Machine Learning with scikit-learn Quick Start Guide

Missing values

Another constraint with scikit-learn is that it cannot handle data with missing values. Therefore, we must check whether our dataset has any missing values in any of the columns to begin with. We can do this by using the following code:

#Checking every column for missing valuesdf.isnull().any()

This produces this output:

Here we note that every column has some amount of missing values.

Missing values can be handled in a variety of ways, such as the following:

• Median imputation
• Mean imputation
• Filling them with the majority value

The amount of techniques is quite large and varies depending on the nature of your dataset. ...