LendingClubDataResearch.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>Lending Club Loan Default Analysis</h1>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pd.set_option(\"display.max_columns\", None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Importing first 1000 rows of data out of 2 million.</h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data used From P2P site LendingClub\n",
    "df= pd.read_csv(r\"E:\\lendingclub\\lending_club_loan_two.csv\", nrows=1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</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>...</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <th>address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>36 months</td>\n",
       "      <td>11.44</td>\n",
       "      <td>329.48</td>\n",
       "      <td>B</td>\n",
       "      <td>B4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36369.0</td>\n",
       "      <td>41.8</td>\n",
       "      <td>25.0</td>\n",
       "      <td>w</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0174 Michelle Gateway\\r\\nMendozaberg, OK 22690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>36 months</td>\n",
       "      <td>11.99</td>\n",
       "      <td>265.68</td>\n",
       "      <td>B</td>\n",
       "      <td>B5</td>\n",
       "      <td>Credit analyst</td>\n",
       "      <td>4 years</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20131.0</td>\n",
       "      <td>53.3</td>\n",
       "      <td>27.0</td>\n",
       "      <td>f</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15600.0</td>\n",
       "      <td>36 months</td>\n",
       "      <td>10.49</td>\n",
       "      <td>506.97</td>\n",
       "      <td>B</td>\n",
       "      <td>B3</td>\n",
       "      <td>Statistician</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>RENT</td>\n",
       "      <td>43057.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11987.0</td>\n",
       "      <td>92.2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>f</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt        term  int_rate  installment grade sub_grade  \\\n",
       "0    10000.0   36 months     11.44       329.48     B        B4   \n",
       "1     8000.0   36 months     11.99       265.68     B        B5   \n",
       "2    15600.0   36 months     10.49       506.97     B        B3   \n",
       "\n",
       "         emp_title emp_length home_ownership  annual_inc  ... open_acc  \\\n",
       "0        Marketing  10+ years           RENT    117000.0  ...     16.0   \n",
       "1  Credit analyst     4 years       MORTGAGE     65000.0  ...     17.0   \n",
       "2     Statistician   < 1 year           RENT     43057.0  ...     13.0   \n",
       "\n",
       "  pub_rec revol_bal revol_util total_acc  initial_list_status  \\\n",
       "0     0.0   36369.0       41.8      25.0                    w   \n",
       "1     0.0   20131.0       53.3      27.0                    f   \n",
       "2     0.0   11987.0       92.2      26.0                    f   \n",
       "\n",
       "  application_type  mort_acc  pub_rec_bankruptcies  \\\n",
       "0       INDIVIDUAL       0.0                   0.0   \n",
       "1       INDIVIDUAL       3.0                   0.0   \n",
       "2       INDIVIDUAL       0.0                   0.0   \n",
       "\n",
       "                                             address  \n",
       "0     0174 Michelle Gateway\\r\\nMendozaberg, OK 22690  \n",
       "1  1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113  \n",
       "2  87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113  \n",
       "\n",
       "[3 rows x 27 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Data Cleaning</h3>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#removing unit - months from term column \n",
    "df['term'] = df['term'].str.replace('months', '')\n",
    "df['term'] = df['term'].astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</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>...</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <th>address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.44</td>\n",
       "      <td>329.48</td>\n",
       "      <td>B</td>\n",
       "      <td>B4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>RENT</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36369.0</td>\n",
       "      <td>41.8</td>\n",
       "      <td>25.0</td>\n",
       "      <td>w</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0174 Michelle Gateway\\r\\nMendozaberg, OK 22690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.99</td>\n",
       "      <td>265.68</td>\n",
       "      <td>B</td>\n",
       "      <td>B5</td>\n",
       "      <td>Credit analyst</td>\n",
       "      <td>4 years</td>\n",
       "      <td>MORTGAGE</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20131.0</td>\n",
       "      <td>53.3</td>\n",
       "      <td>27.0</td>\n",
       "      <td>f</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15600.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10.49</td>\n",
       "      <td>506.97</td>\n",
       "      <td>B</td>\n",
       "      <td>B3</td>\n",
       "      <td>Statistician</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>RENT</td>\n",
       "      <td>43057.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11987.0</td>\n",
       "      <td>92.2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>f</td>\n",
       "      <td>INDIVIDUAL</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  term  int_rate  installment grade sub_grade        emp_title  \\\n",
       "0    10000.0    36     11.44       329.48     B        B4        Marketing   \n",
       "1     8000.0    36     11.99       265.68     B        B5  Credit analyst    \n",
       "2    15600.0    36     10.49       506.97     B        B3     Statistician   \n",
       "\n",
       "  emp_length home_ownership  annual_inc  ... open_acc pub_rec revol_bal  \\\n",
       "0  10+ years           RENT    117000.0  ...     16.0     0.0   36369.0   \n",
       "1    4 years       MORTGAGE     65000.0  ...     17.0     0.0   20131.0   \n",
       "2   < 1 year           RENT     43057.0  ...     13.0     0.0   11987.0   \n",
       "\n",
       "  revol_util total_acc  initial_list_status application_type  mort_acc  \\\n",
       "0       41.8      25.0                    w       INDIVIDUAL       0.0   \n",
       "1       53.3      27.0                    f       INDIVIDUAL       3.0   \n",
       "2       92.2      26.0                    f       INDIVIDUAL       0.0   \n",
       "\n",
       "   pub_rec_bankruptcies                                            address  \n",
       "0                   0.0     0174 Michelle Gateway\\r\\nMendozaberg, OK 22690  \n",
       "1                   0.0  1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113  \n",
       "2                   0.0  87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113  \n",
       "\n",
       "[3 rows x 27 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.max_rows', None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dropping all records having any Null values in its rows\n",
    "df = df.dropna(how='any',axis=0) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 869 entries, 0 to 999\n",
      "Data columns (total 27 columns):\n",
      " #   Column                Non-Null Count  Dtype  \n",
      "---  ------                --------------  -----  \n",
      " 0   loan_amnt             869 non-null    float64\n",
      " 1   term                  869 non-null    int32  \n",
      " 2   int_rate              869 non-null    float64\n",
      " 3   installment           869 non-null    float64\n",
      " 4   grade                 869 non-null    object \n",
      " 5   sub_grade             869 non-null    object \n",
      " 6   emp_title             869 non-null    object \n",
      " 7   emp_length            869 non-null    object \n",
      " 8   home_ownership        869 non-null    object \n",
      " 9   annual_inc            869 non-null    float64\n",
      " 10  verification_status   869 non-null    object \n",
      " 11  issue_d               869 non-null    object \n",
      " 12  loan_status           869 non-null    object \n",
      " 13  purpose               869 non-null    object \n",
      " 14  title                 869 non-null    object \n",
      " 15  dti                   869 non-null    float64\n",
      " 16  earliest_cr_line      869 non-null    object \n",
      " 17  open_acc              869 non-null    float64\n",
      " 18  pub_rec               869 non-null    float64\n",
      " 19  revol_bal             869 non-null    float64\n",
      " 20  revol_util            869 non-null    float64\n",
      " 21  total_acc             869 non-null    float64\n",
      " 22  initial_list_status   869 non-null    object \n",
      " 23  application_type      869 non-null    object \n",
      " 24  mort_acc              869 non-null    float64\n",
      " 25  pub_rec_bankruptcies  869 non-null    float64\n",
      " 26  address               869 non-null    object \n",
      "dtypes: float64(12), int32(1), object(14)\n",
      "memory usage: 186.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</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>...</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <th>address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [loan_amnt, term, int_rate, installment, grade, sub_grade, emp_title, emp_length, home_ownership, annual_inc, verification_status, issue_d, loan_status, purpose, title, dti, earliest_cr_line, open_acc, pub_rec, revol_bal, revol_util, total_acc, initial_list_status, application_type, mort_acc, pub_rec_bankruptcies, address]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 27 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#chcking if data has 10 years or is it so ,\n",
    "#all exact 10 years have been considered 10+ years in general. \n",
    "df.loc[df['emp_length'] == '10 years']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#no rows indicate our assumption of exact 10 years as 10+ years holds true."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data cleaning\n",
    "\n",
