Credit Risk Evaluator.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "numpy: 1.19.2\n",
      "pandas: 1.1.5\n",
      "sklearn: 0.23.2\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "print('numpy: %s' % np.__version__)\n",
    "\n",
    "import pandas as pd\n",
    "print('pandas: %s' % pd.__version__)\n",
    "\n",
    "from pathlib import Path\n",
    "\n",
    "import sklearn\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
    "print('sklearn: %s' % sklearn.__version__)\n",
    "\n",
    "from sklearn.metrics import confusion_matrix, classification_report\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prework: clean data, data in 2 seperate files for train and test\n",
    "### Check Columns are the SAME"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Display all the columns for the dataframes (not-truncated)\n",
    "pd.set_option('display.max_columns', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def check_test_and_train_matching_columns(train_df, test_df):\n",
    "    # Display warning if columns do not match\n",
    "    inner_join = set(train_df.columns) & set(test_df.columns)\n",
    "    full_join = set(train_df.columns) | set(test_df.columns)\n",
    "    unmatching_columns = list(full_join - inner_join)\n",
    "\n",
    "    if (len(unmatching_columns) != 0):\n",
    "        print(\"Columns count does not match at...\")\n",
    "        return unmatching_columns\n",
    "    else:\n",
    "        print(\"Columns match!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Columns match!\n"
     ]
    }
   ],
   "source": [
    "# was duplicating the index file to add \"Unnamed: 0\"\n",
    "# still not dropping index column\n",
    "train_df = pd.read_csv(Path('Resources/2019loans.csv',index=False)).drop(['Unnamed: 0'],axis=1)\n",
    "test_df = pd.read_csv(Path('Resources/2020Q1loans.csv',index=False)).drop(['Unnamed: 0'],axis=1)\n",
    "check_test_and_train_matching_columns(train_df,test_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "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>index</th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>pymnt_plan</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</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_amnt</th>\n",
       "      <th>collections_12_mths_ex_med</th>\n",
       "      <th>policy_code</th>\n",
       "      <th>application_type</th>\n",
       "      <th>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>open_acc_6m</th>\n",
       "      <th>open_act_il</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_inq</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",
       "      <th>hardship_flag</th>\n",
       "      <th>debt_settlement_flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>57107</td>\n",
       "      <td>13375.0</td>\n",
       "      <td>0.1797</td>\n",
       "      <td>483.34</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>223000.0</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>29.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39728.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>w</td>\n",
       "      <td>12804.66</td>\n",
       "      <td>12804.66</td>\n",
       "      <td>953.33</td>\n",
       "      <td>953.33</td>\n",
       "      <td>570.34</td>\n",
       "      <td>382.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>483.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>465790.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>82290.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24683.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>60200.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>31053.0</td>\n",
       "      <td>7317.0</td>\n",
       "      <td>77.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>577150.0</td>\n",
       "      <td>122018.0</td>\n",
       "      <td>32000.0</td>\n",
       "      <td>170200.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>141451</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>0.1308</td>\n",
       "      <td>478.68</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>123000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>11.26</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9585.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>w</td>\n",
       "      <td>15152.97</td>\n",
       "      <td>15152.97</td>\n",
       "      <td>10037.02</td>\n",
       "      <td>10037.02</td>\n",
       "      <td>5847.03</td>\n",
       "      <td>4189.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>478.68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60769.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>18311.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4311.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>20900.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3798.0</td>\n",
       "      <td>6990.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>33.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>132750.0</td>\n",
       "      <td>27896.0</td>\n",
       "      <td>15900.0</td>\n",
       "      <td>35398.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>321143</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>448.95</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>197000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>11.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16708.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>w</td>\n",
       "      <td>15724.23</td>\n",
       "      <td>15724.23</td>\n",
       "      <td>6971.52</td>\n",
       "      <td>6971.52</td>\n",
       "      <td>4275.77</td>\n",
       "      <td>2695.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>448.95</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>617946.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>97335.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11026.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>25900.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>51496.0</td>\n",
       "      <td>5892.0</td>\n",
       "      <td>73.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>239.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>85.7</td>\n",
       "      <td>33.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>628160.0</td>\n",
       "      <td>114043.0</td>\n",
       "      <td>22600.0</td>\n",
       "      <td>90340.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11778</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>100.22</td>\n",
       "      <td>RENT</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>18.08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8809.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>w</td>\n",
       "      <td>2930.77</td>\n",
       "      <td>2930.77</td>\n",
       "      <td>81.63</td>\n",
       "      <td>81.63</td>\n",
       "      <td>69.23</td>\n",
       "      <td>12.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.76</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>568.0</td>\n",
       "      <td>20761.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11952.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2409.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>26600.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1730.0</td>\n",
       "      <td>13470.0</td>\n",
       "      <td>32.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>16.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42006.0</td>\n",
       "      <td>20761.0</td>\n",
       "      <td>19900.0</td>\n",
       "      <td>15406.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>169382</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>0.1612</td>\n",
       "      <td>1056.49</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>133000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>27.77</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65420.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>w</td>\n",
       "      <td>20778.03</td>\n",
       "      <td>20778.03</td>\n",
       "      <td>14763.99</td>\n",
       "      <td>14763.99</td>\n",
       "      <td>9221.97</td>\n",
       "      <td>5542.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1056.49</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237839.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>43636.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19804.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>88100.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18295.0</td>\n",
       "      <td>18517.0</td>\n",
       "      <td>76.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>174.0</td>\n",
       "      <td>369.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>66.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>283248.0</td>\n",
       "      <td>109056.0</td>\n",
       "      <td>79500.0</td>\n",
       "      <td>58778.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    index  loan_amnt  int_rate  installment home_ownership  annual_inc  \\\n",
       "0   57107    13375.0    0.1797       483.34       MORTGAGE    223000.0   \n",
       "1  141451    21000.0    0.1308       478.68       MORTGAGE    123000.0   \n",
       "2  321143    20000.0    0.1240       448.95       MORTGAGE    197000.0   \n",
       "3   11778     3000.0    0.1240       100.22           RENT     45000.0   \n",
       "4  169382    30000.0    0.1612      1056.49       MORTGAGE    133000.0   \n",
       "\n",
       "  verification_status loan_status pymnt_plan    dti  delinq_2yrs  \\\n",
       "0        Not Verified    low_risk          n  29.99          0.0   \n",
       "1     Source Verified    low_risk          n  11.26          2.0   \n",
       "2     Source Verified    low_risk          n  11.28          0.0   \n",
       "3        Not Verified    low_risk          n  18.08          0.0   \n",
       "4     Source Verified    low_risk          n  27.77          0.0   \n",
       "\n",
       "   inq_last_6mths  open_acc  pub_rec  revol_bal  total_acc  \\\n",
       "0             0.0      15.0      0.0    39728.0       38.0   \n",
       "1             0.0      16.0      0.0     9585.0       20.0   \n",
       "2             0.0      12.0      0.0    16708.0       36.0   \n",
       "3             0.0      12.0      1.0     8809.0       19.0   \n",
       "4             2.0      13.0      0.0    65420.0       51.0   \n",
       "\n",
       "  initial_list_status  out_prncp  out_prncp_inv  total_pymnt  total_pymnt_inv  \\\n",
       "0                   w   12804.66       12804.66       953.33           953.33   \n",
       "1                   w   15152.97       15152.97     10037.02         10037.02   \n",
       "2                   w   15724.23       15724.23      6971.52          6971.52   \n",
       "3                   w    2930.77        2930.77        81.63            81.63   \n",
       "4                   w   20778.03       20778.03     14763.99         14763.99   \n",
       "\n",
       "   total_rec_prncp  total_rec_int  total_rec_late_fee  recoveries  \\\n",
       "0           570.34         382.99                 0.0         0.0   \n",
       "1          5847.03        4189.99                 0.0         0.0   \n",
       "2          4275.77        2695.75                 0.0         0.0   \n",
       "3            69.23          12.40                 0.0         0.0   \n",
       "4          9221.97        5542.02                 0.0         0.0   \n",
       "\n",
       "   collection_recovery_fee  last_pymnt_amnt  collections_12_mths_ex_med  \\\n",
       "0                      0.0           483.34                         0.0   \n",
       "1                      0.0           478.68                         0.0   \n",
       "2                      0.0           448.95                         0.0   \n",
       "3                      0.0            85.76                         1.0   \n",
       "4                      0.0          1056.49                         0.0   \n",
       "\n",
       "   policy_code application_type  acc_now_delinq  tot_coll_amt  tot_cur_bal  \\\n",
       "0          1.0       Individual             0.0           0.0     465790.0   \n",
       "1          1.0       Individual             0.0           0.0      60769.0   \n",
       "2          1.0       Individual             0.0           0.0     617946.0   \n",
       "3          1.0       Individual             0.0         568.0      20761.0   \n",
       "4          1.0       Individual             0.0           0.0     237839.0   \n",
       "\n",
       "   open_acc_6m  open_act_il  open_il_12m  open_il_24m  mths_since_rcnt_il  \\\n",
       "0          2.0          7.0          3.0          7.0                 7.0   \n",
       "1          0.0          2.0          0.0          1.0                17.0   \n",
       "2          1.0          7.0          1.0          2.0                 5.0   \n",
       "3          2.0          4.0          2.0          2.0                 8.0   \n",
       "4          2.0          3.0          1.0          3.0                 5.0   \n",
       "\n",
       "   total_bal_il  il_util  open_rv_12m  open_rv_24m  max_bal_bc  all_util  \\\n",
       "0       82290.0     70.0          1.0          1.0     24683.0      69.0   \n",
       "1       18311.0     52.0          0.0          4.0      4311.0      50.0   \n",
       "2       97335.0    108.0          0.0          0.0     11026.0      98.0   \n",
       "3       11952.0     78.0          2.0          4.0      2409.0      49.0   \n",
       "4       43636.0     74.0          1.0          1.0     19804.0      74.0   \n",
       "\n",
       "   total_rev_hi_lim  inq_fi  total_cu_tl  inq_last_12m  acc_open_past_24mths  \\\n",
       "0           60200.0     1.0         12.0           2.0                   9.0   \n",
       "1           20900.0     1.0          0.0           1.0                   5.0   \n",
       "2           25900.0     2.0          0.0           2.0                   3.0   \n",
       "3           26600.0     4.0          4.0           2.0                   6.0   \n",
       "4           88100.0     2.0         11.0           3.0                   4.0   \n",
       "\n",
       "   avg_cur_bal  bc_open_to_buy  bc_util  chargeoff_within_12_mths  \\\n",
       "0      31053.0          7317.0     77.1                       0.0   \n",
       "1       3798.0          6990.0     56.0                       0.0   \n",
       "2      51496.0          5892.0     73.9                       0.0   \n",
       "3       1730.0         13470.0     32.3                       0.0   \n",
       "4      18295.0         18517.0     76.7                       0.0   \n",
       "\n",
       "   delinq_amnt  mo_sin_old_il_acct  mo_sin_old_rev_tl_op  \\\n",
       "0          0.0               160.0                 350.0   \n",
       "1          0.0               165.0                 142.0   \n",
       "2          0.0               254.0                 239.0   \n",
       "3          0.0               135.0                 146.0   \n",
       "4          0.0               174.0                 369.0   \n",
       "\n",
       "   mo_sin_rcnt_rev_tl_op  mo_sin_rcnt_tl  mort_acc  mths_since_recent_bc  \\\n",
       "0                    3.0             3.0       1.0                   3.0   \n",
       "1                   13.0            13.0       1.0                  17.0   \n",
       "2                   30.0             5.0       3.0                 173.0   \n",
       "3                    2.0             2.0       0.0                   2.0   \n",
       "4                    1.0             1.0       2.0                  34.0   \n",
       "\n",
       "   mths_since_recent_inq  num_accts_ever_120_pd  num_actv_bc_tl  \\\n",
       "0                    8.0                    0.0             1.0   \n",
       "1                   10.0                    1.0             5.0   \n",
       "2                    5.0                    1.0             3.0   \n",
       "3                    8.0                    0.0             5.0   \n",
       "4                    0.0                    0.0             6.0   \n",
       "\n",
       "   num_actv_rev_tl  num_bc_sats  num_bc_tl  num_il_tl  num_op_rev_tl  \\\n",
       "0              4.0          2.0        5.0       18.0            7.0   \n",
       "1              8.0          6.0        7.0        5.0           13.0   \n",
       "2              3.0          3.0        5.0       26.0            4.0   \n",
       "3              6.0          6.0        6.0        8.0            8.0   \n",
       "4              9.0          6.0       19.0       17.0            9.0   \n",
       "\n",
       "   num_rev_accts  num_rev_tl_bal_gt_0  num_sats  num_tl_120dpd_2m  \\\n",
       "0           17.0                  4.0      15.0               0.0   \n",
       "1           14.0                  8.0      16.0               0.0   \n",
       "2            7.0                  3.0      12.0               0.0   \n",
       "3           11.0                  6.0      12.0               0.0   \n",
       "4           32.0                  9.0      13.0               0.0   \n",
       "\n",
       "   num_tl_30dpd  num_tl_90g_dpd_24m  num_tl_op_past_12m  pct_tl_nvr_dlq  \\\n",
       "0           0.0                 0.0                 5.0           100.0   \n",
       "1           0.0                 0.0                 0.0            85.0   \n",
       "2           0.0                 0.0                 1.0            85.7   \n",
       "3           0.0                 0.0                 4.0           100.0   \n",
       "4           0.0                 0.0                 2.0           100.0   \n",
       "\n",
       "   percent_bc_gt_75  pub_rec_bankruptcies  tax_liens  tot_hi_cred_lim  \\\n",
       "0              50.0                   0.0        0.0         577150.0   \n",
       "1              33.3                   0.0        0.0         132750.0   \n",
       "2              33.3                   0.0        0.0         628160.0   \n",
       "3              16.7                   1.0        0.0          42006.0   \n",
       "4              66.7                   0.0        0.0         283248.0   \n",
       "\n",
       "   total_bal_ex_mort  total_bc_limit  total_il_high_credit_limit  \\\n",
       "0           122018.0         32000.0                    170200.0   \n",
       "1            27896.0         15900.0                     35398.0   \n",
       "2           114043.0         22600.0                     90340.0   \n",
       "3            20761.0         19900.0                     15406.0   \n",
       "4           109056.0         79500.0                     58778.0   \n",
       "\n",
       "  hardship_flag debt_settlement_flag  \n",
       "0             N                    N  \n",
       "1             N                    N  \n",
       "2             N                    N  \n",
       "3             N                    N  \n",
       "4             N                    N  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 12180 entries, 0 to 12179\n",
      "Data columns (total 85 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   index                       12180 non-null  int64  \n",
      " 1   loan_amnt                   12180 non-null  float64\n",
      " 2   int_rate                    12180 non-null  float64\n",
      " 3   installment                 12180 non-null  float64\n",
      " 4   home_ownership              12180 non-null  object \n",
      " 5   annual_inc                  12180 non-null  float64\n",
      " 6   verification_status         12180 non-null  object \n",
      " 7   loan_status                 12180 non-null  object \n",
      " 8   pymnt_plan                  12180 non-null  object \n",
      " 9   dti                         12180 non-null  float64\n",
      " 10  delinq_2yrs                 12180 non-null  float64\n",
      " 11  inq_last_6mths              12180 non-null  float64\n",
      " 12  open_acc                    12180 non-null  float64\n",
