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Numpy beginner’s guide 2nd edition: mini review

June 15, 2013

When writing complex python scripts and programs, especially in 3D graphics and animation, you often find yourself needing some quick and easy tools that will help you manipulate large datasets, usually in the form of matrices and vectors.

Using simple nested lists can work, but there’s a faster, more elegant tool for the job that has quite a number of benefits up its sleeve: NumPy.

NumPy is a well tested, feature rich framework for creating and manipulating arrays and matrices, commonly used in scientific computing.

Recently, Packt publishing released a new title focused on Numpy: “NumPy Beginner’s Guide 2nd Edition” (by Ivan Idris), and I was one of the lucky people who got free review copies.

Mini Review

NumPy Beginner’s Guide 2nd Ed (which is also available as an eBook) gives a thorough review of NumPy and its uses in scientific computing (a topic not often reviewed in such books).

Table of contents
Chapter 1: NumPy Quick Start
Chapter 2: Beginning with NumPy Fundamentals
Chapter 3: Get in Terms with Commonly Used Functions
Chapter 4: Convenience Functions for Your Convenience
Chapter 5: Working with Matrices and ufuncs
Chapter 6: Move Further with NumPy Modules
Chapter 7: Peeking into Special Routines
Chapter 8: Assure Quality with Testing
Chapter 9: Plotting with Matplotlib
Chapter 10: When NumPy is Not Enough – SciPy and Beyond
Chapter 11: Playing with Pygame

The book is very well written, and tries (quite successfully) to address this specialized, complicated subject in a light, simplified manner without losing depth and oversimplifying. The book includes many down to earth examples and sample code, and many interesting exercises that help implement the material.

It starts with a nice, gradual introduction to NumPy, its functions, data structures and uses (and of course, how to install it). Then, the book addresses how to handle, analyze and manipulate larger datasets with examples from stock market data. Around half way, the book focuses on matrices and linear systems. The last few subjects cover advanced topics which I didn’t delve into yet.

All in all, a very good book, fun to read and useful. Recommended to anyone interested in manipulating arrays, matrices and large datasets in python efficiently.


From → Programming, Python

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