Client Payment Behavior Analysis

This repository analyzes client payment behavior using the CREDIT dataset , focusing on factors like age, gender, income, and housing type to compare defaulters vs. non-defaulters.

Key Features

• Data Preprocessing: Categorizing age (YEARS_BIRTH_CATEGORY), handling missing values, and outliers.
• Exploratory Data Analysis (EDA): Visualizing payment behavior based on gender, age, income, and housing type.

Visualizations

• Bar plots and pie charts for client demographics.
• Box plots for income comparisons.

Requirements

• Python 3.x
• Libraries: pandas, matplotlib, seaborn, scipy