      " 13  pub_rec                     12180 non-null  float64\n",
      " 14  revol_bal                   12180 non-null  float64\n",
      " 15  total_acc                   12180 non-null  float64\n",
      " 16  initial_list_status         12180 non-null  object \n",
      " 17  out_prncp                   12180 non-null  float64\n",
      " 18  out_prncp_inv               12180 non-null  float64\n",
      " 19  total_pymnt                 12180 non-null  float64\n",
      " 20  total_pymnt_inv             12180 non-null  float64\n",
      " 21  total_rec_prncp             12180 non-null  float64\n",
      " 22  total_rec_int               12180 non-null  float64\n",
      " 23  total_rec_late_fee          12180 non-null  float64\n",
      " 24  recoveries                  12180 non-null  float64\n",
      " 25  collection_recovery_fee     12180 non-null  float64\n",
      " 26  last_pymnt_amnt             12180 non-null  float64\n",
      " 27  collections_12_mths_ex_med  12180 non-null  float64\n",
      " 28  policy_code                 12180 non-null  float64\n",
      " 29  application_type            12180 non-null  object \n",
      " 30  acc_now_delinq              12180 non-null  float64\n",
      " 31  tot_coll_amt                12180 non-null  float64\n",
      " 32  tot_cur_bal                 12180 non-null  float64\n",
      " 33  open_acc_6m                 12180 non-null  float64\n",
      " 34  open_act_il                 12180 non-null  float64\n",
      " 35  open_il_12m                 12180 non-null  float64\n",
      " 36  open_il_24m                 12180 non-null  float64\n",
      " 37  mths_since_rcnt_il          12180 non-null  float64\n",
      " 38  total_bal_il                12180 non-null  float64\n",
      " 39  il_util                     12180 non-null  float64\n",
      " 40  open_rv_12m                 12180 non-null  float64\n",
      " 41  open_rv_24m                 12180 non-null  float64\n",
      " 42  max_bal_bc                  12180 non-null  float64\n",
      " 43  all_util                    12180 non-null  float64\n",
      " 44  total_rev_hi_lim            12180 non-null  float64\n",
      " 45  inq_fi                      12180 non-null  float64\n",
      " 46  total_cu_tl                 12180 non-null  float64\n",
      " 47  inq_last_12m                12180 non-null  float64\n",
      " 48  acc_open_past_24mths        12180 non-null  float64\n",
      " 49  avg_cur_bal                 12180 non-null  float64\n",
      " 50  bc_open_to_buy              12180 non-null  float64\n",
      " 51  bc_util                     12180 non-null  float64\n",
      " 52  chargeoff_within_12_mths    12180 non-null  float64\n",
      " 53  delinq_amnt                 12180 non-null  float64\n",
      " 54  mo_sin_old_il_acct          12180 non-null  float64\n",
      " 55  mo_sin_old_rev_tl_op        12180 non-null  float64\n",
      " 56  mo_sin_rcnt_rev_tl_op       12180 non-null  float64\n",
      " 57  mo_sin_rcnt_tl              12180 non-null  float64\n",
      " 58  mort_acc                    12180 non-null  float64\n",
      " 59  mths_since_recent_bc        12180 non-null  float64\n",
      " 60  mths_since_recent_inq       12180 non-null  float64\n",
      " 61  num_accts_ever_120_pd       12180 non-null  float64\n",
      " 62  num_actv_bc_tl              12180 non-null  float64\n",
      " 63  num_actv_rev_tl             12180 non-null  float64\n",
      " 64  num_bc_sats                 12180 non-null  float64\n",
      " 65  num_bc_tl                   12180 non-null  float64\n",
      " 66  num_il_tl                   12180 non-null  float64\n",
      " 67  num_op_rev_tl               12180 non-null  float64\n",
      " 68  num_rev_accts               12180 non-null  float64\n",
      " 69  num_rev_tl_bal_gt_0         12180 non-null  float64\n",
      " 70  num_sats                    12180 non-null  float64\n",
      " 71  num_tl_120dpd_2m            12180 non-null  float64\n",
      " 72  num_tl_30dpd                12180 non-null  float64\n",
      " 73  num_tl_90g_dpd_24m          12180 non-null  float64\n",
      " 74  num_tl_op_past_12m          12180 non-null  float64\n",
      " 75  pct_tl_nvr_dlq              12180 non-null  float64\n",
      " 76  percent_bc_gt_75            12180 non-null  float64\n",
      " 77  pub_rec_bankruptcies        12180 non-null  float64\n",
      " 78  tax_liens                   12180 non-null  float64\n",
      " 79  tot_hi_cred_lim             12180 non-null  float64\n",
      " 80  total_bal_ex_mort           12180 non-null  float64\n",
      " 81  total_bc_limit              12180 non-null  float64\n",
      " 82  total_il_high_credit_limit  12180 non-null  float64\n",
      " 83  hardship_flag               12180 non-null  object \n",
      " 84  debt_settlement_flag        12180 non-null  object \n",
      "dtypes: float64(76), int64(1), object(8)\n",
      "memory usage: 7.9+ MB\n"
     ]
    }
   ],
   "source": [
    "train_df.info()\n",
    "# can drop the first column: is a duplicate of index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "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>index</th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>pymnt_plan</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</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_amnt</th>\n",
       "      <th>collections_12_mths_ex_med</th>\n",
       "      <th>policy_code</th>\n",
       "      <th>application_type</th>\n",
       "      <th>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>open_acc_6m</th>\n",
       "      <th>open_act_il</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_inq</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",
       "      <th>hardship_flag</th>\n",
       "      <th>debt_settlement_flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4697</th>\n",
       "      <td>77282</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>673.42</td>\n",
       "      <td>RENT</td>\n",
       "      <td>140480.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>high_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>15.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23215.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>f</td>\n",
       "      <td>26196.18</td>\n",
       "      <td>26196.18</td>\n",
       "      <td>6713.53</td>\n",
       "      <td>6713.53</td>\n",
       "      <td>3803.82</td>\n",
       "      <td>2909.71</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>110873.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>87658.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>11107.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>52300.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5835.0</td>\n",
       "      <td>26178.0</td>\n",
       "      <td>45.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>28.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>159688.0</td>\n",
       "      <td>110873.0</td>\n",
       "      <td>48400.0</td>\n",
       "      <td>107388.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4698</th>\n",
       "      <td>77291</td>\n",
       "      <td>24000.0</td>\n",
       "      <td>0.0756</td>\n",
       "      <td>747.22</td>\n",
       "      <td>RENT</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>high_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>26.81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>459.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>w</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>4526.54</td>\n",
       "      <td>4526.54</td>\n",
       "      <td>1195.80</td>\n",
       "      <td>288.56</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3042.18</td>\n",
       "      <td>547.5924</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>18928.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>18469.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>31600.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2103.0</td>\n",
       "      <td>13300.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>62375.0</td>\n",
       "      <td>18928.0</td>\n",
       "      <td>13300.0</td>\n",
       "      <td>30775.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4699</th>\n",
       "      <td>77292</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>0.2305</td>\n",
       "      <td>387.36</td>\n",
       "      <td>RENT</td>\n",
       "      <td>33000.0</td>\n",
       "      <td>Verified</td>\n",
       "      <td>high_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>38.51</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6342.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>f</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2685.91</td>\n",
       "      <td>2685.91</td>\n",
       "      <td>1534.41</td>\n",
       "      <td>1151.50</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>26680.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5901.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>13700.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5504.0</td>\n",
       "      <td>2599.0</td>\n",
       "      <td>69.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43250.0</td>\n",
       "      <td>33022.0</td>\n",
       "      <td>8500.0</td>\n",
       "      <td>29550.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4700</th>\n",
       "      <td>77297</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>0.1862</td>\n",
       "      <td>205.86</td>\n",
       "      <td>RENT</td>\n",
       "      <td>38000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>high_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>16.36</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11636.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>w</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>2075.44</td>\n",
       "      <td>2075.44</td>\n",
       "      <td>185.00</td>\n",
       "      <td>416.03</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1474.41</td>\n",
       "      <td>265.3938</td>\n",
       "      <td>205.86</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19595.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7959.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>416.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>21500.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2449.0</td>\n",
       "      <td>1084.0</td>\n",
       "      <td>27.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31357.0</td>\n",
       "      <td>19595.0</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>9657.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4701</th>\n",
       "      <td>77304</td>\n",
       "      <td>30000.0</td>\n",
       "      <td>0.2055</td>\n",
       "      <td>1123.34</td>\n",
       "      <td>RENT</td>\n",
       "      <td>180000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>high_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>12.06</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4771.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>f</td>\n",
       "      <td>28770.38</td>\n",
       "      <td>28770.38</td>\n",
       "      <td>5582.45</td>\n",
       "      <td>5582.45</td>\n",
       "      <td>1229.62</td>\n",
       "      <td>4352.83</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1123.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3835.0</td>\n",
       "      <td>209389.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>204618.0</td>\n",
       "      <td>62.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1650.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>8700.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>26174.0</td>\n",
       "      <td>1768.0</td>\n",
       "      <td>68.4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>33.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>218686.0</td>\n",
       "      <td>209389.0</td>\n",
       "      <td>5600.0</td>\n",
       "      <td>209986.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      index  loan_amnt  int_rate  installment home_ownership  annual_inc  \\\n",
       "4697  77282    30000.0    0.1240       673.42           RENT    140480.0   \n",
       "4698  77291    24000.0    0.0756       747.22           RENT     50000.0   \n",
       "4699  77292    10000.0    0.2305       387.36           RENT     33000.0   \n",
       "4700  77297     8000.0    0.1862       205.86           RENT     38000.0   \n",
       "4701  77304    30000.0    0.2055      1123.34           RENT    180000.0   \n",
       "\n",
       "     verification_status loan_status pymnt_plan    dti  delinq_2yrs  \\\n",
       "4697     Source Verified   high_risk          n  15.74          0.0   \n",
       "4698        Not Verified   high_risk          n  26.81          0.0   \n",
       "4699            Verified   high_risk          n  38.51          0.0   \n",
       "4700     Source Verified   high_risk          n  16.36          0.0   \n",
       "4701     Source Verified   high_risk          n  12.06          0.0   \n",
       "\n",
       "      inq_last_6mths  open_acc  pub_rec  revol_bal  total_acc  \\\n",
       "4697             0.0      20.0      0.0    23215.0       32.0   \n",
       "4698             0.0       9.0      0.0      459.0       10.0   \n",
       "4699             2.0       7.0      0.0     6342.0       13.0   \n",
       "4700             1.0       8.0      1.0    11636.0       20.0   \n",
       "4701             0.0       8.0      0.0     4771.0       24.0   \n",
       "\n",
       "     initial_list_status  out_prncp  out_prncp_inv  total_pymnt  \\\n",
       "4697                   f   26196.18       26196.18      6713.53   \n",
       "4698                   w       0.00           0.00      4526.54   \n",
       "4699                   f       0.00           0.00      2685.91   \n",
       "4700                   w       0.00           0.00      2075.44   \n",
       "4701                   f   28770.38       28770.38      5582.45   \n",
       "\n",
       "      total_pymnt_inv  total_rec_prncp  total_rec_int  total_rec_late_fee  \\\n",
       "4697          6713.53          3803.82        2909.71                 0.0   \n",
       "4698          4526.54          1195.80         288.56                 0.0   \n",
       "4699          2685.91          1534.41        1151.50                 0.0   \n",
       "4700          2075.44           185.00         416.03                 0.0   \n",
       "4701          5582.45          1229.62        4352.83                 0.0   \n",
       "\n",
       "      recoveries  collection_recovery_fee  last_pymnt_amnt  \\\n",
       "4697        0.00                   0.0000             0.00   \n",
       "4698     3042.18                 547.5924             0.00   \n",
       "4699        0.00                   0.0000             0.00   \n",
       "4700     1474.41                 265.3938           205.86   \n",
       "4701        0.00                   0.0000          1123.34   \n",
       "\n",
       "      collections_12_mths_ex_med  policy_code application_type  \\\n",
       "4697                         0.0          1.0       Individual   \n",
       "4698                         1.0          1.0       Individual   \n",
       "4699                         0.0          1.0       Individual   \n",
       "4700                         0.0          1.0       Individual   \n",
       "4701                         0.0          1.0       Individual   \n",
       "\n",
       "      acc_now_delinq  tot_coll_amt  tot_cur_bal  open_acc_6m  open_act_il  \\\n",
       "4697             0.0           0.0     110873.0          2.0         11.0   \n",
       "4698             0.0          84.0      18928.0          1.0          2.0   \n",
       "4699             0.0           0.0      33022.0          2.0          3.0   \n",
       "4700             0.0           0.0      19595.0          3.0          1.0   \n",
       "4701             0.0        3835.0     209389.0          0.0          3.0   \n",
       "\n",
       "      open_il_12m  open_il_24m  mths_since_rcnt_il  total_bal_il  il_util  \\\n",
       "4697          2.0          7.0                 4.0       87658.0     82.0   \n",
       "4698          1.0          1.0                 8.0       18469.0     60.0   \n",
       "4699          3.0          5.0                 3.0       26680.0     90.0   \n",
       "4700          0.0          1.0                15.0        7959.0     82.0   \n",
       "4701          1.0          1.0                 9.0      204618.0     62.0   \n",
       "\n",
       "      open_rv_12m  open_rv_24m  max_bal_bc  all_util  total_rev_hi_lim  \\\n",
       "4697          0.0          5.0     11107.0      69.0           52300.0   \n",
       "4698          1.0          2.0         0.0      30.0           31600.0   \n",
       "4699          2.0          3.0      5901.0      76.0           13700.0   \n",
       "4700          2.0          3.0       416.0      63.0           21500.0   \n",
       "4701          0.0          2.0      1650.0      61.0            8700.0   \n",
       "\n",
       "      inq_fi  total_cu_tl  inq_last_12m  acc_open_past_24mths  avg_cur_bal  \\\n",
       "4697     1.0          0.0           2.0                  12.0       5835.0   \n",
       "4698     0.0          0.0           0.0                   3.0       2103.0   \n",
       "4699     2.0          0.0           3.0                   8.0       5504.0   \n",
       "4700     1.0          5.0           1.0                   5.0       2449.0   \n",
       "4701     2.0          0.0           2.0                   3.0      26174.0   \n",
       "\n",
       "      bc_open_to_buy  bc_util  chargeoff_within_12_mths  delinq_amnt  \\\n",
       "4697         26178.0     45.9                       0.0          0.0   \n",
       "4698         13300.0      0.0                       0.0          0.0   \n",
       "4699          2599.0     69.4                       0.0          0.0   \n",
       "4700          1084.0     27.7                       0.0          0.0   \n",
       "4701          1768.0     68.4                       0.0          0.0   \n",
       "\n",
       "      mo_sin_old_il_acct  mo_sin_old_rev_tl_op  mo_sin_rcnt_rev_tl_op  \\\n",
       "4697                95.0                 103.0                   15.0   \n",
       "4698                45.0                  49.0                    5.0   \n",
       "4699                88.0                  62.0                   10.0   \n",
       "4700               121.0                 100.0                    2.0   \n",
       "4701               178.0                  37.0                   19.0   \n",
       "\n",
       "      mo_sin_rcnt_tl  mort_acc  mths_since_recent_bc  mths_since_recent_inq  \\\n",
       "4697             4.0       2.0                  15.0                    2.0   \n",
       "4698             5.0       0.0                  19.0                   18.0   \n",
       "4699             3.0       0.0                  11.0                    5.0   \n",
       "4700             2.0       0.0                  26.0                    5.0   \n",
       "4701             9.0       0.0                  19.0                    9.0   \n",
       "\n",
       "      num_accts_ever_120_pd  num_actv_bc_tl  num_actv_rev_tl  num_bc_sats  \\\n",
       "4697                    0.0             6.0              7.0          8.0   \n",
       "4698                    0.0             0.0              2.0          2.0   \n",
       "4699                    0.0             1.0              2.0          1.0   \n",
       "4700                    1.0             1.0              5.0          1.0   \n",
       "4701                    0.0             3.0              5.0          3.0   \n",
       "\n",
       "      num_bc_tl  num_il_tl  num_op_rev_tl  num_rev_accts  num_rev_tl_bal_gt_0  \\\n",
       "4697        8.0       20.0            9.0           10.0                  7.0   \n",
       "4698        2.0        3.0            7.0            7.0                  2.0   \n",
