One of the growing areas of use for Python is within the scientific communities. One issue, which has always been an issue, is that Python is not very efficient when doing numeric calculations. Luckily, Python’s very design is meant to make it relatively easy to expand its functionality. The core module that helps in scientific calculations is the Numpy module. Numpy takes the most inefficient parts of dealing with numerical calculations and outsources them to external libraries that are written in C. It uses the same standard open source libraries that are used in other applications written ...
© Joey Bernard 2016
Joey Bernard, Python Recipes Handbook, 10.1007/978-1-4842-0241-8_11
11. Numerics and Numpy
Joey Bernard1
(1)Fredericton, New Brunswick, Canada
Get Python Recipes Handbook: A Problem-Solution Approach now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
