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Functional Python Programming

You're reading from   Functional Python Programming Discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads

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Product type Paperback
Published in Apr 2018
Publisher Packt
ISBN-13 9781788627061
Length 408 pages
Edition 2nd Edition
Languages
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Toc

Table of Contents (18) Chapters Close

Preface 1. Understanding Functional Programming 2. Introducing Essential Functional Concepts FREE CHAPTER 3. Functions, Iterators, and Generators 4. Working with Collections 5. Higher-Order Functions 6. Recursions and Reductions 7. Additional Tuple Techniques 8. The Itertools Module 9. More Itertools Techniques 10. The Functools Module 11. Decorator Design Techniques 12. The Multiprocessing and Threading Modules 13. Conditional Expressions and the Operator Module 14. The PyMonad Library 15. A Functional Approach to Web Services 16. Optimizations and Improvements 17. Other Books You May Enjoy

Group-by reduction from many items to fewer

A very common operation is a reduction that groups values by some key or indicator. In SQL, this is often called the SELECT GROUP BY operation. The raw data is grouped by some column's value and reductions (sometimes aggregate functions) are applied to other columns. The SQL aggregate functions include SUM, COUNT, MAX, and MIN.

The statistical summary, called the mode, is a count that's grouped by some independent variable. Python offers us several ways to group data before computing a reduction of the grouped values. We'll start by looking at two ways to get simple counts of grouped data. Then we'll look at ways to compute different summaries of grouped data.

We'll use the trip data that we computed in Chapter 4, Working with Collections. This data started as a sequence of latitude-longitude waypoints. We restructured...

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