LeningClub贷款违约预测模型.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import missingno as msno\n",
    "import warnings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "#默认设置\n",
    "%matplotlib inline\n",
    "pd.set_option('display.float_format',lambda x:'%.4f'%x)#数值格式，避免科学计数法\n",
    "#plt样式\n",
    "plt.style.use('ggplot')\n",
    "sns.set_style('whitegrid')\n",
    "warnings.filterwarnings('ignore')#忽略警告"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true
   },
   "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>id</th>\n",
       "      <th>member_id</th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>funded_amnt</th>\n",
       "      <th>funded_amnt_inv</th>\n",
       "      <th>term</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>grade</th>\n",
       "      <th>sub_grade</th>\n",
       "      <th>emp_title</th>\n",
       "      <th>emp_length</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>issue_d</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>pymnt_plan</th>\n",
       "      <th>url</th>\n",
       "      <th>desc</th>\n",
       "      <th>purpose</th>\n",
       "      <th>title</th>\n",
       "      <th>zip_code</th>\n",
       "      <th>addr_state</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>earliest_cr_line</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>mths_since_last_delinq</th>\n",
       "      <th>mths_since_last_record</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</th>\n",
       "      <th>revol_util</th>\n",
       "      <th>total_acc</th>\n",
       "      <th>initial_list_status</th>\n",
       "      <th>out_prncp</th>\n",
       "      <th>out_prncp_inv</th>\n",
       "      <th>total_pymnt</th>\n",
       "      <th>total_pymnt_inv</th>\n",
       "      <th>total_rec_prncp</th>\n",
       "      <th>total_rec_int</th>\n",
       "      <th>total_rec_late_fee</th>\n",
       "      <th>recoveries</th>\n",
       "      <th>collection_recovery_fee</th>\n",
       "      <th>last_pymnt_d</th>\n",
       "      <th>last_pymnt_amnt</th>\n",
       "      <th>next_pymnt_d</th>\n",
       "      <th>last_credit_pull_d</th>\n",
       "      <th>collections_12_mths_ex_med</th>\n",
       "      <th>mths_since_last_major_derog</th>\n",
       "      <th>policy_code</th>\n",
       "      <th>application_type</th>\n",
       "      <th>annual_inc_joint</th>\n",
       "      <th>dti_joint</th>\n",
       "      <th>verification_status_joint</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_il_6m</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1077501</td>\n",
       "      <td>1296599</td>\n",
       "      <td>5000.0000</td>\n",
       "      <td>5000.0000</td>\n",
       "      <td>4975.0000</td>\n",
       "      <td>36 months</td>\n",
       "      <td>10.6500</td>\n",
       "      <td>162.8700</td>\n",
       "      <td>B</td>\n",
       "      <td>B2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>24000.0000</td>\n",
       "      <td>Verified</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>Fully Paid</td>\n",
       "      <td>n</td>\n",
       "      <td>https://www.lendingclub.com/browse/loanDetail....</td>\n",
       "      <td>Borrower added on 12/22/11 &gt; I need to upgra...</td>\n",
       "      <td>credit_card</td>\n",
       "      <td>Computer</td>\n",
       "      <td>860xx</td>\n",
       "      <td>AZ</td>\n",
       "      <td>27.6500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Jan-1985</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>13648.0000</td>\n",
       "      <td>83.7000</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>f</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5861.0714</td>\n",
       "      <td>5831.7800</td>\n",
       "      <td>5000.0000</td>\n",
       "      <td>861.0700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Jan-2015</td>\n",
       "      <td>171.6200</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jan-2016</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1077430</td>\n",
       "      <td>1314167</td>\n",
       "      <td>2500.0000</td>\n",
       "      <td>2500.0000</td>\n",
       "      <td>2500.0000</td>\n",
       "      <td>60 months</td>\n",
       "      <td>15.2700</td>\n",
       "      <td>59.8300</td>\n",
       "      <td>C</td>\n",
       "      <td>C4</td>\n",
       "      <td>Ryder</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>RENT</td>\n",
       "      <td>30000.0000</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>Charged Off</td>\n",
       "      <td>n</td>\n",
       "      <td>https://www.lendingclub.com/browse/loanDetail....</td>\n",
       "      <td>Borrower added on 12/22/11 &gt; I plan to use t...</td>\n",
       "      <td>car</td>\n",
       "      <td>bike</td>\n",
       "      <td>309xx</td>\n",
       "      <td>GA</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Apr-1999</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1687.0000</td>\n",
       "      <td>9.4000</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>f</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1008.7100</td>\n",
       "      <td>1008.7100</td>\n",
       "      <td>456.4600</td>\n",
       "      <td>435.1700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>117.0800</td>\n",
       "      <td>1.1100</td>\n",
       "      <td>Apr-2013</td>\n",
       "      <td>119.6600</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sep-2013</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1077175</td>\n",
       "      <td>1313524</td>\n",
       "      <td>2400.0000</td>\n",
       "      <td>2400.0000</td>\n",
       "      <td>2400.0000</td>\n",
       "      <td>36 months</td>\n",
       "      <td>15.9600</td>\n",
       "      <td>84.3300</td>\n",
       "      <td>C</td>\n",
       "      <td>C5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>12252.0000</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>Fully Paid</td>\n",
       "      <td>n</td>\n",
       "      <td>https://www.lendingclub.com/browse/loanDetail....</td>\n",
       "      <td>NaN</td>\n",
       "      <td>small_business</td>\n",
       "      <td>real estate business</td>\n",
       "      <td>606xx</td>\n",
       "      <td>IL</td>\n",
       "      <td>8.7200</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Nov-2001</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2956.0000</td>\n",
       "      <td>98.5000</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>f</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>3003.6536</td>\n",
       "      <td>3003.6500</td>\n",
       "      <td>2400.0000</td>\n",
       "      <td>603.6500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Jun-2014</td>\n",
       "      <td>649.9100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jan-2016</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1076863</td>\n",
       "      <td>1277178</td>\n",
       "      <td>10000.0000</td>\n",
       "      <td>10000.0000</td>\n",
       "      <td>10000.0000</td>\n",
       "      <td>36 months</td>\n",
       "      <td>13.4900</td>\n",
       "      <td>339.3100</td>\n",
       "      <td>C</td>\n",
       "      <td>C1</td>\n",
       "      <td>AIR RESOURCES BOARD</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>49200.0000</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>Fully Paid</td>\n",
       "      <td>n</td>\n",
       "      <td>https://www.lendingclub.com/browse/loanDetail....</td>\n",
       "      <td>Borrower added on 12/21/11 &gt; to pay for prop...</td>\n",
       "      <td>other</td>\n",
       "      <td>personel</td>\n",
       "      <td>917xx</td>\n",
       "      <td>CA</td>\n",
       "      <td>20.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Feb-1996</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>35.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5598.0000</td>\n",
       "      <td>21.0000</td>\n",
       "      <td>37.0000</td>\n",
       "      <td>f</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>12226.3022</td>\n",
       "      <td>12226.3000</td>\n",
       "      <td>10000.0000</td>\n",
       "      <td>2209.3300</td>\n",
       "      <td>16.9700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Jan-2015</td>\n",
       "      <td>357.4800</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Jan-2015</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1075358</td>\n",
       "      <td>1311748</td>\n",
       "      <td>3000.0000</td>\n",
       "      <td>3000.0000</td>\n",
       "      <td>3000.0000</td>\n",
       "      <td>60 months</td>\n",
       "      <td>12.6900</td>\n",
       "      <td>67.7900</td>\n",
       "      <td>B</td>\n",
       "      <td>B5</td>\n",
       "      <td>University Medical Group</td>\n",
       "      <td>1 year</td>\n",
       "      <td>RENT</td>\n",
       "      <td>80000.0000</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>Dec-2011</td>\n",
       "      <td>Current</td>\n",
       "      <td>n</td>\n",
       "      <td>https://www.lendingclub.com/browse/loanDetail....</td>\n",
       "      <td>Borrower added on 12/21/11 &gt; I plan on combi...</td>\n",
       "      <td>other</td>\n",
       "      <td>Personal</td>\n",
       "      <td>972xx</td>\n",
       "      <td>OR</td>\n",
       "      <td>17.9400</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Jan-1996</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>38.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>27783.0000</td>\n",
       "      <td>53.9000</td>\n",
       "      <td>38.0000</td>\n",
       "      <td>f</td>\n",
       "      <td>766.9000</td>\n",
       "      <td>766.9000</td>\n",
       "      <td>3242.1700</td>\n",
       "      <td>3242.1700</td>\n",
       "      <td>2233.1000</td>\n",
       "      <td>1009.0700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>Jan-2016</td>\n",
       "      <td>67.7900</td>\n",
       "      <td>Feb-2016</td>\n",
       "      <td>Jan-2016</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  member_id  loan_amnt  funded_amnt  funded_amnt_inv        term  \\\n",
       "0  1077501    1296599  5000.0000    5000.0000        4975.0000   36 months   \n",
       "1  1077430    1314167  2500.0000    2500.0000        2500.0000   60 months   \n",
       "2  1077175    1313524  2400.0000    2400.0000        2400.0000   36 months   \n",
       "3  1076863    1277178 10000.0000   10000.0000       10000.0000   36 months   \n",
       "4  1075358    1311748  3000.0000    3000.0000        3000.0000   60 months   \n",
       "\n",
       "   int_rate  installment grade sub_grade                 emp_title emp_length  \\\n",
       "0   10.6500     162.8700     B        B2                       NaN  10+ years   \n",
       "1   15.2700      59.8300     C        C4                     Ryder   < 1 year   \n",
       "2   15.9600      84.3300     C        C5                       NaN  10+ years   \n",
       "3   13.4900     339.3100     C        C1       AIR RESOURCES BOARD  10+ years   \n",
       "4   12.6900      67.7900     B        B5  University Medical Group     1 year   \n",
       "\n",
       "  home_ownership  annual_inc verification_status   issue_d  loan_status  \\\n",
       "0           RENT  24000.0000            Verified  Dec-2011   Fully Paid   \n",
       "1           RENT  30000.0000     Source Verified  Dec-2011  Charged Off   \n",
       "2           RENT  12252.0000        Not Verified  Dec-2011   Fully Paid   \n",
       "3           RENT  49200.0000     Source Verified  Dec-2011   Fully Paid   \n",
       "4           RENT  80000.0000     Source Verified  Dec-2011      Current   \n",
       "\n",
       "  pymnt_plan                                                url  \\\n",
       "0          n  https://www.lendingclub.com/browse/loanDetail....   \n",
       "1          n  https://www.lendingclub.com/browse/loanDetail....   \n",
       "2          n  https://www.lendingclub.com/browse/loanDetail....   \n",
       "3          n  https://www.lendingclub.com/browse/loanDetail....   \n",
       "4          n  https://www.lendingclub.com/browse/loanDetail....   \n",
       "\n",
       "                                                desc         purpose  \\\n",
       "0    Borrower added on 12/22/11 > I need to upgra...     credit_card   \n",
       "1    Borrower added on 12/22/11 > I plan to use t...             car   \n",
       "2                                                NaN  small_business   \n",
       "3    Borrower added on 12/21/11 > to pay for prop...           other   \n",
       "4    Borrower added on 12/21/11 > I plan on combi...           other   \n",
       "\n",
       "                  title zip_code addr_state     dti  delinq_2yrs  \\\n",
       "0              Computer    860xx         AZ 27.6500       0.0000   \n",
       "1                  bike    309xx         GA  1.0000       0.0000   \n",
       "2  real estate business    606xx         IL  8.7200       0.0000   \n",
       "3              personel    917xx         CA 20.0000       0.0000   \n",
       "4              Personal    972xx         OR 17.9400       0.0000   \n",
       "\n",
       "  earliest_cr_line  inq_last_6mths  mths_since_last_delinq  \\\n",
       "0         Jan-1985          1.0000                     nan   \n",
       "1         Apr-1999          5.0000                     nan   \n",
       "2         Nov-2001          2.0000                     nan   \n",
       "3         Feb-1996          1.0000                 35.0000   \n",
       "4         Jan-1996          0.0000                 38.0000   \n",
       "\n",
       "   mths_since_last_record  open_acc  pub_rec  revol_bal  revol_util  \\\n",
       "0                     nan    3.0000   0.0000 13648.0000     83.7000   \n",
       "1                     nan    3.0000   0.0000  1687.0000      9.4000   \n",
       "2                     nan    2.0000   0.0000  2956.0000     98.5000   \n",
       "3                     nan   10.0000   0.0000  5598.0000     21.0000   \n",
       "4                     nan   15.0000   0.0000 27783.0000     53.9000   \n",
       "\n",
       "   total_acc initial_list_status  out_prncp  out_prncp_inv  total_pymnt  \\\n",
       "0     9.0000                   f     0.0000         0.0000    5861.0714   \n",
       "1     4.0000                   f     0.0000         0.0000    1008.7100   \n",
       "2    10.0000                   f     0.0000         0.0000    3003.6536   \n",
       "3    37.0000                   f     0.0000         0.0000   12226.3022   \n",
       "4    38.0000                   f   766.9000       766.9000    3242.1700   \n",
       "\n",
       "   total_pymnt_inv  total_rec_prncp  total_rec_int  total_rec_late_fee  \\\n",
       "0        5831.7800        5000.0000       861.0700              0.0000   \n",
       "1        1008.7100         456.4600       435.1700              0.0000   \n",
       "2        3003.6500        2400.0000       603.6500              0.0000   \n",
       "3       12226.3000       10000.0000      2209.3300             16.9700   \n",
       "4        3242.1700        2233.1000      1009.0700              0.0000   \n",
       "\n",
       "   recoveries  collection_recovery_fee last_pymnt_d  last_pymnt_amnt  \\\n",
       "0      0.0000                   0.0000     Jan-2015         171.6200   \n",
       "1    117.0800                   1.1100     Apr-2013         119.6600   \n",
       "2      0.0000                   0.0000     Jun-2014         649.9100   \n",
       "3      0.0000                   0.0000     Jan-2015         357.4800   \n",
       "4      0.0000                   0.0000     Jan-2016          67.7900   \n",
       "\n",
       "  next_pymnt_d last_credit_pull_d  collections_12_mths_ex_med  \\\n",
       "0          NaN           Jan-2016                      0.0000   \n",
       "1          NaN           Sep-2013                      0.0000   \n",
       "2          NaN           Jan-2016                      0.0000   \n",
       "3          NaN           Jan-2015                      0.0000   \n",
       "4     Feb-2016           Jan-2016                      0.0000   \n",
