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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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Toc

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

Preface

The SciPy stack is a collection of open source libraries of the powerful Python scripting language, together with its interactive shells. This environment offers a cutting-edge platform for numerical computation, programming, visualization, and publishing, and is used by some of the world's leading mathematicians, scientists, and engineers. It works on any operating system that supports Python and is very easy to install and completely free of charge! It can effectively transform into a data-processing and system-prototyping environment.

The SciPy stack is a popular Python ecosystem used for mathematical and scientific computing tasks. It can be used to perform a variety of data science tasks, from data manipulation to visualization. Utilizing the offerings of SciPy to perform your data science tasks is a very tricky proposition.

This book will show you how you can put to use the various functionalities offered by the SciPy stack in the most efficient way possible. With the help of this book, you will solve real-world problems in linear algebra, numerical analysis, visualization, and much more, including independent recipes drawn from the fields of statistics, scientific computation, and visualization. You will master the different tasks associated with using SciPy and its related libraries, such as NumPy, Matplotlib, pandas and more, in the best way. This book will ensure that you have a practical understanding of not only how a particular feature in SciPy stack works but also its applications in real-world problems.

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