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Applying Math with Python

You're reading from   Applying Math with Python Practical recipes for solving computational math problems using Python programming and its libraries

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781838989750
Length 358 pages
Edition 1st Edition
Languages
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Authors (2):
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Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
Sam Morley Sam Morley
Author Profile Icon Sam Morley
Sam Morley
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Table of Contents (12) Chapters Close

Preface 1. Basic Packages, Functions, and Concepts 2. Mathematical Plotting with Matplotlib FREE CHAPTER 3. Calculus and Differential Equations 4. Working with Randomness and Probability 5. Working with Trees and Networks 6. Working with Data and Statistics 7. Regression and Forecasting 8. Geometric Problems 9. Finding Optimal Solutions 10. Miscellaneous Topics 11. Other Books You May Enjoy

Further reading

There are a large number of textbooks on statistics and statistical theory. The following book was used as reference for this chapter:

  • Mendenhall, W., Beaver, R., and Beaver, B., (2006), Introduction To Probability And Statistics, 12th ed., (Belmont, Calif.: Thomson Brooks/Cole)

The pandas documentation (https://pandas.pydata.org/docs/index.html) and the following pandas book serve as good references for working with pandas:

  • McKinney, W.,(2017),Python for Data Analysis, 2nd ed.,(Sebastopol: O'Reilly Media, Inc, US)

The SciPy documentation (https://docs.scipy.org/doc/scipy/reference/tutorial/stats.html) also contains detailed information about the statistics module that was used several times in this chapter.

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