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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 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

Selecting data with both integers and labels

The .iloc and .loc indexers each select data by either integer or label location but are not able to handle a combination of both input types at the same time. In earlier versions of pandas, another indexer, .ix, was available to select data by both integer and label location. While this conveniently worked for those specific situations, it was ambiguous by nature and was a source of confusion for many pandas users. The .ix indexer has subsequently been deprecated and thus should be avoided.

Getting ready

Before the .ix deprecation, it was possible to select the first five rows and the columns of the college dataset from UGDS_WHITE through UGDS_UNKN using college.ix[:5, 'UGDS_WHITE...

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