SciPy Recipes

L. Felipe Martins, Ruben Oliva Ramos, V Kishore Ayyadevara

  • 出版商: Packt Publishing
  • 出版日期: 2017-12-22
  • 售價: $1,310
  • 貴賓價: 9.5$1,245
  • 語言: 英文
  • 頁數: 386
  • 裝訂: Paperback
  • ISBN: 1788291468
  • ISBN-13: 9781788291460
  • 下單後立即進貨 (約3~4週)


Key Features

  • Tackle a variety of scientific and technical computing problems with ease, using the popular SciPy stack
  • Covers a wide range of data science tasks using SciPy and related libraries such as NumPy, pandas and matplotlib
  • Contains practical, easy to follow recipes on using SciPy in the best possible manner

Book Description

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, right 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 field of statistics, scientific computation and visualization. You will master the different tasks associated with using SciPy and the related libraries such as NumPy, Matplotlib, Pandas and more, in the most optimal way. This book will ensure that you not only have a practical understanding of how a particular feature in SciPy stack works, but also its application to real-world problems.

What you will learn

  • Tackle sophisticated problems in scientific computing with the SciPy stack
  • Get a solid foundation in scientific computing with Python and open-source software
  • Presents 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
  • Empowers users to further explore the library and find solutions to their own computational needs
  • Discusses best-practices and efficient methods in the solution of computational problems