    "df_with_plus_removed= df['emp_length'].str.split(\"+\").str[0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_with_years_removed = df_with_plus_removed.str.replace('years', '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          10\n",
       "1          4 \n",
       "2    < 1 year\n",
       "3          6 \n",
       "4          9 \n",
       "Name: emp_length, dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_with_years_removed.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.options.mode.chained_assignment = None \n",
    "#avoids warning caused by using inplace = True"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Catagorizing String Data</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.application_type.replace(to_replace=dict(INDIVIDUAL=1, JOINT=0), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.initial_list_status.replace(to_replace=dict(w=1, f=0), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['RENT', 'MORTGAGE', 'OWN'], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pd.unique(df[['Col1', 'Col2']].values.ravel('K')) for 2 colums' unique values\n",
    "pd.unique(df[['home_ownership']].values.ravel('K'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.home_ownership.replace(to_replace=dict(OWN=1, RENT=0,MORTGAGE=3), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</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>...</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <th>address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.44</td>\n",
       "      <td>329.48</td>\n",
       "      <td>B</td>\n",
       "      <td>B4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36369.0</td>\n",
       "      <td>41.8</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0174 Michelle Gateway\\r\\nMendozaberg, OK 22690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.99</td>\n",
       "      <td>265.68</td>\n",
       "      <td>B</td>\n",
       "      <td>B5</td>\n",
       "      <td>Credit analyst</td>\n",
       "      <td>4 years</td>\n",
       "      <td>3</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20131.0</td>\n",
       "      <td>53.3</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15600.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10.49</td>\n",
       "      <td>506.97</td>\n",
       "      <td>B</td>\n",
       "      <td>B3</td>\n",
       "      <td>Statistician</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>0</td>\n",
       "      <td>43057.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11987.0</td>\n",
       "      <td>92.2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  term  int_rate  installment grade sub_grade        emp_title  \\\n",
       "0    10000.0    36     11.44       329.48     B        B4        Marketing   \n",
       "1     8000.0    36     11.99       265.68     B        B5  Credit analyst    \n",
       "2    15600.0    36     10.49       506.97     B        B3     Statistician   \n",
       "\n",
       "  emp_length  home_ownership  annual_inc  ... open_acc pub_rec revol_bal  \\\n",
       "0  10+ years               0    117000.0  ...     16.0     0.0   36369.0   \n",
       "1    4 years               3     65000.0  ...     17.0     0.0   20131.0   \n",
       "2   < 1 year               0     43057.0  ...     13.0     0.0   11987.0   \n",
       "\n",
       "  revol_util total_acc  initial_list_status application_type  mort_acc  \\\n",
       "0       41.8      25.0                    1                1       0.0   \n",
       "1       53.3      27.0                    0                1       3.0   \n",
       "2       92.2      26.0                    0                1       0.0   \n",
       "\n",
       "   pub_rec_bankruptcies                                            address  \n",
       "0                   0.0     0174 Michelle Gateway\\r\\nMendozaberg, OK 22690  \n",
       "1                   0.0  1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113  \n",
       "2                   0.0  87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113  \n",
       "\n",
       "[3 rows x 27 columns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Not Verified', 'Source Verified', 'Verified'], dtype=object)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.unique(df[['verification_status']].values.ravel('K'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "mapping = {'Not Verified': 0, 'Verified': 1,'Source Verified' : 2}\n",
    "#avoid inplace\n",
    "df=df.replace({'verification_status': mapping})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</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>...</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <th>address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.44</td>\n",
       "      <td>329.48</td>\n",
       "      <td>B</td>\n",
       "      <td>B4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36369.0</td>\n",
       "      <td>41.8</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0174 Michelle Gateway\\r\\nMendozaberg, OK 22690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.99</td>\n",
       "      <td>265.68</td>\n",
       "      <td>B</td>\n",
       "      <td>B5</td>\n",
       "      <td>Credit analyst</td>\n",
       "      <td>4 years</td>\n",
       "      <td>3</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20131.0</td>\n",
       "      <td>53.3</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15600.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10.49</td>\n",
       "      <td>506.97</td>\n",
       "      <td>B</td>\n",
       "      <td>B3</td>\n",
       "      <td>Statistician</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>0</td>\n",
       "      <td>43057.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11987.0</td>\n",
       "      <td>92.2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  term  int_rate  installment grade sub_grade        emp_title  \\\n",
       "0    10000.0    36     11.44       329.48     B        B4        Marketing   \n",
       "1     8000.0    36     11.99       265.68     B        B5  Credit analyst    \n",
       "2    15600.0    36     10.49       506.97     B        B3     Statistician   \n",
       "\n",
       "  emp_length  home_ownership  annual_inc  ...  open_acc pub_rec revol_bal  \\\n",
       "0  10+ years               0    117000.0  ...      16.0     0.0   36369.0   \n",
       "1    4 years               3     65000.0  ...      17.0     0.0   20131.0   \n",
       "2   < 1 year               0     43057.0  ...      13.0     0.0   11987.0   \n",
       "\n",
       "  revol_util total_acc  initial_list_status application_type  mort_acc  \\\n",
       "0       41.8      25.0                    1                1       0.0   \n",
       "1       53.3      27.0                    0                1       3.0   \n",
       "2       92.2      26.0                    0                1       0.0   \n",
       "\n",
       "   pub_rec_bankruptcies                                            address  \n",
       "0                   0.0     0174 Michelle Gateway\\r\\nMendozaberg, OK 22690  \n",
       "1                   0.0  1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113  \n",
       "2                   0.0  87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113  \n",
       "\n",
       "[3 rows x 27 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['B', 'A', 'C', 'E', 'D', 'F', 'G'], dtype=object)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.unique(df[['grade']].values.ravel('K'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "grade_mapping = {'A': 1, 'B': 2,'C' : 3,'D': 4, 'E': 5,'F' : 6,'G' : 7}\n",
    "df=df.replace({'grade': grade_mapping})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</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>...</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <th>address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.44</td>\n",
       "      <td>329.48</td>\n",
       "      <td>2</td>\n",
       "      <td>B4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36369.0</td>\n",
       "      <td>41.8</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0174 Michelle Gateway\\r\\nMendozaberg, OK 22690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.99</td>\n",
       "      <td>265.68</td>\n",
       "      <td>2</td>\n",
       "      <td>B5</td>\n",
       "      <td>Credit analyst</td>\n",
       "      <td>4 years</td>\n",
       "      <td>3</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20131.0</td>\n",
       "      <td>53.3</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15600.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10.49</td>\n",
       "      <td>506.97</td>\n",
       "      <td>2</td>\n",
       "      <td>B3</td>\n",
       "      <td>Statistician</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>0</td>\n",
       "      <td>43057.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11987.0</td>\n",
       "      <td>92.2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  term  int_rate  installment  grade sub_grade        emp_title  \\\n",
       "0    10000.0    36     11.44       329.48      2        B4        Marketing   \n",
       "1     8000.0    36     11.99       265.68      2        B5  Credit analyst    \n",
       "2    15600.0    36     10.49       506.97      2        B3     Statistician   \n",
       "\n",
       "  emp_length  home_ownership  annual_inc  ...  open_acc pub_rec revol_bal  \\\n",
       "0  10+ years               0    117000.0  ...      16.0     0.0   36369.0   \n",
       "1    4 years               3     65000.0  ...      17.0     0.0   20131.0   \n",
       "2   < 1 year               0     43057.0  ...      13.0     0.0   11987.0   \n",
       "\n",
       "  revol_util total_acc  initial_list_status application_type  mort_acc  \\\n",
       "0       41.8      25.0                    1                1       0.0   \n",
       "1       53.3      27.0                    0                1       3.0   \n",
       "2       92.2      26.0                    0                1       0.0   \n",
       "\n",
       "   pub_rec_bankruptcies                                            address  \n",
       "0                   0.0     0174 Michelle Gateway\\r\\nMendozaberg, OK 22690  \n",
       "1                   0.0  1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113  \n",
