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

Removing the MultiIndex after grouping

Inevitably, when using groupby, you will create a MultiIndex. MultiIndexes can happen in both the index and the columns. DataFrames with MultiIndexes are more difficult to navigate and occasionally have confusing column names as well.

In this recipe, we perform an aggregation with the .groupby method to create a DataFrame with a MultiIndex for the rows and columns. Then, we manipulate the index so that it has a single level and the column names are descriptive.

How to do it…

  1. Read in the flights dataset, write a statement to find the total and average miles flown, and the maximum and minimum arrival delay for each airline for each weekday:
    >>> flights = pd.read_csv('data/flights.csv')
    >>> airline_info = (flights
    ...     .groupby(['AIRLINE', 'WEEKDAY'])
    ...     .agg({'DIST':['sum', 'mean'],
    ...           'ARR_DELAY':[&apos...