       "4699        3.0        7.0            3.0            6.0                  2.0   \n",
       "4700        7.0        5.0            6.0           13.0                  5.0   \n",
       "4701        3.0       18.0            5.0            5.0                  5.0   \n",
       "\n",
       "      num_sats  num_tl_120dpd_2m  num_tl_30dpd  num_tl_90g_dpd_24m  \\\n",
       "4697      20.0               0.0           0.0                 0.0   \n",
       "4698       9.0               0.0           0.0                 0.0   \n",
       "4699       7.0               0.0           0.0                 0.0   \n",
       "4700       8.0               0.0           0.0                 0.0   \n",
       "4701       8.0               0.0           0.0                 0.0   \n",
       "\n",
       "      num_tl_op_past_12m  pct_tl_nvr_dlq  percent_bc_gt_75  \\\n",
       "4697                 2.0           100.0              28.6   \n",
       "4698                 2.0           100.0               0.0   \n",
       "4699                 5.0           100.0               0.0   \n",
       "4700                 3.0            95.0               0.0   \n",
       "4701                 1.0           100.0              33.3   \n",
       "\n",
       "      pub_rec_bankruptcies  tax_liens  tot_hi_cred_lim  total_bal_ex_mort  \\\n",
       "4697                   0.0        0.0         159688.0           110873.0   \n",
       "4698                   0.0        0.0          62375.0            18928.0   \n",
       "4699                   0.0        0.0          43250.0            33022.0   \n",
       "4700                   1.0        0.0          31357.0            19595.0   \n",
       "4701                   0.0        0.0         218686.0           209389.0   \n",
       "\n",
       "      total_bc_limit  total_il_high_credit_limit hardship_flag  \\\n",
       "4697         48400.0                    107388.0             N   \n",
       "4698         13300.0                     30775.0             N   \n",
       "4699          8500.0                     29550.0             N   \n",
       "4700          1500.0                      9657.0             N   \n",
       "4701          5600.0                    209986.0             N   \n",
       "\n",
       "     debt_settlement_flag  \n",
       "4697                    N  \n",
       "4698                    N  \n",
       "4699                    N  \n",
       "4700                    N  \n",
       "4701                    N  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 4702 entries, 0 to 4701\n",
      "Data columns (total 85 columns):\n",
      " #   Column                      Non-Null Count  Dtype  \n",
      "---  ------                      --------------  -----  \n",
      " 0   index                       4702 non-null   int64  \n",
      " 1   loan_amnt                   4702 non-null   float64\n",
      " 2   int_rate                    4702 non-null   float64\n",
      " 3   installment                 4702 non-null   float64\n",
      " 4   home_ownership              4702 non-null   object \n",
      " 5   annual_inc                  4702 non-null   float64\n",
      " 6   verification_status         4702 non-null   object \n",
      " 7   loan_status                 4702 non-null   object \n",
      " 8   pymnt_plan                  4702 non-null   object \n",
      " 9   dti                         4702 non-null   float64\n",
      " 10  delinq_2yrs                 4702 non-null   float64\n",
      " 11  inq_last_6mths              4702 non-null   float64\n",
      " 12  open_acc                    4702 non-null   float64\n",
      " 13  pub_rec                     4702 non-null   float64\n",
      " 14  revol_bal                   4702 non-null   float64\n",
      " 15  total_acc                   4702 non-null   float64\n",
      " 16  initial_list_status         4702 non-null   object \n",
      " 17  out_prncp                   4702 non-null   float64\n",
      " 18  out_prncp_inv               4702 non-null   float64\n",
      " 19  total_pymnt                 4702 non-null   float64\n",
      " 20  total_pymnt_inv             4702 non-null   float64\n",
      " 21  total_rec_prncp             4702 non-null   float64\n",
      " 22  total_rec_int               4702 non-null   float64\n",
      " 23  total_rec_late_fee          4702 non-null   float64\n",
      " 24  recoveries                  4702 non-null   float64\n",
      " 25  collection_recovery_fee     4702 non-null   float64\n",
      " 26  last_pymnt_amnt             4702 non-null   float64\n",
      " 27  collections_12_mths_ex_med  4702 non-null   float64\n",
      " 28  policy_code                 4702 non-null   float64\n",
      " 29  application_type            4702 non-null   object \n",
      " 30  acc_now_delinq              4702 non-null   float64\n",
      " 31  tot_coll_amt                4702 non-null   float64\n",
      " 32  tot_cur_bal                 4702 non-null   float64\n",
      " 33  open_acc_6m                 4702 non-null   float64\n",
      " 34  open_act_il                 4702 non-null   float64\n",
      " 35  open_il_12m                 4702 non-null   float64\n",
      " 36  open_il_24m                 4702 non-null   float64\n",
      " 37  mths_since_rcnt_il          4702 non-null   float64\n",
      " 38  total_bal_il                4702 non-null   float64\n",
      " 39  il_util                     4702 non-null   float64\n",
      " 40  open_rv_12m                 4702 non-null   float64\n",
      " 41  open_rv_24m                 4702 non-null   float64\n",
      " 42  max_bal_bc                  4702 non-null   float64\n",
      " 43  all_util                    4702 non-null   float64\n",
      " 44  total_rev_hi_lim            4702 non-null   float64\n",
      " 45  inq_fi                      4702 non-null   float64\n",
      " 46  total_cu_tl                 4702 non-null   float64\n",
      " 47  inq_last_12m                4702 non-null   float64\n",
      " 48  acc_open_past_24mths        4702 non-null   float64\n",
      " 49  avg_cur_bal                 4702 non-null   float64\n",
      " 50  bc_open_to_buy              4702 non-null   float64\n",
      " 51  bc_util                     4702 non-null   float64\n",
      " 52  chargeoff_within_12_mths    4702 non-null   float64\n",
      " 53  delinq_amnt                 4702 non-null   float64\n",
      " 54  mo_sin_old_il_acct          4702 non-null   float64\n",
      " 55  mo_sin_old_rev_tl_op        4702 non-null   float64\n",
      " 56  mo_sin_rcnt_rev_tl_op       4702 non-null   float64\n",
      " 57  mo_sin_rcnt_tl              4702 non-null   float64\n",
      " 58  mort_acc                    4702 non-null   float64\n",
      " 59  mths_since_recent_bc        4702 non-null   float64\n",
      " 60  mths_since_recent_inq       4702 non-null   float64\n",
      " 61  num_accts_ever_120_pd       4702 non-null   float64\n",
      " 62  num_actv_bc_tl              4702 non-null   float64\n",
      " 63  num_actv_rev_tl             4702 non-null   float64\n",
      " 64  num_bc_sats                 4702 non-null   float64\n",
      " 65  num_bc_tl                   4702 non-null   float64\n",
      " 66  num_il_tl                   4702 non-null   float64\n",
      " 67  num_op_rev_tl               4702 non-null   float64\n",
      " 68  num_rev_accts               4702 non-null   float64\n",
      " 69  num_rev_tl_bal_gt_0         4702 non-null   float64\n",
      " 70  num_sats                    4702 non-null   float64\n",
      " 71  num_tl_120dpd_2m            4702 non-null   float64\n",
      " 72  num_tl_30dpd                4702 non-null   float64\n",
      " 73  num_tl_90g_dpd_24m          4702 non-null   float64\n",
      " 74  num_tl_op_past_12m          4702 non-null   float64\n",
      " 75  pct_tl_nvr_dlq              4702 non-null   float64\n",
      " 76  percent_bc_gt_75            4702 non-null   float64\n",
      " 77  pub_rec_bankruptcies        4702 non-null   float64\n",
      " 78  tax_liens                   4702 non-null   float64\n",
      " 79  tot_hi_cred_lim             4702 non-null   float64\n",
      " 80  total_bal_ex_mort           4702 non-null   float64\n",
      " 81  total_bc_limit              4702 non-null   float64\n",
      " 82  total_il_high_credit_limit  4702 non-null   float64\n",
      " 83  hardship_flag               4702 non-null   object \n",
      " 84  debt_settlement_flag        4702 non-null   object \n",
      "dtypes: float64(76), int64(1), object(8)\n",
      "memory usage: 3.0+ MB\n"
     ]
    }
   ],
   "source": [
    "test_df.info()\n",
    "# can drop the first column: is a duplicate of info: happened when grabbing the files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# index is a column, don't want as a feature so remove from test and train\n",
    "# delete column without having to reassign dataFrame\n",
    "# df.drop('column_name', axis=1, inplace=True)\n",
    "train_df.drop('index', axis=1, inplace=True)\n",
    "test_df.drop('index', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "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>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>pymnt_plan</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</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_amnt</th>\n",
       "      <th>collections_12_mths_ex_med</th>\n",
       "      <th>policy_code</th>\n",
       "      <th>application_type</th>\n",
       "      <th>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>open_acc_6m</th>\n",
       "      <th>open_act_il</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_inq</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",
       "      <th>hardship_flag</th>\n",
       "      <th>debt_settlement_flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13375.0</td>\n",
       "      <td>0.1797</td>\n",
       "      <td>483.34</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>223000.0</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>29.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39728.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>w</td>\n",
       "      <td>12804.66</td>\n",
       "      <td>12804.66</td>\n",
       "      <td>953.33</td>\n",
       "      <td>953.33</td>\n",
       "      <td>570.34</td>\n",
       "      <td>382.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>483.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>465790.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>82290.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24683.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>60200.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>31053.0</td>\n",
       "      <td>7317.0</td>\n",
       "      <td>77.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>577150.0</td>\n",
       "      <td>122018.0</td>\n",
       "      <td>32000.0</td>\n",
       "      <td>170200.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21000.0</td>\n",
       "      <td>0.1308</td>\n",
       "      <td>478.68</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>123000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>11.26</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9585.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>w</td>\n",
       "      <td>15152.97</td>\n",
       "      <td>15152.97</td>\n",
       "      <td>10037.02</td>\n",
       "      <td>10037.02</td>\n",
       "      <td>5847.03</td>\n",
       "      <td>4189.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>478.68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60769.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>18311.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4311.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>20900.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3798.0</td>\n",
       "      <td>6990.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>33.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>132750.0</td>\n",
       "      <td>27896.0</td>\n",
       "      <td>15900.0</td>\n",
       "      <td>35398.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20000.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>448.95</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>197000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>11.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16708.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>w</td>\n",
       "      <td>15724.23</td>\n",
       "      <td>15724.23</td>\n",
       "      <td>6971.52</td>\n",
       "      <td>6971.52</td>\n",
       "      <td>4275.77</td>\n",
       "      <td>2695.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>448.95</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>617946.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>97335.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11026.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>25900.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>51496.0</td>\n",
       "      <td>5892.0</td>\n",
       "      <td>73.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>239.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>85.7</td>\n",
       "      <td>33.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>628160.0</td>\n",
       "      <td>114043.0</td>\n",
       "      <td>22600.0</td>\n",
       "      <td>90340.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>100.22</td>\n",
       "      <td>RENT</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>18.08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8809.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>w</td>\n",
       "      <td>2930.77</td>\n",
       "      <td>2930.77</td>\n",
       "      <td>81.63</td>\n",
       "      <td>81.63</td>\n",
       "      <td>69.23</td>\n",
       "      <td>12.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.76</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>568.0</td>\n",
       "      <td>20761.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11952.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2409.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>26600.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1730.0</td>\n",
       "      <td>13470.0</td>\n",
       "      <td>32.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>16.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42006.0</td>\n",
       "      <td>20761.0</td>\n",
       "      <td>19900.0</td>\n",
       "      <td>15406.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>0.1612</td>\n",
       "      <td>1056.49</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>133000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>27.77</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65420.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>w</td>\n",
       "      <td>20778.03</td>\n",
       "      <td>20778.03</td>\n",
       "      <td>14763.99</td>\n",
       "      <td>14763.99</td>\n",
       "      <td>9221.97</td>\n",
       "      <td>5542.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1056.49</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237839.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>43636.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19804.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>88100.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18295.0</td>\n",
       "      <td>18517.0</td>\n",
       "      <td>76.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>174.0</td>\n",
       "      <td>369.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>66.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>283248.0</td>\n",
       "      <td>109056.0</td>\n",
       "      <td>79500.0</td>\n",
       "      <td>58778.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  int_rate  installment home_ownership  annual_inc  \\\n",
       "0    13375.0    0.1797       483.34       MORTGAGE    223000.0   \n",
       "1    21000.0    0.1308       478.68       MORTGAGE    123000.0   \n",
       "2    20000.0    0.1240       448.95       MORTGAGE    197000.0   \n",
       "3     3000.0    0.1240       100.22           RENT     45000.0   \n",
       "4    30000.0    0.1612      1056.49       MORTGAGE    133000.0   \n",
       "\n",
       "  verification_status loan_status pymnt_plan    dti  delinq_2yrs  \\\n",
       "0        Not Verified    low_risk          n  29.99          0.0   \n",
       "1     Source Verified    low_risk          n  11.26          2.0   \n",
       "2     Source Verified    low_risk          n  11.28          0.0   \n",
       "3        Not Verified    low_risk          n  18.08          0.0   \n",
       "4     Source Verified    low_risk          n  27.77          0.0   \n",
       "\n",
       "   inq_last_6mths  open_acc  pub_rec  revol_bal  total_acc  \\\n",
       "0             0.0      15.0      0.0    39728.0       38.0   \n",
       "1             0.0      16.0      0.0     9585.0       20.0   \n",
       "2             0.0      12.0      0.0    16708.0       36.0   \n",
       "3             0.0      12.0      1.0     8809.0       19.0   \n",
       "4             2.0      13.0      0.0    65420.0       51.0   \n",
       "\n",
       "  initial_list_status  out_prncp  out_prncp_inv  total_pymnt  total_pymnt_inv  \\\n",
       "0                   w   12804.66       12804.66       953.33           953.33   \n",
       "1                   w   15152.97       15152.97     10037.02         10037.02   \n",
       "2                   w   15724.23       15724.23      6971.52          6971.52   \n",
       "3                   w    2930.77        2930.77        81.63            81.63   \n",
       "4                   w   20778.03       20778.03     14763.99         14763.99   \n",
       "\n",
       "   total_rec_prncp  total_rec_int  total_rec_late_fee  recoveries  \\\n",
       "0           570.34         382.99                 0.0         0.0   \n",
       "1          5847.03        4189.99                 0.0         0.0   \n",
       "2          4275.77        2695.75                 0.0         0.0   \n",
       "3            69.23          12.40                 0.0         0.0   \n",
       "4          9221.97        5542.02                 0.0         0.0   \n",
       "\n",
       "   collection_recovery_fee  last_pymnt_amnt  collections_12_mths_ex_med  \\\n",
       "0                      0.0           483.34                         0.0   \n",
       "1                      0.0           478.68                         0.0   \n",
       "2                      0.0           448.95                         0.0   \n",
       "3                      0.0            85.76                         1.0   \n",
       "4                      0.0          1056.49                         0.0   \n",
       "\n",
       "   policy_code application_type  acc_now_delinq  tot_coll_amt  tot_cur_bal  \\\n",
       "0          1.0       Individual             0.0           0.0     465790.0   \n",
       "1          1.0       Individual             0.0           0.0      60769.0   \n",
       "2          1.0       Individual             0.0           0.0     617946.0   \n",
       "3          1.0       Individual             0.0         568.0      20761.0   \n",
       "4          1.0       Individual             0.0           0.0     237839.0   \n",
       "\n",
       "   open_acc_6m  open_act_il  open_il_12m  open_il_24m  mths_since_rcnt_il  \\\n",
       "0          2.0          7.0          3.0          7.0                 7.0   \n",
       "1          0.0          2.0          0.0          1.0                17.0   \n",
       "2          1.0          7.0          1.0          2.0                 5.0   \n",
       "3          2.0          4.0          2.0          2.0                 8.0   \n",
       "4          2.0          3.0          1.0          3.0                 5.0   \n",
       "\n",
       "   total_bal_il  il_util  open_rv_12m  open_rv_24m  max_bal_bc  all_util  \\\n",
