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)

Selecting data with both integers and labels

The .iloc and .loc indexers each select data by either integer or label location but are not able to handle a combination of both input types at the same time. In earlier versions of pandas, another indexer, .ix, was available to select data by both integer and label location. While this conveniently worked for those specific situations, it was ambiguous by nature and was a source of confusion for many pandas users. The .ix indexer has subsequently been deprecated and thus should be avoided.

Getting ready

Before the .ix deprecation, it was possible to select the first five rows and the columns of the college dataset from UGDS_WHITE through UGDS_UNKN using college.ix[:5, 'UGDS_WHITE...