Introduction to Exploratory Data Analysis (EDA)

The exploratory data analysis (EDA) is an essential part in building any of machine learning models. In the EDA, you explore the data using the statistical methods (or concepts) to extract useful insights out of it.

Usually, the EDA involves the following steps in the process:

1. Data Source
2. Data Cleaning
3. Univariate (or, One Variable) Analysis
4. Bivariate (or, Two Variables) Analysis
5. Derived Metrics (Creating more variables or columns)

Let's discuss each topic in detail.