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SciPy Recipes

You're reading from   SciPy Recipes A cookbook with over 110 proven recipes for performing mathematical and scientific computations

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Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788291460
Length 386 pages
Edition 1st Edition
Languages
Tools
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Authors (3):
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V Kishore Ayyadevara V Kishore Ayyadevara
Author Profile Icon V Kishore Ayyadevara
V Kishore Ayyadevara
Ruben Oliva Ramos Ruben Oliva Ramos
Author Profile Icon Ruben Oliva Ramos
Ruben Oliva Ramos
Luiz Felipe Martins Luiz Felipe Martins
Author Profile Icon Luiz Felipe Martins
Luiz Felipe Martins
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Table of Contents (11) Chapters Close

Preface 1. Getting to Know the Tools FREE CHAPTER 2. Getting Started with NumPy 3. Using Matplotlib to Create Graphs 4. Data Wrangling with pandas 5. Matrices and Linear Algebra 6. Solving Equations and Optimization 7. Constants and Special Functions 8. Calculus, Interpolation, and Differential Equations 9. Statistics and Probability 10. Advanced Computations with SciPy

Operations on arrays

NumPy defines a rich set of operations and functions for the ndarray type. NumPy defines the notion of a universal function, abbreviated as ufunc, which is a function object that can be applied to arbitrary arrays. Universal functions are objects of ufunc type, and NumPy provides a vast collection of built-in ufunc functions, covering all computations needed in scientific and data applications.

A ufunc is specialized towards the element by element application of a function. That is, if x is an array object, and f is a ufunc, the f(x) expression will apply the function f to every element of array x, and return a new object with the resulting values.

A ufunc follows a strict functional protocol; applying the f function to x will never change the elements of the x arrays themselves, but return a new array with the values of f applied to each element of x. User...
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