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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

Who this book is for

Python developers, aspiring data scientists, and analysts who want to get started with scientific computing using Python will find this book to be a useful resource. If you want to learn how to manipulate and visualize your data using the SciPy stack, this book will also help you. A basic understanding of Python programming is all you need to get started.

This book is for readers who want learn more about SciPy in specific topics and gain the basic knowledge required to solve problems. The following are the objectives:

  • Tackle sophisticated problems in scientific computing with the SciPy stack
  • Get a solid foundation in scientific computing with Python and open source software
  • Present common tasks related to SciPy and associated libraries such as NumPy, pandas, and Matplotlib
  • Perform mathematical operations and work with the statistical and probability functions in SciPy
  • Empower users to further explore the library and find solutions to their own computational needs
  • Discuss best practices and efficient methods in the solution of computational problems
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