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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

Getting started with numpy.ndarray


In this section, we will go over some of the internals of numpy ndarray, including its structure and behavior. Let's start. Type in the following statements in the IPython prompt:

In [1]: import numpy as np 
 
In [2]: x = np.array([[1,2,3],[2,3,4]]) 
 
In [3]: print(x)

NumPy shares the names of its functions with functions in other modules, such as the math module in the Python standard library. Using imports like the following there is not recommended:

from numpy import * 

As it may overwrite many functions that are already in the global namespace, which is not recommended. This may lead to unexpected behavior from your code and may introduce very subtle bugs in it . This may also create conflicts in the code itself, (example numPy has any and will cause conflicts with the system any keyword) and may cause confusion when reviewing or debugging a piece of code. Therefore, it is important and recommended to always follow the import...

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