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

Defining an aggregation

In this recipe, we examine the flights dataset and perform the simplest aggregation involving only a single grouping column, a single aggregating column, and a single aggregating function. We will find the average arrival delay for each airline. pandas has different syntaxes to create an aggregation, and this recipe will show them.

How to do it…

  1. Read in the flights dataset:
    >>> import pandas as pd
    >>> import numpy as np
    >>> flights = pd.read_csv('data/flights.csv')
    >>> flights.head()
    0      1    1        4  ...      65.0        0         0
    1      1    1        4  ...     -13.0        0         0
    2      1    1        4  ...      35.0        0         0
    3      1    1        4  ...      -7.0        0         0
    4      1    1        4  ...      39.0        0         0
    
  2. Define the grouping columns (AIRLINE), aggregating columns (ARR_DELAY), and aggregating functions (mean). Place...