Book Image

Pandas 1.x Cookbook - Second Edition

By : Matt Harrison, Theodore Petrou
Book Image

Pandas 1.x Cookbook - Second Edition

By: Matt Harrison, Theodore Petrou

Overview of this book

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 as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter. This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. 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. Many advanced recipes combine several different features across the pandas library to generate results.
Table of Contents (17 chapters)
15
Other Books You May Enjoy
16
Index

Introduction

Filtering data from a dataset is one of the most common and basic operations. There are numerous ways to filter (or subset) data in pandas with Boolean indexing. Boolean indexing (also known as Boolean selection) can be a confusing term, but in pandas-land, it refers to selecting rows by providing a Boolean array, a pandas Series with the same index, but a True or False for each row. The name comes from NumPy, where similar filtering logic works, so while it is really a Series with Boolean values in it, it is also referred to as a Boolean array.

We will begin by creating Boolean Series and calculating statistics on them and then move on to creating more complex conditionals before using Boolean indexing in a wide variety of ways to filter data.