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Pandas Cookbook

You're reading from   Pandas Cookbook Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python

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Product type Paperback
Published in Oct 2017
Publisher Packt
ISBN-13 9781784393878
Length 532 pages
Edition 1st Edition
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Author (1):
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Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
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Table of Contents (12) Chapters Close

Preface 1. Pandas Foundations 2. Essential DataFrame Operations FREE CHAPTER 3. Beginning Data Analysis 4. Selecting Subsets of Data 5. Boolean Indexing 6. Index Alignment 7. Grouping for Aggregation, Filtration, and Transformation 8. Restructuring Data into a Tidy Form 9. Combining Pandas Objects 10. Time Series Analysis 11. Visualization with Matplotlib, Pandas, and Seaborn

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, each expression must be wrapped in parentheses or an error will be raised.

Getting ready

Constructing a precise filter for your dataset might have you combining multiple boolean expressions together to extract an exact subset. In this recipe, we construct multiple boolean expressions before combining them together 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.

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