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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
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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
Classes

In mathematics, when we write , we refer to a mathematical object for which we know many methods from elementary calculus. For example:

  • We might want to evaluate at , that is, compute , which returns a real number.
  • We might want to compute its derivative, which gives us another mathematical object, cos.
  • We might want to compute the first three coefficients of its Taylor polynomial.

These methods may be applied not only to sin but also to other sufficiently smooth functions. There are, however, other mathematical objects, for example, the number 5, for which these methods would make no sense.

Objects that have the same methods are grouped together in abstract classes, for example, functions. Every statement and every method that can be applied to functions in general applies in particular to sin or cos.

Other examples for such classes might be a rational number...

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