Paperback: 263 pages
Publisher: Packt Publishing - ebooks Account; 2nd Revised ed. edition (May 29, 2015)
Product Dimensions: 7.5 x 0.6 x 9.2 inches
Shipping Weight: 1.2 pounds (View shipping rates and policies)
Average Customer Review: 3.8 out of 5 stars See all reviews (4 customer reviews)
Best Sellers Rank: #1,933,156 in Books (See Top 100 in Books) #160 in Books > Computers & Technology > Hardware & DIY > Mainframes & Minicomputers #1101 in Books > Computers & Technology > Programming > Languages & Tools > Python #2263 in Books > Textbooks > Computer Science > Graphics & Visualization
When it comes to software, I learn best from evaluating examples, and then modifying those examples to fit my needs. The cookbook type format is great for that, and the NumPy book here is no exception.This book doesn't just give math related examples of what numpy can do, but it uses a number of other libraries, such as scipy, matplotlib, pillow to highlight numpy related features. There is even a section with exchanging data with MATLAB/Octave as well as R. A lot of examples involve image and audio processing which is a good illustration of numpy's capabilities.The part that I really enjoy is that there is a chapter dedicated to profiling and debugging, where it is explained how to evaluate how fast/efficient your code is written, and gives instructions to how to properly debug with ipython, which is something I haven't seen much of elsewhere.I only discussed a small number of chapters, but this book does a decent job covering numpy's capabilities, but it does an excellent job highlighting its interaction with other libraries, as well as best practices with profiling and testing.
Awesome book, with tons of useful information. I bought this book to help me with my stock analysis program. However, The plethora of information in this book on processing images, audio, and statistics have helped me with many other projects, including analyzing network traffic (Chapter 9 is a great help to enable fast processing with python). Being a secure development TDD guy, chapters 7 & 8 sealed the deal for me.
The book is just an introduction in Numpy. In the second edition two chapters are added; Latest and Greatest in Numpy and Exploratory and Predictive Data Analysis with NumPy Unfortunately the code for the examples con not be downloaded from the Packt webpage, so the examples can not be executed. The book describes the installation of IPython, matplotlib but the installation of Numpy is not described. Nevertheless the book also contains some useful examples.
This book has a lot of information in it and may be a great book if was titled "random python recipes". I was looking for a book on NumPy and while Bumpy is used throughout the book the there is no focus. I would not recommend this book
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