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Functional Python Programming

You're reading from   Functional Python Programming Create succinct and expressive implementations with functional programming in Python

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781784396992
Length 360 pages
Edition 1st Edition
Languages
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Author (1):
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Steven F. Lott Steven F. Lott
Author Profile Icon Steven F. Lott
Steven F. Lott
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Table of Contents (18) Chapters Close

Preface 1. Introducing Functional Programming 2. Introducing Some Functional Features 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 Index

Avoiding stateful classes by using families of tuples

In several previous examples, we've shown the idea of Wrap-Unwrap design patterns that allow us to work with immutable tuples and namedtuples. The point of this kind of designs is to use immutable objects that wrap other immutable objects instead of mutable instance variables.

A common statistical measure of correlation between two sets of data is the Spearman rank correlation. This compares the rankings of two variables. Rather than trying to compare values, which might have different scales, we'll compare the relative orders. For more information, visit http://en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient.

Computing the Spearman rank correlation requires assigning a rank value to each observation. It seems like we should be able to use enumerate(sorted()) to do this. Given two sets of possibly correlated data, we can transform each set into a sequence of rank values and compute a measure of correlation.

We...

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