This new NumPy book provides an easy start to NumPy for those who want to churn numbers in Python programming language, whether you don't have much programming background or you are switching from your favorite language. The author of the book uses quite a friendly tone throughout the book. Most of the important aspects of NumPy is well covered with well explained examples. The examples provided are step by step explained, starting from the basic array/matrix creation to more complex tasks like signal analysis and linear algebra related calculations.
To get best out of this book, it is recommended that you would try out the examples and challenge yourself with the exercises given in have a go sections of the book. If you are feeling lazy for some reason, you can get the source code from the book's page. I finished perusing the book in about a week (having a few years of NumPy experience has definitely role in this). For me reading and understanding through stock market related examples were a bit boring, but if you are in to financial business you might enjoy putting NumPy in your toolstack with the help of this book. Notably, besides the basic NumPy beginners chapters, the book extends into basic Matplotlib and SciPy lands. A lot of examples use Matplotlib to create plots and better illustrate the operations at hand (e.g. curve fitting, statistical distributions) It is a bit surprising to see MaskedArray module didn't get any mention in the book. However, with the basics you gained, it should be fairly easy to start experimenting with masked array functions of NumPy.
Overall, if you are looking for a book to get started in NumPy in about 200 pages, you might give this one a chance. It is available in both print and electronic formats. Further on, you can try their advanced matplotlib and and Sage books, if you are willing to enhance your scientific Python skills.
Final Note: I received a review copy from the publisher. Thanks to Packt publishing for their contributions to open-source literature and providing me a free copy of the book.
To get best out of this book, it is recommended that you would try out the examples and challenge yourself with the exercises given in have a go sections of the book. If you are feeling lazy for some reason, you can get the source code from the book's page. I finished perusing the book in about a week (having a few years of NumPy experience has definitely role in this). For me reading and understanding through stock market related examples were a bit boring, but if you are in to financial business you might enjoy putting NumPy in your toolstack with the help of this book. Notably, besides the basic NumPy beginners chapters, the book extends into basic Matplotlib and SciPy lands. A lot of examples use Matplotlib to create plots and better illustrate the operations at hand (e.g. curve fitting, statistical distributions) It is a bit surprising to see MaskedArray module didn't get any mention in the book. However, with the basics you gained, it should be fairly easy to start experimenting with masked array functions of NumPy.
Overall, if you are looking for a book to get started in NumPy in about 200 pages, you might give this one a chance. It is available in both print and electronic formats. Further on, you can try their advanced matplotlib and and Sage books, if you are willing to enhance your scientific Python skills.
Final Note: I received a review copy from the publisher. Thanks to Packt publishing for their contributions to open-source literature and providing me a free copy of the book.
