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Scientific Computing with Python

You're reading from   Scientific Computing with Python High-performance scientific computing with NumPy, SciPy, and pandas

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Length 392 pages
Edition 2nd Edition
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Authors (4):
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Olivier Verdier Olivier Verdier
Author Profile Icon Olivier Verdier
Olivier Verdier
Jan Erik Solem Jan Erik Solem
Author Profile Icon Jan Erik Solem
Jan Erik Solem
Claus Führer Claus Führer
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Claus Führer
Claus Fuhrer Claus Fuhrer
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Claus Fuhrer
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Table of Contents (23) Chapters Close

Preface 1. Getting Started 2. Variables and Basic Types FREE CHAPTER 3. Container Types 4. Linear Algebra - Arrays 5. Advanced Array Concepts 6. Plotting 7. Functions 8. Classes 9. Iterating 10. Series and Dataframes - Working with Pandas 11. Communication by a Graphical User Interface 12. Error and Exception Handling 13. Namespaces, Scopes, and Modules 14. Input and Output 15. Testing 16. Symbolic Computations - SymPy 17. Interacting with the Operating System 18. Python for Parallel Computing 19. Comprehensive Examples 20. About Packt 21. Other Books You May Enjoy 22. References
Symbolic Computations - SymPy

In this chapter, we will give a brief introduction to using Python for symbolic computations. There is powerful software on the market for performing symbolic computations, for example, Maple™ or Mathematica™. But sometimes, it might be favorable to make symbolic calculations in the language or framework you are used to. At this stage of the book, we assume that this language is Python, so we seek a tool in Python—the module SymPy.

A complete description of SymPy, if even possible, would fill an entire book, and that is not the purpose of this chapter. Instead, we will stake out a path into this tool by examining some guiding examples, giving a flavor of the potential of this tool as a complement to NumPy and SciPy.

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