       "2                   0.0  87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113  \n",
       "\n",
       "[3 rows x 27 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Fully Paid', 'Charged Off'], dtype=object)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.unique(df[['loan_status']].values.ravel('K'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "loan_status_mapping = {'Fully Paid': 1, 'Charged Off': 2}\n",
    "df=df.replace({'loan_status': loan_status_mapping})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.07215581086783944"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['loan_status'].corr(df['verification_status'])\n",
    "#this correlation is not accurate as it is uses pearson which isnt accurate for categorical values\n",
    "#but only for continuous ones."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Data Correlation</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "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>loan_amnt</th>\n",
       "      <th>term</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>grade</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>dti</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>loan_amnt</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.393977</td>\n",
       "      <td>0.150712</td>\n",
       "      <td>0.951031</td>\n",
       "      <td>0.165343</td>\n",
       "      <td>0.186125</td>\n",
       "      <td>0.405123</td>\n",
       "      <td>0.194583</td>\n",
       "      <td>0.014507</td>\n",
       "      <td>0.009141</td>\n",
       "      <td>0.192229</td>\n",
       "      <td>-0.088576</td>\n",
       "      <td>0.377737</td>\n",
       "      <td>0.089385</td>\n",
       "      <td>0.223559</td>\n",
       "      <td>0.082525</td>\n",
       "      <td>0.030559</td>\n",
       "      <td>0.198116</td>\n",
       "      <td>-0.118863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>term</th>\n",
       "      <td>0.393977</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.433398</td>\n",
       "      <td>0.141138</td>\n",
       "      <td>0.473918</td>\n",
       "      <td>0.115521</td>\n",
       "      <td>0.084677</td>\n",
       "      <td>0.210480</td>\n",
       "      <td>0.167627</td>\n",
       "      <td>0.084180</td>\n",
       "      <td>0.097722</td>\n",
       "      <td>0.034706</td>\n",
       "      <td>0.083010</td>\n",
       "      <td>0.050219</td>\n",
       "      <td>0.121359</td>\n",
       "      <td>0.203933</td>\n",
       "      <td>0.018679</td>\n",
       "      <td>0.095370</td>\n",
       "      <td>-0.003266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>int_rate</th>\n",
       "      <td>0.150712</td>\n",
       "      <td>0.433398</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.151313</td>\n",
       "      <td>0.955033</td>\n",
       "      <td>-0.037689</td>\n",
       "      <td>-0.058952</td>\n",
       "      <td>0.118578</td>\n",
       "      <td>0.240296</td>\n",
       "      <td>0.128170</td>\n",
       "      <td>0.016962</td>\n",
       "      <td>0.130949</td>\n",
       "      <td>-0.014446</td>\n",
       "      <td>0.244861</td>\n",
       "      <td>0.000707</td>\n",
       "      <td>-0.075077</td>\n",
       "      <td>0.034754</td>\n",
       "      <td>-0.040504</td>\n",
       "      <td>0.115559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installment</th>\n",
       "      <td>0.951031</td>\n",
       "      <td>0.141138</td>\n",
       "      <td>0.151313</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.148657</td>\n",
       "      <td>0.152400</td>\n",
       "      <td>0.388377</td>\n",
       "      <td>0.161826</td>\n",
       "      <td>-0.004164</td>\n",
       "      <td>-0.001188</td>\n",
       "      <td>0.167551</td>\n",
       "      <td>-0.085996</td>\n",
       "      <td>0.363899</td>\n",
       "      <td>0.112501</td>\n",
       "      <td>0.192044</td>\n",
       "      <td>0.012418</td>\n",
       "      <td>0.030072</td>\n",
       "      <td>0.168885</td>\n",
       "      <td>-0.106371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>grade</th>\n",
       "      <td>0.165343</td>\n",
       "      <td>0.473918</td>\n",
       "      <td>0.955033</td>\n",
       "      <td>0.148657</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.033157</td>\n",
       "      <td>-0.038373</td>\n",
       "      <td>0.138500</td>\n",
       "      <td>0.269864</td>\n",
       "      <td>0.119401</td>\n",
       "      <td>0.023363</td>\n",
       "      <td>0.143920</td>\n",
       "      <td>-0.012877</td>\n",
       "      <td>0.200147</td>\n",
       "      <td>0.023155</td>\n",
       "      <td>-0.016197</td>\n",
       "      <td>0.020564</td>\n",
       "      <td>-0.034856</td>\n",
       "      <td>0.125895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_ownership</th>\n",
       "      <td>0.186125</td>\n",
       "      <td>0.115521</td>\n",
       "      <td>-0.037689</td>\n",
       "      <td>0.152400</td>\n",
       "      <td>-0.033157</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.156085</td>\n",
       "      <td>-0.011990</td>\n",
       "      <td>-0.033007</td>\n",
       "      <td>0.029773</td>\n",
       "      <td>0.130183</td>\n",
       "      <td>-0.038408</td>\n",
       "      <td>0.226346</td>\n",
       "      <td>0.071325</td>\n",
       "      <td>0.246277</td>\n",
       "      <td>0.062869</td>\n",
       "      <td>0.012850</td>\n",
       "      <td>0.486560</td>\n",
       "      <td>-0.055044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>annual_inc</th>\n",
       "      <td>0.405123</td>\n",
       "      <td>0.084677</td>\n",
       "      <td>-0.058952</td>\n",
       "      <td>0.388377</td>\n",
       "      <td>-0.038373</td>\n",
       "      <td>0.156085</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.092528</td>\n",
       "      <td>-0.060335</td>\n",
       "      <td>-0.225210</td>\n",
       "      <td>0.174758</td>\n",
       "      <td>-0.062400</td>\n",
       "      <td>0.370829</td>\n",
       "      <td>0.001781</td>\n",
       "      <td>0.224277</td>\n",
       "      <td>0.045810</td>\n",
       "      <td>0.014372</td>\n",
       "      <td>0.231179</td>\n",
       "      <td>-0.093171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>verification_status</th>\n",
       "      <td>0.194583</td>\n",
       "      <td>0.210480</td>\n",
       "      <td>0.118578</td>\n",
       "      <td>0.161826</td>\n",
       "      <td>0.138500</td>\n",
       "      <td>-0.011990</td>\n",
       "      <td>0.092528</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.072156</td>\n",
       "      <td>0.068389</td>\n",
       "      <td>0.088359</td>\n",
       "      <td>0.048765</td>\n",
       "      <td>0.045697</td>\n",
       "      <td>0.015837</td>\n",
       "      <td>0.091732</td>\n",
       "      <td>0.081396</td>\n",
       "      <td>0.042144</td>\n",
       "      <td>-0.003610</td>\n",
       "      <td>0.027591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>loan_status</th>\n",
       "      <td>0.014507</td>\n",
       "      <td>0.167627</td>\n",
       "      <td>0.240296</td>\n",
       "      <td>-0.004164</td>\n",
       "      <td>0.269864</td>\n",
       "      <td>-0.033007</td>\n",
       "      <td>-0.060335</td>\n",
       "      <td>0.072156</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.066024</td>\n",
       "      <td>-0.014313</td>\n",
       "      <td>0.051850</td>\n",
       "      <td>-0.064325</td>\n",
       "      <td>0.052526</td>\n",
       "      <td>-0.063668</td>\n",
       "      <td>0.055846</td>\n",
       "      <td>0.015690</td>\n",
       "      <td>-0.047565</td>\n",
       "      <td>0.022349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dti</th>\n",
       "      <td>0.009141</td>\n",
       "      <td>0.084180</td>\n",
       "      <td>0.128170</td>\n",
       "      <td>-0.001188</td>\n",
       "      <td>0.119401</td>\n",
       "      <td>0.029773</td>\n",
       "      <td>-0.225210</td>\n",
       "      <td>0.068389</td>\n",
       "      <td>0.066024</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.357242</td>\n",
       "      <td>-0.031170</td>\n",
       "      <td>0.161887</td>\n",
       "      <td>0.201147</td>\n",
       "      <td>0.280258</td>\n",
       "      <td>0.047471</td>\n",
       "      <td>-0.046355</td>\n",
       "      <td>0.017684</td>\n",
       "      <td>-0.028990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>open_acc</th>\n",
       "      <td>0.192229</td>\n",
       "      <td>0.097722</td>\n",
       "      <td>0.016962</td>\n",
       "      <td>0.167551</td>\n",
       "      <td>0.023363</td>\n",
       "      <td>0.130183</td>\n",
       "      <td>0.174758</td>\n",
       "      <td>0.088359</td>\n",
       "      <td>-0.014313</td>\n",
       "      <td>0.357242</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.080222</td>\n",
       "      <td>0.292319</td>\n",
       "      <td>-0.103485</td>\n",
       "      <td>0.667995</td>\n",
       "      <td>0.030256</td>\n",
       "      <td>-0.010423</td>\n",
       "      <td>0.116653</td>\n",
       "      <td>-0.086420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pub_rec</th>\n",
       "      <td>-0.088576</td>\n",
       "      <td>0.034706</td>\n",
       "      <td>0.130949</td>\n",
       "      <td>-0.085996</td>\n",
       "      <td>0.143920</td>\n",
       "      <td>-0.038408</td>\n",
       "      <td>-0.062400</td>\n",
       "      <td>0.048765</td>\n",
       "      <td>0.051850</td>\n",
       "      <td>-0.031170</td>\n",
       "      <td>-0.080222</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.144440</td>\n",
       "      <td>-0.059893</td>\n",
       "      <td>-0.000057</td>\n",
       "      <td>0.031181</td>\n",
       "      <td>0.012766</td>\n",
       "      <td>0.045052</td>\n",
       "      <td>0.775557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revol_bal</th>\n",
       "      <td>0.377737</td>\n",
       "      <td>0.083010</td>\n",
       "      <td>-0.014446</td>\n",
       "      <td>0.363899</td>\n",
       "      <td>-0.012877</td>\n",
       "      <td>0.226346</td>\n",
       "      <td>0.370829</td>\n",
       "      <td>0.045697</td>\n",
