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
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16
Index

Examining the Index object

As was discussed previously, each axis of a Series and a DataFrame has an Index object that labels the values. There are many different types of Index objects, but they all share common behavior. All Index objects, except for the MultiIndex, are single-dimensional data structures that combine the functionality of Python sets and NumPy ndarrays.

In this recipe, we will examine the column index of the college dataset and explore much of its functionality.

How to do it…

  1. Read in the college dataset, and create a variable columns that holds the column index:
    >>> import pandas as pd
    >>> import numpy as np
    >>> college = pd.read_csv("data/college.csv")
    >>> columns = college.columns
    >>> columns
    Index(['INSTNM', 'CITY', 'STABBR', 'HBCU', 'MENONLY', 'WOMENONLY', 'RELAFFIL',
           'SATVRMID&apos...