LGBM-Model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the basic libraries\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Datasets/Loan_V2.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>id</th>\n",
       "      <th>member_id</th>\n",
       "      <th>loan_amnt</th>\n",
       "      <th>funded_amnt</th>\n",
       "      <th>funded_amnt_inv</th>\n",
       "      <th>term</th>\n",
       "      <th>int_rate</th>\n",
       "      <th>grade</th>\n",
       "      <th>sub_grade</th>\n",
       "      <th>...</th>\n",
       "      <th>dti</th>\n",
       "      <th>issue_month</th>\n",
       "      <th>issue_year</th>\n",
       "      <th>inc_ratio</th>\n",
       "      <th>categorized_inc_ratio</th>\n",
       "      <th>categorised_int_rate_perc</th>\n",
       "      <th>categorised_emp_length</th>\n",
       "      <th>categorised_annual_inc</th>\n",
       "      <th>categorised_dti</th>\n",
       "      <th>categorised_loan_amnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>1077501</td>\n",
       "      <td>1296599</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>4975.0</td>\n",
       "      <td>36</td>\n",
       "      <td>10.65</td>\n",
       "      <td>B</td>\n",
       "      <td>B2</td>\n",
       "      <td>...</td>\n",
       "      <td>27.65</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2011</td>\n",
       "      <td>20.833333</td>\n",
       "      <td>High</td>\n",
       "      <td>Medium</td>\n",
       "      <td>Senior Level</td>\n",
       "      <td>Low</td>\n",
       "      <td>Very High</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1077430</td>\n",
       "      <td>1314167</td>\n",
       "      <td>2500</td>\n",
       "      <td>2500</td>\n",
       "      <td>2500.0</td>\n",
       "      <td>60</td>\n",
       "      <td>15.27</td>\n",
       "      <td>C</td>\n",
       "      <td>C4</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2011</td>\n",
       "      <td>8.333333</td>\n",
       "      <td>Low</td>\n",
       "      <td>Very High</td>\n",
       "      <td>Entry Level</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>1077175</td>\n",
       "      <td>1313524</td>\n",
       "      <td>2400</td>\n",
       "      <td>2400</td>\n",
       "      <td>2400.0</td>\n",
       "      <td>36</td>\n",
       "      <td>15.96</td>\n",
       "      <td>C</td>\n",
       "      <td>C5</td>\n",
       "      <td>...</td>\n",
       "      <td>8.72</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2011</td>\n",
       "      <td>19.588639</td>\n",
       "      <td>High</td>\n",
       "      <td>Very High</td>\n",
       "      <td>Senior Level</td>\n",
       "      <td>Low</td>\n",
       "      <td>Medium</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5</td>\n",
       "      <td>1075269</td>\n",
       "      <td>1311441</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>36</td>\n",
       "      <td>7.90</td>\n",
       "      <td>A</td>\n",
       "      <td>A4</td>\n",
       "      <td>...</td>\n",
       "      <td>11.20</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2011</td>\n",
       "      <td>13.888889</td>\n",
       "      <td>Medium</td>\n",
       "      <td>Low</td>\n",
       "      <td>Junior Level</td>\n",
       "      <td>Low</td>\n",
       "      <td>Medium</td>\n",
       "      <td>Low</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6</td>\n",
       "      <td>1069639</td>\n",
       "      <td>1304742</td>\n",
       "      <td>7000</td>\n",
       "      <td>7000</td>\n",
       "      <td>7000.0</td>\n",
       "      <td>60</td>\n",
       "      <td>15.96</td>\n",
       "      <td>C</td>\n",
       "      <td>C5</td>\n",
       "      <td>...</td>\n",
       "      <td>23.51</td>\n",
       "      <td>Dec</td>\n",
       "      <td>2011</td>\n",
       "      <td>14.892350</td>\n",
       "      <td>Medium</td>\n",
       "      <td>Very High</td>\n",
       "      <td>Middle Level</td>\n",
       "      <td>Medium</td>\n",
       "      <td>Very High</td>\n",
       "      <td>Medium</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0       id  member_id  loan_amnt  funded_amnt  funded_amnt_inv  \\\n",
       "0           0  1077501    1296599       5000         5000           4975.0   \n",
       "1           1  1077430    1314167       2500         2500           2500.0   \n",
       "2           2  1077175    1313524       2400         2400           2400.0   \n",