       "      <td>-0.064325</td>\n",
       "      <td>0.161887</td>\n",
       "      <td>0.292319</td>\n",
       "      <td>-0.144440</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.298252</td>\n",
       "      <td>0.264283</td>\n",
       "      <td>0.043884</td>\n",
       "      <td>-0.004004</td>\n",
       "      <td>0.240043</td>\n",
       "      <td>-0.188632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revol_util</th>\n",
       "      <td>0.089385</td>\n",
       "      <td>0.050219</td>\n",
       "      <td>0.244861</td>\n",
       "      <td>0.112501</td>\n",
       "      <td>0.200147</td>\n",
       "      <td>0.071325</td>\n",
       "      <td>0.001781</td>\n",
       "      <td>0.015837</td>\n",
       "      <td>0.052526</td>\n",
       "      <td>0.201147</td>\n",
       "      <td>-0.103485</td>\n",
       "      <td>-0.059893</td>\n",
       "      <td>0.298252</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.056111</td>\n",
       "      <td>-0.080994</td>\n",
       "      <td>-0.002118</td>\n",
       "      <td>0.027079</td>\n",
       "      <td>-0.102935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_acc</th>\n",
       "      <td>0.223559</td>\n",
       "      <td>0.121359</td>\n",
       "      <td>0.000707</td>\n",
       "      <td>0.192044</td>\n",
       "      <td>0.023155</td>\n",
       "      <td>0.246277</td>\n",
       "      <td>0.224277</td>\n",
       "      <td>0.091732</td>\n",
       "      <td>-0.063668</td>\n",
       "      <td>0.280258</td>\n",
       "      <td>0.667995</td>\n",
       "      <td>-0.000057</td>\n",
       "      <td>0.264283</td>\n",
       "      <td>-0.056111</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.041173</td>\n",
       "      <td>-0.028916</td>\n",
       "      <td>0.419358</td>\n",
       "      <td>0.036291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>initial_list_status</th>\n",
       "      <td>0.082525</td>\n",
       "      <td>0.203933</td>\n",
       "      <td>-0.075077</td>\n",
       "      <td>0.012418</td>\n",
       "      <td>-0.016197</td>\n",
       "      <td>0.062869</td>\n",
       "      <td>0.045810</td>\n",
       "      <td>0.081396</td>\n",
       "      <td>0.055846</td>\n",
       "      <td>0.047471</td>\n",
       "      <td>0.030256</td>\n",
       "      <td>0.031181</td>\n",
       "      <td>0.043884</td>\n",
       "      <td>-0.080994</td>\n",
       "      <td>0.041173</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.039049</td>\n",
       "      <td>0.026520</td>\n",
       "      <td>0.012382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>application_type</th>\n",
       "      <td>0.030559</td>\n",
       "      <td>0.018679</td>\n",
       "      <td>0.034754</td>\n",
       "      <td>0.030072</td>\n",
       "      <td>0.020564</td>\n",
       "      <td>0.012850</td>\n",
       "      <td>0.014372</td>\n",
       "      <td>0.042144</td>\n",
       "      <td>0.015690</td>\n",
       "      <td>-0.046355</td>\n",
       "      <td>-0.010423</td>\n",
       "      <td>0.012766</td>\n",
       "      <td>-0.004004</td>\n",
       "      <td>-0.002118</td>\n",
       "      <td>-0.028916</td>\n",
       "      <td>-0.039049</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.036482</td>\n",
       "      <td>0.012071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mort_acc</th>\n",
       "      <td>0.198116</td>\n",
       "      <td>0.095370</td>\n",
       "      <td>-0.040504</td>\n",
       "      <td>0.168885</td>\n",
       "      <td>-0.034856</td>\n",
       "      <td>0.486560</td>\n",
       "      <td>0.231179</td>\n",
       "      <td>-0.003610</td>\n",
       "      <td>-0.047565</td>\n",
       "      <td>0.017684</td>\n",
       "      <td>0.116653</td>\n",
       "      <td>0.045052</td>\n",
       "      <td>0.240043</td>\n",
       "      <td>0.027079</td>\n",
       "      <td>0.419358</td>\n",
       "      <td>0.026520</td>\n",
       "      <td>-0.036482</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <td>-0.118863</td>\n",
       "      <td>-0.003266</td>\n",
       "      <td>0.115559</td>\n",
       "      <td>-0.106371</td>\n",
       "      <td>0.125895</td>\n",
       "      <td>-0.055044</td>\n",
       "      <td>-0.093171</td>\n",
       "      <td>0.027591</td>\n",
       "      <td>0.022349</td>\n",
       "      <td>-0.028990</td>\n",
       "      <td>-0.086420</td>\n",
       "      <td>0.775557</td>\n",
       "      <td>-0.188632</td>\n",
       "      <td>-0.102935</td>\n",
       "      <td>0.036291</td>\n",
       "      <td>0.012382</td>\n",
       "      <td>0.012071</td>\n",
       "      <td>0.059237</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      loan_amnt      term  int_rate  installment     grade  \\\n",
       "loan_amnt              1.000000  0.393977  0.150712     0.951031  0.165343   \n",
       "term                   0.393977  1.000000  0.433398     0.141138  0.473918   \n",
       "int_rate               0.150712  0.433398  1.000000     0.151313  0.955033   \n",
       "installment            0.951031  0.141138  0.151313     1.000000  0.148657   \n",
       "grade                  0.165343  0.473918  0.955033     0.148657  1.000000   \n",
       "home_ownership         0.186125  0.115521 -0.037689     0.152400 -0.033157   \n",
       "annual_inc             0.405123  0.084677 -0.058952     0.388377 -0.038373   \n",
       "verification_status    0.194583  0.210480  0.118578     0.161826  0.138500   \n",
       "loan_status            0.014507  0.167627  0.240296    -0.004164  0.269864   \n",
       "dti                    0.009141  0.084180  0.128170    -0.001188  0.119401   \n",
       "open_acc               0.192229  0.097722  0.016962     0.167551  0.023363   \n",
       "pub_rec               -0.088576  0.034706  0.130949    -0.085996  0.143920   \n",
       "revol_bal              0.377737  0.083010 -0.014446     0.363899 -0.012877   \n",
       "revol_util             0.089385  0.050219  0.244861     0.112501  0.200147   \n",
       "total_acc              0.223559  0.121359  0.000707     0.192044  0.023155   \n",
       "initial_list_status    0.082525  0.203933 -0.075077     0.012418 -0.016197   \n",
       "application_type       0.030559  0.018679  0.034754     0.030072  0.020564   \n",
       "mort_acc               0.198116  0.095370 -0.040504     0.168885 -0.034856   \n",
       "pub_rec_bankruptcies  -0.118863 -0.003266  0.115559    -0.106371  0.125895   \n",
       "\n",
       "                      home_ownership  annual_inc  verification_status  \\\n",
       "loan_amnt                   0.186125    0.405123             0.194583   \n",
       "term                        0.115521    0.084677             0.210480   \n",
       "int_rate                   -0.037689   -0.058952             0.118578   \n",
       "installment                 0.152400    0.388377             0.161826   \n",
       "grade                      -0.033157   -0.038373             0.138500   \n",
       "home_ownership              1.000000    0.156085            -0.011990   \n",
       "annual_inc                  0.156085    1.000000             0.092528   \n",
       "verification_status        -0.011990    0.092528             1.000000   \n",
       "loan_status                -0.033007   -0.060335             0.072156   \n",
       "dti                         0.029773   -0.225210             0.068389   \n",
       "open_acc                    0.130183    0.174758             0.088359   \n",
       "pub_rec                    -0.038408   -0.062400             0.048765   \n",
       "revol_bal                   0.226346    0.370829             0.045697   \n",
       "revol_util                  0.071325    0.001781             0.015837   \n",
       "total_acc                   0.246277    0.224277             0.091732   \n",
       "initial_list_status         0.062869    0.045810             0.081396   \n",
       "application_type            0.012850    0.014372             0.042144   \n",
       "mort_acc                    0.486560    0.231179            -0.003610   \n",
       "pub_rec_bankruptcies       -0.055044   -0.093171             0.027591   \n",
       "\n",
       "                      loan_status       dti  open_acc   pub_rec  revol_bal  \\\n",
       "loan_amnt                0.014507  0.009141  0.192229 -0.088576   0.377737   \n",
       "term                     0.167627  0.084180  0.097722  0.034706   0.083010   \n",
       "int_rate                 0.240296  0.128170  0.016962  0.130949  -0.014446   \n",
       "installment             -0.004164 -0.001188  0.167551 -0.085996   0.363899   \n",
       "grade                    0.269864  0.119401  0.023363  0.143920  -0.012877   \n",
       "home_ownership          -0.033007  0.029773  0.130183 -0.038408   0.226346   \n",
       "annual_inc              -0.060335 -0.225210  0.174758 -0.062400   0.370829   \n",
       "verification_status      0.072156  0.068389  0.088359  0.048765   0.045697   \n",
       "loan_status              1.000000  0.066024 -0.014313  0.051850  -0.064325   \n",
       "dti                      0.066024  1.000000  0.357242 -0.031170   0.161887   \n",
       "open_acc                -0.014313  0.357242  1.000000 -0.080222   0.292319   \n",
       "pub_rec                  0.051850 -0.031170 -0.080222  1.000000  -0.144440   \n",
       "revol_bal               -0.064325  0.161887  0.292319 -0.144440   1.000000   \n",
       "revol_util               0.052526  0.201147 -0.103485 -0.059893   0.298252   \n",
       "total_acc               -0.063668  0.280258  0.667995 -0.000057   0.264283   \n",
       "initial_list_status      0.055846  0.047471  0.030256  0.031181   0.043884   \n",
       "application_type         0.015690 -0.046355 -0.010423  0.012766  -0.004004   \n",
       "mort_acc                -0.047565  0.017684  0.116653  0.045052   0.240043   \n",
       "pub_rec_bankruptcies     0.022349 -0.028990 -0.086420  0.775557  -0.188632   \n",
       "\n",
       "                      revol_util  total_acc  initial_list_status  \\\n",
       "loan_amnt               0.089385   0.223559             0.082525   \n",
       "term                    0.050219   0.121359             0.203933   \n",
       "int_rate                0.244861   0.000707            -0.075077   \n",