       "\n",
       "   mths_since_last_major_derog  policy_code application_type  \\\n",
       "0                          nan       1.0000       INDIVIDUAL   \n",
       "1                          nan       1.0000       INDIVIDUAL   \n",
       "2                          nan       1.0000       INDIVIDUAL   \n",
       "3                          nan       1.0000       INDIVIDUAL   \n",
       "4                          nan       1.0000       INDIVIDUAL   \n",
       "\n",
       "   annual_inc_joint  dti_joint verification_status_joint  acc_now_delinq  \\\n",
       "0               nan        nan                       NaN          0.0000   \n",
       "1               nan        nan                       NaN          0.0000   \n",
       "2               nan        nan                       NaN          0.0000   \n",
       "3               nan        nan                       NaN          0.0000   \n",
       "4               nan        nan                       NaN          0.0000   \n",
       "\n",
       "   tot_coll_amt  tot_cur_bal  open_acc_6m  open_il_6m  open_il_12m  \\\n",
       "0           nan          nan          nan         nan          nan   \n",
       "1           nan          nan          nan         nan          nan   \n",
       "2           nan          nan          nan         nan          nan   \n",
       "3           nan          nan          nan         nan          nan   \n",
       "4           nan          nan          nan         nan          nan   \n",
       "\n",
       "   open_il_24m  mths_since_rcnt_il  total_bal_il  il_util  open_rv_12m  \\\n",
       "0          nan                 nan           nan      nan          nan   \n",
       "1          nan                 nan           nan      nan          nan   \n",
       "2          nan                 nan           nan      nan          nan   \n",
       "3          nan                 nan           nan      nan          nan   \n",
       "4          nan                 nan           nan      nan          nan   \n",
       "\n",
       "   open_rv_24m  max_bal_bc  all_util  total_rev_hi_lim  inq_fi  total_cu_tl  \\\n",
       "0          nan         nan       nan               nan     nan          nan   \n",
       "1          nan         nan       nan               nan     nan          nan   \n",
       "2          nan         nan       nan               nan     nan          nan   \n",
       "3          nan         nan       nan               nan     nan          nan   \n",
       "4          nan         nan       nan               nan     nan          nan   \n",
       "\n",
       "   inq_last_12m  \n",
       "0           nan  \n",
       "1           nan  \n",
       "2           nan  \n",
       "3           nan  \n",
       "4           nan  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = open('E:/数据集/lending-club-loan-data/loan.csv',encoding='utf-8')\n",
    "data = pd.read_csv(path)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(887379, 74)"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.shape  #887379个样本， 74个特征"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "先进行空值的查看"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dti_joint                     0.9994\n",
       "verification_status_joint     0.9994\n",
       "annual_inc_joint              0.9994\n",
       "il_util                       0.9790\n",
       "mths_since_rcnt_il            0.9765\n",
       "all_util                      0.9759\n",
       "max_bal_bc                    0.9759\n",
       "open_rv_24m                   0.9759\n",
       "open_rv_12m                   0.9759\n",
       "total_cu_tl                   0.9759\n",
       "total_bal_il                  0.9759\n",
       "open_il_24m                   0.9759\n",
       "open_il_12m                   0.9759\n",
       "open_il_6m                    0.9759\n",
       "open_acc_6m                   0.9759\n",
       "inq_fi                        0.9759\n",
       "inq_last_12m                  0.9759\n",
       "desc                          0.8580\n",
       "mths_since_last_record        0.8456\n",
       "mths_since_last_major_derog   0.7502\n",
       "mths_since_last_delinq        0.5120\n",
       "next_pymnt_d                  0.2851\n",
       "total_rev_hi_lim              0.0792\n",
       "tot_cur_bal                   0.0792\n",
       "tot_coll_amt                  0.0792\n",
       "emp_title                     0.0580\n",
       "emp_length                    0.0505\n",
       "last_pymnt_d                  0.0199\n",
       "revol_util                    0.0006\n",
       "title                         0.0002\n",
       "collections_12_mths_ex_med    0.0002\n",
       "last_credit_pull_d            0.0001\n",
       "earliest_cr_line              0.0000\n",
       "total_acc                     0.0000\n",
       "inq_last_6mths                0.0000\n",
       "open_acc                      0.0000\n",
       "pub_rec                       0.0000\n",
       "delinq_2yrs                   0.0000\n",
       "acc_now_delinq                0.0000\n",
       "annual_inc                    0.0000\n",
       "home_ownership                0.0000\n",
       "sub_grade                     0.0000\n",
       "grade                         0.0000\n",
       "installment                   0.0000\n",
       "int_rate                      0.0000\n",
       "term                          0.0000\n",
       "funded_amnt_inv               0.0000\n",
       "url                           0.0000\n",
       "loan_amnt                     0.0000\n",
       "verification_status           0.0000\n",
       "issue_d                       0.0000\n",
       "loan_status                   0.0000\n",
       "member_id                     0.0000\n",
       "pymnt_plan                    0.0000\n",
       "funded_amnt                   0.0000\n",
       "out_prncp                     0.0000\n",
       "purpose                       0.0000\n",
       "zip_code                      0.0000\n",
       "application_type              0.0000\n",
       "policy_code                   0.0000\n",
       "last_pymnt_amnt               0.0000\n",
       "collection_recovery_fee       0.0000\n",
       "recoveries                    0.0000\n",
       "total_rec_late_fee            0.0000\n",
       "total_rec_int                 0.0000\n",
       "total_rec_prncp               0.0000\n",
       "total_pymnt_inv               0.0000\n",
       "total_pymnt                   0.0000\n",
       "out_prncp_inv                 0.0000\n",
       "initial_list_status           0.0000\n",
       "revol_bal                     0.0000\n",
       "dti                           0.0000\n",
       "addr_state                    0.0000\n",
       "id                            0.0000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_rows',None)\n",
    "data.isnull().sum(axis = 0).sort_values(ascending = False)/len(data)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由上可见某些特征存在大量空值，我们选择剔除空值超过40%的特征\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "#剔除空值超过40%的特征\n",
    "data.dropna(thresh=len(data)*0.4,inplace=True,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mths_since_last_delinq       0.5120\n",
       "next_pymnt_d                 0.2851\n",
       "tot_cur_bal                  0.0792\n",
       "total_rev_hi_lim             0.0792\n",
       "tot_coll_amt                 0.0792\n",
       "emp_title                    0.0580\n",
       "emp_length                   0.0505\n",
       "last_pymnt_d                 0.0199\n",
       "revol_util                   0.0006\n",
       "title                        0.0002\n",
       "collections_12_mths_ex_med   0.0002\n",
       "last_credit_pull_d           0.0001\n",
       "total_acc                    0.0000\n",
       "delinq_2yrs                  0.0000\n",
       "earliest_cr_line             0.0000\n",
       "open_acc                     0.0000\n",
       "pub_rec                      0.0000\n",
       "inq_last_6mths               0.0000\n",
       "acc_now_delinq               0.0000\n",
       "annual_inc                   0.0000\n",
       "out_prncp_inv                0.0000\n",
       "out_prncp                    0.0000\n",
       "issue_d                      0.0000\n",
       "verification_status          0.0000\n",
       "home_ownership               0.0000\n",
       "application_type             0.0000\n",
       "sub_grade                    0.0000\n",
       "grade                        0.0000\n",
       "installment                  0.0000\n",
       "int_rate                     0.0000\n",
       "term                         0.0000\n",
       "funded_amnt_inv              0.0000\n",
       "funded_amnt                  0.0000\n",
       "loan_amnt                    0.0000\n",
       "member_id                    0.0000\n",
       "loan_status                  0.0000\n",
       "pymnt_plan                   0.0000\n",
       "url                          0.0000\n",
       "total_rec_late_fee           0.0000\n",
       "initial_list_status          0.0000\n",
       "total_pymnt                  0.0000\n",
       "total_pymnt_inv              0.0000\n",
       "revol_bal                    0.0000\n",
       "total_rec_prncp              0.0000\n",
       "total_rec_int                0.0000\n",
       "recoveries                   0.0000\n",
       "purpose                      0.0000\n",
       "collection_recovery_fee      0.0000\n",
       "last_pymnt_amnt              0.0000\n",
       "dti                          0.0000\n",
       "addr_state                   0.0000\n",
       "zip_code                     0.0000\n",
       "policy_code                  0.0000\n",
       "id                           0.0000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.isna().sum().sort_values(ascending = False)/len(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "还剩55个特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(887379, 53)"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#每个特征至少有2种取值\n",
    "data = data.loc[:,data.apply(pd.Series.nunique)!=1]  #不重复元素个数不为1\n",
    "data.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "还剩53个特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "float64    30\n",
       "object     21\n",
       "int64       2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 先处理object类型的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "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>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>term</th>\n",
       "      <td>887379</td>\n",
       "      <td>2</td>\n",
       "      <td>36 months</td>\n",
       "      <td>621125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>grade</th>\n",
       "      <td>887379</td>\n",
       "      <td>7</td>\n",
       "      <td>B</td>\n",
       "      <td>254535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sub_grade</th>\n",
       "      <td>887379</td>\n",
       "      <td>35</td>\n",
       "      <td>B3</td>\n",
       "      <td>56323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>emp_title</th>\n",
       "      <td>835917</td>\n",
       "      <td>299271</td>\n",
       "      <td>Teacher</td>\n",
       "      <td>13469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>emp_length</th>\n",
       "      <td>842554</td>\n",
       "      <td>11</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>291569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_ownership</th>\n",
       "      <td>887379</td>\n",
       "      <td>6</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>443557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>verification_status</th>\n",
       "      <td>887379</td>\n",
       "      <td>3</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>329558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>issue_d</th>\n",
       "      <td>887379</td>\n",
       "      <td>103</td>\n",
       "      <td>Oct-2015</td>\n",
       "      <td>48631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>loan_status</th>\n",
       "      <td>887379</td>\n",
       "      <td>10</td>\n",
       "      <td>Current</td>\n",
       "      <td>601779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pymnt_plan</th>\n",
       "      <td>887379</td>\n",
       "      <td>2</td>\n",
       "      <td>n</td>\n",
       "      <td>887369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>url</th>\n",
       "      <td>887379</td>\n",
       "      <td>887379</td>\n",
       "      <td>https://www.lendingclub.com/browse/loanDetail....</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose</th>\n",
       "      <td>887379</td>\n",
       "      <td>14</td>\n",
       "      <td>debt_consolidation</td>\n",
       "      <td>524215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>title</th>\n",
       "      <td>887227</td>\n",
       "      <td>63144</td>\n",
       "      <td>Debt consolidation</td>\n",
       "      <td>414001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zip_code</th>\n",
       "      <td>887379</td>\n",
       "      <td>935</td>\n",
       "      <td>945xx</td>\n",
       "      <td>9770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>addr_state</th>\n",
       "      <td>887379</td>\n",
       "      <td>51</td>\n",
       "      <td>CA</td>\n",
       "      <td>129517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>earliest_cr_line</th>\n",
       "      <td>887350</td>\n",
       "      <td>697</td>\n",
       "      <td>Aug-2001</td>\n",
       "      <td>6659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>initial_list_status</th>\n",
       "      <td>887379</td>\n",
       "      <td>2</td>\n",
       "      <td>f</td>\n",
       "      <td>456848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_pymnt_d</th>\n",
       "      <td>869720</td>\n",
       "      <td>98</td>\n",
       "      <td>Jan-2016</td>\n",
       "      <td>470150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>next_pymnt_d</th>\n",
       "      <td>634408</td>\n",
       "      <td>100</td>\n",
       "      <td>Feb-2016</td>\n",
       "      <td>553406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_credit_pull_d</th>\n",
       "      <td>887326</td>\n",
       "      <td>103</td>\n",
       "      <td>Jan-2016</td>\n",
       "      <td>730574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>application_type</th>\n",
       "      <td>887379</td>\n",
       "      <td>2</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>886868</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      count  unique  \\\n",
       "term                 887379       2   \n",
       "grade                887379       7   \n",
       "sub_grade            887379      35   \n",
       "emp_title            835917  299271   \n",
       "emp_length           842554      11   \n",
       "home_ownership       887379       6   \n",
       "verification_status  887379       3   \n",
       "issue_d              887379     103   \n",
       "loan_status          887379      10   \n",
       "pymnt_plan           887379       2   \n",
       "url                  887379  887379   \n",
       "purpose              887379      14   \n",
       "title                887227   63144   \n",
       "zip_code             887379     935   \n",
       "addr_state           887379      51   \n",
       "earliest_cr_line     887350     697   \n",
       "initial_list_status  887379       2   \n",
       "last_pymnt_d         869720      98   \n",
       "next_pymnt_d         634408     100   \n",
       "last_credit_pull_d   887326     103   \n",
       "application_type     887379       2   \n",
       "\n",
       "                                                                   top    freq  \n",
       "term                                                         36 months  621125  \n",
       "grade                                                                B  254535  \n",
       "sub_grade                                                           B3   56323  \n",
       "emp_title                                                      Teacher   13469  \n",
