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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

Computing expected values and displaying a contingency table

The expected defect production is a combined probability. We'll compute the shift defect probability multiplied by the probability based on defect type. This will allow us to compute all 12 probabilities from all combinations of shift and defect type. We can weight these with the observed numbers and compute the detailed expectation for defects.

The following code calculates expected values:

expected = {
(s, t): P_shift[s]*P_type[t]*total
for t in P_type
for s in P_shift
}

We'll create a dictionary that parallels the initial defectsCounter object. This dictionary will have a sequence of two-tuples with keys and values. The keys will be two-tuples of shift and defect type. Our dictionary is built from a generator expression that explicitly enumerates all combinations of keys from the P_shift and...

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