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  • Book Overview & Buying NumPy Essentials
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NumPy Essentials

NumPy Essentials

By : Jaidev Deshpande, Chin, Tanmay Dutta, Shane Holloway
3.3 (3)
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NumPy Essentials

NumPy Essentials

3.3 (3)
By: Jaidev Deshpande, Chin, Tanmay Dutta, Shane Holloway

Overview of this book

In today’s world of science and technology, it’s all about speed and flexibility. When it comes to scientific computing, NumPy tops the list. NumPy gives you both the speed and high productivity you need. This book will walk you through NumPy using clear, step-by-step examples and just the right amount of theory. We will guide you through wider applications of NumPy in scientific computing and will then focus on the fundamentals of NumPy, including array objects, functions, and matrices, each of them explained with practical examples. You will then learn about different NumPy modules while performing mathematical operations such as calculating the Fourier Transform; solving linear systems of equations, interpolation, extrapolation, regression, and curve fitting; and evaluating integrals and derivatives. We will also introduce you to using Cython with NumPy arrays and writing extension modules for NumPy code using the C API. This book will give you exposure to the vast NumPy library and help you build efficient, high-speed programs using a wide range of mathematical features.
Table of Contents (11 chapters)
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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 numPy...

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NumPy Essentials
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