Hands-On Exploratory Data Analysis with Python

Implementing a multiple linear regression model

When a dependent variable relies on several independent variables, the relationship can be captured using multiple linear regression. Multiple linear regression can be viewed as an extension of simple linear regression. When it comes to implementing multiple linear regression using sklearn, there is not much difference between simple and multiple linear regression:

1. Simply include the extra columns in the X variable and run the code. So, let's include the additional columns for the X variable and follow the same code.
2. Remember, a two-dimensional linear regression model is a straight line; it is a plane in three dimensions, and a hyperplane in over three dimensions:

# Preparing the dataX = ...