       "emp_length                                                   10+ years  291569  \n",
       "home_ownership                                                MORTGAGE  443557  \n",
       "verification_status                                    Source Verified  329558  \n",
       "issue_d                                                       Oct-2015   48631  \n",
       "loan_status                                                    Current  601779  \n",
       "pymnt_plan                                                           n  887369  \n",
       "url                  https://www.lendingclub.com/browse/loanDetail....       1  \n",
       "purpose                                             debt_consolidation  524215  \n",
       "title                                               Debt consolidation  414001  \n",
       "zip_code                                                         945xx    9770  \n",
       "addr_state                                                          CA  129517  \n",
       "earliest_cr_line                                              Aug-2001    6659  \n",
       "initial_list_status                                                  f  456848  \n",
       "last_pymnt_d                                                  Jan-2016  470150  \n",
       "next_pymnt_d                                                  Feb-2016  553406  \n",
       "last_credit_pull_d                                            Jan-2016  730574  \n",
       "application_type                                            INDIVIDUAL  886868  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_columns',None)\n",
    "data.select_dtypes(include=['object']).describe().T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "next_pymnt_d           252971\n",
       "emp_title               51462\n",
       "emp_length              44825\n",
       "last_pymnt_d            17659\n",
       "title                     152\n",
       "last_credit_pull_d         53\n",
       "earliest_cr_line           29\n",
       "application_type            0\n",
       "issue_d                     0\n",
       "grade                       0\n",
       "sub_grade                   0\n",
       "home_ownership              0\n",
       "verification_status         0\n",
       "url                         0\n",
       "loan_status                 0\n",
       "pymnt_plan                  0\n",
       "purpose                     0\n",
       "zip_code                    0\n",
       "addr_state                  0\n",
       "initial_list_status         0\n",
       "term                        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.select_dtypes('object').isna().sum().sort_values(ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['term', 'grade', 'sub_grade', 'emp_title', 'emp_length',\n",
       "       'home_ownership', 'verification_status', 'issue_d', 'loan_status',\n",
       "       'pymnt_plan', 'url', 'purpose', 'title', 'zip_code', 'addr_state',\n",
       "       'earliest_cr_line', 'initial_list_status', 'last_pymnt_d',\n",
       "       'next_pymnt_d', 'last_credit_pull_d', 'application_type'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#建立data的备份数据集loans\n",
    "loans = data.copy()\n",
    "\n",
    "#填补loans object列中的缺失数据\n",
    "objectcolumns = loans.select_dtypes('object').columns\n",
    "objectcolumns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "#用Unknown填充object空值\n",
    "loans[objectcolumns] = loans[objectcolumns].fillna('Unknown')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "term                   0\n",
       "grade                  0\n",
       "sub_grade              0\n",
       "emp_title              0\n",
       "emp_length             0\n",
       "home_ownership         0\n",
       "verification_status    0\n",
       "issue_d                0\n",
       "loan_status            0\n",
       "pymnt_plan             0\n",
       "url                    0\n",
       "purpose                0\n",
       "title                  0\n",
       "zip_code               0\n",
       "addr_state             0\n",
       "earliest_cr_line       0\n",
       "initial_list_status    0\n",
       "last_pymnt_d           0\n",
       "next_pymnt_d           0\n",
       "last_credit_pull_d     0\n",
       "application_type       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans[objectcolumns].isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 处理float缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "mths_since_last_delinq       0.5120\n",
       "total_rev_hi_lim             0.0792\n",
       "tot_cur_bal                  0.0792\n",
       "tot_coll_amt                 0.0792\n",
       "revol_util                   0.0006\n",
       "collections_12_mths_ex_med   0.0002\n",
       "delinq_2yrs                  0.0000\n",
       "inq_last_6mths               0.0000\n",
       "open_acc                     0.0000\n",
       "pub_rec                      0.0000\n",
       "total_acc                    0.0000\n",
       "acc_now_delinq               0.0000\n",
       "annual_inc                   0.0000\n",
       "total_pymnt_inv              0.0000\n",
       "last_pymnt_amnt              0.0000\n",
       "funded_amnt                  0.0000\n",
       "funded_amnt_inv              0.0000\n",
       "int_rate                     0.0000\n",
       "installment                  0.0000\n",
       "dti                          0.0000\n",
       "collection_recovery_fee      0.0000\n",
       "total_pymnt                  0.0000\n",
       "recoveries                   0.0000\n",
       "total_rec_late_fee           0.0000\n",
       "revol_bal                    0.0000\n",
       "total_rec_int                0.0000\n",
       "total_rec_prncp              0.0000\n",
       "out_prncp                    0.0000\n",
       "out_prncp_inv                0.0000\n",
       "loan_amnt                    0.0000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans.select_dtypes('float').isna().sum().sort_values(ascending = False)/len(loans)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['loan_amnt', 'funded_amnt', 'funded_amnt_inv', 'int_rate',\n",
       "       'installment', 'annual_inc', 'dti', 'delinq_2yrs', 'inq_last_6mths',\n",
       "       'mths_since_last_delinq', 'open_acc', 'pub_rec', 'revol_bal',\n",
       "       'revol_util', 'total_acc', 'out_prncp', 'out_prncp_inv', 'total_pymnt',\n",
       "       'total_pymnt_inv', 'total_rec_prncp', 'total_rec_int',\n",
       "       'total_rec_late_fee', 'recoveries', 'collection_recovery_fee',\n",
       "       'last_pymnt_amnt', 'collections_12_mths_ex_med', 'acc_now_delinq',\n",
       "       'tot_coll_amt', 'tot_cur_bal', 'total_rev_hi_lim'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numcolumns = loans.select_dtypes('float').columns\n",
    "numcolumns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "#用sklearn 的Imputer模块填补缺数值类的失值\n",
    "from sklearn.preprocessing import Imputer\n",
    "imr = Imputer()#默认用每一列的均值填补本列空值\n",
    "imr = imr.fit(loans[numcolumns])\n",
    "loans[numcolumns] = imr.transform(loans[numcolumns])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "loan_amnt                     0\n",
       "funded_amnt                   0\n",
       "funded_amnt_inv               0\n",
       "int_rate                      0\n",
       "installment                   0\n",
       "annual_inc                    0\n",
       "dti                           0\n",
       "delinq_2yrs                   0\n",
       "inq_last_6mths                0\n",
       "mths_since_last_delinq        0\n",
       "open_acc                      0\n",
       "pub_rec                       0\n",
       "revol_bal                     0\n",
       "revol_util                    0\n",
       "total_acc                     0\n",
       "out_prncp                     0\n",
       "out_prncp_inv                 0\n",
       "total_pymnt                   0\n",
       "total_pymnt_inv               0\n",
       "total_rec_prncp               0\n",
       "total_rec_int                 0\n",
       "total_rec_late_fee            0\n",
       "recoveries                    0\n",
       "collection_recovery_fee       0\n",
       "last_pymnt_amnt               0\n",
       "collections_12_mths_ex_med    0\n",
       "acc_now_delinq                0\n",
       "tot_coll_amt                  0\n",
       "tot_cur_bal                   0\n",
       "total_rev_hi_lim              0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans[numcolumns].isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                            0\n",
       "member_id                     0\n",
       "loan_amnt                     0\n",
       "funded_amnt                   0\n",
       "funded_amnt_inv               0\n",
       "term                          0\n",
       "int_rate                      0\n",
       "installment                   0\n",
       "grade                         0\n",
       "sub_grade                     0\n",
       "emp_title                     0\n",
       "emp_length                    0\n",
       "home_ownership                0\n",
       "annual_inc                    0\n",
       "verification_status           0\n",
       "issue_d                       0\n",
       "loan_status                   0\n",
       "pymnt_plan                    0\n",
       "url                           0\n",
       "purpose                       0\n",
       "title                         0\n",
       "zip_code                      0\n",
       "addr_state                    0\n",
       "dti                           0\n",
       "delinq_2yrs                   0\n",
       "earliest_cr_line              0\n",
       "inq_last_6mths                0\n",
       "mths_since_last_delinq        0\n",
       "open_acc                      0\n",
       "pub_rec                       0\n",
       "revol_bal                     0\n",
       "revol_util                    0\n",
       "total_acc                     0\n",
       "initial_list_status           0\n",
       "out_prncp                     0\n",
       "out_prncp_inv                 0\n",
       "total_pymnt                   0\n",
       "total_pymnt_inv               0\n",
       "total_rec_prncp               0\n",
       "total_rec_int                 0\n",
       "total_rec_late_fee            0\n",
       "recoveries                    0\n",
       "collection_recovery_fee       0\n",
       "last_pymnt_d                  0\n",
       "last_pymnt_amnt               0\n",
       "next_pymnt_d                  0\n",
       "last_credit_pull_d            0\n",
       "collections_12_mths_ex_med    0\n",
       "application_type              0\n",
       "acc_now_delinq                0\n",
       "tot_coll_amt                  0\n",
       "tot_cur_bal                   0\n",
       "total_rev_hi_lim              0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans.isna().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "整个数据集中没有缺失值"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 剔除无效特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'member_id', 'loan_amnt', 'funded_amnt', 'funded_amnt_inv',\n",
       "       'term', 'int_rate', 'installment', 'grade', 'sub_grade', 'emp_title',\n",
       "       'emp_length', 'home_ownership', 'annual_inc', 'verification_status',\n",
       "       'issue_d', 'loan_status', 'pymnt_plan', 'url', 'purpose', 'title',\n",
       "       'zip_code', 'addr_state', 'dti', 'delinq_2yrs', 'earliest_cr_line',\n",
       "       'inq_last_6mths', 'mths_since_last_delinq', 'open_acc', 'pub_rec',\n",
       "       'revol_bal', 'revol_util', 'total_acc', 'initial_list_status',\n",
       "       'out_prncp', 'out_prncp_inv', 'total_pymnt', 'total_pymnt_inv',\n",
       "       'total_rec_prncp', 'total_rec_int', 'total_rec_late_fee', 'recoveries',\n",
       "       'collection_recovery_fee', 'last_pymnt_d', 'last_pymnt_amnt',\n",
       "       'next_pymnt_d', 'last_credit_pull_d', 'collections_12_mths_ex_med',\n",
       "       'application_type', 'acc_now_delinq', 'tot_coll_amt', 'tot_cur_bal',\n",
       "       'total_rev_hi_lim'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "观察数据发现：\n",
    "sub_grade 与 Grade 重复\n",
    "\n",
    "zip_code  policy_code url title year addr_state  next_pymnt_d 等没有作用\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "#剔除对模型没有意义的特征\n",
    "del_feature = ['sub_grade', 'emp_title',  'title', 'zip_code', 'addr_state','url',\n",
    "              'issue_d', 'pymnt_plan',  'earliest_cr_line', 'initial_list_status',\n",
    "               'last_pymnt_d','next_pymnt_d','last_credit_pull_d']\n",
    "loans_2 = loans.drop(del_feature,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(887379, 40)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans_2.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "还剩下40个特征"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 特征工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Current                                                601779\n",
       "Fully Paid                                             207723\n",
       "Charged Off                                             45248\n",
       "Late (31-120 days)                                      11591\n",
       "Issued                                                   8460\n",
       "In Grace Period                                          6253\n",
       "Late (16-30 days)                                        2357\n",
       "Does not meet the credit policy. Status:Fully Paid       1988\n",
       "Default                                                  1219\n",
       "Does not meet the credit policy. Status:Charged Off       761\n",
       "Name: loan_status, dtype: int64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#将object类型用数值编码\n",
    "loans_2['loan_status'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "#正常为0 违约为1\n",
    "def Coding(x):\n",
    "    if x in ('Current','Fully Paid'):\n",
    "        return 0\n",
    "    else:\n",
    "        return 1\n",
    "\n",
    "loans_2['loan_status'] = loans_2['loan_status'].apply(Coding)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    809502\n",
       "1     77877\n",
       "Name: loan_status, dtype: int64"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans_2['loan_status'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Percentage of each Loan Status')"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x504 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize = (14,7))\n",
    "plt.subplot(121)\n",
    "sns.countplot(x = 'loan_status',data = loans_2)\n",
    "plt.title('Frequency of each Loan Status')\n",
    "plt.subplot(122)\n",
    "loans_2['loan_status'].value_counts().plot(kind = 'pie',autopct = '%1.2f')\n",
    "plt.title('Percentage of each Loan Status')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "#将emp_length,grade特征的文字值用数值表示\n",
    "mapping_dict = {\n",
    "    'emp_length':{\n",
    "        '10+ years':10,\n",
    "        '9 years' :9,\n",
    "        '8 years' :8,\n",
    "        '7 years' :7,\n",
    "        '6 years' :6,\n",
    "        '5 years' :5,\n",
    "        '4 years' :4,\n",
    "        '3 years' :3,\n",
    "        '2 years' :2,\n",
    "        '1 year' :1,\n",
    "        '< 1 year':0,\n",
    "        'Unknown' :0\n",
    "    },\n",
    "    'grade':{\n",
    "        'A':1,\n",
    "        'B':2,\n",
    "        'C':3,\n",
    "        'D':4,\n",
    "        'E':5,\n",
    "        'F':6,\n",
    "        'G':7\n",
    "    }\n",
    "}\n",
    "\n",
    "loans_2 = loans_2.replace(mapping_dict)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "scrolled": true
   },
   "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>emp_length</th>\n",
       "      <th>grade</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>115430</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>57095</td>\n",
       "      <td>148202.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>78870</td>\n",
       "      <td>254535.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70026</td>\n",
