The book introduces the IPython basics and then focuses on how to combine IPython with some of the most useful libraries for data analysis such as Numpy, Matplotlib, Basemap and Pandas. Every topic is covered with examples and the code presented is also available online. The references proposed are always up-to-date and give the reader the opportunity to discovery resources not covered in the book.
Favorite chapter
The Chapter 5 is a little gem. Here, you can find an introduction on how to use IPython to write high performance code through Cython and the parallel programming facilities of IPython. The attention paid by the author on how to write efficient code is remarkable.
Conclusions
This book definitely achieves its goal to provide a technical introduction to IPython. It is intended for Python users who want an easy to follow introduction to IPython, but also experienced users will find this book useful. It is to notice that, at the moment, this is the only book about IPython.