       "3           5  1075269    1311441       5000         5000           5000.0   \n",
       "4           6  1069639    1304742       7000         7000           7000.0   \n",
       "\n",
       "   term  int_rate grade sub_grade  ...    dti issue_month  issue_year  \\\n",
       "0    36     10.65     B        B2  ...  27.65         Dec        2011   \n",
       "1    60     15.27     C        C4  ...   1.00         Dec        2011   \n",
       "2    36     15.96     C        C5  ...   8.72         Dec        2011   \n",
       "3    36      7.90     A        A4  ...  11.20         Dec        2011   \n",
       "4    60     15.96     C        C5  ...  23.51         Dec        2011   \n",
       "\n",
       "   inc_ratio categorized_inc_ratio categorised_int_rate_perc  \\\n",
       "0  20.833333                  High                    Medium   \n",
       "1   8.333333                   Low                 Very High   \n",
       "2  19.588639                  High                 Very High   \n",
       "3  13.888889                Medium                       Low   \n",
       "4  14.892350                Medium                 Very High   \n",
       "\n",
       "  categorised_emp_length categorised_annual_inc  categorised_dti  \\\n",
       "0           Senior Level                    Low        Very High   \n",
       "1            Entry Level                    Low              Low   \n",
       "2           Senior Level                    Low           Medium   \n",
       "3           Junior Level                    Low           Medium   \n",
       "4           Middle Level                 Medium        Very High   \n",
       "\n",
       "  categorised_loan_amnt  \n",
       "0                   Low  \n",
       "1                   Low  \n",
       "2                   Low  \n",
       "3                   Low  \n",
       "4                Medium  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 34460 entries, 0 to 34459\n",
      "Data columns (total 28 columns):\n",
      " #   Column                     Non-Null Count  Dtype  \n",
      "---  ------                     --------------  -----  \n",
      " 0   Unnamed: 0                 34460 non-null  int64  \n",
      " 1   id                         34460 non-null  int64  \n",
      " 2   member_id                  34460 non-null  int64  \n",
      " 3   loan_amnt                  34460 non-null  int64  \n",
      " 4   funded_amnt                34460 non-null  int64  \n",
      " 5   funded_amnt_inv            34460 non-null  float64\n",
      " 6   term                       34460 non-null  int64  \n",
      " 7   int_rate                   34460 non-null  float64\n",
      " 8   grade                      34460 non-null  object \n",
      " 9   sub_grade                  34460 non-null  object \n",
      " 10  emp_length                 34460 non-null  int64  \n",
      " 11  home_ownership             34460 non-null  object \n",
      " 12  annual_inc                 34460 non-null  float64\n",
      " 13  verification_status        34460 non-null  object \n",
      " 14  issue_d                    34460 non-null  object \n",
      " 15  loan_status                34460 non-null  object \n",
      " 16  purpose                    34460 non-null  object \n",
      " 17  addr_state                 34460 non-null  object \n",
      " 18  dti                        34460 non-null  float64\n",
      " 19  issue_month                34460 non-null  object \n",
      " 20  issue_year                 34460 non-null  int64  \n",
      " 21  inc_ratio                  34460 non-null  float64\n",
      " 22  categorized_inc_ratio      34460 non-null  object \n",
      " 23  categorised_int_rate_perc  34460 non-null  object \n",
      " 24  categorised_emp_length     34460 non-null  object \n",
      " 25  categorised_annual_inc     34460 non-null  object \n",
      " 26  categorised_dti            34460 non-null  object \n",
      " 27  categorised_loan_amnt      34460 non-null  object \n",
      "dtypes: float64(5), int64(8), object(15)\n",
      "memory usage: 7.4+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(columns='Unnamed: 0',axis=1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 34460 entries, 0 to 34459\n",
      "Data columns (total 27 columns):\n",
      " #   Column                     Non-Null Count  Dtype  \n",
      "---  ------                     --------------  -----  \n",