       "      <td>245860.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>52529</td>\n",
       "      <td>139542.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>55704</td>\n",
       "      <td>70705.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>42950</td>\n",
       "      <td>23046.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>44594</td>\n",
       "      <td>5489.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>43955</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>34657</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>291569</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    emp_length       grade\n",
       "0       115430         nan\n",
       "1        57095 148202.0000\n",
       "2        78870 254535.0000\n",
       "3        70026 245860.0000\n",
       "4        52529 139542.0000\n",
       "5        55704  70705.0000\n",
       "6        42950  23046.0000\n",
       "7        44594   5489.0000\n",
       "8        43955         nan\n",
       "9        34657         nan\n",
       "10      291569         nan"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans_2[['emp_length','grade']].apply(pd.value_counts)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上可以看出 emp_length，grade 已转为数值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "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>id</th>\n",
       "      <th>member_id</th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>funded_amnt</th>\n",
       "      <th>funded_amnt_inv</th>\n",
       "      <th>term</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>grade</th>\n",
       "      <th>emp_length</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>purpose</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>mths_since_last_delinq</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</th>\n",
       "      <th>revol_util</th>\n",
       "      <th>total_acc</th>\n",
       "      <th>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>application_type</th>\n",
       "      <th>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>total_rev_hi_lim</th>\n",
       "      <th>home_ownership_ANY</th>\n",
       "      <th>home_ownership_MORTGAGE</th>\n",
       "      <th>home_ownership_NONE</th>\n",
       "      <th>home_ownership_OTHER</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>application_type_INDIVIDUAL</th>\n",
       "      <th>application_type_JOINT</th>\n",
       "      <th>purpose_car</th>\n",
       "      <th>purpose_credit_card</th>\n",
       "      <th>purpose_debt_consolidation</th>\n",
       "      <th>purpose_educational</th>\n",
       "      <th>purpose_home_improvement</th>\n",
       "      <th>purpose_house</th>\n",
       "      <th>purpose_major_purchase</th>\n",
       "      <th>purpose_medical</th>\n",
       "      <th>purpose_moving</th>\n",
       "      <th>purpose_other</th>\n",
       "      <th>purpose_renewable_energy</th>\n",
       "      <th>purpose_small_business</th>\n",
       "      <th>purpose_vacation</th>\n",
       "      <th>purpose_wedding</th>\n",
       "      <th>term_ 36 months</th>\n",
       "      <th>term_ 60 months</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1077501</td>\n",
       "      <td>1296599</td>\n",
       "      <td>5000.0000</td>\n",
       "      <td>5000.0000</td>\n",
       "      <td>4975.0000</td>\n",
       "      <td>36 months</td>\n",
       "      <td>10.6500</td>\n",
       "      <td>162.8700</td>\n",
       "      <td>2</td>\n",
       "      <td>10</td>\n",
       "      <td>RENT</td>\n",
       "      <td>24000.0000</td>\n",
       "      <td>Verified</td>\n",
       "      <td>0</td>\n",
       "      <td>credit_card</td>\n",
       "      <td>27.6500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>34.0638</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>13648.0000</td>\n",
       "      <td>83.7000</td>\n",
       "      <td>9.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5861.0714</td>\n",
       "      <td>5831.7800</td>\n",
       "      <td>5000.0000</td>\n",
       "      <td>861.0700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>171.6200</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>225.7026</td>\n",
       "      <td>139458.1893</td>\n",
       "      <td>32068.6200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1077430</td>\n",
       "      <td>1314167</td>\n",
       "      <td>2500.0000</td>\n",
       "      <td>2500.0000</td>\n",
       "      <td>2500.0000</td>\n",
       "      <td>60 months</td>\n",
       "      <td>15.2700</td>\n",
       "      <td>59.8300</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>RENT</td>\n",
       "      <td>30000.0000</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>1</td>\n",
       "      <td>car</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5.0000</td>\n",
       "      <td>34.0638</td>\n",
       "      <td>3.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1687.0000</td>\n",
       "      <td>9.4000</td>\n",
       "      <td>4.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1008.7100</td>\n",
       "      <td>1008.7100</td>\n",
       "      <td>456.4600</td>\n",
       "      <td>435.1700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>117.0800</td>\n",
       "      <td>1.1100</td>\n",
       "      <td>119.6600</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>225.7026</td>\n",
       "      <td>139458.1893</td>\n",
       "      <td>32068.6200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1077175</td>\n",
       "      <td>1313524</td>\n",
       "      <td>2400.0000</td>\n",
       "      <td>2400.0000</td>\n",
       "      <td>2400.0000</td>\n",
       "      <td>36 months</td>\n",
       "      <td>15.9600</td>\n",
       "      <td>84.3300</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>RENT</td>\n",
       "      <td>12252.0000</td>\n",
       "      <td>Not Verified</td>\n",
       "      <td>0</td>\n",
       "      <td>small_business</td>\n",
       "      <td>8.7200</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>34.0638</td>\n",
       "      <td>2.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>2956.0000</td>\n",
       "      <td>98.5000</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>3003.6536</td>\n",
       "      <td>3003.6500</td>\n",
       "      <td>2400.0000</td>\n",
       "      <td>603.6500</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>649.9100</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>225.7026</td>\n",
       "      <td>139458.1893</td>\n",
       "      <td>32068.6200</td>\n",
       "      <td>0</td>\n",
       "      <td>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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1076863</td>\n",
       "      <td>1277178</td>\n",
       "      <td>10000.0000</td>\n",
       "      <td>10000.0000</td>\n",
       "      <td>10000.0000</td>\n",
       "      <td>36 months</td>\n",
       "      <td>13.4900</td>\n",
       "      <td>339.3100</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>RENT</td>\n",
       "      <td>49200.0000</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>0</td>\n",
       "      <td>other</td>\n",
       "      <td>20.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>35.0000</td>\n",
       "      <td>10.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>5598.0000</td>\n",
       "      <td>21.0000</td>\n",
       "      <td>37.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>12226.3022</td>\n",
       "      <td>12226.3000</td>\n",
       "      <td>10000.0000</td>\n",
       "      <td>2209.3300</td>\n",
       "      <td>16.9700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>357.4800</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>225.7026</td>\n",
       "      <td>139458.1893</td>\n",
       "      <td>32068.6200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1075358</td>\n",
       "      <td>1311748</td>\n",
       "      <td>3000.0000</td>\n",
       "      <td>3000.0000</td>\n",
       "      <td>3000.0000</td>\n",
       "      <td>60 months</td>\n",
       "      <td>12.6900</td>\n",
       "      <td>67.7900</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>RENT</td>\n",
       "      <td>80000.0000</td>\n",
       "      <td>Source Verified</td>\n",
       "      <td>0</td>\n",
       "      <td>other</td>\n",
       "      <td>17.9400</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>38.0000</td>\n",
       "      <td>15.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>27783.0000</td>\n",
       "      <td>53.9000</td>\n",
       "      <td>38.0000</td>\n",
       "      <td>766.9000</td>\n",
       "      <td>766.9000</td>\n",
       "      <td>3242.1700</td>\n",
       "      <td>3242.1700</td>\n",
       "      <td>2233.1000</td>\n",
       "      <td>1009.0700</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>67.7900</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>225.7026</td>\n",
       "      <td>139458.1893</td>\n",
       "      <td>32068.6200</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        id  member_id  loan_amnt  funded_amnt  funded_amnt_inv        term  \\\n",
       "0  1077501    1296599  5000.0000    5000.0000        4975.0000   36 months   \n",
       "1  1077430    1314167  2500.0000    2500.0000        2500.0000   60 months   \n",
       "2  1077175    1313524  2400.0000    2400.0000        2400.0000   36 months   \n",
       "3  1076863    1277178 10000.0000   10000.0000       10000.0000   36 months   \n",
       "4  1075358    1311748  3000.0000    3000.0000        3000.0000   60 months   \n",
       "\n",
       "   int_rate  installment  grade  emp_length home_ownership  annual_inc  \\\n",
       "0   10.6500     162.8700      2          10           RENT  24000.0000   \n",
       "1   15.2700      59.8300      3           0           RENT  30000.0000   \n",
       "2   15.9600      84.3300      3          10           RENT  12252.0000   \n",
       "3   13.4900     339.3100      3          10           RENT  49200.0000   \n",
       "4   12.6900      67.7900      2           1           RENT  80000.0000   \n",
       "\n",
       "  verification_status  loan_status         purpose     dti  delinq_2yrs  \\\n",
       "0            Verified            0     credit_card 27.6500       0.0000   \n",
       "1     Source Verified            1             car  1.0000       0.0000   \n",
       "2        Not Verified            0  small_business  8.7200       0.0000   \n",
       "3     Source Verified            0           other 20.0000       0.0000   \n",
       "4     Source Verified            0           other 17.9400       0.0000   \n",
       "\n",
       "   inq_last_6mths  mths_since_last_delinq  open_acc  pub_rec  revol_bal  \\\n",
       "0          1.0000                 34.0638    3.0000   0.0000 13648.0000   \n",
       "1          5.0000                 34.0638    3.0000   0.0000  1687.0000   \n",
       "2          2.0000                 34.0638    2.0000   0.0000  2956.0000   \n",
       "3          1.0000                 35.0000   10.0000   0.0000  5598.0000   \n",
       "4          0.0000                 38.0000   15.0000   0.0000 27783.0000   \n",
       "\n",
       "   revol_util  total_acc  out_prncp  out_prncp_inv  total_pymnt  \\\n",
       "0     83.7000     9.0000     0.0000         0.0000    5861.0714   \n",
       "1      9.4000     4.0000     0.0000         0.0000    1008.7100   \n",
       "2     98.5000    10.0000     0.0000         0.0000    3003.6536   \n",
       "3     21.0000    37.0000     0.0000         0.0000   12226.3022   \n",
       "4     53.9000    38.0000   766.9000       766.9000    3242.1700   \n",
       "\n",
       "   total_pymnt_inv  total_rec_prncp  total_rec_int  total_rec_late_fee  \\\n",
       "0        5831.7800        5000.0000       861.0700              0.0000   \n",
       "1        1008.7100         456.4600       435.1700              0.0000   \n",
       "2        3003.6500        2400.0000       603.6500              0.0000   \n",
       "3       12226.3000       10000.0000      2209.3300             16.9700   \n",
       "4        3242.1700        2233.1000      1009.0700              0.0000   \n",
       "\n",
       "   recoveries  collection_recovery_fee  last_pymnt_amnt  \\\n",
       "0      0.0000                   0.0000         171.6200   \n",
       "1    117.0800                   1.1100         119.6600   \n",
       "2      0.0000                   0.0000         649.9100   \n",
       "3      0.0000                   0.0000         357.4800   \n",
       "4      0.0000                   0.0000          67.7900   \n",
       "\n",
       "   collections_12_mths_ex_med application_type  acc_now_delinq  tot_coll_amt  \\\n",
       "0                      0.0000       INDIVIDUAL          0.0000      225.7026   \n",
       "1                      0.0000       INDIVIDUAL          0.0000      225.7026   \n",
       "2                      0.0000       INDIVIDUAL          0.0000      225.7026   \n",
       "3                      0.0000       INDIVIDUAL          0.0000      225.7026   \n",
       "4                      0.0000       INDIVIDUAL          0.0000      225.7026   \n",
       "\n",
       "   tot_cur_bal  total_rev_hi_lim  home_ownership_ANY  home_ownership_MORTGAGE  \\\n",
       "0  139458.1893        32068.6200                   0                        0   \n",
       "1  139458.1893        32068.6200                   0                        0   \n",
       "2  139458.1893        32068.6200                   0                        0   \n",
       "3  139458.1893        32068.6200                   0                        0   \n",
       "4  139458.1893        32068.6200                   0                        0   \n",
       "\n",
       "   home_ownership_NONE  home_ownership_OTHER  home_ownership_OWN  \\\n",
       "0                    0                     0                   0   \n",
       "1                    0                     0                   0   \n",
       "2                    0                     0                   0   \n",
       "3                    0                     0                   0   \n",
       "4                    0                     0                   0   \n",
       "\n",
       "   home_ownership_RENT  verification_status_Not Verified  \\\n",
       "0                    1                                 0   \n",
       "1                    1                                 0   \n",
       "2                    1                                 1   \n",
       "3                    1                                 0   \n",
       "4                    1                                 0   \n",
       "\n",
       "   verification_status_Source Verified  verification_status_Verified  \\\n",
       "0                                    0                             1   \n",
       "1                                    1                             0   \n",
       "2                                    0                             0   \n",
       "3                                    1                             0   \n",
       "4                                    1                             0   \n",
       "\n",
       "   application_type_INDIVIDUAL  application_type_JOINT  purpose_car  \\\n",
       "0                            1                       0            0   \n",
       "1                            1                       0            1   \n",
       "2                            1                       0            0   \n",
       "3                            1                       0            0   \n",
       "4                            1                       0            0   \n",
       "\n",
       "   purpose_credit_card  purpose_debt_consolidation  purpose_educational  \\\n",
       "0                    1                           0                    0   \n",
       "1                    0                           0                    0   \n",
       "2                    0                           0                    0   \n",
       "3                    0                           0                    0   \n",