       "0       82290.0     70.0          1.0          1.0     24683.0      69.0   \n",
       "1       18311.0     52.0          0.0          4.0      4311.0      50.0   \n",
       "2       97335.0    108.0          0.0          0.0     11026.0      98.0   \n",
       "3       11952.0     78.0          2.0          4.0      2409.0      49.0   \n",
       "4       43636.0     74.0          1.0          1.0     19804.0      74.0   \n",
       "\n",
       "   total_rev_hi_lim  inq_fi  total_cu_tl  inq_last_12m  acc_open_past_24mths  \\\n",
       "0           60200.0     1.0         12.0           2.0                   9.0   \n",
       "1           20900.0     1.0          0.0           1.0                   5.0   \n",
       "2           25900.0     2.0          0.0           2.0                   3.0   \n",
       "3           26600.0     4.0          4.0           2.0                   6.0   \n",
       "4           88100.0     2.0         11.0           3.0                   4.0   \n",
       "\n",
       "   avg_cur_bal  bc_open_to_buy  bc_util  chargeoff_within_12_mths  \\\n",
       "0      31053.0          7317.0     77.1                       0.0   \n",
       "1       3798.0          6990.0     56.0                       0.0   \n",
       "2      51496.0          5892.0     73.9                       0.0   \n",
       "3       1730.0         13470.0     32.3                       0.0   \n",
       "4      18295.0         18517.0     76.7                       0.0   \n",
       "\n",
       "   delinq_amnt  mo_sin_old_il_acct  mo_sin_old_rev_tl_op  \\\n",
       "0          0.0               160.0                 350.0   \n",
       "1          0.0               165.0                 142.0   \n",
       "2          0.0               254.0                 239.0   \n",
       "3          0.0               135.0                 146.0   \n",
       "4          0.0               174.0                 369.0   \n",
       "\n",
       "   mo_sin_rcnt_rev_tl_op  mo_sin_rcnt_tl  mort_acc  mths_since_recent_bc  \\\n",
       "0                    3.0             3.0       1.0                   3.0   \n",
       "1                   13.0            13.0       1.0                  17.0   \n",
       "2                   30.0             5.0       3.0                 173.0   \n",
       "3                    2.0             2.0       0.0                   2.0   \n",
       "4                    1.0             1.0       2.0                  34.0   \n",
       "\n",
       "   mths_since_recent_inq  num_accts_ever_120_pd  num_actv_bc_tl  \\\n",
       "0                    8.0                    0.0             1.0   \n",
       "1                   10.0                    1.0             5.0   \n",
       "2                    5.0                    1.0             3.0   \n",
       "3                    8.0                    0.0             5.0   \n",
       "4                    0.0                    0.0             6.0   \n",
       "\n",
       "   num_actv_rev_tl  num_bc_sats  num_bc_tl  num_il_tl  num_op_rev_tl  \\\n",
       "0              4.0          2.0        5.0       18.0            7.0   \n",
       "1              8.0          6.0        7.0        5.0           13.0   \n",
       "2              3.0          3.0        5.0       26.0            4.0   \n",
       "3              6.0          6.0        6.0        8.0            8.0   \n",
       "4              9.0          6.0       19.0       17.0            9.0   \n",
       "\n",
       "   num_rev_accts  num_rev_tl_bal_gt_0  num_sats  num_tl_120dpd_2m  \\\n",
       "0           17.0                  4.0      15.0               0.0   \n",
       "1           14.0                  8.0      16.0               0.0   \n",
       "2            7.0                  3.0      12.0               0.0   \n",
       "3           11.0                  6.0      12.0               0.0   \n",
       "4           32.0                  9.0      13.0               0.0   \n",
       "\n",
       "   num_tl_30dpd  num_tl_90g_dpd_24m  num_tl_op_past_12m  pct_tl_nvr_dlq  \\\n",
       "0           0.0                 0.0                 5.0           100.0   \n",
       "1           0.0                 0.0                 0.0            85.0   \n",
       "2           0.0                 0.0                 1.0            85.7   \n",
       "3           0.0                 0.0                 4.0           100.0   \n",
       "4           0.0                 0.0                 2.0           100.0   \n",
       "\n",
       "   percent_bc_gt_75  pub_rec_bankruptcies  tax_liens  tot_hi_cred_lim  \\\n",
       "0              50.0                   0.0        0.0         577150.0   \n",
       "1              33.3                   0.0        0.0         132750.0   \n",
       "2              33.3                   0.0        0.0         628160.0   \n",
       "3              16.7                   1.0        0.0          42006.0   \n",
       "4              66.7                   0.0        0.0         283248.0   \n",
       "\n",
       "   total_bal_ex_mort  total_bc_limit  total_il_high_credit_limit  \\\n",
       "0           122018.0         32000.0                    170200.0   \n",
       "1            27896.0         15900.0                     35398.0   \n",
       "2           114043.0         22600.0                     90340.0   \n",
       "3            20761.0         19900.0                     15406.0   \n",
       "4           109056.0         79500.0                     58778.0   \n",
       "\n",
       "  hardship_flag debt_settlement_flag  \n",
       "0             N                    N  \n",
       "1             N                    N  \n",
       "2             N                    N  \n",
       "3             N                    N  \n",
       "4             N                    N  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>pymnt_plan</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</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_amnt</th>\n",
       "      <th>collections_12_mths_ex_med</th>\n",
       "      <th>policy_code</th>\n",
       "      <th>application_type</th>\n",
       "      <th>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>open_acc_6m</th>\n",
       "      <th>open_act_il</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_inq</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",
       "      <th>hardship_flag</th>\n",
       "      <th>debt_settlement_flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13375.0</td>\n",
       "      <td>0.1797</td>\n",
       "      <td>483.34</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>223000.0</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>29.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39728.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>w</td>\n",
       "      <td>12804.66</td>\n",
       "      <td>12804.66</td>\n",
       "      <td>953.33</td>\n",
       "      <td>953.33</td>\n",
       "      <td>570.34</td>\n",
       "      <td>382.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>483.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>465790.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>82290.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24683.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>60200.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>31053.0</td>\n",
       "      <td>7317.0</td>\n",
       "      <td>77.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>577150.0</td>\n",
       "      <td>122018.0</td>\n",
       "      <td>32000.0</td>\n",
       "      <td>170200.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21000.0</td>\n",
       "      <td>0.1308</td>\n",
       "      <td>478.68</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>123000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>11.26</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9585.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>w</td>\n",
       "      <td>15152.97</td>\n",
       "      <td>15152.97</td>\n",
       "      <td>10037.02</td>\n",
       "      <td>10037.02</td>\n",
       "      <td>5847.03</td>\n",
       "      <td>4189.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>478.68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60769.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>18311.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4311.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>20900.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3798.0</td>\n",
       "      <td>6990.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>33.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>132750.0</td>\n",
       "      <td>27896.0</td>\n",
       "      <td>15900.0</td>\n",
       "      <td>35398.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20000.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>448.95</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>197000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>11.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16708.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>w</td>\n",
       "      <td>15724.23</td>\n",
       "      <td>15724.23</td>\n",
       "      <td>6971.52</td>\n",
       "      <td>6971.52</td>\n",
       "      <td>4275.77</td>\n",
       "      <td>2695.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>448.95</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>617946.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>97335.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11026.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>25900.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>51496.0</td>\n",
       "      <td>5892.0</td>\n",
       "      <td>73.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>239.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>85.7</td>\n",
       "      <td>33.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>628160.0</td>\n",
       "      <td>114043.0</td>\n",
       "      <td>22600.0</td>\n",
       "      <td>90340.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>100.22</td>\n",
       "      <td>RENT</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>18.08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8809.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>w</td>\n",
       "      <td>2930.77</td>\n",
       "      <td>2930.77</td>\n",
       "      <td>81.63</td>\n",
       "      <td>81.63</td>\n",
       "      <td>69.23</td>\n",
       "      <td>12.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.76</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>568.0</td>\n",
       "      <td>20761.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11952.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2409.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>26600.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1730.0</td>\n",
       "      <td>13470.0</td>\n",
       "      <td>32.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>16.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42006.0</td>\n",
       "      <td>20761.0</td>\n",
       "      <td>19900.0</td>\n",
       "      <td>15406.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>0.1612</td>\n",
       "      <td>1056.49</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>133000.0</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>low_risk</td>\n",
       "      <td>n</td>\n",
       "      <td>27.77</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65420.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>w</td>\n",
       "      <td>20778.03</td>\n",
       "      <td>20778.03</td>\n",
       "      <td>14763.99</td>\n",
       "      <td>14763.99</td>\n",
       "      <td>9221.97</td>\n",
       "      <td>5542.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1056.49</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Individual</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237839.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>43636.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19804.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>88100.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18295.0</td>\n",
       "      <td>18517.0</td>\n",
       "      <td>76.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>174.0</td>\n",
       "      <td>369.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>66.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>283248.0</td>\n",
       "      <td>109056.0</td>\n",
       "      <td>79500.0</td>\n",
       "      <td>58778.0</td>\n",
       "      <td>N</td>\n",
       "      <td>N</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  int_rate  installment home_ownership  annual_inc  \\\n",
       "0    13375.0    0.1797       483.34       MORTGAGE    223000.0   \n",
       "1    21000.0    0.1308       478.68       MORTGAGE    123000.0   \n",
       "2    20000.0    0.1240       448.95       MORTGAGE    197000.0   \n",
       "3     3000.0    0.1240       100.22           RENT     45000.0   \n",
       "4    30000.0    0.1612      1056.49       MORTGAGE    133000.0   \n",
       "\n",
       "  verification_status loan_status pymnt_plan    dti  delinq_2yrs  \\\n",
       "0        Not Verified    low_risk          n  29.99          0.0   \n",
       "1     Source Verified    low_risk          n  11.26          2.0   \n",
       "2     Source Verified    low_risk          n  11.28          0.0   \n",
       "3        Not Verified    low_risk          n  18.08          0.0   \n",
       "4     Source Verified    low_risk          n  27.77          0.0   \n",
       "\n",
       "   inq_last_6mths  open_acc  pub_rec  revol_bal  total_acc  \\\n",
       "0             0.0      15.0      0.0    39728.0       38.0   \n",
       "1             0.0      16.0      0.0     9585.0       20.0   \n",
       "2             0.0      12.0      0.0    16708.0       36.0   \n",
       "3             0.0      12.0      1.0     8809.0       19.0   \n",
       "4             2.0      13.0      0.0    65420.0       51.0   \n",
       "\n",
       "  initial_list_status  out_prncp  out_prncp_inv  total_pymnt  total_pymnt_inv  \\\n",
       "0                   w   12804.66       12804.66       953.33           953.33   \n",
       "1                   w   15152.97       15152.97     10037.02         10037.02   \n",
       "2                   w   15724.23       15724.23      6971.52          6971.52   \n",
       "3                   w    2930.77        2930.77        81.63            81.63   \n",
       "4                   w   20778.03       20778.03     14763.99         14763.99   \n",
       "\n",
       "   total_rec_prncp  total_rec_int  total_rec_late_fee  recoveries  \\\n",
       "0           570.34         382.99                 0.0         0.0   \n",
       "1          5847.03        4189.99                 0.0         0.0   \n",
       "2          4275.77        2695.75                 0.0         0.0   \n",
       "3            69.23          12.40                 0.0         0.0   \n",
       "4          9221.97        5542.02                 0.0         0.0   \n",
       "\n",
       "   collection_recovery_fee  last_pymnt_amnt  collections_12_mths_ex_med  \\\n",
       "0                      0.0           483.34                         0.0   \n",
       "1                      0.0           478.68                         0.0   \n",
       "2                      0.0           448.95                         0.0   \n",
       "3                      0.0            85.76                         1.0   \n",
       "4                      0.0          1056.49                         0.0   \n",
       "\n",
       "   policy_code application_type  acc_now_delinq  tot_coll_amt  tot_cur_bal  \\\n",
       "0          1.0       Individual             0.0           0.0     465790.0   \n",
       "1          1.0       Individual             0.0           0.0      60769.0   \n",
       "2          1.0       Individual             0.0           0.0     617946.0   \n",
       "3          1.0       Individual             0.0         568.0      20761.0   \n",
       "4          1.0       Individual             0.0           0.0     237839.0   \n",
       "\n",
       "   open_acc_6m  open_act_il  open_il_12m  open_il_24m  mths_since_rcnt_il  \\\n",
       "0          2.0          7.0          3.0          7.0                 7.0   \n",
       "1          0.0          2.0          0.0          1.0                17.0   \n",
       "2          1.0          7.0          1.0          2.0                 5.0   \n",
       "3          2.0          4.0          2.0          2.0                 8.0   \n",
       "4          2.0          3.0          1.0          3.0                 5.0   \n",
       "\n",
       "   total_bal_il  il_util  open_rv_12m  open_rv_24m  max_bal_bc  all_util  \\\n",
       "0       82290.0     70.0          1.0          1.0     24683.0      69.0   \n",
       "1       18311.0     52.0          0.0          4.0      4311.0      50.0   \n",
       "2       97335.0    108.0          0.0          0.0     11026.0      98.0   \n",
       "3       11952.0     78.0          2.0          4.0      2409.0      49.0   \n",
       "4       43636.0     74.0          1.0          1.0     19804.0      74.0   \n",
       "\n",
       "   total_rev_hi_lim  inq_fi  total_cu_tl  inq_last_12m  acc_open_past_24mths  \\\n",
       "0           60200.0     1.0         12.0           2.0                   9.0   \n",
       "1           20900.0     1.0          0.0           1.0                   5.0   \n",
       "2           25900.0     2.0          0.0           2.0                   3.0   \n",
       "3           26600.0     4.0          4.0           2.0                   6.0   \n",
       "4           88100.0     2.0         11.0           3.0                   4.0   \n",
       "\n",
       "   avg_cur_bal  bc_open_to_buy  bc_util  chargeoff_within_12_mths  \\\n",
       "0      31053.0          7317.0     77.1                       0.0   \n",
       "1       3798.0          6990.0     56.0                       0.0   \n",
       "2      51496.0          5892.0     73.9                       0.0   \n",
       "3       1730.0         13470.0     32.3                       0.0   \n",
       "4      18295.0         18517.0     76.7                       0.0   \n",
       "\n",
       "   delinq_amnt  mo_sin_old_il_acct  mo_sin_old_rev_tl_op  \\\n",
       "0          0.0               160.0                 350.0   \n",
       "1          0.0               165.0                 142.0   \n",
       "2          0.0               254.0                 239.0   \n",
       "3          0.0               135.0                 146.0   \n",
       "4          0.0               174.0                 369.0   \n",
       "\n",
       "   mo_sin_rcnt_rev_tl_op  mo_sin_rcnt_tl  mort_acc  mths_since_recent_bc  \\\n",
       "0                    3.0             3.0       1.0                   3.0   \n",
       "1                   13.0            13.0       1.0                  17.0   \n",
       "2                   30.0             5.0       3.0                 173.0   \n",
       "3                    2.0             2.0       0.0                   2.0   \n",
       "4                    1.0             1.0       2.0                  34.0   \n",
       "\n",
       "   mths_since_recent_inq  num_accts_ever_120_pd  num_actv_bc_tl  \\\n",
       "0                    8.0                    0.0             1.0   \n",
       "1                   10.0                    1.0             5.0   \n",
       "2                    5.0                    1.0             3.0   \n",
       "3                    8.0                    0.0             5.0   \n",
       "4                    0.0                    0.0             6.0   \n",
       "\n",
       "   num_actv_rev_tl  num_bc_sats  num_bc_tl  num_il_tl  num_op_rev_tl  \\\n",
       "0              4.0          2.0        5.0       18.0            7.0   \n",
       "1              8.0          6.0        7.0        5.0           13.0   \n",
