Book Image

Pandas Cookbook

By : Theodore Petrou
Book Image

Pandas Cookbook

By: Theodore Petrou

Overview of this book

This book will provide you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas 0.20. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands like one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter. Many advanced recipes combine several different features across the pandas 0.20 library to generate results.
Table of Contents (12 chapters)

Renaming axis levels for easy reshaping

Reshaping with the stack/unstack methods is far easier when each axis (index/column) level has a name. Pandas allows users to reference each axis level by integer location or by name. Since integer location is implicit and not explicit, you should consider using level names whenever possible. This advice follows from The Zen of Python (http://bit.ly/2xE83uC), a short list of guiding principles for Python of which the second one is Explicit is better than implicit.

Getting ready

When grouping or aggregating with multiple columns, the resulting pandas object will have multiple levels in one or both of the axes. In this recipe, we will name each level of each axis and then use the methods...