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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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Toc

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

Slicing rows lazily

The previous recipes in this chapter showed how the .iloc and .loc indexers were used to select subsets of both Series and DataFrames in either dimension. A shortcut to select the rows exists with just the indexing operator itself. This is just a shortcut to show additional features of pandas, but the primary function of the indexing operator is actually to select DataFrame columns. If you want to select rows, it is best to use .iloc or .loc, as they are unambiguous.

Getting ready

In this recipe, we pass a slice object to both the Series and DataFrame indexing operators.

How to do it...

...
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