NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.

NumPy (Num erical Py thon) is an open source Python library that’s widely used in science and engineering. The NumPy library contains multidimensional array data structures, such as the homogeneous, N-dimensional ndarray, and a large library of functions that operate efficiently on these data structures.

The only prerequisite for installing NumPy is Python itself. If you don’t have Python yet and want the simplest way to get started, we recommend you use the Anaconda Distribution - it includes Python, NumPy, and many other commonly used packages for …

Dec 14, 2024 · This reference manual details functions, modules, and objects included in NumPy, describing what they are and what they do. For learning how to use NumPy, see the complete documentation.

The reference guide contains a detailed description of the functions, modules, and objects included in NumPy. The reference describes how the methods work and which parameters can be used.

Web Latest (development) documentation NumPy Enhancement Proposals Versions: Numpy 2.2 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] Numpy 2.1 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] Numpy 2.0 Manual [HTML+zip] [Reference Guide PDF] [User Guide PDF] Numpy 1.26 Manual [HTML+zip] Numpy 1.25 Manual [HTML+zip] Numpy 1.24 ...

Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community.

F2PY facilitates creating/building native Python C/API extension modules that make it possible to call Fortran 77/90/95 external subroutines and Fortran 90/95 module subroutines as well as C functions;

NumPy arrays facilitate advanced mathematical and other types of operations on large numbers of data. Typi-cally, such operations are executed more efficiently and with less code than is possible using Python’s built-in sequences.

NumPy reference Routines and objects by topic Mathematical functionsMathematical functions # Trigonometric functions #