Assembling an imputation pipeline with Feature-engine

Feature-engine is an open source Python library that allows us to easily implement different imputation techniques for different feature subsets. Often, our datasets contain a mix of numerical and categorical variables, with few or many missing values. Therefore, we normally perform different imputation techniques on different variables, depending on the nature of the variable and the machine learning algorithm we want to build. With Feature-engine, we can assemble multiple imputation techniques in a single step, and in this recipe, we will learn how to do this.

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