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Pandas 1.x Cookbook

You're reading from   Pandas 1.x Cookbook Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python

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Product type Paperback
Published in Feb 2020
Publisher Packt
ISBN-13 9781839213106
Length 626 pages
Edition 2nd Edition
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Authors (2):
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Theodore Petrou Theodore Petrou
Author Profile Icon Theodore Petrou
Theodore Petrou
Matthew Harrison Matthew Harrison
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Matthew Harrison
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Toc

Table of Contents (17) Chapters Close

Preface 1. Pandas Foundations 2. Essential DataFrame Operations FREE CHAPTER 3. Creating and Persisting DataFrames 4. Beginning Data Analysis 5. Exploratory Data Analysis 6. Selecting Subsets of Data 7. Filtering Rows 8. Index Alignment 9. Grouping for Aggregation, Filtration, and Transformation 10. Restructuring Data into a Tidy Form 11. Combining Pandas Objects 12. Time Series Analysis 13. Visualization with Matplotlib, Pandas, and Seaborn 14. Debugging and Testing Pandas 15. Other Books You May Enjoy
16. Index

Producing Cartesian products

Whenever a Series or DataFrame operates with another Series or DataFrame, the indexes (both the row index and column index) of each object align first before any operation begins. This index alignment happens behind the scenes and can be very surprising for those new to pandas. This alignment always creates a Cartesian product between the indexes unless the indexes are identical.

A Cartesian product is a mathematical term that usually appears in set theory. A Cartesian product between two sets is all the combinations of pairs of both sets. For example, the 52 cards in a standard playing card deck represent a Cartesian product between the 13 ranks (A, 2, 3,…, Q, K) and the four suits.

Producing a Cartesian product isn't always the intended outcome, but it's essential to be aware of how and when it occurs so as to avoid unintended consequences. In this recipe, two Series with overlapping but non-identical indexes are added together...

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