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Group: Abhishek Jain & Vipul Sharma

Group Representative : Abhishek Jain

Group Member : Vipul Sharma

Objectives:

  • Lending club is the largest online loan marketplace, facilitating personal loans, business loans, and financing of medical procedures. Borrowers can easily access lower interest rate loans through a fast online interface. .

  • We need to identify the risky loan applicants so that such loans can be reduced thereby cutting down the amount of credit loss. Identification of such applicants using EDA is the aim of this case study.

  • In other words, the company wants to understand the driving factors (or driver variables) behind loan default, i.e. the variables which are strong indicators of default.

# importing libariries required

import pandas as pd
import numpy as np
import jovian
import matplotlib.pyplot as plt
import seaborn as sns
# importing the csv file(data_set)

path=r'F:\upGrad\PGDM\Main_Course\Statistics\Lending Club Case Study\loan'
data = pd.read_csv(path+ r'\loan.csv', encoding = "ISO-8859-1")
data.shape
(39717, 111)