(PRWEB) December 06, 2011
The book comes packed with real world examples enabling readers to perform high performance calculations with efficient NumPy code, execute complex linear algebra and mathematical computations, and analyze large data sets with statistical functions.
NumPy is the fundamental package needed for scientific computing with Python. Among other things, it contains a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, useful linear algebra, Fourier transform, and random number capabilities. Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
NumPy 1.5 Beginner's Guide covers every NumPy related concept: installation, functions, matrices, and modules to testing with suitable examples. The book delivers to its readers a strong base in NumPy arrays and universal functions. It also details certain related scientific projects like Matplotlib for plotting mathematical NumPy results, and the SciPy project through examples.
Through this book, users can learn fundamental features like installing NumPy, loading arrays from files and writing them, creating NumPy matrices, using basic modules that NumPy offers and writing unit tests for NumPy code.
The book is written as a beginner's guide, scattered with practical real- world examples and relevant screenshots throughout to bring in assistance for even the novice.
NumPy 1.5 Beginner's Guide is written for every programmer, scientist or engineer with a basic Python knowledge and interested in doing numerical computations with Python. For detailed information about the book, please visit http://link.packtpub.com/9HNnAT.