How to Handle Missing Data: Common Approaches Explained

Dealing with missing data is a crucial step in data analysis. Here's a common approach:

A. Filling in the missing data with the mean or median value

This method, known as mean/median imputation, replaces missing values with the average (mean) or the middle value (median) of the available data for that feature. It's simple but might distort data distribution, especially with large amounts of missing data.