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

Selecting with Booleans, integer location, and labels

Previously, we covered a wide range of recipes on selecting different subsets of data through the .iloc and .loc attributes. Both of these select rows and columns simultaneously by either integer location or label.

In this recipe, we will filter both rows and columns with the .iloc and .loc attributes.

How to do it…

  1. Read in the movie dataset, set the index as the title, and then create a Boolean array matching all movies with a content rating of G and an IMDB score less than 4:
    >>> movie = pd.read_csv(
    ...     "data/movie.csv", index_col="movie_title"
    ... )
    >>> c1 = movie["content_rating"] == "G"
    >>> c2 = movie["imdb_score"] < 4
    >>> criteria = c1 & c2
    
  2. Let's first pass these criteria to .loc to filter the rows:
    >>> movie_loc = movie.loc[criteria]
    >>> movie_loc...