       "installment             0.112501   0.192044             0.012418   \n",
       "grade                   0.200147   0.023155            -0.016197   \n",
       "home_ownership          0.071325   0.246277             0.062869   \n",
       "annual_inc              0.001781   0.224277             0.045810   \n",
       "verification_status     0.015837   0.091732             0.081396   \n",
       "loan_status             0.052526  -0.063668             0.055846   \n",
       "dti                     0.201147   0.280258             0.047471   \n",
       "open_acc               -0.103485   0.667995             0.030256   \n",
       "pub_rec                -0.059893  -0.000057             0.031181   \n",
       "revol_bal               0.298252   0.264283             0.043884   \n",
       "revol_util              1.000000  -0.056111            -0.080994   \n",
       "total_acc              -0.056111   1.000000             0.041173   \n",
       "initial_list_status    -0.080994   0.041173             1.000000   \n",
       "application_type       -0.002118  -0.028916            -0.039049   \n",
       "mort_acc                0.027079   0.419358             0.026520   \n",
       "pub_rec_bankruptcies   -0.102935   0.036291             0.012382   \n",
       "\n",
       "                      application_type  mort_acc  pub_rec_bankruptcies  \n",
       "loan_amnt                     0.030559  0.198116             -0.118863  \n",
       "term                          0.018679  0.095370             -0.003266  \n",
       "int_rate                      0.034754 -0.040504              0.115559  \n",
       "installment                   0.030072  0.168885             -0.106371  \n",
       "grade                         0.020564 -0.034856              0.125895  \n",
       "home_ownership                0.012850  0.486560             -0.055044  \n",
       "annual_inc                    0.014372  0.231179             -0.093171  \n",
       "verification_status           0.042144 -0.003610              0.027591  \n",
       "loan_status                   0.015690 -0.047565              0.022349  \n",
       "dti                          -0.046355  0.017684             -0.028990  \n",
       "open_acc                     -0.010423  0.116653             -0.086420  \n",
       "pub_rec                       0.012766  0.045052              0.775557  \n",
       "revol_bal                    -0.004004  0.240043             -0.188632  \n",
       "revol_util                   -0.002118  0.027079             -0.102935  \n",
       "total_acc                    -0.028916  0.419358              0.036291  \n",
       "initial_list_status          -0.039049  0.026520              0.012382  \n",
       "application_type              1.000000 -0.036482              0.012071  \n",
       "mort_acc                     -0.036482  1.000000              0.059237  \n",
       "pub_rec_bankruptcies          0.012071  0.059237              1.000000  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>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>...</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <th>address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.44</td>\n",
       "      <td>329.48</td>\n",
       "      <td>2</td>\n",
       "      <td>B4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>10+ years</td>\n",
       "      <td>0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36369.0</td>\n",
       "      <td>41.8</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0174 Michelle Gateway\\r\\nMendozaberg, OK 22690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.99</td>\n",
       "      <td>265.68</td>\n",
       "      <td>2</td>\n",
       "      <td>B5</td>\n",
       "      <td>Credit analyst</td>\n",
       "      <td>4 years</td>\n",
       "      <td>3</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20131.0</td>\n",
       "      <td>53.3</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15600.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10.49</td>\n",
       "      <td>506.97</td>\n",
       "      <td>2</td>\n",
       "      <td>B3</td>\n",
       "      <td>Statistician</td>\n",
       "      <td>&lt; 1 year</td>\n",
       "      <td>0</td>\n",
       "      <td>43057.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11987.0</td>\n",
       "      <td>92.2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  term  int_rate  installment  grade sub_grade        emp_title  \\\n",
       "0    10000.0    36     11.44       329.48      2        B4        Marketing   \n",
       "1     8000.0    36     11.99       265.68      2        B5  Credit analyst    \n",
       "2    15600.0    36     10.49       506.97      2        B3     Statistician   \n",
       "\n",
       "  emp_length  home_ownership  annual_inc  ...  open_acc pub_rec  revol_bal  \\\n",
       "0  10+ years               0    117000.0  ...      16.0     0.0    36369.0   \n",
       "1    4 years               3     65000.0  ...      17.0     0.0    20131.0   \n",
       "2   < 1 year               0     43057.0  ...      13.0     0.0    11987.0   \n",
       "\n",
       "  revol_util total_acc  initial_list_status application_type  mort_acc  \\\n",
       "0       41.8      25.0                    1                1       0.0   \n",
       "1       53.3      27.0                    0                1       3.0   \n",
       "2       92.2      26.0                    0                1       0.0   \n",
       "\n",
       "   pub_rec_bankruptcies                                            address  \n",
       "0                   0.0     0174 Michelle Gateway\\r\\nMendozaberg, OK 22690  \n",
       "1                   0.0  1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113  \n",
       "2                   0.0  87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113  \n",
       "\n",
       "[3 rows x 27 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2], dtype=int64)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.unique(df[['loan_status']].values.ravel('K'))\n",
    "#all unique values in loan_status columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['emp_length']=df_with_years_removed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['10', '4 ', '< 1 year', '6 ', '9 ', '2 ', '3 ', '8 ', '7 ', '5 ',\n",
       "       '1 year'], dtype=object)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['emp_length']\n",
    "pd.unique(df['emp_length'].values.ravel('K'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_with_less_than_1_year_replaced = df['emp_length'].str.replace('< 1 year', '0.6')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     10\n",
       "1     4 \n",
       "2    0.6\n",
       "Name: emp_length, dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_with_less_than_1_year_replaced.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_with_1_year_as_1=df_with_less_than_1_year_replaced.str.replace('1 year', '1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['emp_length']=df_with_1_year_as_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>term</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>installment</th>\n",
       "      <th>grade</th>\n",
       "      <th>home_ownership</th>\n",
       "      <th>annual_inc</th>\n",
       "      <th>verification_status</th>\n",
       "      <th>loan_status</th>\n",
       "      <th>dti</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>loan_amnt</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.393977</td>\n",
       "      <td>0.150712</td>\n",
       "      <td>0.951031</td>\n",
       "      <td>0.165343</td>\n",
       "      <td>0.186125</td>\n",
       "      <td>0.405123</td>\n",
       "      <td>0.194583</td>\n",
       "      <td>0.014507</td>\n",
       "      <td>0.009141</td>\n",
       "      <td>0.192229</td>\n",
       "      <td>-0.088576</td>\n",
       "      <td>0.377737</td>\n",
       "      <td>0.089385</td>\n",
       "      <td>0.223559</td>\n",
       "      <td>0.082525</td>\n",
       "      <td>0.030559</td>\n",
       "      <td>0.198116</td>\n",
       "      <td>-0.118863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>term</th>\n",
       "      <td>0.393977</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.433398</td>\n",
       "      <td>0.141138</td>\n",
       "      <td>0.473918</td>\n",
       "      <td>0.115521</td>\n",
       "      <td>0.084677</td>\n",
       "      <td>0.210480</td>\n",
       "      <td>0.167627</td>\n",
       "      <td>0.084180</td>\n",
       "      <td>0.097722</td>\n",
       "      <td>0.034706</td>\n",
       "      <td>0.083010</td>\n",
       "      <td>0.050219</td>\n",
       "      <td>0.121359</td>\n",
       "      <td>0.203933</td>\n",
       "      <td>0.018679</td>\n",
       "      <td>0.095370</td>\n",
       "      <td>-0.003266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>int_rate</th>\n",
       "      <td>0.150712</td>\n",
       "      <td>0.433398</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.151313</td>\n",
       "      <td>0.955033</td>\n",
       "      <td>-0.037689</td>\n",
       "      <td>-0.058952</td>\n",
       "      <td>0.118578</td>\n",
       "      <td>0.240296</td>\n",
       "      <td>0.128170</td>\n",
       "      <td>0.016962</td>\n",
       "      <td>0.130949</td>\n",
       "      <td>-0.014446</td>\n",
       "      <td>0.244861</td>\n",
       "      <td>0.000707</td>\n",
       "      <td>-0.075077</td>\n",
       "      <td>0.034754</td>\n",
       "      <td>-0.040504</td>\n",
       "      <td>0.115559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>installment</th>\n",
       "      <td>0.951031</td>\n",
       "      <td>0.141138</td>\n",
       "      <td>0.151313</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.148657</td>\n",
       "      <td>0.152400</td>\n",
       "      <td>0.388377</td>\n",
       "      <td>0.161826</td>\n",
       "      <td>-0.004164</td>\n",
       "      <td>-0.001188</td>\n",
       "      <td>0.167551</td>\n",
       "      <td>-0.085996</td>\n",
       "      <td>0.363899</td>\n",
       "      <td>0.112501</td>\n",
       "      <td>0.192044</td>\n",
       "      <td>0.012418</td>\n",
       "      <td>0.030072</td>\n",
       "      <td>0.168885</td>\n",
