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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
Calculus and Differential Equations

In this chapter, we will discuss various topics related to calculus. Calculus is the branch of mathematics that concerns the processes of differentiation and integration. Geometrically, the derivative of a function represents the gradient of the curve of the function, and the integral of a function represents the area below the curve of the function. Of course, these characterizations only hold in certain circumstances, but they provide a reasonable foundation for this chapter.

We start by looking at calculus for a simple class of functions: the polynomials. In the first recipe, we create a class that represents a polynomial and define methods that differentiate and integrate the polynomial. Polynomials are convenient because the derivative or integral of a polynomial is again a polynomial. Then, we use the SymPy package to perform symbolic differentiation and integration on more general...

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