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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

13.3.4 Some useful modules

 

 

The list of useful Python modules is vast. In the following table, we have given a very short segment of such a list, focused on modules related to mathematical and engineering applications (Table 13.2):

Module

Description

scipy

Functions used in scientific computing

numpy

Support arrays and related methods

matplotlib

Plotting and visualization 

functools

Partial application of functions

itertools

Iterator tools to provide special capabilities, such as slicing to generators

re

Regular expressions for advanced string handling

sys

System-specific functions

os

Operating system interfaces such as directory listing and file handling

datetime

Representing dates and date increments

time

Returning wall clock time

timeit

Measuring execution time

sympy

Computer arithmetic package (symbolic computations...

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