      " 0   id                         34460 non-null  int64  \n",
      " 1   member_id                  34460 non-null  int64  \n",
      " 2   loan_amnt                  34460 non-null  int64  \n",
      " 3   funded_amnt                34460 non-null  int64  \n",
      " 4   funded_amnt_inv            34460 non-null  float64\n",
      " 5   term                       34460 non-null  int64  \n",
      " 6   int_rate                   34460 non-null  float64\n",
      " 7   grade                      34460 non-null  object \n",
      " 8   sub_grade                  34460 non-null  object \n",
      " 9   emp_length                 34460 non-null  int64  \n",
      " 10  home_ownership             34460 non-null  object \n",
      " 11  annual_inc                 34460 non-null  float64\n",
      " 12  verification_status        34460 non-null  object \n",
      " 13  issue_d                    34460 non-null  object \n",
      " 14  loan_status                34460 non-null  object \n",
      " 15  purpose                    34460 non-null  object \n",
      " 16  addr_state                 34460 non-null  object \n",
      " 17  dti                        34460 non-null  float64\n",
      " 18  issue_month                34460 non-null  object \n",
      " 19  issue_year                 34460 non-null  int64  \n",
      " 20  inc_ratio                  34460 non-null  float64\n",
      " 21  categorized_inc_ratio      34460 non-null  object \n",
      " 22  categorised_int_rate_perc  34460 non-null  object \n",
      " 23  categorised_emp_length     34460 non-null  object \n",
      " 24  categorised_annual_inc     34460 non-null  object \n",
      " 25  categorised_dti            34460 non-null  object \n",
      " 26  categorised_loan_amnt      34460 non-null  object \n",
      "dtypes: float64(5), int64(7), object(15)\n",
      "memory usage: 7.1+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_col = df.select_dtypes(include='object')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 34460 entries, 0 to 34459\n",
      "Data columns (total 15 columns):\n",
      " #   Column                     Non-Null Count  Dtype \n",
      "---  ------                     --------------  ----- \n",
      " 0   grade                      34460 non-null  object\n",
      " 1   sub_grade                  34460 non-null  object\n",
      " 2   home_ownership             34460 non-null  object\n",
      " 3   verification_status        34460 non-null  object\n",
      " 4   issue_d                    34460 non-null  object\n",
      " 5   loan_status                34460 non-null  object\n",
      " 6   purpose                    34460 non-null  object\n",
      " 7   addr_state                 34460 non-null  object\n",
      " 8   issue_month                34460 non-null  object\n",
      " 9   categorized_inc_ratio      34460 non-null  object\n",
      " 10  categorised_int_rate_perc  34460 non-null  object\n",
      " 11  categorised_emp_length     34460 non-null  object\n",
      " 12  categorised_annual_inc     34460 non-null  object\n",
      " 13  categorised_dti            34460 non-null  object\n",
      " 14  categorised_loan_amnt      34460 non-null  object\n",
      "dtypes: object(15)\n",
      "memory usage: 3.9+ MB\n"
     ]
    }
   ],
   "source": [
    "cat_col.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_col = df.select_dtypes(include=['int','float'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 34460 entries, 0 to 34459\n",
      "Data columns (total 12 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   id               34460 non-null  int64  \n",
      " 1   member_id        34460 non-null  int64  \n",
      " 2   loan_amnt        34460 non-null  int64  \n",
      " 3   funded_amnt      34460 non-null  int64  \n",
      " 4   funded_amnt_inv  34460 non-null  float64\n",
      " 5   term             34460 non-null  int64  \n",
      " 6   int_rate         34460 non-null  float64\n",
      " 7   emp_length       34460 non-null  int64  \n",
      " 8   annual_inc       34460 non-null  float64\n",
      " 9   dti              34460 non-null  float64\n",
      " 10  issue_year       34460 non-null  int64  \n",
      " 11  inc_ratio        34460 non-null  float64\n",
      "dtypes: float64(5), int64(7)\n",
      "memory usage: 3.2 MB\n"
     ]
    }
   ],
   "source": [
    "num_col.info()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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