</td>\n",
              "      <td>64</td>\n",
              "      <td>2283</td>\n",
              "      <td>2653</td>\n",
              "      <td>0.1150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>UT</th>\n",
              "      <td>39</td>\n",
              "      <td>6</td>\n",
              "      <td>208</td>\n",
              "      <td>253</td>\n",
              "      <td>0.1540</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VA</th>\n",
              "      <td>175</td>\n",
              "      <td>38</td>\n",
              "      <td>1163</td>\n",
              "      <td>1376</td>\n",
              "      <td>0.1270</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VT</th>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>45</td>\n",
              "      <td>52</td>\n",
              "      <td>0.1150</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WA</th>\n",
              "      <td>127</td>\n",
              "      <td>21</td>\n",
              "      <td>679</td>\n",
              "      <td>827</td>\n",
              "      <td>0.1540</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WI</th>\n",
              "      <td>62</td>\n",
              "      <td>20</td>\n",
              "      <td>369</td>\n",
              "      <td>451</td>\n",
              "      <td>0.1370</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WV</th>\n",
              "      <td>21</td>\n",
              "      <td>5</td>\n",
              "      <td>151</td>\n",
              "      <td>177</td>\n",
              "      <td>0.1190</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>WY</th>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>76</td>\n",
              "      <td>83</td>\n",
              "      <td>0.0480</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "loan_status  Charged Off  Current  Fully Paid   All  Probability_Charged Off\n",
              "addr_state                                                                  \n",
              "AK                    14        2          62    78                   0.1790\n",
              "AL                    54       17         378   449                   0.1200\n",
              "AR                    25       10         203   238                   0.1050\n",
              "AZ                   118       29         709   856                   0.1380\n",
              "CA                  1104      149        5682  6935                   0.1590\n",
              "CO                    95       26         652   773                   0.1230\n",
              "CT                    94       24         602   720                   0.1310\n",
              "DC                    15        3         190   208                   0.0720\n",
              "DE                    12        1          99   112                   0.1070\n",
              "FL                   495       85        2231  2811                   0.1760\n",
              "GA                   213       38        1118  1369                   0.1560\n",
              "HI                    28        7         138   173                   0.1620\n",
              "IL                   194       47        1245  1486                   0.1310\n",
              "KS                    31       16         218   265                   0.1170\n",
              "KY                    45       12         266   323                   0.1390\n",
              "LA                    52        9         363   424                   0.1230\n",
              "MA                   153       42        1100  1295                   0.1180\n",
              "MD                   160       26         838  1024                   0.1560\n",
              "MI                   102       16         593   711                   0.1430\n",
              "MN                    81       10         517   608                   0.1330\n",
              "MO                   113       16         549   678                   0.1670\n",
              "MS                     2        0          16    18                   0.1110\n",
              "MT                    11        2          71    84                   0.1310\n",
              "NC                   114       38         622   774                   0.1470\n",
              "NH                    25        5         138   168                   0.1490\n",
              "NJ                   274       57        1458  1789                   0.1530\n",
              "NM                    30        5         149   184                   0.1630\n",
              "NV                   106       17         366   489                   0.2170\n",
              "NY                   485      109        3108  3702                   0.1310\n",
              "OH                   152       44        1012  1208                   0.1260\n",
              "OK                    40       12         244   296                   0.1350\n",
              "OR                    71       16         362   449                   0.1580\n",
              "PA                   177       49        1270  1496                   0.1180\n",
              "RI                    24        4         164   192                   0.1250\n",
              "SC                    65       13         381   459                   0.1420\n",
              "SD                    12        2          50    64                   0.1880\n",
              "TN                     2        0          15    17                   0.1180\n",
              "TX                   306       64        2283  2653                   0.1150\n",
              "UT                    39        6         208   253                   0.1540\n",
              "VA                   175       38        1163  1376                   0.1270\n",
              "VT                     6        1          45    52                   0.1150\n",
              "WA                   127       21         679   827                   0.1540\n",
