Preface

Whether you are new to scientific/analytic programming, or a seasoned expert, this book will provide you with the skills you need to successfully create, optimize, and distribute your Python/NumPy analytical modules.

Starting from the beginning, this book will cover the key features of NumPy arrays and the details of tuning the data format to make it most fit to your analytical needs. You will then get a walkthrough of the core and submodules that are common to various multidimensional, data-typed analysis. Next, you will move on to key technical implementations, such as linear algebra and Fourier analysis. Finally, you will learn about extending your NumPy capabilities for both functionality and performance by using Cython and the NumPy C API. The last chapter of this book also provides advanced materials to help you learn further by yourself.

This guide is an invaluable tutorial if you are planning to use NumPy in analytical projects.