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Secret Recipes of the Python Ninja

You're reading from   Secret Recipes of the Python Ninja Over 70 recipes that uncover powerful programming tactics in Python

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788294874
Length 380 pages
Edition 1st Edition
Languages
Tools
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Toc

Table of Contents (17) Chapters Close

Title Page
Copyright and Credits
Packt Upsell
Foreword
Contributors
Preface
1. Working with Python Modules FREE CHAPTER 2. Utilizing the Python Interpreter 3. Working with Decorators 4. Using Python Collections 5. Generators, Coroutines, and Parallel Processing 6. Working with Python's Math Module 7. Improving Python Performance with PyPy 8. Python Enhancement Proposals 9. Documenting with LyX 1. Other Books You May Enjoy Index

Implementing basic statistics


Starting in version 3.4, basic statistical tools were provided to Python. While nowhere near as comprehensive as NumPy, SciPy, Pandas, or the like, they are useful when having to perform simple calculations and not wanting, or having access to, advanced numeric modules.

How to do it...

Note that the import statement is omitted in the following screenshots:

  1. The mean(data) function returns the normal average of a sequence or iterator:

    • The line 3 is the mean of integers.
    • The line 4 is the mean of floats.
    • The lines 6 and line 8 show that fractions can be averaged, as well as decimals.
  1. The harmonic_mean(data) function returns the harmonic average of a sequence or iterator. The harmonic mean is the reciprocal of the arithmetic mean of the reciprocals of the argument and is typically used when the average of rates or rations is needed.

For example, if a car traveled for a given distance at 60 mph, then the same distance back at 50 mph, its average speed would be the harmonic...

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