3 years ago

Category: machine-learning

by In this post, you will learn about how to use Python's Sklearn SimpleImputer for imputing/replacing numerical and categorical missing data using different strategies.

Here is the link, Replace missing values with mean, median and mode. Handling missing values is a key part of data preprocessing and hence, it is of utmost importance for data scientists/machine learning engineers to learn different techniques in relation imputing / replacing numerical or categorical missing values with appropriate value based on appropriate strategies.

Here is the Python code sample representing the usage of SimpleImputor for replacing numerical missing value with the mean.