I've finished reading the book "Learning Scipy for Numerical and Scientific Computing". This book comes to the scientific python series that PacktPub are bringing to the Python Developers! Congratulations! As the title informs: it includes Scipy, Numpy and Matplotlib. I only missed some further information about IPython, but it wasn't the goal of the book, so it goes well even leaved out.
It covers several important topics that are not as commonly covered, specially with several snippets illustrating special functions presented at Scipy library. For the developers it will be another great reference book to complement the native docs that comes with the library. I enjoyed the author focused more on numerical analysis functions, it is one of the most used functions at the library.
The bool also brings chapters on more specific applications: signal processing, data mining and computational geometry. There is an extra chapter about the integration with another languages, but I found it not dense enough to explain those integrations. I really missed more start-off examples showing how to install the f2py or how to use Scipy with C/C++.
Overall the Learning Scipy for Numerical and Scientific Computing book is a good book on Scipy covering lots of mathematics with examples in Python. The book has a good size and it helps the scientists and scientific developers (by the way the non-developers will face some difficulties due to the heavy math that comes with the examples) to have a good overview on the library before exploring the reference material.
Thanks Kenny for the invitation to review this book, and congratulations to Francisco for bringing one more technical book for scientific python computing to the series!