       "4                    0                           0                    0   \n",
       "\n",
       "   purpose_home_improvement  purpose_house  purpose_major_purchase  \\\n",
       "0                         0              0                       0   \n",
       "1                         0              0                       0   \n",
       "2                         0              0                       0   \n",
       "3                         0              0                       0   \n",
       "4                         0              0                       0   \n",
       "\n",
       "   purpose_medical  purpose_moving  purpose_other  purpose_renewable_energy  \\\n",
       "0                0               0              0                         0   \n",
       "1                0               0              0                         0   \n",
       "2                0               0              0                         0   \n",
       "3                0               0              1                         0   \n",
       "4                0               0              1                         0   \n",
       "\n",
       "   purpose_small_business  purpose_vacation  purpose_wedding  term_ 36 months  \\\n",
       "0                       0                 0                0                1   \n",
       "1                       0                 0                0                0   \n",
       "2                       1                 0                0                1   \n",
       "3                       0                 0                0                1   \n",
       "4                       0                 0                0                0   \n",
       "\n",
       "   term_ 60 months  \n",
       "0                0  \n",
       "1                1  \n",
       "2                0  \n",
       "3                0  \n",
       "4                1  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#one_hot编码\n",
    "oh_feature = [\"home_ownership\", \"verification_status\", \"application_type\",\"purpose\", \"term\"] \n",
    "dumm_feature = pd.get_dummies(loans_2[oh_feature])\n",
    "loans_2 = pd.concat([loans_2,dumm_feature],axis=1)\n",
    "loans_2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(887379, 67)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans_2.isna() .shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "经过one_hot操作变成了67个特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(887379, 7)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loans_2.loc[:,loans_2.columns.str.contains('home_ownership')].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(887379, 62)"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#剔除被one_hot 的特征\n",
    "loans_2 = loans_2.drop(oh_feature,axis=1)\n",
    "loans_2.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 特征缩放"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_col = loans_2.select_dtypes(['float64','int64']).columns\n",
    "num_col = num_col.drop('loan_status')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "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>id</th>\n",
       "      <th>member_id</th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>funded_amnt</th>\n",
       "      <th>funded_amnt_inv</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>grade</th>\n",
       "      <th>emp_length</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>mths_since_last_delinq</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</th>\n",
       "      <th>revol_util</th>\n",
       "      <th>total_acc</th>\n",
       "      <th>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>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>total_rev_hi_lim</th>\n",
       "      <th>home_ownership_ANY</th>\n",
       "      <th>home_ownership_MORTGAGE</th>\n",
       "      <th>home_ownership_NONE</th>\n",
       "      <th>home_ownership_OTHER</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>application_type_INDIVIDUAL</th>\n",
       "      <th>application_type_JOINT</th>\n",
       "      <th>purpose_car</th>\n",
       "      <th>purpose_credit_card</th>\n",
       "      <th>purpose_debt_consolidation</th>\n",
       "      <th>purpose_educational</th>\n",
       "      <th>purpose_home_improvement</th>\n",
       "      <th>purpose_house</th>\n",
       "      <th>purpose_major_purchase</th>\n",
       "      <th>purpose_medical</th>\n",
       "      <th>purpose_moving</th>\n",
       "      <th>purpose_other</th>\n",
       "      <th>purpose_renewable_energy</th>\n",
       "      <th>purpose_small_business</th>\n",
       "      <th>purpose_vacation</th>\n",
       "      <th>purpose_wedding</th>\n",
       "      <th>term_ 36 months</th>\n",
       "      <th>term_ 60 months</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1.3750</td>\n",
       "      <td>-1.3978</td>\n",
       "      <td>-1.1565</td>\n",
       "      <td>-1.1556</td>\n",
       "      <td>-1.1523</td>\n",
       "      <td>-0.5926</td>\n",
       "      <td>-1.1215</td>\n",
       "      <td>-0.6083</td>\n",
       "      <td>1.1281</td>\n",
       "      <td>-0.7887</td>\n",
       "      <td>0</td>\n",
       "      <td>0.5522</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>0.3059</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-1.6077</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>-0.1459</td>\n",
       "      <td>1.2016</td>\n",
       "      <td>-1.3739</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.2157</td>\n",
       "      <td>-0.2153</td>\n",
       "      <td>-0.1144</td>\n",
       "      <td>-0.4265</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.4156</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.3750</td>\n",
       "      <td>-1.3971</td>\n",
       "      <td>-1.4528</td>\n",
       "      <td>-1.4522</td>\n",
       "      <td>-1.4454</td>\n",
       "      <td>0.4617</td>\n",
       "      <td>-1.5434</td>\n",
       "      <td>0.1536</td>\n",
       "      <td>-1.4986</td>\n",
       "      <td>-0.6960</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.9980</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>4.3121</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-1.6077</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>-0.6793</td>\n",
       "      <td>-1.9166</td>\n",
       "      <td>-1.7962</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.8322</td>\n",
       "      <td>-0.8300</td>\n",
       "      <td>-0.8001</td>\n",
       "      <td>-0.6298</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>0.1737</td>\n",
       "      <td>-0.0597</td>\n",
       "      <td>-0.4264</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-1.3750</td>\n",
       "      <td>-1.3971</td>\n",
       "      <td>-1.4647</td>\n",
       "      <td>-1.4641</td>\n",
       "      <td>-1.4573</td>\n",
       "      <td>0.6192</td>\n",
       "      <td>-1.4431</td>\n",
       "      <td>0.1536</td>\n",
       "      <td>1.1281</td>\n",
       "      <td>-0.9703</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.5490</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>1.3074</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>-1.7958</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>-0.6227</td>\n",
       "      <td>1.8228</td>\n",
       "      <td>-1.2895</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.5787</td>\n",
       "      <td>-0.5758</td>\n",
       "      <td>-0.5068</td>\n",
       "      <td>-0.5494</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.3158</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1.3750</td>\n",
       "      <td>-1.3986</td>\n",
       "      <td>-0.5637</td>\n",
       "      <td>-0.5625</td>\n",
       "      <td>-0.5570</td>\n",
       "      <td>0.0555</td>\n",
       "      <td>-0.3989</td>\n",
       "      <td>0.1536</td>\n",
       "      <td>1.1281</td>\n",
       "      <td>-0.3992</td>\n",
       "      <td>0</td>\n",
       "      <td>0.1072</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>0.3059</td>\n",
       "      <td>0.0612</td>\n",
       "      <td>-0.2912</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>-0.5049</td>\n",
       "      <td>-1.4298</td>\n",
       "      <td>0.9908</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>0.5930</td>\n",
       "      <td>0.5997</td>\n",
       "      <td>0.6403</td>\n",
       "      <td>0.2169</td>\n",
       "      <td>4.0543</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.3768</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-1.3751</td>\n",
       "      <td>-1.3972</td>\n",
       "      <td>-1.3936</td>\n",
       "      <td>-1.3929</td>\n",
       "      <td>-1.3862</td>\n",
       "      <td>-0.1271</td>\n",
       "      <td>-1.5108</td>\n",
       "      <td>-0.6083</td>\n",
       "      <td>-1.2359</td>\n",
       "      <td>0.0769</td>\n",
       "      <td>0</td>\n",
       "      <td>-0.0126</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>-0.6957</td>\n",
       "      <td>0.2575</td>\n",
       "      <td>0.6491</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>0.4843</td>\n",
       "      <td>-0.0490</td>\n",
       "      <td>1.0753</td>\n",
       "      <td>-0.8991</td>\n",
       "      <td>-0.8990</td>\n",
       "      <td>-0.5484</td>\n",
       "      <td>-0.5454</td>\n",
       "      <td>-0.5320</td>\n",
       "      <td>-0.3559</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.4372</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id  member_id  loan_amnt  funded_amnt  funded_amnt_inv  int_rate  \\\n",
       "0 -1.3750    -1.3978    -1.1565      -1.1556          -1.1523   -0.5926   \n",
       "1 -1.3750    -1.3971    -1.4528      -1.4522          -1.4454    0.4617   \n",
       "2 -1.3750    -1.3971    -1.4647      -1.4641          -1.4573    0.6192   \n",
       "3 -1.3750    -1.3986    -0.5637      -0.5625          -0.5570    0.0555   \n",
       "4 -1.3751    -1.3972    -1.3936      -1.3929          -1.3862   -0.1271   \n",
       "\n",
       "   installment   grade  emp_length  annual_inc  loan_status     dti  \\\n",
       "0      -1.1215 -0.6083      1.1281     -0.7887            0  0.5522   \n",
       "1      -1.5434  0.1536     -1.4986     -0.6960            1 -0.9980   \n",
       "2      -1.4431  0.1536      1.1281     -0.9703            0 -0.5490   \n",
       "3      -0.3989  0.1536      1.1281     -0.3992            0  0.1072   \n",
       "4      -1.5108 -0.6083     -1.2359      0.0769            0 -0.0126   \n",
       "\n",
       "   delinq_2yrs  inq_last_6mths  mths_since_last_delinq  open_acc  pub_rec  \\\n",
       "0      -0.3647          0.3059                  0.0000   -1.6077  -0.3355   \n",
       "1      -0.3647          4.3121                  0.0000   -1.6077  -0.3355   \n",
       "2      -0.3647          1.3074                  0.0000   -1.7958  -0.3355   \n",
       "3      -0.3647          0.3059                  0.0612   -0.2912  -0.3355   \n",
       "4      -0.3647         -0.6957                  0.2575    0.6491  -0.3355   \n",
       "\n",
       "   revol_bal  revol_util  total_acc  out_prncp  out_prncp_inv  total_pymnt  \\\n",
       "0    -0.1459      1.2016    -1.3739    -0.9894        -0.9894      -0.2157   \n",
       "1    -0.6793     -1.9166    -1.7962    -0.9894        -0.9894      -0.8322   \n",
       "2    -0.6227      1.8228    -1.2895    -0.9894        -0.9894      -0.5787   \n",
       "3    -0.5049     -1.4298     0.9908    -0.9894        -0.9894       0.5930   \n",
       "4     0.4843     -0.0490     1.0753    -0.8991        -0.8990      -0.5484   \n",
       "\n",
       "   total_pymnt_inv  total_rec_prncp  total_rec_int  total_rec_late_fee  \\\n",
       "0          -0.2153          -0.1144        -0.4265             -0.0970   \n",
       "1          -0.8300          -0.8001        -0.6298             -0.0970   \n",
       "2          -0.5758          -0.5068        -0.5494             -0.0970   \n",
       "3           0.5997           0.6403         0.2169              4.0543   \n",
       "4          -0.5454          -0.5320        -0.3559             -0.0970   \n",
       "\n",
       "   recoveries  collection_recovery_fee  last_pymnt_amnt  \\\n",
       "0     -0.1121                  -0.0773          -0.4156   \n",
       "1      0.1737                  -0.0597          -0.4264   \n",
       "2     -0.1121                  -0.0773          -0.3158   \n",
       "3     -0.1121                  -0.0773          -0.3768   \n",
       "4     -0.1121                  -0.0773          -0.4372   \n",
       "\n",
       "   collections_12_mths_ex_med  acc_now_delinq  tot_coll_amt  tot_cur_bal  \\\n",
       "0                     -0.1072         -0.0643        0.0000       0.0000   \n",
       "1                     -0.1072         -0.0643        0.0000       0.0000   \n",
       "2                     -0.1072         -0.0643        0.0000       0.0000   \n",
       "3                     -0.1072         -0.0643        0.0000       0.0000   \n",
       "4                     -0.1072         -0.0643        0.0000       0.0000   \n",
       "\n",
       "   total_rev_hi_lim  home_ownership_ANY  home_ownership_MORTGAGE  \\\n",
       "0            0.0000                   0                        0   \n",
       "1            0.0000                   0                        0   \n",
       "2            0.0000                   0                        0   \n",
       "3            0.0000                   0                        0   \n",
       "4            0.0000                   0                        0   \n",
       "\n",
       "   home_ownership_NONE  home_ownership_OTHER  home_ownership_OWN  \\\n",
       "0                    0                     0                   0   \n",
       "1                    0                     0                   0   \n",
       "2                    0                     0                   0   \n",
       "3                    0                     0                   0   \n",
       "4                    0                     0                   0   \n",
       "\n",
       "   home_ownership_RENT  verification_status_Not Verified  \\\n",
       "0                    1                                 0   \n",
       "1                    1                                 0   \n",
       "2                    1                                 1   \n",
       "3                    1                                 0   \n",
       "4                    1                                 0   \n",
       "\n",
       "   verification_status_Source Verified  verification_status_Verified  \\\n",
       "0                                    0                             1   \n",
       "1                                    1                             0   \n",
       "2                                    0                             0   \n",
       "3                                    1                             0   \n",
       "4                                    1                             0   \n",
       "\n",
       "   application_type_INDIVIDUAL  application_type_JOINT  purpose_car  \\\n",
       "0                            1                       0            0   \n",
       "1                            1                       0            1   \n",
       "2                            1                       0            0   \n",
       "3                            1                       0            0   \n",
       "4                            1                       0            0   \n",
       "\n",
       "   purpose_credit_card  purpose_debt_consolidation  purpose_educational  \\\n",
       "0                    1                           0                    0   \n",
       "1                    0                           0                    0   \n",
       "2                    0                           0                    0   \n",
       "3                    0                           0                    0   \n",
       "4                    0                           0                    0   \n",
       "\n",