       "2              3.0          3.0        5.0       26.0            4.0   \n",
       "3              6.0          6.0        6.0        8.0            8.0   \n",
       "4              9.0          6.0       19.0       17.0            9.0   \n",
       "\n",
       "   num_rev_accts  num_rev_tl_bal_gt_0  num_sats  num_tl_120dpd_2m  \\\n",
       "0           17.0                  4.0      15.0               0.0   \n",
       "1           14.0                  8.0      16.0               0.0   \n",
       "2            7.0                  3.0      12.0               0.0   \n",
       "3           11.0                  6.0      12.0               0.0   \n",
       "4           32.0                  9.0      13.0               0.0   \n",
       "\n",
       "   num_tl_30dpd  num_tl_90g_dpd_24m  num_tl_op_past_12m  pct_tl_nvr_dlq  \\\n",
       "0           0.0                 0.0                 5.0           100.0   \n",
       "1           0.0                 0.0                 0.0            85.0   \n",
       "2           0.0                 0.0                 1.0            85.7   \n",
       "3           0.0                 0.0                 4.0           100.0   \n",
       "4           0.0                 0.0                 2.0           100.0   \n",
       "\n",
       "   percent_bc_gt_75  pub_rec_bankruptcies  tax_liens  tot_hi_cred_lim  \\\n",
       "0              50.0                   0.0        0.0         577150.0   \n",
       "1              33.3                   0.0        0.0         132750.0   \n",
       "2              33.3                   0.0        0.0         628160.0   \n",
       "3              16.7                   1.0        0.0          42006.0   \n",
       "4              66.7                   0.0        0.0         283248.0   \n",
       "\n",
       "   total_bal_ex_mort  total_bc_limit  total_il_high_credit_limit  \\\n",
       "0           122018.0         32000.0                    170200.0   \n",
       "1            27896.0         15900.0                     35398.0   \n",
       "2           114043.0         22600.0                     90340.0   \n",
       "3            20761.0         19900.0                     15406.0   \n",
       "4           109056.0         79500.0                     58778.0   \n",
       "\n",
       "  hardship_flag debt_settlement_flag  \n",
       "0             N                    N  \n",
       "1             N                    N  \n",
       "2             N                    N  \n",
       "3             N                    N  \n",
       "4             N                    N  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Review some of the data we have:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "high_risk    6090\n",
       "low_risk     6090\n",
       "Name: loan_status, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# some of our key X value, and loan amount , home_ownership, annual_inc see if balanced\n",
    "# our y value: loan_status. : particularly high_risk (known label)\n",
    "# not sure of any exact specifications, so keep all as is (review notes in readme.md)\n",
    "train_df['loan_status'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nloan_amt value counts\\n10000.0    1042\\n20000.0     695\\n15000.0     588\\n40000.0     580\\n12000.0     466\\n           ... \\n23050.0       1\\n17050.0       1\\n30050.0       1\\n6650.0        1\\n35325.0       1\\n\\nhome_ownership value counts:\\nMORTGAGE    5800\\nRENT        4944\\nOWN         1371\\nANY           65\\n\\n\\nannual_inc value counts:\\n60000.0     423\\n75000.0     390\\n65000.0     388\\n80000.0     368\\n50000.0     366\\n           ... \\n36465.0       1\\n111843.0      1\\n63092.0       1\\n76980.0       1\\n46080.0       1\\n\\nloan_status:\\nlow_risk     6090\\nhigh_risk    6090\\n\\n'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "loan_amt value counts\n",
    "10000.0    1042\n",
    "20000.0     695\n",
    "15000.0     588\n",
    "40000.0     580\n",
    "12000.0     466\n",
    "           ... \n",
    "23050.0       1\n",
    "17050.0       1\n",
    "30050.0       1\n",
    "6650.0        1\n",
    "35325.0       1\n",
    "\n",
    "home_ownership value counts:\n",
    "MORTGAGE    5800\n",
    "RENT        4944\n",
    "OWN         1371\n",
    "ANY           65\n",
    "\n",
    "\n",
    "annual_inc value counts:\n",
    "60000.0     423\n",
    "75000.0     390\n",
    "65000.0     388\n",
    "80000.0     368\n",
    "50000.0     366\n",
    "           ... \n",
    "36465.0       1\n",
    "111843.0      1\n",
    "63092.0       1\n",
    "76980.0       1\n",
    "46080.0       1\n",
    "\n",
    "loan_status:\n",
    "low_risk     6090\n",
    "high_risk    6090\n",
    "\n",
    "'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preprocessing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\ni  Label\\tloan_status\\n0\\t1\\t   low_risk\\n1\\t1\\t   low_risk\\n2\\t1\\t   low_risk\\n3\\t1\\t   low_risk\\n12175\\t0\\thigh_risk\\n12176\\t0\\thigh_risk\\n12177\\t0\\thigh_risk\\n12178\\t0\\thigh_risk\\n12179\\t0\\thigh_risk\\n\\n'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert categorical data to numeric (where object to numeric -> get_dummies) and separate target feature(X) \n",
    "# Want dummies for all categorical (sometimes using one-hot-key could use individually to make categorical values)\n",
    "#For training data\n",
    "y_train = LabelEncoder().fit_transform(train_df['loan_status'])\n",
    "#train_df['Label'] = LabelEncoder().fit_transform(train_df['loan_status'])\n",
    "\n",
    "'''\n",
    "i  Label\tloan_status\n",
    "0\t1\t   low_risk\n",
    "1\t1\t   low_risk\n",
    "2\t1\t   low_risk\n",
    "3\t1\t   low_risk\n",
    "12175\t0\thigh_risk\n",
    "12176\t0\thigh_risk\n",
    "12177\t0\thigh_risk\n",
    "12178\t0\thigh_risk\n",
    "12179\t0\thigh_risk\n",
    "\n",
    "'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# want to set the high and low risk columns for y, labels as dict\n",
    "X_train = train_df.drop(columns = [\"loan_status\"])   # remove the y label\n",
    "X_train = pd.get_dummies(X_train)  # converts all categorical data to numeric"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "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>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</th>\n",
       "      <th>total_acc</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_amnt</th>\n",
       "      <th>collections_12_mths_ex_med</th>\n",
       "      <th>policy_code</th>\n",
       "      <th>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>open_acc_6m</th>\n",
       "      <th>open_act_il</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_inq</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",
       "      <th>home_ownership_ANY</th>\n",
       "      <th>home_ownership_MORTGAGE</th>\n",
       "      <th>home_ownership_OWN</th>\n",
       "      <th>home_ownership_RENT</th>\n",
       "      <th>verification_status_Not Verified</th>\n",
       "      <th>verification_status_Source Verified</th>\n",
       "      <th>verification_status_Verified</th>\n",
       "      <th>pymnt_plan_n</th>\n",
       "      <th>initial_list_status_f</th>\n",
       "      <th>initial_list_status_w</th>\n",
       "      <th>application_type_Individual</th>\n",
       "      <th>application_type_Joint App</th>\n",
       "      <th>hardship_flag_N</th>\n",
       "      <th>hardship_flag_Y</th>\n",
       "      <th>debt_settlement_flag_N</th>\n",
       "      <th>debt_settlement_flag_Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>13375.0</td>\n",
       "      <td>0.1797</td>\n",
       "      <td>483.34</td>\n",
       "      <td>223000.0</td>\n",
       "      <td>29.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>39728.0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>12804.66</td>\n",
       "      <td>12804.66</td>\n",
       "      <td>953.33</td>\n",
       "      <td>953.33</td>\n",
       "      <td>570.34</td>\n",
       "      <td>382.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>483.34</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>465790.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>82290.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>24683.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>60200.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>31053.0</td>\n",
       "      <td>7317.0</td>\n",
       "      <td>77.1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>577150.0</td>\n",
       "      <td>122018.0</td>\n",
       "      <td>32000.0</td>\n",
       "      <td>170200.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>21000.0</td>\n",
       "      <td>0.1308</td>\n",
       "      <td>478.68</td>\n",
       "      <td>123000.0</td>\n",
       "      <td>11.26</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9585.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>15152.97</td>\n",
       "      <td>15152.97</td>\n",
       "      <td>10037.02</td>\n",
       "      <td>10037.02</td>\n",
       "      <td>5847.03</td>\n",
       "      <td>4189.99</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>478.68</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60769.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>18311.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4311.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>20900.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3798.0</td>\n",
       "      <td>6990.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>33.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>132750.0</td>\n",
       "      <td>27896.0</td>\n",
       "      <td>15900.0</td>\n",
       "      <td>35398.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20000.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>448.95</td>\n",
       "      <td>197000.0</td>\n",
       "      <td>11.28</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16708.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>15724.23</td>\n",
       "      <td>15724.23</td>\n",
       "      <td>6971.52</td>\n",
       "      <td>6971.52</td>\n",
       "      <td>4275.77</td>\n",
       "      <td>2695.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>448.95</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>617946.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>97335.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11026.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>25900.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>51496.0</td>\n",
       "      <td>5892.0</td>\n",
       "      <td>73.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>239.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>85.7</td>\n",
       "      <td>33.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>628160.0</td>\n",
       "      <td>114043.0</td>\n",
       "      <td>22600.0</td>\n",
       "      <td>90340.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3000.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>100.22</td>\n",
       "      <td>45000.0</td>\n",
       "      <td>18.08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8809.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>2930.77</td>\n",
       "      <td>2930.77</td>\n",
       "      <td>81.63</td>\n",
       "      <td>81.63</td>\n",
       "      <td>69.23</td>\n",
       "      <td>12.40</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.76</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>568.0</td>\n",
       "      <td>20761.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11952.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2409.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>26600.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1730.0</td>\n",
       "      <td>13470.0</td>\n",
       "      <td>32.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>16.7</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42006.0</td>\n",
       "      <td>20761.0</td>\n",
       "      <td>19900.0</td>\n",
       "      <td>15406.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30000.0</td>\n",
       "      <td>0.1612</td>\n",
       "      <td>1056.49</td>\n",
       "      <td>133000.0</td>\n",
       "      <td>27.77</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>65420.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>20778.03</td>\n",
       "      <td>20778.03</td>\n",
       "      <td>14763.99</td>\n",
       "      <td>14763.99</td>\n",
       "      <td>9221.97</td>\n",
       "      <td>5542.02</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1056.49</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>237839.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>43636.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>19804.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>88100.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>18295.0</td>\n",
       "      <td>18517.0</td>\n",
       "      <td>76.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>174.0</td>\n",
       "      <td>369.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>66.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>283248.0</td>\n",
       "      <td>109056.0</td>\n",
       "      <td>79500.0</td>\n",
       "      <td>58778.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  int_rate  installment  annual_inc    dti  delinq_2yrs  \\\n",
       "0    13375.0    0.1797       483.34    223000.0  29.99          0.0   \n",
       "1    21000.0    0.1308       478.68    123000.0  11.26          2.0   \n",
       "2    20000.0    0.1240       448.95    197000.0  11.28          0.0   \n",
       "3     3000.0    0.1240       100.22     45000.0  18.08          0.0   \n",
       "4    30000.0    0.1612      1056.49    133000.0  27.77          0.0   \n",
       "\n",
       "   inq_last_6mths  open_acc  pub_rec  revol_bal  total_acc  out_prncp  \\\n",
       "0             0.0      15.0      0.0    39728.0       38.0   12804.66   \n",
       "1             0.0      16.0      0.0     9585.0       20.0   15152.97   \n",
       "2             0.0      12.0      0.0    16708.0       36.0   15724.23   \n",
       "3             0.0      12.0      1.0     8809.0       19.0    2930.77   \n",
       "4             2.0      13.0      0.0    65420.0       51.0   20778.03   \n",
       "\n",
       "   out_prncp_inv  total_pymnt  total_pymnt_inv  total_rec_prncp  \\\n",
       "0       12804.66       953.33           953.33           570.34   \n",
       "1       15152.97     10037.02         10037.02          5847.03   \n",
       "2       15724.23      6971.52          6971.52          4275.77   \n",
       "3        2930.77        81.63            81.63            69.23   \n",
       "4       20778.03     14763.99         14763.99          9221.97   \n",
       "\n",
       "   total_rec_int  total_rec_late_fee  recoveries  collection_recovery_fee  \\\n",
       "0         382.99                 0.0         0.0                      0.0   \n",
       "1        4189.99                 0.0         0.0                      0.0   \n",
       "2        2695.75                 0.0         0.0                      0.0   \n",
       "3          12.40                 0.0         0.0                      0.0   \n",
       "4        5542.02                 0.0         0.0                      0.0   \n",
       "\n",
       "   last_pymnt_amnt  collections_12_mths_ex_med  policy_code  acc_now_delinq  \\\n",
       "0           483.34                         0.0          1.0             0.0   \n",
       "1           478.68                         0.0          1.0             0.0   \n",
       "2           448.95                         0.0          1.0             0.0   \n",
       "3            85.76                         1.0          1.0             0.0   \n",
       "4          1056.49                         0.0          1.0             0.0   \n",
       "\n",
       "   tot_coll_amt  tot_cur_bal  open_acc_6m  open_act_il  open_il_12m  \\\n",
       "0           0.0     465790.0          2.0          7.0          3.0   \n",
       "1           0.0      60769.0          0.0          2.0          0.0   \n",
       "2           0.0     617946.0          1.0          7.0          1.0   \n",
       "3         568.0      20761.0          2.0          4.0          2.0   \n",
       "4           0.0     237839.0          2.0          3.0          1.0   \n",
       "\n",
       "   open_il_24m  mths_since_rcnt_il  total_bal_il  il_util  open_rv_12m  \\\n",
       "0          7.0                 7.0       82290.0     70.0          1.0   \n",
       "1          1.0                17.0       18311.0     52.0          0.0   \n",
       "2          2.0                 5.0       97335.0    108.0          0.0   \n",
       "3          2.0                 8.0       11952.0     78.0          2.0   \n",
       "4          3.0                 5.0       43636.0     74.0          1.0   \n",
       "\n",
       "   open_rv_24m  max_bal_bc  all_util  total_rev_hi_lim  inq_fi  total_cu_tl  \\\n",
       "0          1.0     24683.0      69.0           60200.0     1.0         12.0   \n",
       "1          4.0      4311.0      50.0           20900.0     1.0          0.0   \n",
       "2          0.0     11026.0      98.0           25900.0     2.0          0.0   \n",
       "3          4.0      2409.0      49.0           26600.0     4.0          4.0   \n",
       "4          1.0     19804.0      74.0           88100.0     2.0         11.0   \n",
       "\n",
       "   inq_last_12m  acc_open_past_24mths  avg_cur_bal  bc_open_to_buy  bc_util  \\\n",
       "0           2.0                   9.0      31053.0          7317.0     77.1   \n",
       "1           1.0                   5.0       3798.0          6990.0     56.0   \n",
       "2           2.0                   3.0      51496.0          5892.0     73.9   \n",
       "3           2.0                   6.0       1730.0         13470.0     32.3   \n",
       "4           3.0                   4.0      18295.0         18517.0     76.7   \n",
       "\n",
       "   chargeoff_within_12_mths  delinq_amnt  mo_sin_old_il_acct  \\\n",
       "0                       0.0          0.0               160.0   \n",
       "1                       0.0          0.0               165.0   \n",
       "2                       0.0          0.0               254.0   \n",
       "3                       0.0          0.0               135.0   \n",
       "4                       0.0          0.0               174.0   \n",
       "\n",
       "   mo_sin_old_rev_tl_op  mo_sin_rcnt_rev_tl_op  mo_sin_rcnt_tl  mort_acc  \\\n",
       "0                 350.0                    3.0             3.0       1.0   \n",
       "1                 142.0                   13.0            13.0       1.0   \n",
       "2                 239.0                   30.0             5.0       3.0   \n",
       "3                 146.0                    2.0             2.0       0.0   \n",
       "4                 369.0                    1.0             1.0       2.0   \n",
       "\n",
       "   mths_since_recent_bc  mths_since_recent_inq  num_accts_ever_120_pd  \\\n",
       "0                   3.0                    8.0                    0.0   \n",
       "1                  17.0                   10.0                    1.0   \n",
       "2                 173.0                    5.0                    1.0   \n",
       "3                   2.0                    8.0                    0.0   \n",
       "4                  34.0                    0.0                    0.0   \n",
       "\n",
       "   num_actv_bc_tl  num_actv_rev_tl  num_bc_sats  num_bc_tl  num_il_tl  \\\n",
       "0             1.0              4.0          2.0        5.0       18.0   \n",
       "1             5.0              8.0          6.0        7.0        5.0   \n",
       "2             3.0              3.0          3.0        5.0       26.0   \n",
       "3             5.0              6.0          6.0        6.0        8.0   \n",
