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)

Slicing rows lazily

The previous recipes in this chapter showed how the .iloc and .loc indexers were used to select subsets of both Series and DataFrames in either dimension. A shortcut to select the rows exists with just the indexing operator itself. This is just a shortcut to show additional features of pandas, but the primary function of the indexing operator is actually to select DataFrame columns. If you want to select rows, it is best to use .iloc or .loc, as they are unambiguous.

Getting ready

In this recipe, we pass a slice object to both the Series and DataFrame indexing operators.

How to do it...

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