       "   purpose_home_improvement  purpose_house  purpose_major_purchase  \\\n",
       "0                         0              0                       0   \n",
       "1                         0              0                       0   \n",
       "2                         0              0                       0   \n",
       "3                         0              0                       0   \n",
       "4                         0              0                       0   \n",
       "\n",
       "   purpose_medical  purpose_moving  purpose_other  purpose_renewable_energy  \\\n",
       "0                0               0              0                         0   \n",
       "1                0               0              0                         0   \n",
       "2                0               0              0                         0   \n",
       "3                0               0              1                         0   \n",
       "4                0               0              1                         0   \n",
       "\n",
       "   purpose_small_business  purpose_vacation  purpose_wedding  term_ 36 months  \\\n",
       "0                       0                 0                0                1   \n",
       "1                       0                 0                0                0   \n",
       "2                       1                 0                0                1   \n",
       "3                       0                 0                0                1   \n",
       "4                       0                 0                0                0   \n",
       "\n",
       "   term_ 60 months  \n",
       "0                0  \n",
       "1                1  \n",
       "2                0  \n",
       "3                0  \n",
       "4                1  "
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#标准化处理，并建立loans_3保存\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "ssc = StandardScaler()\n",
    "loans_3 = loans_2\n",
    "#数据太多只能分列标准化处理\n",
    "for name in num_col:\n",
    "    loans_3[name] = ssc.fit_transform(np.array(loans_2[name]).reshape(-1,1))\n",
    "loans_3.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 特征选择"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = loans_3.drop('loan_status',axis=1)\n",
    "y = loans_3['loan_status']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "scrolled": true
   },
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.4198</td>\n",
       "      <td>-1.0189</td>\n",
       "      <td>0.0862</td>\n",
       "      <td>0.9832</td>\n",
       "      <td>1.5837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>member_id</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.4486</td>\n",
       "      <td>-1.0005</td>\n",
       "      <td>0.0868</td>\n",
       "      <td>0.9733</td>\n",
       "      <td>1.5984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>loan_amnt</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.6899</td>\n",
       "      <td>-0.8008</td>\n",
       "      <td>-0.2081</td>\n",
       "      <td>0.6217</td>\n",
       "      <td>2.4000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>funded_amnt</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.6894</td>\n",
       "      <td>-0.7998</td>\n",
       "      <td>-0.2066</td>\n",
       "      <td>0.6237</td>\n",
       "      <td>2.4031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>funded_amnt_inv</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.7416</td>\n",
       "      <td>-0.7939</td>\n",
       "      <td>-0.2017</td>\n",
       "      <td>0.6275</td>\n",
       "      <td>2.4043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>int_rate</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.8090</td>\n",
       "      <td>-0.7432</td>\n",
       "      <td>-0.0586</td>\n",
       "      <td>0.6740</td>\n",
       "      <td>3.5928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installment</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.7243</td>\n",
       "      <td>-0.7208</td>\n",
       "      <td>-0.2218</td>\n",
       "      <td>0.5565</td>\n",
       "      <td>4.1310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>grade</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.3701</td>\n",
       "      <td>-0.6083</td>\n",
       "      <td>0.1536</td>\n",
       "      <td>0.9154</td>\n",
       "      <td>3.2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>emp_length</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.4986</td>\n",
       "      <td>-0.9732</td>\n",
       "      <td>0.0774</td>\n",
       "      <td>1.1281</td>\n",
       "      <td>1.1281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>annual_inc</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.1597</td>\n",
       "      <td>-0.4641</td>\n",
       "      <td>-0.1550</td>\n",
       "      <td>0.2314</td>\n",
       "      <td>145.6761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dti</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-1.0562</td>\n",
       "      <td>-0.3634</td>\n",
       "      <td>-0.0295</td>\n",
       "      <td>0.3370</td>\n",
       "      <td>580.5983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>44.8669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.6957</td>\n",
       "      <td>-0.6957</td>\n",
       "      <td>-0.6957</td>\n",
       "      <td>0.3059</td>\n",
       "      <td>32.3561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mths_since_last_delinq</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-2.2281</td>\n",
       "      <td>-0.1350</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>10.0687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>open_acc</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-2.1719</td>\n",
       "      <td>-0.6674</td>\n",
       "      <td>-0.1031</td>\n",
       "      <td>0.4611</td>\n",
       "      <td>14.7542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pub_rec</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>147.4103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revol_bal</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.7545</td>\n",
       "      <td>-0.4672</td>\n",
       "      <td>-0.2250</td>\n",
       "      <td>0.1743</td>\n",
       "      <td>128.7708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revol_util</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-2.3111</td>\n",
       "      <td>-0.7289</td>\n",
       "      <td>0.0391</td>\n",
       "      <td>0.7778</td>\n",
       "      <td>35.1371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_acc</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-2.0496</td>\n",
       "      <td>-0.6983</td>\n",
       "      <td>-0.1071</td>\n",
       "      <td>0.5686</td>\n",
       "      <td>12.1392</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>out_prncp</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.2290</td>\n",
       "      <td>0.6188</td>\n",
       "      <td>4.8237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>out_prncp_inv</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.2290</td>\n",
       "      <td>0.6189</td>\n",
       "      <td>4.8261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_pymnt</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.9603</td>\n",
       "      <td>-0.7171</td>\n",
       "      <td>-0.3384</td>\n",
       "      <td>0.3885</td>\n",
       "      <td>6.3800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_pymnt_inv</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.9586</td>\n",
       "      <td>-0.7165</td>\n",
       "      <td>-0.3389</td>\n",
       "      <td>0.3880</td>\n",
       "      <td>6.4053</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_rec_prncp</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.8690</td>\n",
       "      <td>-0.6878</td>\n",
       "      <td>-0.3837</td>\n",
       "      <td>0.3384</td>\n",
       "      <td>4.4136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_rec_int</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.8375</td>\n",
       "      <td>-0.6268</td>\n",
       "      <td>-0.3253</td>\n",
       "      <td>0.2307</td>\n",
       "      <td>10.7146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_rec_late_fee</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>87.6465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>recoveries</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>81.7058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>collection_recovery_fee</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>110.8480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>last_pymnt_amnt</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.4514</td>\n",
       "      <td>-0.3929</td>\n",
       "      <td>-0.3548</td>\n",
       "      <td>-0.2780</td>\n",
       "      <td>7.1560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>collections_12_mths_ex_med</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>148.9467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>acc_now_delinq</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>180.2922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.0228</td>\n",
       "      <td>-0.0228</td>\n",
       "      <td>-0.0228</td>\n",
       "      <td>-0.0228</td>\n",
       "      <td>924.9779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.9452</td>\n",
       "      <td>-0.7267</td>\n",
       "      <td>-0.2668</td>\n",
       "      <td>0.3818</td>\n",
       "      <td>53.2793</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_rev_hi_lim</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>-0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>-0.8912</td>\n",
       "      <td>-0.4827</td>\n",
       "      <td>-0.1742</td>\n",
       "      <td>0.1593</td>\n",
       "      <td>277.0195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_ownership_ANY</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0018</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_ownership_MORTGAGE</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.4999</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_ownership_NONE</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>0.0075</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_ownership_OTHER</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>0.0143</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_ownership_OWN</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0986</td>\n",
       "      <td>0.2981</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_ownership_RENT</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.4013</td>\n",
       "      <td>0.4902</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>verification_status_Not Verified</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.3006</td>\n",
       "      <td>0.4585</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>verification_status_Source Verified</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.3714</td>\n",
       "      <td>0.4832</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>verification_status_Verified</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.3280</td>\n",
       "      <td>0.4695</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>application_type_INDIVIDUAL</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.9994</td>\n",
       "      <td>0.0240</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>application_type_JOINT</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>0.0240</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_car</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>0.0994</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_credit_card</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.2323</td>\n",
       "      <td>0.4223</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_debt_consolidation</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.5907</td>\n",
       "      <td>0.4917</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_educational</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>0.0218</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_home_improvement</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0584</td>\n",
       "      <td>0.2345</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_house</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0042</td>\n",
       "      <td>0.0645</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_major_purchase</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0195</td>\n",
       "      <td>0.1382</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_medical</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>0.0976</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_moving</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0061</td>\n",
       "      <td>0.0779</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_other</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0483</td>\n",
       "      <td>0.2145</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_renewable_energy</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>0.0254</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_small_business</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0117</td>\n",
       "      <td>0.1075</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_vacation</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>0.0729</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>purpose_wedding</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.0514</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>term_ 36 months</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.7000</td>\n",
       "      <td>0.4583</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>term_ 60 months</th>\n",
       "      <td>887379.0000</td>\n",
       "      <td>0.3000</td>\n",
       "      <td>0.4583</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          count    mean    std     min  \\\n",
       "id                                  887379.0000 -0.0000 1.0000 -1.4198   \n",
       "member_id                           887379.0000 -0.0000 1.0000 -1.4486   \n",
       "loan_amnt                           887379.0000  0.0000 1.0000 -1.6899   \n",
       "funded_amnt                         887379.0000 -0.0000 1.0000 -1.6894   \n",
       "funded_amnt_inv                     887379.0000 -0.0000 1.0000 -1.7416   \n",
       "int_rate                            887379.0000  0.0000 1.0000 -1.8090   \n",
       "installment                         887379.0000 -0.0000 1.0000 -1.7243   \n",
       "grade                               887379.0000 -0.0000 1.0000 -1.3701   \n",
       "emp_length                          887379.0000 -0.0000 1.0000 -1.4986   \n",
       "annual_inc                          887379.0000 -0.0000 1.0000 -1.1597   \n",
       "dti                                 887379.0000 -0.0000 1.0000 -1.0562   \n",
       "delinq_2yrs                         887379.0000 -0.0000 1.0000 -0.3647   \n",
       "inq_last_6mths                      887379.0000 -0.0000 1.0000 -0.6957   \n",
       "mths_since_last_delinq              887379.0000  0.0000 1.0000 -2.2281   \n",
       "open_acc                            887379.0000 -0.0000 1.0000 -2.1719   \n",
       "pub_rec                             887379.0000 -0.0000 1.0000 -0.3355   \n",
       "revol_bal                           887379.0000  0.0000 1.0000 -0.7545   \n",
       "revol_util                          887379.0000  0.0000 1.0000 -2.3111   \n",
       "total_acc                           887379.0000  0.0000 1.0000 -2.0496   \n",
       "out_prncp                           887379.0000  0.0000 1.0000 -0.9894   \n",
       "out_prncp_inv                       887379.0000 -0.0000 1.0000 -0.9894   \n",
       "total_pymnt                         887379.0000 -0.0000 1.0000 -0.9603   \n",
       "total_pymnt_inv                     887379.0000  0.0000 1.0000 -0.9586   \n",
       "total_rec_prncp                     887379.0000  0.0000 1.0000 -0.8690   \n",
       "total_rec_int                       887379.0000  0.0000 1.0000 -0.8375   \n",
