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An action-packed guide for the easy-to-use, high performance, Python based free open source NumPy mathematical library using real-world examples with this book and ebook

  • The first and only book that truly explores NumPy practically

  • Perform high performance calculations with clean and efficient NumPy code

  • Analyze large data sets with statistical functions

  • Execute complex linear algebra and mathematical computations

In Detail

In today's world of science and technology, the hype is all about speed and flexibility. When it comes to scientific computing, NumPy is on the top of the list. NumPy is the fundamental package needed for scientific computing with Python. NumPy will give you both speed and high productivity. Save thousands of dollars on expensive software, while keeping all the flexibility and power of your favourite programming language.

NumPy 1.5 Beginner's Guide will teach you about NumPy from scratch. It includes everything from installation, functions, matrices, and modules to testing, all explained with appropriate examples.

Numpy 1.5 Beginner's Guide will teach you about installing and using NumPy and related concepts.

This book will give you a solid foundation in NumPy arrays and universal functions. At the end of the book, we will explore related scientific computing projects such as Matplotlib for plotting and the SciPy project through examples.

NumPy 1.5 Beginner's Guide will help you be productive with NumPy and write clean and fast code.


Subscriber Reviews

Average Rating: 2.5 out of 5 rating Based on 2 Ratings

"Usefull but Frustrating" - by BarryN on 17-JUN-2012
Reviewer Rating: 1 star rating2 star rating3 star rating4 star rating5 star rating
The book is well organized and the format is easily understandable.  My big complaint may have more to do with Safari Books Online, than the printed copy.  The Table of Contents is out of sync with the material.  Trying to navigate by the TOC takes one to a different location in the text.  

There are lots of helpful examples although they tend to lean heavily toward analyzing stock market data.

Overall a useful resource for those coming to numpy for the first time.

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