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

Grouping with a custom aggregation function

pandas provides a number of aggregation functions to use with the groupby object. At some point, you may need to write your own custom user-defined function that does not exist in pandas or NumPy.

In this recipe, we use the college dataset to calculate the mean and standard deviation of the undergraduate student population per state. We then use this information to find the maximum number of standard deviations from the mean that any single population value is per state.

How to do it…

  1. Read in the college dataset, and find the mean and standard deviation of the undergraduate population by state:
    >>> college = pd.read_csv('data/college.csv')
    >>> (college
    ...     .groupby('STABBR')
    ...     ['UGDS']
    ...     .agg(['mean', 'std'])
    ...     .round(0)
    ... )
              mean      std
    STABBR                 
    AK      2493.0   4052.0
    AL     ...