       "total_rec_late_fee                  887379.0000  0.0000 1.0000 -0.0970   \n",
       "recoveries                          887379.0000 -0.0000 1.0000 -0.1121   \n",
       "collection_recovery_fee             887379.0000  0.0000 1.0000 -0.0773   \n",
       "last_pymnt_amnt                     887379.0000 -0.0000 1.0000 -0.4514   \n",
       "collections_12_mths_ex_med          887379.0000  0.0000 1.0000 -0.1072   \n",
       "acc_now_delinq                      887379.0000 -0.0000 1.0000 -0.0643   \n",
       "tot_coll_amt                        887379.0000  0.0000 1.0000 -0.0228   \n",
       "tot_cur_bal                         887379.0000  0.0000 1.0000 -0.9452   \n",
       "total_rev_hi_lim                    887379.0000 -0.0000 1.0000 -0.8912   \n",
       "home_ownership_ANY                  887379.0000  0.0000 0.0018  0.0000   \n",
       "home_ownership_MORTGAGE             887379.0000  0.4999 0.5000  0.0000   \n",
       "home_ownership_NONE                 887379.0000  0.0001 0.0075  0.0000   \n",
       "home_ownership_OTHER                887379.0000  0.0002 0.0143  0.0000   \n",
       "home_ownership_OWN                  887379.0000  0.0986 0.2981  0.0000   \n",
       "home_ownership_RENT                 887379.0000  0.4013 0.4902  0.0000   \n",
       "verification_status_Not Verified    887379.0000  0.3006 0.4585  0.0000   \n",
       "verification_status_Source Verified 887379.0000  0.3714 0.4832  0.0000   \n",
       "verification_status_Verified        887379.0000  0.3280 0.4695  0.0000   \n",
       "application_type_INDIVIDUAL         887379.0000  0.9994 0.0240  0.0000   \n",
       "application_type_JOINT              887379.0000  0.0006 0.0240  0.0000   \n",
       "purpose_car                         887379.0000  0.0100 0.0994  0.0000   \n",
       "purpose_credit_card                 887379.0000  0.2323 0.4223  0.0000   \n",
       "purpose_debt_consolidation          887379.0000  0.5907 0.4917  0.0000   \n",
       "purpose_educational                 887379.0000  0.0005 0.0218  0.0000   \n",
       "purpose_home_improvement            887379.0000  0.0584 0.2345  0.0000   \n",
       "purpose_house                       887379.0000  0.0042 0.0645  0.0000   \n",
       "purpose_major_purchase              887379.0000  0.0195 0.1382  0.0000   \n",
       "purpose_medical                     887379.0000  0.0096 0.0976  0.0000   \n",
       "purpose_moving                      887379.0000  0.0061 0.0779  0.0000   \n",
       "purpose_other                       887379.0000  0.0483 0.2145  0.0000   \n",
       "purpose_renewable_energy            887379.0000  0.0006 0.0254  0.0000   \n",
       "purpose_small_business              887379.0000  0.0117 0.1075  0.0000   \n",
       "purpose_vacation                    887379.0000  0.0053 0.0729  0.0000   \n",
       "purpose_wedding                     887379.0000  0.0026 0.0514  0.0000   \n",
       "term_ 36 months                     887379.0000  0.7000 0.4583  0.0000   \n",
       "term_ 60 months                     887379.0000  0.3000 0.4583  0.0000   \n",
       "\n",
       "                                        25%     50%     75%      max  \n",
       "id                                  -1.0189  0.0862  0.9832   1.5837  \n",
       "member_id                           -1.0005  0.0868  0.9733   1.5984  \n",
       "loan_amnt                           -0.8008 -0.2081  0.6217   2.4000  \n",
       "funded_amnt                         -0.7998 -0.2066  0.6237   2.4031  \n",
       "funded_amnt_inv                     -0.7939 -0.2017  0.6275   2.4043  \n",
       "int_rate                            -0.7432 -0.0586  0.6740   3.5928  \n",
       "installment                         -0.7208 -0.2218  0.5565   4.1310  \n",
       "grade                               -0.6083  0.1536  0.9154   3.2010  \n",
       "emp_length                          -0.9732  0.0774  1.1281   1.1281  \n",
       "annual_inc                          -0.4641 -0.1550  0.2314 145.6761  \n",
       "dti                                 -0.3634 -0.0295  0.3370 580.5983  \n",
       "delinq_2yrs                         -0.3647 -0.3647 -0.3647  44.8669  \n",
       "inq_last_6mths                      -0.6957 -0.6957  0.3059  32.3561  \n",
       "mths_since_last_delinq              -0.1350  0.0000  0.0000  10.0687  \n",
       "open_acc                            -0.6674 -0.1031  0.4611  14.7542  \n",
       "pub_rec                             -0.3355 -0.3355 -0.3355 147.4103  \n",
       "revol_bal                           -0.4672 -0.2250  0.1743 128.7708  \n",
       "revol_util                          -0.7289  0.0391  0.7778  35.1371  \n",
       "total_acc                           -0.6983 -0.1071  0.5686  12.1392  \n",
       "out_prncp                           -0.9894 -0.2290  0.6188   4.8237  \n",
       "out_prncp_inv                       -0.9894 -0.2290  0.6189   4.8261  \n",
       "total_pymnt                         -0.7171 -0.3384  0.3885   6.3800  \n",
       "total_pymnt_inv                     -0.7165 -0.3389  0.3880   6.4053  \n",
       "total_rec_prncp                     -0.6878 -0.3837  0.3384   4.4136  \n",
       "total_rec_int                       -0.6268 -0.3253  0.2307  10.7146  \n",
       "total_rec_late_fee                  -0.0970 -0.0970 -0.0970  87.6465  \n",
       "recoveries                          -0.1121 -0.1121 -0.1121  81.7058  \n",
       "collection_recovery_fee             -0.0773 -0.0773 -0.0773 110.8480  \n",
       "last_pymnt_amnt                     -0.3929 -0.3548 -0.2780   7.1560  \n",
       "collections_12_mths_ex_med          -0.1072 -0.1072 -0.1072 148.9467  \n",
       "acc_now_delinq                      -0.0643 -0.0643 -0.0643 180.2922  \n",
       "tot_coll_amt                        -0.0228 -0.0228 -0.0228 924.9779  \n",
       "tot_cur_bal                         -0.7267 -0.2668  0.3818  53.2793  \n",
       "total_rev_hi_lim                    -0.4827 -0.1742  0.1593 277.0195  \n",
       "home_ownership_ANY                   0.0000  0.0000  0.0000   1.0000  \n",
       "home_ownership_MORTGAGE              0.0000  0.0000  1.0000   1.0000  \n",
       "home_ownership_NONE                  0.0000  0.0000  0.0000   1.0000  \n",
       "home_ownership_OTHER                 0.0000  0.0000  0.0000   1.0000  \n",
       "home_ownership_OWN                   0.0000  0.0000  0.0000   1.0000  \n",
       "home_ownership_RENT                  0.0000  0.0000  1.0000   1.0000  \n",
       "verification_status_Not Verified     0.0000  0.0000  1.0000   1.0000  \n",
       "verification_status_Source Verified  0.0000  0.0000  1.0000   1.0000  \n",
       "verification_status_Verified         0.0000  0.0000  1.0000   1.0000  \n",
       "application_type_INDIVIDUAL          1.0000  1.0000  1.0000   1.0000  \n",
       "application_type_JOINT               0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_car                          0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_credit_card                  0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_debt_consolidation           0.0000  1.0000  1.0000   1.0000  \n",
       "purpose_educational                  0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_home_improvement             0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_house                        0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_major_purchase               0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_medical                      0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_moving                       0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_other                        0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_renewable_energy             0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_small_business               0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_vacation                     0.0000  0.0000  0.0000   1.0000  \n",
       "purpose_wedding                      0.0000  0.0000  0.0000   1.0000  \n",
       "term_ 36 months                      0.0000  1.0000  1.0000   1.0000  \n",
       "term_ 60 months                      0.0000  0.0000  1.0000   1.0000  "
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X.describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数据集太大，笔记本吃不消，所以选取部分数据训练模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "#选取后5万条数据\n",
    "X_part = X[-50000:]\n",
    "y_part = y[-50000:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "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>id</th>\n",
       "      <th>member_id</th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>funded_amnt</th>\n",
       "      <th>funded_amnt_inv</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>grade</th>\n",
       "      <th>emp_length</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>dti</th>\n",
       "      <th>delinq_2yrs</th>\n",
       "      <th>inq_last_6mths</th>\n",
       "      <th>mths_since_last_delinq</th>\n",
       "      <th>open_acc</th>\n",
       "      <th>pub_rec</th>\n",
       "      <th>revol_bal</th>\n",
       "      <th>revol_util</th>\n",
       "      <th>total_acc</th>\n",
       "      <th>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>acc_now_delinq</th>\n",
       "      <th>tot_coll_amt</th>\n",
       "      <th>tot_cur_bal</th>\n",
       "      <th>total_rev_hi_lim</th>\n",
       "      <th>home_ownership_ANY</th>\n",
       "      <th>home_ownership_MORTGAGE</th>\n",
       "      <th>home_ownership_NONE</th>\n",
       "      <th>home_ownership_OTHER</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>application_type_INDIVIDUAL</th>\n",
       "      <th>application_type_JOINT</th>\n",
       "      <th>purpose_car</th>\n",
       "      <th>purpose_credit_card</th>\n",
       "      <th>purpose_debt_consolidation</th>\n",
       "      <th>purpose_educational</th>\n",
       "      <th>purpose_home_improvement</th>\n",
       "      <th>purpose_house</th>\n",
       "      <th>purpose_major_purchase</th>\n",
       "      <th>purpose_medical</th>\n",
       "      <th>purpose_moving</th>\n",
       "      <th>purpose_other</th>\n",
       "      <th>purpose_renewable_energy</th>\n",
       "      <th>purpose_small_business</th>\n",
       "      <th>purpose_vacation</th>\n",
       "      <th>purpose_wedding</th>\n",
       "      <th>term_ 36 months</th>\n",
       "      <th>term_ 60 months</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>837379</th>\n",
       "      <td>0.3183</td>\n",
       "      <td>0.3132</td>\n",
       "      <td>1.5701</td>\n",
       "      <td>1.5728</td>\n",
       "      <td>1.5751</td>\n",
       "      <td>1.2765</td>\n",
       "      <td>1.1760</td>\n",
       "      <td>1.6773</td>\n",
       "      <td>0.0774</td>\n",
       "      <td>0.2778</td>\n",
       "      <td>0.5417</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>-0.6957</td>\n",
       "      <td>0.8461</td>\n",
       "      <td>0.4611</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>0.1165</td>\n",
       "      <td>-0.0280</td>\n",
       "      <td>0.7375</td>\n",
       "      <td>1.9479</td>\n",
       "      <td>1.9491</td>\n",
       "      <td>-0.0444</td>\n",
       "      <td>-0.0397</td>\n",
       "      <td>-0.4083</td>\n",
       "      <td>1.1465</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.3004</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>1.0853</td>\n",
       "      <td>0.1065</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837380</th>\n",
       "      <td>0.3713</td>\n",
       "      <td>0.3656</td>\n",
       "      <td>-1.0972</td>\n",
       "      <td>-1.0963</td>\n",
       "      <td>-1.0901</td>\n",
       "      <td>-1.1563</td>\n",
       "      <td>-1.0808</td>\n",
       "      <td>-0.6083</td>\n",
       "      <td>-0.9732</td>\n",
       "      <td>0.1541</td>\n",
       "      <td>-0.0929</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>-0.6957</td>\n",
       "      <td>0.3883</td>\n",
       "      <td>1.4014</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>2.0547</td>\n",
       "      <td>-1.3374</td>\n",
       "      <td>2.5955</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.9894</td>\n",
       "      <td>-0.2392</td>\n",
       "      <td>-0.2352</td>\n",
       "      <td>-0.0389</td>\n",
       "      <td>-0.7536</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>0.5887</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>-0.0228</td>\n",
       "      <td>1.1115</td>\n",
       "      <td>1.9574</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837381</th>\n",
       "      <td>0.3801</td>\n",
       "      <td>0.3739</td>\n",
       "      <td>-0.9194</td>\n",
       "      <td>-0.9184</td>\n",
       "      <td>-0.9124</td>\n",
       "      <td>0.5393</td>\n",
       "      <td>-0.7861</td>\n",
       "      <td>0.9154</td>\n",
       "      <td>-0.7106</td>\n",
       "      <td>0.4633</td>\n",
       "      <td>-0.1301</td>\n",
       "      <td>0.7951</td>\n",
       "      <td>0.3059</td>\n",
       "      <td>-1.2469</td>\n",
       "      <td>2.5298</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>0.4159</td>\n",
       "      <td>1.1765</td>\n",
       "      <td>2.7644</td>\n",
       "      <td>-0.3777</td>\n",
       "      <td>-0.3775</td>\n",
       "      <td>-0.6190</td>\n",
       "      <td>-0.6162</td>\n",
       "      <td>-0.5966</td>\n",
       "      <td>-0.4169</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.4003</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>-0.0228</td>\n",
       "      <td>2.5679</td>\n",
       "      <td>-0.0130</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837382</th>\n",
       "      <td>0.3713</td>\n",
       "      <td>0.3655</td>\n",
       "      <td>0.0290</td>\n",
       "      <td>0.0306</td>\n",
       "      <td>0.0352</td>\n",
       "      <td>0.0190</td>\n",
       "      <td>-0.3804</td>\n",
       "      <td>0.1536</td>\n",
       "      <td>-0.1852</td>\n",
       "      <td>-0.5414</td>\n",
       "      <td>0.8233</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>-0.6957</td>\n",
       "      <td>-0.5928</td>\n",
       "      <td>0.2730</td>\n",
       "      <td>-0.3355</td>\n",
       "      <td>-0.3703</td>\n",
       "      <td>-1.1528</td>\n",
       "      <td>1.2442</td>\n",
       "      <td>0.5340</td>\n",
       "      <td>0.5346</td>\n",
       "      <td>-0.4812</td>\n",
       "      <td>-0.4779</td>\n",
       "      <td>-0.5579</td>\n",
       "      <td>-0.0215</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.3796</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>0.0581</td>\n",
       "      <td>-0.4206</td>\n",
       "      <td>-0.0241</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>837383</th>\n",
       "      <td>0.3717</td>\n",
       "      <td>0.3660</td>\n",
       "      <td>0.6217</td>\n",
       "      <td>0.6237</td>\n",
       "      <td>0.6246</td>\n",
       "      <td>-0.2183</td>\n",
       "      <td>0.9433</td>\n",
       "      <td>0.1536</td>\n",
       "      <td>-1.4986</td>\n",
       "      <td>0.6333</td>\n",
       "      <td>0.3835</td>\n",
       "      <td>-0.3647</td>\n",
       "      <td>0.3059</td>\n",
       "      <td>3.5279</td>\n",
       "      <td>0.2730</td>\n",
       "      <td>1.3824</td>\n",
       "      <td>-0.1599</td>\n",
       "      <td>0.7316</td>\n",
       "      <td>0.4841</td>\n",
       "      <td>0.7351</td>\n",
       "      <td>0.7337</td>\n",
       "      <td>-0.0382</td>\n",
       "      <td>-0.0347</td>\n",
       "      <td>-0.0611</td>\n",
       "      <td>0.0716</td>\n",
       "      <td>-0.0970</td>\n",
       "      <td>-0.1121</td>\n",
       "      <td>-0.0773</td>\n",
       "      <td>-0.3122</td>\n",
       "      <td>-0.1072</td>\n",
       "      <td>-0.0643</td>\n",
       "      <td>-0.0228</td>\n",
       "      <td>-0.4876</td>\n",
       "      <td>-0.3799</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</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>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id  member_id  loan_amnt  funded_amnt  funded_amnt_inv  int_rate  \\\n",
