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 variable values as column names with melt

Like most large Python libraries, pandas has many different ways to accomplish the same task--the differences usually being readability and performance. Pandas contains a DataFrame method named melt that works similarly to the stack method described in the previous recipe but gives a bit more flexibility.

Before pandas version 0.20, melt was only provided as a function that had to be accessed with pd.melt. Pandas is still an evolving library and you need to expect changes with each new version. Pandas has been making a push to move all functions that only operate on DataFrames to methods, such as they did with melt. This is the preferred way to use melt and the way this recipe uses it. Check the What's New part of the pandas documentation to stay up to date with all the changes (http://bit.ly/2xzXIhG).
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