Welcome to Home Credit Default Risk EDA. The data used here was made available on the kaggle website 5 years ago for a competition.Below you can see the competition description:

'Home Credit strives to broaden financial inclusion for the unbanked population by providing a positive and safe borrowing experience. In order to make sure this underserved population has a positive loan experience, Home Credit makes use of a variety of alternative data--including telco and transactional information--to predict their clients' repayment abilities.

While Home Credit is currently using various statistical and machine learning methods to make these predictions, they're challenging Kagglers to help them unlock the full potential of their data. Doing so will ensure that clients capable of repayment are not rejected and that loans are given with a principal, maturity, and repayment calendar that will empower their clients to be successful.'

The goal of this project is to make an exploratory analysis of the data (EDA)

1-Exploratory analysis of the data(EDA)

For this step, I'll answer a few the question:

1-What is the customer's socioeconomic profile?