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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
Miscellaneous Topics

In this chapter, we will look at several topics that don't fit within the categories that we discussed in the previous chapters of this book. Most of these topics are concerned with different ways to facilitate computing and otherwise optimize the execution of our code. Others concern working with specific kinds of data or file formats.

In the first two recipes, we will cover packages that help keep track of units and uncertainties in calculations. These are very important for calculations that concern data that have a direct physical application. In the next recipe, we will look at loading and storing data from NetCDF files. NetCDF is a file format usually used for storing weather and climate data. (NetCDF stands for network common data form.) In the fourth recipe, we'll discuss working with geographical data, such as data that might be associated with weather or climate data. After that...

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