       "4             6.0              9.0          6.0       19.0       17.0   \n",
       "\n",
       "   num_op_rev_tl  num_rev_accts  num_rev_tl_bal_gt_0  num_sats  \\\n",
       "0            7.0           17.0                  4.0      15.0   \n",
       "1           13.0           14.0                  8.0      16.0   \n",
       "2            4.0            7.0                  3.0      12.0   \n",
       "3            8.0           11.0                  6.0      12.0   \n",
       "4            9.0           32.0                  9.0      13.0   \n",
       "\n",
       "   num_tl_120dpd_2m  num_tl_30dpd  num_tl_90g_dpd_24m  num_tl_op_past_12m  \\\n",
       "0               0.0           0.0                 0.0                 5.0   \n",
       "1               0.0           0.0                 0.0                 0.0   \n",
       "2               0.0           0.0                 0.0                 1.0   \n",
       "3               0.0           0.0                 0.0                 4.0   \n",
       "4               0.0           0.0                 0.0                 2.0   \n",
       "\n",
       "   pct_tl_nvr_dlq  percent_bc_gt_75  pub_rec_bankruptcies  tax_liens  \\\n",
       "0           100.0              50.0                   0.0        0.0   \n",
       "1            85.0              33.3                   0.0        0.0   \n",
       "2            85.7              33.3                   0.0        0.0   \n",
       "3           100.0              16.7                   1.0        0.0   \n",
       "4           100.0              66.7                   0.0        0.0   \n",
       "\n",
       "   tot_hi_cred_lim  total_bal_ex_mort  total_bc_limit  \\\n",
       "0         577150.0           122018.0         32000.0   \n",
       "1         132750.0            27896.0         15900.0   \n",
       "2         628160.0           114043.0         22600.0   \n",
       "3          42006.0            20761.0         19900.0   \n",
       "4         283248.0           109056.0         79500.0   \n",
       "\n",
       "   total_il_high_credit_limit  home_ownership_ANY  home_ownership_MORTGAGE  \\\n",
       "0                    170200.0                   0                        1   \n",
       "1                     35398.0                   0                        1   \n",
       "2                     90340.0                   0                        1   \n",
       "3                     15406.0                   0                        0   \n",
       "4                     58778.0                   0                        1   \n",
       "\n",
       "   home_ownership_OWN  home_ownership_RENT  verification_status_Not Verified  \\\n",
       "0                   0                    0                                 1   \n",
       "1                   0                    0                                 0   \n",
       "2                   0                    0                                 0   \n",
       "3                   0                    1                                 1   \n",
       "4                   0                    0                                 0   \n",
       "\n",
       "   verification_status_Source Verified  verification_status_Verified  \\\n",
       "0                                    0                             0   \n",
       "1                                    1                             0   \n",
       "2                                    1                             0   \n",
       "3                                    0                             0   \n",
       "4                                    1                             0   \n",
       "\n",
       "   pymnt_plan_n  initial_list_status_f  initial_list_status_w  \\\n",
       "0             1                      0                      1   \n",
       "1             1                      0                      1   \n",
       "2             1                      0                      1   \n",
       "3             1                      0                      1   \n",
       "4             1                      0                      1   \n",
       "\n",
       "   application_type_Individual  application_type_Joint App  hardship_flag_N  \\\n",
       "0                            1                           0                1   \n",
       "1                            1                           0                1   \n",
       "2                            1                           0                1   \n",
       "3                            1                           0                1   \n",
       "4                            1                           0                1   \n",
       "\n",
       "   hardship_flag_Y  debt_settlement_flag_N  debt_settlement_flag_Y  \n",
       "0                0                       1                       0  \n",
       "1                0                       1                       0  \n",
       "2                0                       1                       0  \n",
       "3                0                       1                       0  \n",
       "4                0                       1                       0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 1 1 ... 0 0 0]\n",
      "12180\n",
      "12180\n",
      "(12180, 92) (12180,)\n"
     ]
    }
   ],
   "source": [
    "print(y_train)\n",
    "# low risk = 1\n",
    "# high risk = 0\n",
    "print(len(y_train))\n",
    "print(len(X_train))\n",
    "print(X_train.shape, y_train.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "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>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</th>\n",
       "      <th>total_acc</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_amnt</th>\n",
       "      <th>collections_12_mths_ex_med</th>\n",
       "      <th>policy_code</th>\n",
       "      <th>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>open_acc_6m</th>\n",
       "      <th>open_act_il</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_inq</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",
       "      <th>home_ownership_ANY</th>\n",
       "      <th>home_ownership_MORTGAGE</th>\n",
       "      <th>home_ownership_OWN</th>\n",
       "      <th>home_ownership_RENT</th>\n",
       "      <th>verification_status_Not Verified</th>\n",
       "      <th>verification_status_Source Verified</th>\n",
       "      <th>verification_status_Verified</th>\n",
       "      <th>pymnt_plan_n</th>\n",
       "      <th>initial_list_status_f</th>\n",
       "      <th>initial_list_status_w</th>\n",
       "      <th>application_type_Individual</th>\n",
       "      <th>application_type_Joint App</th>\n",
       "      <th>hardship_flag_N</th>\n",
       "      <th>hardship_flag_Y</th>\n",
       "      <th>debt_settlement_flag_N</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40000.0</td>\n",
       "      <td>0.0819</td>\n",
       "      <td>814.70</td>\n",
       "      <td>140000.0</td>\n",
       "      <td>19.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9471.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>33249.95</td>\n",
       "      <td>33249.95</td>\n",
       "      <td>9740.00</td>\n",
       "      <td>9740.00</td>\n",
       "      <td>6750.05</td>\n",
       "      <td>2989.95</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>814.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>377773.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>61443.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3218.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>86500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>20987.0</td>\n",
       "      <td>65129.0</td>\n",
       "      <td>12.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>97.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>527975.0</td>\n",
       "      <td>70914.0</td>\n",
       "      <td>74600.0</td>\n",
       "      <td>99475.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6000.0</td>\n",
       "      <td>0.1524</td>\n",
       "      <td>208.70</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>11.52</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1280.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6185.59</td>\n",
       "      <td>6185.59</td>\n",
       "      <td>6000.00</td>\n",
       "      <td>185.59</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5773.27</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23460.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>22180.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>713.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2933.0</td>\n",
       "      <td>4680.0</td>\n",
       "      <td>20.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>66.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34628.0</td>\n",
       "      <td>23460.0</td>\n",
       "      <td>5900.0</td>\n",
       "      <td>23628.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3600.0</td>\n",
       "      <td>0.1695</td>\n",
       "      <td>128.27</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>6.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4757.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3603.73</td>\n",
       "      <td>3603.73</td>\n",
       "      <td>3600.00</td>\n",
       "      <td>3.73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3607.12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19183.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>14426.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4757.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>8100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3837.0</td>\n",
       "      <td>2543.0</td>\n",
       "      <td>65.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23100.0</td>\n",
       "      <td>19183.0</td>\n",
       "      <td>7300.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20000.0</td>\n",
       "      <td>0.1524</td>\n",
       "      <td>478.33</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>12.13</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12731.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>17624.06</td>\n",
       "      <td>17624.06</td>\n",
       "      <td>4766.37</td>\n",
       "      <td>4766.37</td>\n",
       "      <td>2375.94</td>\n",
       "      <td>2390.43</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>478.33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43817.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>31086.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5917.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>20500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7303.0</td>\n",
       "      <td>6496.0</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56481.0</td>\n",
       "      <td>43817.0</td>\n",
       "      <td>13800.0</td>\n",
       "      <td>35981.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3600.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>120.27</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>16.08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10413.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3602.48</td>\n",
       "      <td>3602.48</td>\n",
       "      <td>3600.00</td>\n",
       "      <td>2.48</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3604.96</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32448.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>22035.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5985.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5408.0</td>\n",
       "      <td>10587.0</td>\n",
       "      <td>49.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45977.0</td>\n",
       "      <td>32448.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>24977.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  int_rate  installment  annual_inc    dti  delinq_2yrs  \\\n",
       "0    40000.0    0.0819       814.70    140000.0  19.75          0.0   \n",
       "1     6000.0    0.1524       208.70     55000.0  11.52          2.0   \n",
       "2     3600.0    0.1695       128.27     42000.0   6.74          0.0   \n",
       "3    20000.0    0.1524       478.33    100000.0  12.13          0.0   \n",
       "4     3600.0    0.1240       120.27     50000.0  16.08          0.0   \n",
       "\n",
       "   inq_last_6mths  open_acc  pub_rec  revol_bal  total_acc  out_prncp  \\\n",
       "0             1.0      18.0      0.0     9471.0       45.0   33249.95   \n",
       "1             0.0       8.0      0.0     1280.0       12.0       0.00   \n",
       "2             0.0       6.0      0.0     4757.0        6.0       0.00   \n",
       "3             2.0       7.0      0.0    12731.0       21.0   17624.06   \n",
       "4             3.0       6.0      0.0    10413.0        6.0       0.00   \n",
       "\n",
       "   out_prncp_inv  total_pymnt  total_pymnt_inv  total_rec_prncp  \\\n",
       "0       33249.95      9740.00          9740.00          6750.05   \n",
       "1           0.00      6185.59          6185.59          6000.00   \n",
       "2           0.00      3603.73          3603.73          3600.00   \n",
       "3       17624.06      4766.37          4766.37          2375.94   \n",
       "4           0.00      3602.48          3602.48          3600.00   \n",
       "\n",
       "   total_rec_int  total_rec_late_fee  recoveries  collection_recovery_fee  \\\n",
       "0        2989.95                 0.0         0.0                      0.0   \n",
       "1         185.59                 0.0         0.0                      0.0   \n",
       "2           3.73                 0.0         0.0                      0.0   \n",
       "3        2390.43                 0.0         0.0                      0.0   \n",
       "4           2.48                 0.0         0.0                      0.0   \n",
       "\n",
       "   last_pymnt_amnt  collections_12_mths_ex_med  policy_code  acc_now_delinq  \\\n",
       "0           814.70                         0.0          1.0             0.0   \n",
       "1          5773.27                         0.0          1.0             0.0   \n",
       "2          3607.12                         0.0          1.0             0.0   \n",
       "3           478.33                         0.0          1.0             0.0   \n",
       "4          3604.96                         0.0          1.0             0.0   \n",
       "\n",
       "   tot_coll_amt  tot_cur_bal  open_acc_6m  open_act_il  open_il_12m  \\\n",
       "0           0.0     377773.0          1.0          6.0          1.0   \n",
       "1           0.0      23460.0          1.0          1.0          1.0   \n",
       "2           0.0      19183.0          0.0          3.0          0.0   \n",
       "3           0.0      43817.0          1.0          2.0          1.0   \n",
       "4           0.0      32448.0          2.0          2.0          1.0   \n",
       "\n",
       "   open_il_24m  mths_since_rcnt_il  total_bal_il  il_util  open_rv_12m  \\\n",
       "0          2.0                 9.0       61443.0     51.0          1.0   \n",
       "1          1.0                 6.0       22180.0     94.0          0.0   \n",
       "2          0.0                40.0       14426.0     96.0          1.0   \n",
       "3          3.0                11.0       31086.0     86.0          3.0   \n",
       "4          1.0                 9.0       22035.0     88.0          2.0   \n",
       "\n",
       "   open_rv_24m  max_bal_bc  all_util  total_rev_hi_lim  inq_fi  total_cu_tl  \\\n",
       "0          1.0      3218.0      26.0           86500.0     0.0          2.0   \n",
       "1          1.0       713.0      68.0           11000.0     1.0          1.0   \n",
       "2          2.0      4757.0      83.0            8100.0     0.0          0.0   \n",
       "3          3.0      5917.0      78.0           20500.0     0.0          3.0   \n",
       "4          2.0      5985.0      71.0           21000.0     3.0          1.0   \n",
       "\n",
       "   inq_last_12m  acc_open_past_24mths  avg_cur_bal  bc_open_to_buy  bc_util  \\\n",
       "0           1.0                   3.0      20987.0         65129.0     12.7   \n",
       "1           3.0                   2.0       2933.0          4680.0     20.7   \n",
       "2           2.0                   2.0       3837.0          2543.0     65.2   \n",
       "3           3.0                   6.0       7303.0          6496.0     52.9   \n",
       "4          14.0                   3.0       5408.0         10587.0     49.6   \n",
       "\n",
       "   chargeoff_within_12_mths  delinq_amnt  mo_sin_old_il_acct  \\\n",
       "0                       0.0          0.0               192.0   \n",
       "1                       0.0          0.0               143.0   \n",
       "2                       0.0          0.0                54.0   \n",
       "3                       0.0          0.0               132.0   \n",
       "4                       0.0          0.0                40.0   \n",
       "\n",
       "   mo_sin_old_rev_tl_op  mo_sin_rcnt_rev_tl_op  mo_sin_rcnt_tl  mort_acc  \\\n",
       "0                 180.0                    2.0             2.0       3.0   \n",
       "1                 144.0                   22.0             6.0       0.0   \n",
       "2                 107.0                    9.0             9.0       0.0   \n",
       "3                 290.0                    4.0             4.0       0.0   \n",
       "4                 159.0                    3.0             3.0       0.0   \n",
       "\n",
       "   mths_since_recent_bc  mths_since_recent_inq  num_accts_ever_120_pd  \\\n",
       "0                  44.0                    2.0                    0.0   \n",
       "1                  59.0                    6.0                    0.0   \n",
       "2                   9.0                    7.0                    0.0   \n",
       "3                   7.0                    5.0                    0.0   \n",
       "4                   3.0                    3.0                    0.0   \n",
       "\n",
       "   num_actv_bc_tl  num_actv_rev_tl  num_bc_sats  num_bc_tl  num_il_tl  \\\n",
       "0             6.0              6.0          6.0       10.0       20.0   \n",
       "1             2.0              3.0          2.0        2.0        3.0   \n",
       "2             1.0              1.0          2.0        2.0        3.0   \n",
       "3             2.0              4.0          3.0        8.0        8.0   \n",
       "4             4.0              4.0          4.0        4.0        2.0   \n",
       "\n",
       "   num_op_rev_tl  num_rev_accts  num_rev_tl_bal_gt_0  num_sats  \\\n",
       "0           11.0           22.0                  6.0      18.0   \n",
       "1            7.0            9.0                  3.0       8.0   \n",
       "2            3.0            3.0                  1.0       6.0   \n",
       "3            5.0           12.0                  4.0       7.0   \n",
       "4            4.0            4.0                  4.0       6.0   \n",
       "\n",
       "   num_tl_120dpd_2m  num_tl_30dpd  num_tl_90g_dpd_24m  num_tl_op_past_12m  \\\n",
       "0               0.0           0.0                 0.0                 2.0   \n",
       "1               0.0           0.0                 0.0                 1.0   \n",
       "2               0.0           0.0                 0.0                 1.0   \n",
       "3               0.0           0.0                 0.0                 4.0   \n",
       "4               0.0           0.0                 0.0                 3.0   \n",
       "\n",
       "   pct_tl_nvr_dlq  percent_bc_gt_75  pub_rec_bankruptcies  tax_liens  \\\n",
       "0            97.7               0.0                   0.0        0.0   \n",
       "1            66.7               0.0                   0.0        0.0   \n",
       "2           100.0               0.0                   0.0        0.0   \n",
       "3           100.0              50.0                   0.0        0.0   \n",
