Feature Transformation for Multiple Linear Regression in Python

Data processing and transformation is an iterative process and in a way, it can never be'perfect'. Because as we gain more understanding on the dataset, such as the inner relationships between target variable and features, or the business context, we think of new ways to deal with them. Recently I started working on media mix models and some predictive models utilizing multiple linear regression. In this post, I will introduce the thought process and different ways to deal with variables for modeling purpose. I will use King County house price data set (a modified version for more fun) as an example.