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NumPy Essentials

You're reading from  NumPy Essentials

Product type Book
Published in Apr 2016
Publisher
ISBN-13 9781784393670
Pages 156 pages
Edition 1st Edition
Languages
Authors (3):
Leo (Liang-Huan) Chin Leo (Liang-Huan) Chin
Profile icon Leo (Liang-Huan) Chin
Tanmay Dutta Tanmay Dutta
Profile icon Tanmay Dutta
Shane Holloway Shane Holloway
Profile icon Shane Holloway
View More author details

Table of Contents (16) Chapters

NumPy Essentials
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. An Introduction to NumPy 2. The NumPy ndarray Object 3. Using NumPy Arrays 4. NumPy Core and Libs Submodules 5. Linear Algebra in NumPy 6. Fourier Analysis in NumPy 7. Building and Distributing NumPy Code 8. Speeding Up NumPy with Cython 9. Introduction to the NumPy C-API 10. Further Reading

Summary


NumPy is certainly the core to scientific computation using Python: many modules are based on it. Although sometimes you might find that NumPy has no analytics modules, it certainly provides you with a way of reaching out to a wide range of scientific modules.

We hope the last chapter of this book has given you a good idea about using these modules with NumPy and makes your script more efficient (there are still so many handy NumPy modules we can't cover in this book; just spend an afternoon on GitHub or PyPI, and you may find a handful of them). Last but not least, thank you for spending time with us going through so many functions. Have some fun with NumPy now!

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