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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

Calculating weighted mean SAT scores per state with apply

The groupby object has four methods that accept a function (or functions) to perform a calculation on each group. These four methods are agg, filter, transform, and apply. Each of the first three of these methods has a very specific output that the function must return. agg must return a scalar value, filter must return a boolean, and transform must return a Series with the same length as the passed group. The apply method, however, may return a scalar value, a Series, or even a DataFrame of any shape, therefore making it very flexible. It is also called only once per group, which contrasts with transform and agg that get called once for each non-grouping column. The apply method's ability to return a single object when operating on multiple columns at the same time makes the calculation in this recipe possible.

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