8 Top Books on Data Cleaning and Feature Engineering

Data preparation is the transformation of raw data into a form that is more appropriate for modeling.

It is a challenging topic to discuss as the data differs in form, type, and structure from project to project.

Nevertheless, there are common data preparation tasks across projects. It is a huge field of study and goes by many names, such as “data cleaning,” “data wrangling,” “data preprocessing,” “feature engineering,” and more. Some of these are distinct data preparation tasks, and some of the terms are used to describe the entire data preparation process.

Even though it is a challenging topic to discuss, there are a number of books on the topic.

In this post, you will discover the top books on data cleaning, data preparation, feature engineering, and related topics.

Let’s get started.

Kick-start your project with my new book Data Preparation for Machine Learning, including step-by-step tutorials and the Python source code files for all examples.

Overview

The focus here is on data preparation for tabular data, e.g. data in the form of a table with rows and columns as it looks in an excel spreadsheet.

Data preparation is an important topic for all data types, although specialty
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