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Pandas 1.x Cookbook

Pandas 1.x Cookbook - Second Edition

By : Matthew Harrison, Theodore Petrou
4.5 (28)
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Pandas 1.x Cookbook

Pandas 1.x Cookbook

4.5 (28)
By: Matthew 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)
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15
Other Books You May Enjoy
16
Index

Selecting the largest of each group by sorting

One of the most basic and common operations to perform during data analysis is to select rows containing the largest value of some column within a group. For instance, this would be like finding the highest-rated film of each year or the highest-grossing film by content rating. To accomplish this task, we need to sort the groups as well as the column used to rank each member of the group, and then extract the highest member of each group.

In this recipe, we will find the highest-rated film of each year.

How to do it…

  1. Read in the movie dataset and slim it down to just the three columns we care about: movie_title, title_year, and imdb_score:
    >>> movie = pd.read_csv("data/movie.csv")
    >>> movie[["movie_title", "title_year", "imdb_score"]]
                                         movie_title  ...
    0                                         Avatar  ...
    1 ...
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