Python Data Cleaning Cookbook

Preface

This book is a practical guide to data cleaning, broadly defined as all tasks necessary to prepare data for analysis. It is organized by the tasks usually completed during the data cleaning process: importing data, viewing data diagnostically, identifying outliers and unexpected values, imputing values, tidying data, and so on. Each recipe walks the reader from raw data through the completion of a specific data cleaning task.

There are already a number of very good pandas books. Unsurprisingly, there is some overlap between those texts and this one. However, the emphasis here is different. I focus as much on the why as on the how in this book.

Since pandas is still relatively new, the lessons I have learned about cleaning data have been ...