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Pandas 1.x Cookbook

Pandas 1.x Cookbook

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
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16
Index

Constructing multiple Boolean conditions

In Python, Boolean expressions use the built-in logical operators and, or, and not. These keywords do not work with Boolean indexing in pandas and are respectively replaced with &, |, and ~. Additionally, when combining expressions, each expression must be wrapped in parentheses, or an error will be raised (due to operator precedence).

Constructing a filter for your dataset might require combining multiple Boolean expressions together to pull out the rows you need. In this recipe, we construct multiple Boolean expressions before combining them to find all the movies that have an imdb_score greater than 8, a content_rating of PG-13, and a title_year either before 2000 or after 2009.

How to do it…

  1. Load in the movie dataset and set the title as the index:
    >>> movie = pd.read_csv(
    ...     "data/movie.csv", index_col="movie_title"
    ... )
    
  2. Create a variable to hold each...

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