       "4           100.0              25.0                   0.0        0.0   \n",
       "\n",
       "   tot_hi_cred_lim  total_bal_ex_mort  total_bc_limit  \\\n",
       "0         527975.0            70914.0         74600.0   \n",
       "1          34628.0            23460.0          5900.0   \n",
       "2          23100.0            19183.0          7300.0   \n",
       "3          56481.0            43817.0         13800.0   \n",
       "4          45977.0            32448.0         21000.0   \n",
       "\n",
       "   total_il_high_credit_limit  home_ownership_ANY  home_ownership_MORTGAGE  \\\n",
       "0                     99475.0                   0                        1   \n",
       "1                     23628.0                   0                        0   \n",
       "2                     15000.0                   0                        0   \n",
       "3                     35981.0                   0                        0   \n",
       "4                     24977.0                   0                        0   \n",
       "\n",
       "   home_ownership_OWN  home_ownership_RENT  verification_status_Not Verified  \\\n",
       "0                   0                    0                                 1   \n",
       "1                   0                    1                                 1   \n",
       "2                   0                    1                                 1   \n",
       "3                   0                    1                                 1   \n",
       "4                   0                    1                                 1   \n",
       "\n",
       "   verification_status_Source Verified  verification_status_Verified  \\\n",
       "0                                    0                             0   \n",
       "1                                    0                             0   \n",
       "2                                    0                             0   \n",
       "3                                    0                             0   \n",
       "4                                    0                             0   \n",
       "\n",
       "   pymnt_plan_n  initial_list_status_f  initial_list_status_w  \\\n",
       "0             1                      0                      1   \n",
       "1             1                      0                      1   \n",
       "2             1                      0                      1   \n",
       "3             1                      0                      1   \n",
       "4             1                      0                      1   \n",
       "\n",
       "   application_type_Individual  application_type_Joint App  hardship_flag_N  \\\n",
       "0                            1                           0                1   \n",
       "1                            1                           0                1   \n",
       "2                            1                           0                1   \n",
       "3                            1                           0                1   \n",
       "4                            1                           0                1   \n",
       "\n",
       "   hardship_flag_Y  debt_settlement_flag_N  \n",
       "0                0                       1  \n",
       "1                0                       1  \n",
       "2                0                       1  \n",
       "3                0                       1  \n",
       "4                0                       1  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert categorical data to numeric and separate target feature \n",
    "# For testing data\n",
    "y_test = LabelEncoder().fit_transform(test_df['loan_status'])\n",
    "X_test = test_df.drop(columns = [\"loan_status\"])\n",
    "X_test = pd.get_dummies(X_test)\n",
    "X_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1 1 1 ... 0 0 0]\n",
      "4702\n",
      "4702\n",
      "(4702, 91) (4702,)\n"
     ]
    }
   ],
   "source": [
    "print(y_test)\n",
    "# low risk = 1\n",
    "# high risk = 0\n",
    "print(len(y_test))\n",
    "print(len(X_test))\n",
    "print(X_test.shape, y_test.shape)\n",
    "# can see that the y_test is missing one of the dummy columns because the shape has 91 col. rather than 92"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Columns count does not match at...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['debt_settlement_flag_Y']"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# add missing dummy variables to testing set\n",
    "# find any missing column\n",
    "check_test_and_train_matching_columns(X_train, X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set the missing value for the column debt_settlement_flag_N=1 , debt_settlement_flag_Y=0\n",
    "# add the column with the value of 0, then check the head and/or shape\n",
    "X_test['debt_settlement_flag_Y'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4702, 92)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "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>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</th>\n",
       "      <th>total_acc</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_amnt</th>\n",
       "      <th>collections_12_mths_ex_med</th>\n",
       "      <th>policy_code</th>\n",
       "      <th>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>open_acc_6m</th>\n",
       "      <th>open_act_il</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_inq</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",
       "      <th>home_ownership_ANY</th>\n",
       "      <th>home_ownership_MORTGAGE</th>\n",
       "      <th>home_ownership_OWN</th>\n",
       "      <th>home_ownership_RENT</th>\n",
       "      <th>verification_status_Not Verified</th>\n",
       "      <th>verification_status_Source Verified</th>\n",
       "      <th>verification_status_Verified</th>\n",
       "      <th>pymnt_plan_n</th>\n",
       "      <th>initial_list_status_f</th>\n",
       "      <th>initial_list_status_w</th>\n",
       "      <th>application_type_Individual</th>\n",
       "      <th>application_type_Joint App</th>\n",
       "      <th>hardship_flag_N</th>\n",
       "      <th>hardship_flag_Y</th>\n",
       "      <th>debt_settlement_flag_N</th>\n",
       "      <th>debt_settlement_flag_Y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>40000.0</td>\n",
       "      <td>0.0819</td>\n",
       "      <td>814.70</td>\n",
       "      <td>140000.0</td>\n",
       "      <td>19.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9471.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>33249.95</td>\n",
       "      <td>33249.95</td>\n",
       "      <td>9740.00</td>\n",
       "      <td>9740.00</td>\n",
       "      <td>6750.05</td>\n",
       "      <td>2989.95</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>814.70</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>377773.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>61443.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3218.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>86500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>20987.0</td>\n",
       "      <td>65129.0</td>\n",
       "      <td>12.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>97.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>527975.0</td>\n",
       "      <td>70914.0</td>\n",
       "      <td>74600.0</td>\n",
       "      <td>99475.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6000.0</td>\n",
       "      <td>0.1524</td>\n",
       "      <td>208.70</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>11.52</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1280.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>6185.59</td>\n",
       "      <td>6185.59</td>\n",
       "      <td>6000.00</td>\n",
       "      <td>185.59</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5773.27</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23460.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>22180.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>713.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2933.0</td>\n",
       "      <td>4680.0</td>\n",
       "      <td>20.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>144.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>66.7</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34628.0</td>\n",
       "      <td>23460.0</td>\n",
       "      <td>5900.0</td>\n",
       "      <td>23628.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3600.0</td>\n",
       "      <td>0.1695</td>\n",
       "      <td>128.27</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>6.74</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4757.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3603.73</td>\n",
       "      <td>3603.73</td>\n",
       "      <td>3600.00</td>\n",
       "      <td>3.73</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3607.12</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19183.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>14426.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4757.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>8100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3837.0</td>\n",
       "      <td>2543.0</td>\n",
       "      <td>65.2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23100.0</td>\n",
       "      <td>19183.0</td>\n",
       "      <td>7300.0</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20000.0</td>\n",
       "      <td>0.1524</td>\n",
       "      <td>478.33</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>12.13</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12731.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>17624.06</td>\n",
       "      <td>17624.06</td>\n",
       "      <td>4766.37</td>\n",
       "      <td>4766.37</td>\n",
       "      <td>2375.94</td>\n",
       "      <td>2390.43</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>478.33</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43817.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>31086.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5917.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>20500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7303.0</td>\n",
       "      <td>6496.0</td>\n",
       "      <td>52.9</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>56481.0</td>\n",
       "      <td>43817.0</td>\n",
       "      <td>13800.0</td>\n",
       "      <td>35981.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3600.0</td>\n",
       "      <td>0.1240</td>\n",
       "      <td>120.27</td>\n",
       "      <td>50000.0</td>\n",
       "      <td>16.08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10413.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>3602.48</td>\n",
       "      <td>3602.48</td>\n",
       "      <td>3600.00</td>\n",
       "      <td>2.48</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3604.96</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32448.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>22035.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5985.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5408.0</td>\n",
       "      <td>10587.0</td>\n",
       "      <td>49.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45977.0</td>\n",
       "      <td>32448.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>24977.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  int_rate  installment  annual_inc    dti  delinq_2yrs  \\\n",
       "0    40000.0    0.0819       814.70    140000.0  19.75          0.0   \n",
       "1     6000.0    0.1524       208.70     55000.0  11.52          2.0   \n",
       "2     3600.0    0.1695       128.27     42000.0   6.74          0.0   \n",
       "3    20000.0    0.1524       478.33    100000.0  12.13          0.0   \n",
       "4     3600.0    0.1240       120.27     50000.0  16.08          0.0   \n",
       "\n",
       "   inq_last_6mths  open_acc  pub_rec  revol_bal  total_acc  out_prncp  \\\n",
       "0             1.0      18.0      0.0     9471.0       45.0   33249.95   \n",
       "1             0.0       8.0      0.0     1280.0       12.0       0.00   \n",
       "2             0.0       6.0      0.0     4757.0        6.0       0.00   \n",
       "3             2.0       7.0      0.0    12731.0       21.0   17624.06   \n",
       "4             3.0       6.0      0.0    10413.0        6.0       0.00   \n",
       "\n",
       "   out_prncp_inv  total_pymnt  total_pymnt_inv  total_rec_prncp  \\\n",
       "0       33249.95      9740.00          9740.00          6750.05   \n",
       "1           0.00      6185.59          6185.59          6000.00   \n",
       "2           0.00      3603.73          3603.73          3600.00   \n",
       "3       17624.06      4766.37          4766.37          2375.94   \n",
       "4           0.00      3602.48          3602.48          3600.00   \n",
       "\n",
       "   total_rec_int  total_rec_late_fee  recoveries  collection_recovery_fee  \\\n",
       "0        2989.95                 0.0         0.0                      0.0   \n",
       "1         185.59                 0.0         0.0                      0.0   \n",
       "2           3.73                 0.0         0.0                      0.0   \n",
       "3        2390.43                 0.0         0.0                      0.0   \n",
       "4           2.48                 0.0         0.0                      0.0   \n",
       "\n",
       "   last_pymnt_amnt  collections_12_mths_ex_med  policy_code  acc_now_delinq  \\\n",
       "0           814.70                         0.0          1.0             0.0   \n",
       "1          5773.27                         0.0          1.0             0.0   \n",
       "2          3607.12                         0.0          1.0             0.0   \n",
       "3           478.33                         0.0          1.0             0.0   \n",
       "4          3604.96                         0.0          1.0             0.0   \n",
       "\n",
       "   tot_coll_amt  tot_cur_bal  open_acc_6m  open_act_il  open_il_12m  \\\n",
       "0           0.0     377773.0          1.0          6.0          1.0   \n",
       "1           0.0      23460.0          1.0          1.0          1.0   \n",
       "2           0.0      19183.0          0.0          3.0          0.0   \n",
       "3           0.0      43817.0          1.0          2.0          1.0   \n",
       "4           0.0      32448.0          2.0          2.0          1.0   \n",
       "\n",
       "   open_il_24m  mths_since_rcnt_il  total_bal_il  il_util  open_rv_12m  \\\n",
       "0          2.0                 9.0       61443.0     51.0          1.0   \n",
       "1          1.0                 6.0       22180.0     94.0          0.0   \n",
       "2          0.0                40.0       14426.0     96.0          1.0   \n",
       "3          3.0                11.0       31086.0     86.0          3.0   \n",
       "4          1.0                 9.0       22035.0     88.0          2.0   \n",
       "\n",
       "   open_rv_24m  max_bal_bc  all_util  total_rev_hi_lim  inq_fi  total_cu_tl  \\\n",
       "0          1.0      3218.0      26.0           86500.0     0.0          2.0   \n",
       "1          1.0       713.0      68.0           11000.0     1.0          1.0   \n",
       "2          2.0      4757.0      83.0            8100.0     0.0          0.0   \n",
       "3          3.0      5917.0      78.0           20500.0     0.0          3.0   \n",
       "4          2.0      5985.0      71.0           21000.0     3.0          1.0   \n",
       "\n",
       "   inq_last_12m  acc_open_past_24mths  avg_cur_bal  bc_open_to_buy  bc_util  \\\n",
       "0           1.0                   3.0      20987.0         65129.0     12.7   \n",
       "1           3.0                   2.0       2933.0          4680.0     20.7   \n",
       "2           2.0                   2.0       3837.0          2543.0     65.2   \n",
       "3           3.0                   6.0       7303.0          6496.0     52.9   \n",
       "4          14.0                   3.0       5408.0         10587.0     49.6   \n",
       "\n",
       "   chargeoff_within_12_mths  delinq_amnt  mo_sin_old_il_acct  \\\n",
       "0                       0.0          0.0               192.0   \n",
       "1                       0.0          0.0               143.0   \n",
       "2                       0.0          0.0                54.0   \n",
       "3                       0.0          0.0               132.0   \n",
       "4                       0.0          0.0                40.0   \n",
       "\n",
       "   mo_sin_old_rev_tl_op  mo_sin_rcnt_rev_tl_op  mo_sin_rcnt_tl  mort_acc  \\\n",
       "0                 180.0                    2.0             2.0       3.0   \n",
       "1                 144.0                   22.0             6.0       0.0   \n",
       "2                 107.0                    9.0             9.0       0.0   \n",
       "3                 290.0                    4.0             4.0       0.0   \n",
       "4                 159.0                    3.0             3.0       0.0   \n",
       "\n",
       "   mths_since_recent_bc  mths_since_recent_inq  num_accts_ever_120_pd  \\\n",
       "0                  44.0                    2.0                    0.0   \n",
       "1                  59.0                    6.0                    0.0   \n",
       "2                   9.0                    7.0                    0.0   \n",
       "3                   7.0                    5.0                    0.0   \n",
       "4                   3.0                    3.0                    0.0   \n",
       "\n",
       "   num_actv_bc_tl  num_actv_rev_tl  num_bc_sats  num_bc_tl  num_il_tl  \\\n",
       "0             6.0              6.0          6.0       10.0       20.0   \n",
       "1             2.0              3.0          2.0        2.0        3.0   \n",
       "2             1.0              1.0          2.0        2.0        3.0   \n",
       "3             2.0              4.0          3.0        8.0        8.0   \n",
       "4             4.0              4.0          4.0        4.0        2.0   \n",
       "\n",
       "   num_op_rev_tl  num_rev_accts  num_rev_tl_bal_gt_0  num_sats  \\\n",
       "0           11.0           22.0                  6.0      18.0   \n",
       "1            7.0            9.0                  3.0       8.0   \n",
       "2            3.0            3.0                  1.0       6.0   \n",
       "3            5.0           12.0                  4.0       7.0   \n",
       "4            4.0            4.0                  4.0       6.0   \n",
       "\n",
       "   num_tl_120dpd_2m  num_tl_30dpd  num_tl_90g_dpd_24m  num_tl_op_past_12m  \\\n",
       "0               0.0           0.0                 0.0                 2.0   \n",
       "1               0.0           0.0                 0.0                 1.0   \n",
       "2               0.0           0.0                 0.0                 1.0   \n",
       "3               0.0           0.0                 0.0                 4.0   \n",
       "4               0.0           0.0                 0.0                 3.0   \n",
       "\n",
       "   pct_tl_nvr_dlq  percent_bc_gt_75  pub_rec_bankruptcies  tax_liens  \\\n",
       "0            97.7               0.0                   0.0        0.0   \n",
       "1            66.7               0.0                   0.0        0.0   \n",
       "2           100.0               0.0                   0.0        0.0   \n",
       "3           100.0              50.0                   0.0        0.0   \n",
       "4           100.0              25.0                   0.0        0.0   \n",
       "\n",
       "   tot_hi_cred_lim  total_bal_ex_mort  total_bc_limit  \\\n",
       "0         527975.0            70914.0         74600.0   \n",
       "1          34628.0            23460.0          5900.0   \n",
