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Lending Club Analysis

This is a visualization for the dataset containing acceptance/rejection of loan applications based on various factors.
Created on February 19|Last edited on February 19

Accepted DataFrame


plot for fully paid and charged off
050k100k150k200k250k01000200030004000500060007000
plot for fully paid and charged offannual incomeloan_status
loan_status vs annual income < 25k
195019601970198019902000201001000200030004000500060007000
loan_status vs annual income < 25kearliest_cr_lineloan_status
Annual income distribution < 25k
050k100k150k200k250k010μ12μ14μ
Annual income distribution < 25kannual incomecount


The above graphs show us annual income distribution and earliest credit line distribution. In the accepted data frame the no of fully paid and charged-off loans are high for about 50k of loan while most of the applicants are having annual income of about 50k.





The above graphs show us the distribution of various categorical features. Accepted loan applications from various states. year of experience the applicant have and various factors are shown in accepted data frame



Rejected DataFrame:




The above analysis shows us that there is a surge in applications getting rejected in recent years. Also, applications having < 1-year experience are more likely to get rejected. Applications from CA are getting rejected more compared to other states.