       "      <td>-0.106371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>grade</th>\n",
       "      <td>0.165343</td>\n",
       "      <td>0.473918</td>\n",
       "      <td>0.955033</td>\n",
       "      <td>0.148657</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.033157</td>\n",
       "      <td>-0.038373</td>\n",
       "      <td>0.138500</td>\n",
       "      <td>0.269864</td>\n",
       "      <td>0.119401</td>\n",
       "      <td>0.023363</td>\n",
       "      <td>0.143920</td>\n",
       "      <td>-0.012877</td>\n",
       "      <td>0.200147</td>\n",
       "      <td>0.023155</td>\n",
       "      <td>-0.016197</td>\n",
       "      <td>0.020564</td>\n",
       "      <td>-0.034856</td>\n",
       "      <td>0.125895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>home_ownership</th>\n",
       "      <td>0.186125</td>\n",
       "      <td>0.115521</td>\n",
       "      <td>-0.037689</td>\n",
       "      <td>0.152400</td>\n",
       "      <td>-0.033157</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.156085</td>\n",
       "      <td>-0.011990</td>\n",
       "      <td>-0.033007</td>\n",
       "      <td>0.029773</td>\n",
       "      <td>0.130183</td>\n",
       "      <td>-0.038408</td>\n",
       "      <td>0.226346</td>\n",
       "      <td>0.071325</td>\n",
       "      <td>0.246277</td>\n",
       "      <td>0.062869</td>\n",
       "      <td>0.012850</td>\n",
       "      <td>0.486560</td>\n",
       "      <td>-0.055044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>annual_inc</th>\n",
       "      <td>0.405123</td>\n",
       "      <td>0.084677</td>\n",
       "      <td>-0.058952</td>\n",
       "      <td>0.388377</td>\n",
       "      <td>-0.038373</td>\n",
       "      <td>0.156085</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.092528</td>\n",
       "      <td>-0.060335</td>\n",
       "      <td>-0.225210</td>\n",
       "      <td>0.174758</td>\n",
       "      <td>-0.062400</td>\n",
       "      <td>0.370829</td>\n",
       "      <td>0.001781</td>\n",
       "      <td>0.224277</td>\n",
       "      <td>0.045810</td>\n",
       "      <td>0.014372</td>\n",
       "      <td>0.231179</td>\n",
       "      <td>-0.093171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>verification_status</th>\n",
       "      <td>0.194583</td>\n",
       "      <td>0.210480</td>\n",
       "      <td>0.118578</td>\n",
       "      <td>0.161826</td>\n",
       "      <td>0.138500</td>\n",
       "      <td>-0.011990</td>\n",
       "      <td>0.092528</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.072156</td>\n",
       "      <td>0.068389</td>\n",
       "      <td>0.088359</td>\n",
       "      <td>0.048765</td>\n",
       "      <td>0.045697</td>\n",
       "      <td>0.015837</td>\n",
       "      <td>0.091732</td>\n",
       "      <td>0.081396</td>\n",
       "      <td>0.042144</td>\n",
       "      <td>-0.003610</td>\n",
       "      <td>0.027591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>loan_status</th>\n",
       "      <td>0.014507</td>\n",
       "      <td>0.167627</td>\n",
       "      <td>0.240296</td>\n",
       "      <td>-0.004164</td>\n",
       "      <td>0.269864</td>\n",
       "      <td>-0.033007</td>\n",
       "      <td>-0.060335</td>\n",
       "      <td>0.072156</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.066024</td>\n",
       "      <td>-0.014313</td>\n",
       "      <td>0.051850</td>\n",
       "      <td>-0.064325</td>\n",
       "      <td>0.052526</td>\n",
       "      <td>-0.063668</td>\n",
       "      <td>0.055846</td>\n",
       "      <td>0.015690</td>\n",
       "      <td>-0.047565</td>\n",
       "      <td>0.022349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>dti</th>\n",
       "      <td>0.009141</td>\n",
       "      <td>0.084180</td>\n",
       "      <td>0.128170</td>\n",
       "      <td>-0.001188</td>\n",
       "      <td>0.119401</td>\n",
       "      <td>0.029773</td>\n",
       "      <td>-0.225210</td>\n",
       "      <td>0.068389</td>\n",
       "      <td>0.066024</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.357242</td>\n",
       "      <td>-0.031170</td>\n",
       "      <td>0.161887</td>\n",
       "      <td>0.201147</td>\n",
       "      <td>0.280258</td>\n",
       "      <td>0.047471</td>\n",
       "      <td>-0.046355</td>\n",
       "      <td>0.017684</td>\n",
       "      <td>-0.028990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>open_acc</th>\n",
       "      <td>0.192229</td>\n",
       "      <td>0.097722</td>\n",
       "      <td>0.016962</td>\n",
       "      <td>0.167551</td>\n",
       "      <td>0.023363</td>\n",
       "      <td>0.130183</td>\n",
       "      <td>0.174758</td>\n",
       "      <td>0.088359</td>\n",
       "      <td>-0.014313</td>\n",
       "      <td>0.357242</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.080222</td>\n",
       "      <td>0.292319</td>\n",
       "      <td>-0.103485</td>\n",
       "      <td>0.667995</td>\n",
       "      <td>0.030256</td>\n",
       "      <td>-0.010423</td>\n",
       "      <td>0.116653</td>\n",
       "      <td>-0.086420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pub_rec</th>\n",
       "      <td>-0.088576</td>\n",
       "      <td>0.034706</td>\n",
       "      <td>0.130949</td>\n",
       "      <td>-0.085996</td>\n",
       "      <td>0.143920</td>\n",
       "      <td>-0.038408</td>\n",
       "      <td>-0.062400</td>\n",
       "      <td>0.048765</td>\n",
       "      <td>0.051850</td>\n",
       "      <td>-0.031170</td>\n",
       "      <td>-0.080222</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.144440</td>\n",
       "      <td>-0.059893</td>\n",
       "      <td>-0.000057</td>\n",
       "      <td>0.031181</td>\n",
       "      <td>0.012766</td>\n",
       "      <td>0.045052</td>\n",
       "      <td>0.775557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revol_bal</th>\n",
       "      <td>0.377737</td>\n",
       "      <td>0.083010</td>\n",
       "      <td>-0.014446</td>\n",
       "      <td>0.363899</td>\n",
       "      <td>-0.012877</td>\n",
       "      <td>0.226346</td>\n",
       "      <td>0.370829</td>\n",
       "      <td>0.045697</td>\n",
       "      <td>-0.064325</td>\n",
       "      <td>0.161887</td>\n",
       "      <td>0.292319</td>\n",
       "      <td>-0.144440</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.298252</td>\n",
       "      <td>0.264283</td>\n",
       "      <td>0.043884</td>\n",
       "      <td>-0.004004</td>\n",
       "      <td>0.240043</td>\n",
       "      <td>-0.188632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>revol_util</th>\n",
       "      <td>0.089385</td>\n",
       "      <td>0.050219</td>\n",
       "      <td>0.244861</td>\n",
       "      <td>0.112501</td>\n",
       "      <td>0.200147</td>\n",
       "      <td>0.071325</td>\n",
       "      <td>0.001781</td>\n",
       "      <td>0.015837</td>\n",
       "      <td>0.052526</td>\n",
       "      <td>0.201147</td>\n",
       "      <td>-0.103485</td>\n",
       "      <td>-0.059893</td>\n",
       "      <td>0.298252</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.056111</td>\n",
       "      <td>-0.080994</td>\n",
       "      <td>-0.002118</td>\n",
       "      <td>0.027079</td>\n",
       "      <td>-0.102935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>total_acc</th>\n",
       "      <td>0.223559</td>\n",
       "      <td>0.121359</td>\n",
       "      <td>0.000707</td>\n",
       "      <td>0.192044</td>\n",
       "      <td>0.023155</td>\n",
       "      <td>0.246277</td>\n",
       "      <td>0.224277</td>\n",
       "      <td>0.091732</td>\n",
       "      <td>-0.063668</td>\n",
       "      <td>0.280258</td>\n",
       "      <td>0.667995</td>\n",
       "      <td>-0.000057</td>\n",
       "      <td>0.264283</td>\n",
       "      <td>-0.056111</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.041173</td>\n",
       "      <td>-0.028916</td>\n",
       "      <td>0.419358</td>\n",
       "      <td>0.036291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>initial_list_status</th>\n",
       "      <td>0.082525</td>\n",
       "      <td>0.203933</td>\n",
       "      <td>-0.075077</td>\n",
       "      <td>0.012418</td>\n",
       "      <td>-0.016197</td>\n",
       "      <td>0.062869</td>\n",
       "      <td>0.045810</td>\n",
       "      <td>0.081396</td>\n",
       "      <td>0.055846</td>\n",
       "      <td>0.047471</td>\n",
       "      <td>0.030256</td>\n",
       "      <td>0.031181</td>\n",
       "      <td>0.043884</td>\n",
       "      <td>-0.080994</td>\n",
       "      <td>0.041173</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.039049</td>\n",
       "      <td>0.026520</td>\n",
       "      <td>0.012382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>application_type</th>\n",
       "      <td>0.030559</td>\n",
       "      <td>0.018679</td>\n",
       "      <td>0.034754</td>\n",
       "      <td>0.030072</td>\n",
       "      <td>0.020564</td>\n",
       "      <td>0.012850</td>\n",
       "      <td>0.014372</td>\n",
       "      <td>0.042144</td>\n",
       "      <td>0.015690</td>\n",
       "      <td>-0.046355</td>\n",
       "      <td>-0.010423</td>\n",
       "      <td>0.012766</td>\n",
       "      <td>-0.004004</td>\n",
       "      <td>-0.002118</td>\n",
       "      <td>-0.028916</td>\n",
       "      <td>-0.039049</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.036482</td>\n",
       "      <td>0.012071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mort_acc</th>\n",
       "      <td>0.198116</td>\n",
       "      <td>0.095370</td>\n",
       "      <td>-0.040504</td>\n",
       "      <td>0.168885</td>\n",
       "      <td>-0.034856</td>\n",
       "      <td>0.486560</td>\n",
       "      <td>0.231179</td>\n",
       "      <td>-0.003610</td>\n",
       "      <td>-0.047565</td>\n",
       "      <td>0.017684</td>\n",
       "      <td>0.116653</td>\n",
       "      <td>0.045052</td>\n",
       "      <td>0.240043</td>\n",
       "      <td>0.027079</td>\n",
       "      <td>0.419358</td>\n",
       "      <td>0.026520</td>\n",
       "      <td>-0.036482</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <td>-0.118863</td>\n",
