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Pandas Cookbook

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

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Product type Paperback
Published in Oct 2024
Publisher Packt
ISBN-13 9781836205876
Length 404 pages
Edition 3rd Edition
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Authors (2):
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William Ayd William Ayd
Author Profile Icon William Ayd
William Ayd
Matthew Harrison Matthew Harrison
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Matthew Harrison
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Toc

Table of Contents (13) Chapters Close

Preface 1. pandas Foundations FREE CHAPTER 2. Selection and Assignment 3. Data Types 4. The pandas I/O System 5. Algorithms and How to Apply Them 6. Visualization 7. Reshaping DataFrames 8. Group By 9. Temporal Data Types and Algorithms 10. General Usage and Performance Tips 11. The pandas Ecosystem 12. Index

Selection with a MultiIndex – A single level

A pd.MultiIndex is a subclass of a pd.Index that supports hierarchical labels. Depending on who you ask, this can be one of the best or one of the worst features of pandas. After reading this cookbook, I hope you consider it one of the best.

Much of the derision toward the pd.MultiIndex comes from the fact that the syntax used to select from it can easily become ambiguous, especially when using pd.DataFrame[]. The examples below exclusively use the pd.DataFrame.loc method and avoid pd.DataFrame[] to mitigate confusion.

How to do it

pd.MultiIndex.from_tuples can be used to construct a pd.MultiIndex from a list of tuples. In the following example, we create a pd.MultiIndex with two levels – first_name and last_name, sequentially. We will pair this alongside a very simple pd.Series:

index = pd.MultiIndex.from_tuples([
    ("John", "Smith"),
    ("John", "Doe"),
    (&quot...
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