Describing the profile of a bank’s coustomer: Cleaning & EDA
In this project, as a first step, I did cleaned the non-sensical values. The dataset contains some non-sense numerical values and outliers. Also, it contained some typos in categorical variables. The second step, I started with the Exploratory Data Analyst of the cleanned dataset. There are some interesting features behind in the dataset. These were found with the statistical analysis (univariate).
Some Python’s packages used here: pandas, matplotlib and seaborn.