       "837379 0.3183     0.3132     1.5701       1.5728           1.5751    1.2765   \n",
       "837380 0.3713     0.3656    -1.0972      -1.0963          -1.0901   -1.1563   \n",
       "837381 0.3801     0.3739    -0.9194      -0.9184          -0.9124    0.5393   \n",
       "837382 0.3713     0.3655     0.0290       0.0306           0.0352    0.0190   \n",
       "837383 0.3717     0.3660     0.6217       0.6237           0.6246   -0.2183   \n",
       "\n",
       "        installment   grade  emp_length  annual_inc     dti  delinq_2yrs  \\\n",
       "837379       1.1760  1.6773      0.0774      0.2778  0.5417      -0.3647   \n",
       "837380      -1.0808 -0.6083     -0.9732      0.1541 -0.0929      -0.3647   \n",
       "837381      -0.7861  0.9154     -0.7106      0.4633 -0.1301       0.7951   \n",
       "837382      -0.3804  0.1536     -0.1852     -0.5414  0.8233      -0.3647   \n",
       "837383       0.9433  0.1536     -1.4986      0.6333  0.3835      -0.3647   \n",
       "\n",
       "        inq_last_6mths  mths_since_last_delinq  open_acc  pub_rec  revol_bal  \\\n",
       "837379         -0.6957                  0.8461    0.4611  -0.3355     0.1165   \n",
       "837380         -0.6957                  0.3883    1.4014  -0.3355     2.0547   \n",
       "837381          0.3059                 -1.2469    2.5298  -0.3355     0.4159   \n",
       "837382         -0.6957                 -0.5928    0.2730  -0.3355    -0.3703   \n",
       "837383          0.3059                  3.5279    0.2730   1.3824    -0.1599   \n",
       "\n",
       "        revol_util  total_acc  out_prncp  out_prncp_inv  total_pymnt  \\\n",
       "837379     -0.0280     0.7375     1.9479         1.9491      -0.0444   \n",
       "837380     -1.3374     2.5955    -0.9894        -0.9894      -0.2392   \n",
       "837381      1.1765     2.7644    -0.3777        -0.3775      -0.6190   \n",
       "837382     -1.1528     1.2442     0.5340         0.5346      -0.4812   \n",
       "837383      0.7316     0.4841     0.7351         0.7337      -0.0382   \n",
       "\n",
       "        total_pymnt_inv  total_rec_prncp  total_rec_int  total_rec_late_fee  \\\n",
       "837379          -0.0397          -0.4083         1.1465             -0.0970   \n",
       "837380          -0.2352          -0.0389        -0.7536             -0.0970   \n",
       "837381          -0.6162          -0.5966        -0.4169             -0.0970   \n",
       "837382          -0.4779          -0.5579        -0.0215             -0.0970   \n",
       "837383          -0.0347          -0.0611         0.0716             -0.0970   \n",
       "\n",
       "        recoveries  collection_recovery_fee  last_pymnt_amnt  \\\n",
       "837379     -0.1121                  -0.0773          -0.3004   \n",
       "837380     -0.1121                  -0.0773           0.5887   \n",
       "837381     -0.1121                  -0.0773          -0.4003   \n",
       "837382     -0.1121                  -0.0773          -0.3796   \n",
       "837383     -0.1121                  -0.0773          -0.3122   \n",
       "\n",
       "        collections_12_mths_ex_med  acc_now_delinq  tot_coll_amt  tot_cur_bal  \\\n",
       "837379                     -0.1072         -0.0643        0.0160       1.0853   \n",
       "837380                     -0.1072         -0.0643       -0.0228       1.1115   \n",
       "837381                     -0.1072         -0.0643       -0.0228       2.5679   \n",
       "837382                     -0.1072         -0.0643        0.0581      -0.4206   \n",
       "837383                     -0.1072         -0.0643       -0.0228      -0.4876   \n",
       "\n",
       "        total_rev_hi_lim  home_ownership_ANY  home_ownership_MORTGAGE  \\\n",
       "837379            0.1065                   0                        1   \n",
       "837380            1.9574                   0                        1   \n",
       "837381           -0.0130                   0                        0   \n",
       "837382           -0.0241                   0                        1   \n",
       "837383           -0.3799                   0                        0   \n",
       "\n",
       "        home_ownership_NONE  home_ownership_OTHER  home_ownership_OWN  \\\n",
       "837379                    0                     0                   0   \n",
       "837380                    0                     0                   0   \n",
       "837381                    0                     0                   1   \n",
       "837382                    0                     0                   0   \n",
       "837383                    0                     0                   0   \n",
       "\n",
       "        home_ownership_RENT  verification_status_Not Verified  \\\n",
       "837379                    0                                 0   \n",
       "837380                    0                                 0   \n",
       "837381                    0                                 0   \n",
       "837382                    0                                 1   \n",
       "837383                    1                                 0   \n",
       "\n",
       "        verification_status_Source Verified  verification_status_Verified  \\\n",
       "837379                                    1                             0   \n",
       "837380                                    1                             0   \n",
       "837381                                    1                             0   \n",
       "837382                                    0                             0   \n",
       "837383                                    0                             1   \n",
       "\n",
       "        application_type_INDIVIDUAL  application_type_JOINT  purpose_car  \\\n",
       "837379                            1                       0            0   \n",
       "837380                            1                       0            0   \n",
       "837381                            1                       0            0   \n",
       "837382                            1                       0            0   \n",
       "837383                            1                       0            0   \n",
       "\n",
       "        purpose_credit_card  purpose_debt_consolidation  purpose_educational  \\\n",
       "837379                    0                           1                    0   \n",
       "837380                    0                           1                    0   \n",
       "837381                    0                           0                    0   \n",
       "837382                    0                           1                    0   \n",
       "837383                    0                           1                    0   \n",
       "\n",
       "        purpose_home_improvement  purpose_house  purpose_major_purchase  \\\n",
       "837379                         0              0                       0   \n",
       "837380                         0              0                       0   \n",
       "837381                         1              0                       0   \n",
       "837382                         0              0                       0   \n",
       "837383                         0              0                       0   \n",
       "\n",
       "        purpose_medical  purpose_moving  purpose_other  \\\n",
       "837379                0               0              0   \n",
       "837380                0               0              0   \n",
       "837381                0               0              0   \n",
       "837382                0               0              0   \n",
       "837383                0               0              0   \n",
       "\n",
       "        purpose_renewable_energy  purpose_small_business  purpose_vacation  \\\n",
       "837379                         0                       0                 0   \n",
       "837380                         0                       0                 0   \n",
       "837381                         0                       0                 0   \n",
       "837382                         0                       0                 0   \n",
       "837383                         0                       0                 0   \n",
       "\n",
       "        purpose_wedding  term_ 36 months  term_ 60 months  \n",
       "837379                0                0                1  \n",
       "837380                0                1                0  \n",
       "837381                0                1                0  \n",
       "837382                0                0                1  \n",
       "837383                0                1                0  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_part.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "#利用递归消除特征法（Recursive Feature Elimination）降维，将特征降到30个\n",
    "from sklearn.feature_selection import RFE\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "LR_model = LogisticRegression()\n",
    "rfe = RFE(LR_model,30)\n",
    "rfe = rfe.fit(X_part,y_part)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['id', 'member_id', 'loan_amnt', 'funded_amnt', 'funded_amnt_inv',\n",
       "       'int_rate', 'installment', 'out_prncp', 'out_prncp_inv', 'total_pymnt',\n",
       "       'total_pymnt_inv', 'total_rec_prncp', 'total_rec_int',\n",
       "       'total_rec_late_fee', 'recoveries', 'collection_recovery_fee',\n",
       "       'home_ownership_MORTGAGE', 'home_ownership_OWN', 'home_ownership_RENT',\n",
       "       'verification_status_Not Verified',\n",
       "       'verification_status_Source Verified', 'verification_status_Verified',\n",
       "       'application_type_INDIVIDUAL', 'purpose_credit_card', 'purpose_medical',\n",
       "       'purpose_moving', 'purpose_other', 'purpose_small_business',\n",
       "       'term_ 36 months', 'term_ 60 months'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filter_col = X_part.columns[rfe.support_]\n",
    "filter_col"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这些就是降维后的30个特征"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "然后利用皮尔逊相关系谱图找冗余特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Pearson Correlation of Feature')"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colormap = plt.cm.viridis\n",
    "plt.figure(figsize=(15,15))\n",
    "sns.heatmap(loans_3[filter_col].corr(),linewidths=0.1,cmap=colormap,vmax=1,square=True,\n",
    "           linecolor = 'white',annot = True)\n",
    "plt.title('Pearson Correlation of Feature',size = 15)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15\n"
     ]
    }
   ],
   "source": [
    "#从上图看出的冗余特征如下\n",
    "drop_col = ['id','member_id','funded_amnt', 'funded_amnt_inv',\n",
    "            'installment', 'out_prncp_inv','total_pymnt_inv', \n",
    "            'total_rec_prncp', 'total_rec_int','collection_recovery_fee', 'home_ownership_OWN',\n",
    "            'home_ownership_RENT' , 'term_ 36 months', \n",
    "            'verification_status_Source Verified','int_rate']\n",
    "\n",
    "col_new = filter_col.drop(drop_col) #剔除冗余特征\n",
    "print(len(col_new))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "除去一些冗余特征后还剩15个特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1642398f940>"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colormap = plt.cm.viridis\n",
    "plt.figure(figsize = (15,15))\n",
    "sns.heatmap(loans_3[col_new].corr(),linewidths = 0.2,vmax=1,square=True,linecolor='white',\n",
    "           cmap = colormap,annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "'out_prncp'特征相关性还是很高 剔除掉该特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50000, 14)"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col_new = col_new.drop('out_prncp')\n",
    "\n",
    "\n",
    "X_part[col_new].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 筛选重要特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('loan_amnt', 0.34696464883052014)\n",
      "('total_pymnt', 0.5042407911233814)\n",
      "('total_rec_late_fee', 0.04635773283601445)\n",
      "('recoveries', 0.05929912104431219)\n",
      "('home_ownership_MORTGAGE', 0.0056719005858410845)\n",
      "('verification_status_Not Verified', 0.0048713894654482245)\n",
      "('verification_status_Verified', 0.004914566353970865)\n",
      "('application_type_INDIVIDUAL', 0.0)\n",
      "('purpose_credit_card', 0.003980199522309935)\n",
      "('purpose_medical', 0.0011087439191859497)\n",
      "('purpose_moving', 0.0009788904117121896)\n",
      "('purpose_other', 0.0026282173315568466)\n",
      "('purpose_small_business', 0.0016916299384383722)\n",
      "('term_ 60 months', 0.017292168637308612)\n"
     ]
    }
   ],
   "source": [
    "#用随机森林算法判断重要特征\n",
    "names = loans_3[col_new].columns\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "RF_clf = RandomForestClassifier(n_estimators=10,random_state=22)\n",
    "RF_clf.fit(X_part[col_new],y_part)\n",
    "for feature in zip(names,RF_clf.feature_importances_):\n",
    "    print(feature)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "发现total_pymnt,loan_amnt 两个特征很重要"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 训练模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0   0.9368\n",
       "1   0.0632\n",
       "Name: loan_status, dtype: float64"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_part.value_counts()/len(y_part)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "标签类别占比非常不平衡 违约的只占6.3%  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1   0.5000\n",
       "0   0.5000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#利用SMOTE模块平衡数据\n",
    "from imblearn.over_sampling import SMOTE\n",
    "sm = SMOTE(random_state=33)\n",
    "X_balance,y_balance = sm.fit_sample(X_part,y_part)\n",
    "pd.Series(y_balance).value_counts()/len(y_balance)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "标签平衡了"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 模型训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9271593868750266"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#线性回归模型\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "LR_clf = LogisticRegression()\n",
    "LR_clf.fit(X_balance,y_balance)\n",
    "LR_clf.score(X_balance,y_balance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9271593868750266"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看模型的性能\n",
    "from sklearn.metrics import roc_auc_score\n",
    "y_prd = LR_clf.predict(X_balance)\n",
    "roc_auc_score(y_balance,y_prd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.90      0.97      0.93     46842\n",
      "           1       0.96      0.89      0.92     46842\n",
      "\n",
      "   micro avg       0.93      0.93      0.93     93684\n",
      "   macro avg       0.93      0.93      0.93     93684\n",
      "weighted avg       0.93      0.93      0.93     93684\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "print(classification_report(y_balance,y_prd))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9772853422142521"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#决策树模型\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "DT_clf = DecisionTreeClassifier(splitter='random',min_samples_split=10,min_samples_leaf=5)\n",
    "DT_clf.fit(X_balance,y_balance)\n",
    "DT_clf.score(X_balance,y_balance)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.97      0.98      0.98     46842\n",
      "           1       0.98      0.97      0.98     46842\n",
      "\n",
      "   micro avg       0.98      0.98      0.98     93684\n",
      "   macro avg       0.98      0.98      0.98     93684\n",
      "weighted avg       0.98      0.98      0.98     93684\n",
      "\n"
     ]
    }
   ],
   "source": [
    "y_pre_t = DT_clf.predict(X_balance)\n",
    "print(classification_report(y_balance,y_pre_t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9772853422142522"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "roc_auc_score(y_balance,y_pre_t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}