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

Inverting stacked data

DataFrames have two similar methods, .stack and .melt, to convert horizontal column names into vertical column values. DataFrames can invert these two operations with the .unstack and .pivot methods, respectively. .stack and .unstack are methods that allow control over only the column and row indexes, while .melt and .pivot give more flexibility to choose which columns are reshaped.

In this recipe, we will call .stack and .melt on a dataset and promptly invert the operation with the .unstack and .pivot methods.

How to do it…

  1. Read in the college dataset with the institution name as the index, and with only the undergraduate race columns:
    >>> def usecol_func(name):
    ...     return 'UGDS_' in name or name == 'INSTNM'
    >>> college = pd.read_csv('data/college.csv',
    ...     index_col='INSTNM',
    ...     usecols=usecol_func)
    >>> college
                  UGDS_WHITE  UGDS_BLACK...