       "      <td>-0.003266</td>\n",
       "      <td>0.115559</td>\n",
       "      <td>-0.106371</td>\n",
       "      <td>0.125895</td>\n",
       "      <td>-0.055044</td>\n",
       "      <td>-0.093171</td>\n",
       "      <td>0.027591</td>\n",
       "      <td>0.022349</td>\n",
       "      <td>-0.028990</td>\n",
       "      <td>-0.086420</td>\n",
       "      <td>0.775557</td>\n",
       "      <td>-0.188632</td>\n",
       "      <td>-0.102935</td>\n",
       "      <td>0.036291</td>\n",
       "      <td>0.012382</td>\n",
       "      <td>0.012071</td>\n",
       "      <td>0.059237</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      loan_amnt      term  int_rate  installment     grade  \\\n",
       "loan_amnt              1.000000  0.393977  0.150712     0.951031  0.165343   \n",
       "term                   0.393977  1.000000  0.433398     0.141138  0.473918   \n",
       "int_rate               0.150712  0.433398  1.000000     0.151313  0.955033   \n",
       "installment            0.951031  0.141138  0.151313     1.000000  0.148657   \n",
       "grade                  0.165343  0.473918  0.955033     0.148657  1.000000   \n",
       "home_ownership         0.186125  0.115521 -0.037689     0.152400 -0.033157   \n",
       "annual_inc             0.405123  0.084677 -0.058952     0.388377 -0.038373   \n",
       "verification_status    0.194583  0.210480  0.118578     0.161826  0.138500   \n",
       "loan_status            0.014507  0.167627  0.240296    -0.004164  0.269864   \n",
       "dti                    0.009141  0.084180  0.128170    -0.001188  0.119401   \n",
       "open_acc               0.192229  0.097722  0.016962     0.167551  0.023363   \n",
       "pub_rec               -0.088576  0.034706  0.130949    -0.085996  0.143920   \n",
       "revol_bal              0.377737  0.083010 -0.014446     0.363899 -0.012877   \n",
       "revol_util             0.089385  0.050219  0.244861     0.112501  0.200147   \n",
       "total_acc              0.223559  0.121359  0.000707     0.192044  0.023155   \n",
       "initial_list_status    0.082525  0.203933 -0.075077     0.012418 -0.016197   \n",
       "application_type       0.030559  0.018679  0.034754     0.030072  0.020564   \n",
       "mort_acc               0.198116  0.095370 -0.040504     0.168885 -0.034856   \n",
       "pub_rec_bankruptcies  -0.118863 -0.003266  0.115559    -0.106371  0.125895   \n",
       "\n",
       "                      home_ownership  annual_inc  verification_status  \\\n",
       "loan_amnt                   0.186125    0.405123             0.194583   \n",
       "term                        0.115521    0.084677             0.210480   \n",
       "int_rate                   -0.037689   -0.058952             0.118578   \n",
       "installment                 0.152400    0.388377             0.161826   \n",
       "grade                      -0.033157   -0.038373             0.138500   \n",
       "home_ownership              1.000000    0.156085            -0.011990   \n",
       "annual_inc                  0.156085    1.000000             0.092528   \n",
       "verification_status        -0.011990    0.092528             1.000000   \n",
       "loan_status                -0.033007   -0.060335             0.072156   \n",
       "dti                         0.029773   -0.225210             0.068389   \n",
       "open_acc                    0.130183    0.174758             0.088359   \n",
       "pub_rec                    -0.038408   -0.062400             0.048765   \n",
       "revol_bal                   0.226346    0.370829             0.045697   \n",
       "revol_util                  0.071325    0.001781             0.015837   \n",
       "total_acc                   0.246277    0.224277             0.091732   \n",
       "initial_list_status         0.062869    0.045810             0.081396   \n",
       "application_type            0.012850    0.014372             0.042144   \n",
       "mort_acc                    0.486560    0.231179            -0.003610   \n",
       "pub_rec_bankruptcies       -0.055044   -0.093171             0.027591   \n",
       "\n",
       "                      loan_status       dti  open_acc   pub_rec  revol_bal  \\\n",
       "loan_amnt                0.014507  0.009141  0.192229 -0.088576   0.377737   \n",
       "term                     0.167627  0.084180  0.097722  0.034706   0.083010   \n",
       "int_rate                 0.240296  0.128170  0.016962  0.130949  -0.014446   \n",
       "installment             -0.004164 -0.001188  0.167551 -0.085996   0.363899   \n",
       "grade                    0.269864  0.119401  0.023363  0.143920  -0.012877   \n",
       "home_ownership          -0.033007  0.029773  0.130183 -0.038408   0.226346   \n",
       "annual_inc              -0.060335 -0.225210  0.174758 -0.062400   0.370829   \n",
       "verification_status      0.072156  0.068389  0.088359  0.048765   0.045697   \n",
       "loan_status              1.000000  0.066024 -0.014313  0.051850  -0.064325   \n",
       "dti                      0.066024  1.000000  0.357242 -0.031170   0.161887   \n",
       "open_acc                -0.014313  0.357242  1.000000 -0.080222   0.292319   \n",
       "pub_rec                  0.051850 -0.031170 -0.080222  1.000000  -0.144440   \n",
       "revol_bal               -0.064325  0.161887  0.292319 -0.144440   1.000000   \n",
       "revol_util               0.052526  0.201147 -0.103485 -0.059893   0.298252   \n",
       "total_acc               -0.063668  0.280258  0.667995 -0.000057   0.264283   \n",
       "initial_list_status      0.055846  0.047471  0.030256  0.031181   0.043884   \n",
       "application_type         0.015690 -0.046355 -0.010423  0.012766  -0.004004   \n",
       "mort_acc                -0.047565  0.017684  0.116653  0.045052   0.240043   \n",
       "pub_rec_bankruptcies     0.022349 -0.028990 -0.086420  0.775557  -0.188632   \n",
       "\n",
       "                      revol_util  total_acc  initial_list_status  \\\n",
       "loan_amnt               0.089385   0.223559             0.082525   \n",
       "term                    0.050219   0.121359             0.203933   \n",
       "int_rate                0.244861   0.000707            -0.075077   \n",
       "installment             0.112501   0.192044             0.012418   \n",
       "grade                   0.200147   0.023155            -0.016197   \n",
       "home_ownership          0.071325   0.246277             0.062869   \n",
       "annual_inc              0.001781   0.224277             0.045810   \n",
       "verification_status     0.015837   0.091732             0.081396   \n",
       "loan_status             0.052526  -0.063668             0.055846   \n",
       "dti                     0.201147   0.280258             0.047471   \n",
       "open_acc               -0.103485   0.667995             0.030256   \n",
       "pub_rec                -0.059893  -0.000057             0.031181   \n",
       "revol_bal               0.298252   0.264283             0.043884   \n",
       "revol_util              1.000000  -0.056111            -0.080994   \n",
       "total_acc              -0.056111   1.000000             0.041173   \n",
       "initial_list_status    -0.080994   0.041173             1.000000   \n",
       "application_type       -0.002118  -0.028916            -0.039049   \n",
       "mort_acc                0.027079   0.419358             0.026520   \n",
       "pub_rec_bankruptcies   -0.102935   0.036291             0.012382   \n",
       "\n",
       "                      application_type  mort_acc  pub_rec_bankruptcies  \n",
       "loan_amnt                     0.030559  0.198116             -0.118863  \n",
       "term                          0.018679  0.095370             -0.003266  \n",
       "int_rate                      0.034754 -0.040504              0.115559  \n",
       "installment                   0.030072  0.168885             -0.106371  \n",
       "grade                         0.020564 -0.034856              0.125895  \n",
       "home_ownership                0.012850  0.486560             -0.055044  \n",
       "annual_inc                    0.014372  0.231179             -0.093171  \n",
       "verification_status           0.042144 -0.003610              0.027591  \n",
       "loan_status                   0.015690 -0.047565              0.022349  \n",
       "dti                          -0.046355  0.017684             -0.028990  \n",
       "open_acc                     -0.010423  0.116653             -0.086420  \n",
       "pub_rec                       0.012766  0.045052              0.775557  \n",
       "revol_bal                    -0.004004  0.240043             -0.188632  \n",
       "revol_util                   -0.002118  0.027079             -0.102935  \n",
       "total_acc                    -0.028916  0.419358              0.036291  \n",
       "initial_list_status          -0.039049  0.026520              0.012382  \n",
       "application_type              1.000000 -0.036482              0.012071  \n",
       "mort_acc                     -0.036482  1.000000              0.059237  \n",
       "pub_rec_bankruptcies          0.012071  0.059237              1.000000  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2>Heat Map of data correlation</h2>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1872x1872 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "#get correlations of each features in dataset\n",
    "corrmat = df.corr()\n",
    "top_corr_features = corrmat.index\n",
    "plt.figure(figsize=(26,26))\n",
    "#plot heat map\n",
    "g=sns.heatmap(df[top_corr_features].corr(),annot=True,cmap=\"RdYlGn\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(869,)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#total data set = 869\n",
    "df['loan_status'].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(238, 27)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Source verified number who paid = 238\n",
    "df.loc[(df['loan_status'] == 1) & (df['verification_status'] == 2)].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(236, 27)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#verified number who paid = 236\n",
    "df.loc[(df['loan_status'] == 1) & (df['verification_status'] == 1)].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(242, 27)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#un-verified number who paid = 242\n",
