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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 FREE CHAPTER 2. Essential DataFrame Operations 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

Tidying when multiple variables are stored as column values

Tidy datasets must have a single column for each variable. Occasionally, multiple variable names are placed in a single column with their corresponding value placed in another. The general format for this kind of messy data is as follows:

In this example, the first and last three rows represent two distinct observations that should each be rows. The data needs to be pivoted such that it ends up like this:

Getting ready

In this recipe, we identify the column containing the improperly structured variables and pivot it to create tidy data.

How to do it...

...
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