       "2          23100.0            19183.0          7300.0   \n",
       "3          56481.0            43817.0         13800.0   \n",
       "4          45977.0            32448.0         21000.0   \n",
       "\n",
       "   total_il_high_credit_limit  home_ownership_ANY  home_ownership_MORTGAGE  \\\n",
       "0                     99475.0                   0                        1   \n",
       "1                     23628.0                   0                        0   \n",
       "2                     15000.0                   0                        0   \n",
       "3                     35981.0                   0                        0   \n",
       "4                     24977.0                   0                        0   \n",
       "\n",
       "   home_ownership_OWN  home_ownership_RENT  verification_status_Not Verified  \\\n",
       "0                   0                    0                                 1   \n",
       "1                   0                    1                                 1   \n",
       "2                   0                    1                                 1   \n",
       "3                   0                    1                                 1   \n",
       "4                   0                    1                                 1   \n",
       "\n",
       "   verification_status_Source Verified  verification_status_Verified  \\\n",
       "0                                    0                             0   \n",
       "1                                    0                             0   \n",
       "2                                    0                             0   \n",
       "3                                    0                             0   \n",
       "4                                    0                             0   \n",
       "\n",
       "   pymnt_plan_n  initial_list_status_f  initial_list_status_w  \\\n",
       "0             1                      0                      1   \n",
       "1             1                      0                      1   \n",
       "2             1                      0                      1   \n",
       "3             1                      0                      1   \n",
       "4             1                      0                      1   \n",
       "\n",
       "   application_type_Individual  application_type_Joint App  hardship_flag_N  \\\n",
       "0                            1                           0                1   \n",
       "1                            1                           0                1   \n",
       "2                            1                           0                1   \n",
       "3                            1                           0                1   \n",
       "4                            1                           0                1   \n",
       "\n",
       "   hardship_flag_Y  debt_settlement_flag_N  debt_settlement_flag_Y  \n",
       "0                0                       1                       0  \n",
       "1                0                       1                       0  \n",
       "2                0                       1                       0  \n",
       "3                0                       1                       0  \n",
       "4                0                       1                       0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_test.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction - Unscaled Data \n",
    "\n",
    "Prediction UNSCALED Data:\n",
    "Random Forest Classifier should perform better than Logistic Regression because the dataset consists of categorical data, which tends to work best with Random Forest models. Logistic Regression, on the other hand, performs best with linearly separable datasets.\n",
    "\n",
    "https://scholar.smu.edu/cgi/viewcontent.cgi?article=1041&context=datasciencereview#:~:text=In%20general%2C%20logistic%20regression%20performs,variables%20increases%20in%20a%20dataset.\n",
    "\n",
    "About the models: \n",
    "- Logistic Regression is a classification algorithm used to predict a discrete set of classes or categories. (ie:yes/no or true/false)\n",
    "It uses the sigmoid function to return a probability 'value'. \n",
    "\n",
    "- Random Forest Classifier is an ensemble learning method that constructs a set of decision trees from a randomly selected subset of training set and combines them together to return a 'prediction'. \n",
    "------------\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Logistic regression model - unscaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train the Logistic Regression model on the unscaled data and print the model score\n",
    "reg_classifier = LogisticRegression()\n",
    "reg_classifier\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# gives same warnings\n",
    "# trouble converging may be because #'s not scaled\n",
    "# adjusted values so can converge\n",
    "reg_classifier = LogisticRegression(\n",
    "    #solver='lbfgs',     # non linear data, not working as well\n",
    "    solver='liblinear',  # generally better on data with linear relationships, small datasets\n",
    "    #max_iter=1000,   #train loop to opti,# times happens\n",
    "    random_state=0\n",
    "    #stop criteria test various\n",
    "    #tol = .01\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Data Score: 0.707471264367816\n",
      "Testing Data Score: 0.5746490854955338\n"
     ]
    }
   ],
   "source": [
    "reg_classifier.fit(X_train, y_train)\n",
    "print(f\"Training Data Score: {reg_classifier.score(X_train, y_train)}\")\n",
    "print(f\"Testing Data Score: {reg_classifier.score(X_test, y_test)}\")\n",
    "\n",
    "# logistic "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random Forest - Unscaled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 260,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Score RF: 1.0\n",
      "Testing Score RF: 0.638664398128456\n"
     ]
    }
   ],
   "source": [
    "# Train a Random Forest Classifier model and print the model score\n",
    "# trial and error with 50 dflt, smaller dataset 300 ok because not as time consuming, take a long time to train\n",
    "# large datasets 50 could take a long time \n",
    "rf_classifier = RandomForestClassifier(random_state=42, n_estimators=200).fit(X_train, y_train)\n",
    "print(f'Training Score RF: {rf_classifier.score(X_train, y_train)}')\n",
    "print(f'Testing Score RF: {rf_classifier.score(X_test, y_test)}')\n",
    "\n",
    "# Looks to be overfitted because 1.0 in training\n",
    "# accuracy formula (tp + tn)/(tp+tn+fn+fp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results - Unscaled (compare to preciction)\n",
    "\n",
    "#### Logistic Regression (LR):\n",
    "- Training Data Score: 0.707471264367816\n",
    "- Testing Data Score: 0.5746490854955338\n",
    "\n",
    "#### Random Forest Classifier (RF):\n",
    "- Training Score RF: 1.0\n",
    "- Testing Score RF: 0.638664398128456\n",
    "\n",
    "The Random Forest Classifier model did better when both models were not scaled. Although, it looks to be overfitted in training. The complexity may need to be reduced. \n",
    "This was the predicted case because we are using categorical data which works well with Random Forest Classifier. Alternatively, Logistic Regression, on the other hand, performs best with linearly separable datasets. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prediction - Scaled Data \n",
    "Random Forest Classifier SCALING should not make a difference to the Random Forest. \n",
    "Scaling is only needed to be done for distance based algorithms. \n",
    "For tree based algorithms (DecisionTrees), scaling is not required.\n",
    "- https://www.kaggle.com/questions-and-answers/86923\n",
    "- https://www.sciencedirect.com/topics/engineering/random-forest\n",
    "    \n",
    "Thus, Logistic Regression, if scaled out, may do better in this case, than the random-forest. \n",
    "- The Testing score for LR:  0.5746490854955338  (will change)\n",
    "- The Testing score for RF:  0.638664398128456   (will not change much)\n",
    "\n",
    "Because the values are somewhat close, and the RF values should not change much, I am estimating that Linear regression may do better. \n",
    "(Feature scaling can matter because coefficients of features with large variance are small and thus less penalized.)\n",
    "\n",
    "\n",
    "- https://scholar.smu.edu/cgi/viewcontent.cgi?article=1041&context=datasciencereview#:~:text=In%20general%2C%20logistic%20regression%20performs,variables%20increases%20in%20a%20dataset.\n",
    "\n",
    "- https://www.quora.com/How-does-feature-scaling-affect-logistic-regression-model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scale DATA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Scale the data\n",
    "scaler = StandardScaler().fit(X_train)\n",
    "X_train_scaled = scaler.transform(X_train)\n",
    "X_test_scaled = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Scaled Logistic Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Data Score: 0.7078817733990148\n",
      "Testing Data Score: 0.7677584006805614\n"
     ]
    }
   ],
   "source": [
    "# Train the Logistic Regression model on the scaled data and print the model score\n",
    "scaled_LR_clf = LogisticRegression(solver='liblinear',random_state=0 ).fit(X_train_scaled, y_train)\n",
    "print(f\"Training Data Score: {scaled_LR_clf.score(X_train_scaled, y_train)}\")\n",
    "print(f\"Testing Data Score: {scaled_LR_clf.score(X_test_scaled, y_test)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1788,  563],\n",
       "       [ 529, 1822]])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# confusion matrix scaled LR\n",
    "y_true = y_test\n",
    "y_pred = scaled_LR_clf.predict(X_test_scaled)\n",
    "confusion_matrix(y_true, y_pred)\n",
    "\n",
    "#confusion_matrix\n",
    "#tn, fp, \n",
    "#fn, tp "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x252 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show on a plot\n",
    "matrix = confusion_matrix(y_true, y_pred)\n",
    "matrix = matrix.astype('float') / matrix.sum(axis=1)[:, np.newaxis]\n",
    "\n",
    "# Build the plot\n",
    "plt.figure(figsize=(7,3.5))\n",
    "sns.set(font_scale=1.4)\n",
    "sns.heatmap(matrix, annot=True, annot_kws={'size':10},\n",
    "            cmap=plt.cm.Greens, linewidths=0.2)\n",
    "\n",
    "# Add labels to the plot\n",
    "#class_names = ['Low Risk', 'High Risk']\n",
    "class_names = ['High Risk', 'Low Risk']\n",
    "tick_marks = np.arange(len(class_names))\n",
    "tick_marks2 = tick_marks + 0.5\n",
    "plt.xticks(tick_marks, class_names, rotation=0)\n",
    "plt.yticks(tick_marks2, class_names, rotation=0)\n",
    "plt.xlabel('Predicted label')\n",
    "plt.ylabel('True label')\n",
    "plt.title('Confusion Matrix for Logistic Regression Model')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The Confusion Matrix above shows that the Logistic Regression model struggled a bit more at predicting the High Risk label, but overall predicted both labels equally well. A balanced model.\n",
    "\n",
    "Depending on the the business decision, one can try to improve on the scores.\n",
    "\n",
    "##### False-negative \n",
    "- One would see predicted High Risk (label) in 529 cases (23%), but these clients are actually Low Risk.\n",
    "- It is not as detrimental to turn away low risk clients, who do actually qualify. Thus, one might keep this number as it is or it can be higher if reducing the False-Positive.\n",
    "\n",
    "##### False-Positive\n",
    "- One would see predicted Low Risk (label) in 563 cases (24%), but these clients are actually High Risk.\n",
    "- It may be more detrimental to accept loans from these clients labelled low risk, but they are actually high risk. Thus, one might want to minimize this number.\n",
    "\n",
    "Thus, with a balanced model, trying to improve one score will offset another. \n",
    "It may be better to lower the False-Positive scores. \n",
    "                              \n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "   high risk       0.77      0.76      0.77      2351\n",
      "    low risk       0.76      0.77      0.77      2351\n",
      "\n",
      "    accuracy                           0.77      4702\n",
      "   macro avg       0.77      0.77      0.77      4702\n",
      "weighted avg       0.77      0.77      0.77      4702\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Classification Report  \n",
    "# low risk = 1\n",
    "# high risk = 0\n",
    "target_names = ['high risk', 'low risk']\n",
    "print(classification_report(y_true, y_pred, target_names=target_names))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The above classification report shows that precision (accuracy) for high risk is 77%; the model tries to avoid labeling things “high risk” that are not high risk. On the other hand, recall (sensitivity) is a bit lower for high risk 76%, which means that the classifier is missing some 'high risks' because it is trying to be too careful. Because precision and recall are both similar, F1 score is also similar at 77%.\n",
    "\n",
    "High risk and low risk clients are almost equally being turned away for a loan at the same rate because the numbers almost equally match. \n",
    "\n",
    "\n",
    "Suggested Model: Minimize the high risk false positives. In turn the balance will be offset. Although, it may not be as detrimental to the lending facility."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Scaled Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Score RF: 1.0\n",
      "Testing Score RF: 0.6376010208421948\n"
     ]
    }
   ],
   "source": [
    "# Train a Random Forest Classifier model on the scaled data and print the model score\n",
    "scaled_rf_cls = RandomForestClassifier(random_state=42, n_estimators=200).fit(X_train_scaled, y_train)\n",
    "print(f'Training Score RF: {scaled_rf_cls.score(X_train_scaled, y_train)}')\n",
    "print(f'Testing Score RF: {scaled_rf_cls.score(X_test_scaled, y_test)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1872,  479],\n",
       "       [1225, 1126]])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Confusion matrix for RF model\n",
    "y_true2 = y_test\n",
    "y_pred2 = scaled_rf_cls.predict(X_test_scaled)\n",
    "confusion_matrix(y_true2, y_pred2)\n",
    "# fn 1225"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 504x252 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# show on a plot\n",
    "matrix = confusion_matrix(y_true2, y_pred2)\n",
    "matrix = matrix.astype('float') / matrix.sum(axis=1)[:, np.newaxis]\n",
    "\n",
    "# Build the plot\n",
    "plt.figure(figsize=(7,3.5))\n",
    "sns.set(font_scale=1.4)\n",
    "sns.heatmap(matrix, annot=True, annot_kws={'size':10},\n",
    "            cmap=plt.cm.Blues, linewidths=0.2)\n",
    "\n",
    "# Add labels to the plot\n",
    "#class_names = ['Low Risk', 'High Risk']\n",
    "class_names = ['High Risk', 'Low Risk']\n",
    "tick_marks = np.arange(len(class_names))\n",
    "tick_marks2 = tick_marks + 0.5\n",
    "plt.xticks(tick_marks, class_names, rotation=0)\n",
    "plt.yticks(tick_marks2, class_names, rotation=0)\n",
    "plt.xlabel('Predicted label')\n",
    "plt.ylabel('True label')\n",
    "plt.title('Confusion Matrix for Random Forest Model')\n",
    "plt.show()\n",
    "# high tp  tneg\n",
    "# low tp   tneg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The above Confusion Matrix shows that the Random Forest classifier struggled at predicting the Low Risk label. \n",
    "\n",
    "The algorithm is good for high risk at 80%, but struggles for the low risk at 52%\n",
    "\n",
    "The way forward would be to exclusively explore the low risk (as a subset of only low risks, pair plot them)\n",
    "This way one can see different feature sets. \n",
    "There is a struggle in the classification of this class, algorithm clustering, ie) DBSCAN, may be able to identify the noisy data from this class, low risk. \n",
    "\n",
    "* Because there is a lot of noise in this low risk class, scaling the Random Forest did not help. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "   high risk       0.60      0.80      0.69      2351\n",
      "    low risk       0.70      0.48      0.57      2351\n",
      "\n",
      "    accuracy                           0.64      4702\n",
      "   macro avg       0.65      0.64      0.63      4702\n",
      "weighted avg       0.65      0.64      0.63      4702\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Classification Report for Random Forest model\n",
    "print(classification_report(y_true2, y_pred2, target_names=target_names))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Ideally one would like precision, recall, and F1 to all be high. This would show a balanced model. \n",
    "\n",
    "* The high risk precision is 60% accurate (40% false positive - THIS IS HIGH), but the recall is 80%. When the recall (sensitivity) is high this is good. This means that most of those captured as high risk (60%), most instances are being  marked as correct (80% of the time). \n",
    "\n",
    "* The low risk accuracy is 70% (false negatives at 30%). However, the recall (sensitivity) is at 48%. This means that only 48% are correctly being marked as low risk.  \n",
    "\n",
    "Thus, the scaled logistic regression model, with a balanced model, is a better choice model. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Results - Scaled (compare to preciction)\n",
    "\n",
    "#### NOT SCALED Logistic Regression (LR):\n",
    "- Training Data Score: 0.707471264367816\n",
    "- Testing Data Score: 0.5746490854955338\n",
    "\n",
    "#### NOT SCALED Random Forest Classifier (RF):\n",
    "- RF Training Score RF: 1.0\n",
    "- RF Testing Score RF: 0.638664398128456\n",
    "\n",
    "\n",
    "#### Scaled Logistic Regression (LR):\n",
    "- Training Data Score: 0.7078817733990148\n",
    "- Testing Data Score: 0.7677584006805614\n",
    "\n",
    "#### Scaled Random Forest Classifier (RF):\n",
    "- RF Training Score RF: 1.0\n",
    "- RF Testing Score RF: 0.6376010208421948\n",
    "\n",
    "\n",
    "- Overall, scaling greatly improved the score of the Logistic Regression model from 0.5746490854955338 to 0.7677584006805614 so that it outperformed the Random Forest model. The scaled Logistic Regression model was shown to be more balanced. This shows that sometimes a simple model with scaled data can be a better fit than one with more complexity.\n",
    "\n",
    "\n",
    "- This is what was predicted. The overfitting of the Random Forest Classifier model, and the fact that it does not change much with scaling, and in this case did not impove the score. The Random Forest Classifier model was shown to be unbalanced and having too much noise in the low risk category. Whereas, the scaling of the Logistic Regression model helped to 'normalize' the data. \n",
    "\n",
    "\n",
    "- Scaling for Logistic Regression:\n",
    "The implementation of logistic regression you use has a penalty on coefficent size (L1 or L2 norm). In this case, feature scaling matters, because coefficients of features with large variance are small and thus less penalized.\n",
    "Balance the importance of each feature. For example, if you have two independent variables in different ranges [1, 2] and [1000, 2000] and you didn’t scale, then it’s likely the latter variables are considered dominent\n",
    "- https://www.quora.com/How-does-feature-scaling-affect-logistic-regression-model\n",
    "\n",
    "\n",
    "- One can move forward:\n",
    "Exclusively explore the low risk (as a subset of only low risks, pair plot them)\n",
    "This way one can see different feature sets. \n",
    "There is a struggle in the classification of this class, algorithm clustering, ie) DBSCAN, may be able to identify the noisy data from this class, low risk. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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