Key Features

Think about your data intelligently and ask the right questions

Master data cleaning techniques using hands-on examples belonging to diverse domains

Work with detailed, commented, well-tested code samples in Python and R

 Book Description

In data science, data analysis, or machine learning, most of the effort needed to achieve your actual purpose lies in cleaning your data. Using Python, R, and command-line tools, you will learn the essential cleaning steps performed in every production data science or data analysis pipeline. This book not only teaches you data preparation but also what questions you should ask of your data.

The book dives into the practical application of tools and techniques needed for data ingestion, anomaly detection, value imputation, and feature engineering. It also offers long-form exercises at the end of each chapter to practice the skills acquired.