              "WI                    62       20         369   451                   0.1370\n",
              "WV                    21        5         151   177                   0.1190\n",
              "WY                     4        3          76    83                   0.0480"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YyqKI9oZva4Z",
        "colab_type": "text"
      },
      "source": [
        "**Insight:**\n",
        "> Although the chart show that there are few states like 'NV' where there the probability of being charged off is high but there is no trend in it. <br> There are many states which perform similar in terms of loan defaulter for example 'CO','IL','KS','MA' & MS dont have significant changes in the charged off probability hence the variable state can't be cosidered as a very crucial factor to determine is an applicant will default the loan or not."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "og2Y2M3axpTD",
        "colab_type": "text"
      },
      "source": [
        "### understanding the impact of DTI (Debt to Income) on Loan defualter"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hDqUcB4bxwAc",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 736
        },
        "outputId": "2328f3d8-af7c-4b71-e3b4-da6689f76d34"
      },
      "source": [
        "loan_df['dti_level'] = pd.qcut(loan_df['dti'],q=5, labels=slots(loan_df,'dti'))\n",
        "prob_chart(loan_df,\"dti_level\",showtable=True)"
      ],
      "execution_count": 114,
      "outputs": [
        {
          "output_type": "display_data",
          "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>loan_status</th>\n",
              "      <th>Charged Off</th>\n",
              "      <th>Current</th>\n",
              "      <th>Fully Paid</th>\n",
              "      <th>All</th>\n",
              "      <th>Probability_Charged Off</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>dti_level</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Very Low (.aprx 0.0)</th>\n",
              "      <td>946</td>\n",
              "      <td>156</td>\n",
              "      <td>6666</td>\n",
              "      <td>7768</td>\n",
              "      <td>0.1220</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Low (.aprx 7.0)</th>\n",
              "      <td>997</td>\n",
              "      <td>216</td>\n",
              "      <td>6549</td>\n",
              "      <td>7762</td>\n",
              "      <td>0.1280</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Medium (.aprx 12.0)</th>\n",
              "      <td>1137</td>\n",
              "      <td>208</td>\n",
              "      <td>6428</td>\n",
              "      <td>7773</td>\n",
              "      <td>0.1460</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>High (.aprx 15.0)</th>\n",
              "      <td>1196</td>\n",
              "      <td>234</td>\n",
              "      <td>6333</td>\n",
              "      <td>7763</td>\n",
              "      <td>0.1540</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Very High (.aprx 20.0)</th>\n",
              "      <td>1256</td>\n",
              "      <td>302</td>\n",
              "      <td>6201</td>\n",
              "      <td>7759</td>\n",
              "      <td>0.1620</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "loan_status             Charged Off  Current  Fully Paid   All  \\\n",
              "dti_level                                                        \n",
              "Very Low (.aprx 0.0)            946      156        6666  7768   \n",
              "Low (.aprx 7.0)                 997      216        6549  7762   \n",
              "Medium (.aprx 12.0)            1137      208        6428  7773   \n",
              "High (.aprx 15.0)              1196      234        6333  7763   \n",
              "Very High (.aprx 20.0)         1256      302        6201  7759   \n",
              "\n",
              "loan_status             Probability_Charged Off  \n",
              "dti_level                                        \n",
              "Very Low (.aprx 0.0)                     0.1220  \n",
              "Low (.aprx 7.0)                          0.1280  \n",
              "Medium (.aprx 12.0)                      0.1460  \n",
              "High (.aprx 15.0)                        0.1540  \n",
              "Very High (.aprx 20.0)                   0.1620  "
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1080x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0Z1ldhUkyMgg",
        "colab_type": "text"
      },
      "source": [
        "**Insight:**\n",
        "> The heigher the DTI ratio, the more there is a chance that an applicant will default the loan. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hqR7hVuBAQXD",
        "colab_type": "text"
      },
      "source": [
        "# Conclusion"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JCo4L4gWAmv0",
        "colab_type": "text"
      },
      "source": [
        "We have performed different types of analysis to find few of the important factors/variables that needs to be considered to determine is an applicant will default or not. Those variables are as follows:-\n",
        "\n",
        "\n",
        "1.   Grades (grade)\n",
        "> From A to G including the subgrades the trend is the probability of being a loan default increases.\n",
        "2.   Annual Income (annual_inc) \n",
        "> It has a negative co-relation, the more the income, the lesser chance to default the \n",
        "3.   Inerest Rate (int_rate)\n",
        "> It is positively co-related, the more the interest rate the more chance of an applicante to be a loan defaulter\n",
        "4.   Loan Ammount (loan_amnt)\n",
        "> It is positively co-related, the more the loan amount, the more there is a chance of an applicant to be a loan defaulter\n",
        "5.   Debt To Income ratio (dti)\n",
        "> It is positively co-related, the more the DTI, the more there is a chance of an applicant to be a loan defaulter\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    }
  ]
}