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)

Tidying when multiple observational units are stored in the same table

It is generally easier to maintain data when each table contains information from a single observational unit. On the other hand, it can be easier to find insights when all data is in a single table, and in the case of machine learning, all data must be in a single table. The focus of tidy data is not on directly performing analysis. Rather, it is structuring the data so that analysis is easier further down the line, and when there are multiple observational units in one table, they may need to get separated into their own tables.

Getting ready

In this recipe, we use the movie dataset to identify the three observational units (movies, actors, and directors...