If you know Python, but are new to scientific programming and want to enter the world of scientific computation, or perhaps you are a Python developer with experience in analytics, but want to gain insight to enhance your analytical skills. In either case, NumPy or this book is ideal for you. Learning NumPy and how to apply it to your Python programs is perfect as your next step towards building professional analytical applications. It would be helpful to have a bit of familiarity with basic programming concepts and mathematics, but no prior experience is required. The later chapters cover concepts such as package distribution, speeding-up code, and C/C++ integration, which require a certain amount of programming and debugging know-how. The readers are assumed to be able to build C/C++ programs in their preferred choice of OS (use gcc in linux and cygwin/migw and more in Windows).