    "df.loc[(df['loan_status'] == 1) & (df['verification_status'] == 0)].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(153, 27)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#those who never paid\n",
    "#shouldve made it 0 , change later\n",
    "df.loc[(df['loan_status'] == 2)].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3>Understanding correlation</h3>\n",
    "<a>https://medium.com/@outside2SDs/an-overview-of-correlation-measures-between-categorical-and-continuous-variables-4c7f85610365</a></br>\n",
    "<img src=\"https://miro.medium.com/max/700/1*6KNXPv-_3s7cJrcOQxbZCw.png\"\n",
    "     style=\"float: left; margin-right: 10px;\" />"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>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>...</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>application_type</th>\n",
       "      <th>mort_acc</th>\n",
       "      <th>pub_rec_bankruptcies</th>\n",
       "      <th>address</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.44</td>\n",
       "      <td>329.48</td>\n",
       "      <td>2</td>\n",
       "      <td>B4</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>117000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36369.0</td>\n",
       "      <td>41.8</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0174 Michelle Gateway\\r\\nMendozaberg, OK 22690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.99</td>\n",
       "      <td>265.68</td>\n",
       "      <td>2</td>\n",
       "      <td>B5</td>\n",
       "      <td>Credit analyst</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>65000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20131.0</td>\n",
       "      <td>53.3</td>\n",
       "      <td>27.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15600.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10.49</td>\n",
       "      <td>506.97</td>\n",
       "      <td>2</td>\n",
       "      <td>B3</td>\n",
       "      <td>Statistician</td>\n",
       "      <td>0.6</td>\n",
       "      <td>0</td>\n",
       "      <td>43057.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11987.0</td>\n",
       "      <td>92.2</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7200.0</td>\n",
       "      <td>36</td>\n",
       "      <td>6.49</td>\n",
       "      <td>220.65</td>\n",
       "      <td>1</td>\n",
       "      <td>A2</td>\n",
       "      <td>Client Advocate</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>54000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5472.0</td>\n",
       "      <td>21.5</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>823 Reid Ford\\r\\nDelacruzside, MA 00813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24375.0</td>\n",
       "      <td>60</td>\n",
       "      <td>17.27</td>\n",
       "      <td>609.33</td>\n",
       "      <td>3</td>\n",
       "      <td>C5</td>\n",
       "      <td>Destiny Management Inc.</td>\n",
       "      <td>9</td>\n",
       "      <td>3</td>\n",
       "      <td>55000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24584.0</td>\n",
       "      <td>69.8</td>\n",
       "      <td>43.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>679 Luna Roads\\r\\nGreggshire, VA 11650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>13.33</td>\n",
       "      <td>677.07</td>\n",
       "      <td>3</td>\n",
       "      <td>C3</td>\n",
       "      <td>HR Specialist</td>\n",
       "      <td>10</td>\n",
       "      <td>3</td>\n",
       "      <td>86788.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>25757.0</td>\n",
       "      <td>100.6</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1726 Cooper Passage Suite 129\\r\\nNorth Deniseb...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>18000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>5.32</td>\n",
       "      <td>542.07</td>\n",
       "      <td>1</td>\n",
       "      <td>A1</td>\n",
       "      <td>Software Development Engineer</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>125000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4178.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1008 Erika Vista Suite 748\\r\\nEast Stephanie, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>11.14</td>\n",
       "      <td>426.47</td>\n",
       "      <td>2</td>\n",
       "      <td>B2</td>\n",
       "      <td>Office Depot</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>46000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>11.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13425.0</td>\n",
       "      <td>64.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>USCGC Nunez\\r\\nFPO AE 30723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>18900.0</td>\n",
       "      <td>60</td>\n",
       "      <td>10.99</td>\n",
       "      <td>410.84</td>\n",
       "      <td>2</td>\n",
       "      <td>B3</td>\n",
       "      <td>Application Architect</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>103000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18637.0</td>\n",
       "      <td>32.9</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>USCGC Tran\\r\\nFPO AP 22690</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>26300.0</td>\n",
       "      <td>36</td>\n",
       "      <td>16.29</td>\n",
       "      <td>928.40</td>\n",
       "      <td>3</td>\n",
       "      <td>C5</td>\n",
       "      <td>Regado Biosciences</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>115000.0</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22171.0</td>\n",
       "      <td>82.4</td>\n",
       "      <td>37.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3390 Luis Rue\\r\\nMauricestad, VA 00813</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   loan_amnt  term  int_rate  installment  grade sub_grade  \\\n",
       "0    10000.0    36     11.44       329.48      2        B4   \n",
       "1     8000.0    36     11.99       265.68      2        B5   \n",
       "2    15600.0    36     10.49       506.97      2        B3   \n",
       "3     7200.0    36      6.49       220.65      1        A2   \n",
       "4    24375.0    60     17.27       609.33      3        C5   \n",
       "5    20000.0    36     13.33       677.07      3        C3   \n",
       "6    18000.0    36      5.32       542.07      1        A1   \n",
       "7    13000.0    36     11.14       426.47      2        B2   \n",
       "8    18900.0    60     10.99       410.84      2        B3   \n",
       "9    26300.0    36     16.29       928.40      3        C5   \n",
       "\n",
       "                       emp_title emp_length  home_ownership  annual_inc  ...  \\\n",
       "0                      Marketing         10               0    117000.0  ...   \n",
       "1                Credit analyst          4                3     65000.0  ...   \n",
       "2                   Statistician        0.6               0     43057.0  ...   \n",
       "3                Client Advocate         6                0     54000.0  ...   \n",
       "4        Destiny Management Inc.         9                3     55000.0  ...   \n",
       "5                  HR Specialist         10               3     86788.0  ...   \n",
       "6  Software Development Engineer         2                3    125000.0  ...   \n",
       "7                   Office Depot         10               0     46000.0  ...   \n",
       "8          Application Architect         10               0    103000.0  ...   \n",
       "9             Regado Biosciences         3                3    115000.0  ...   \n",
       "\n",
       "   open_acc pub_rec  revol_bal revol_util total_acc  initial_list_status  \\\n",
       "0      16.0     0.0    36369.0       41.8      25.0                    1   \n",
       "1      17.0     0.0    20131.0       53.3      27.0                    0   \n",
       "2      13.0     0.0    11987.0       92.2      26.0                    0   \n",
       "3       6.0     0.0     5472.0       21.5      13.0                    0   \n",
       "4      13.0     0.0    24584.0       69.8      43.0                    0   \n",
       "5       8.0     0.0    25757.0      100.6      23.0                    0   \n",
       "6       8.0     0.0     4178.0        4.9      25.0                    0   \n",
       "7      11.0     0.0    13425.0       64.5      15.0                    0   \n",
       "8      13.0     0.0    18637.0       32.9      40.0                    1   \n",
       "9      13.0     0.0    22171.0       82.4      37.0                    0   \n",
       "\n",
       "  application_type  mort_acc  pub_rec_bankruptcies  \\\n",
       "0                1       0.0                   0.0   \n",
       "1                1       3.0                   0.0   \n",
       "2                1       0.0                   0.0   \n",
       "3                1       0.0                   0.0   \n",
       "4                1       1.0                   0.0   \n",
       "5                1       4.0                   0.0   \n",
       "6                1       3.0                   0.0   \n",
       "7                1       0.0                   0.0   \n",
       "8                1       3.0                   0.0   \n",
       "9                1       1.0                   0.0   \n",
       "\n",
       "                                             address  \n",
       "0     0174 Michelle Gateway\\r\\nMendozaberg, OK 22690  \n",
       "1  1076 Carney Fort Apt. 347\\r\\nLoganmouth, SD 05113  \n",
       "2  87025 Mark Dale Apt. 269\\r\\nNew Sabrina, WV 05113  \n",
       "3            823 Reid Ford\\r\\nDelacruzside, MA 00813  \n",
       "4             679 Luna Roads\\r\\nGreggshire, VA 11650  \n",
       "5  1726 Cooper Passage Suite 129\\r\\nNorth Deniseb...  \n",
       "6  1008 Erika Vista Suite 748\\r\\nEast Stephanie, ...  \n",
       "7                        USCGC Nunez\\r\\nFPO AE 30723  \n",
       "8                         USCGC Tran\\r\\nFPO AP 22690  \n",
       "9             3390 Luis Rue\\r\\nMauricestad, VA 00813  \n",
       "\n",
       "[10 rows x 27 columns]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
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