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 (Numerical Python) 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

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 …

NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O ...

NumPy is the fundamental package for scientific computing in Python. It is a Python library that provides a multidimensional array object, various derived objects (such as masked arrays and matrices), and an assortment of routines for fast operations on arrays, including mathematical, logical, shape manipulation, sorting, selecting, I/O ...

Random sampling (numpy.random) Set routines; Sorting, searching, and counting; Statistics; Test support (numpy.testing) Window functions; Typing (numpy.typing) Packaging (numpy.distutils) NumPy C-API; Array API standard compatibility; CPU/SIMD optimizations; Thread Safety; Global Configuration Options; NumPy security; Status of numpy.distutils ...

NumPy quickstart# Prerequisites# You’ll need to know a bit of Python. For a refresher, see the Python tutorial. To work the examples, you’ll need matplotlib installed in addition to NumPy. Learner profile. This is a quick overview of arrays in NumPy. It demonstrates how n-dimensional (\(n>=2\)) arrays are represented and can be manipulated ...

For the official NumPy documentation visit numpy.org/doc/stable. Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community.

NumPy Documentation. Web; Latest (development) documentation; NumPy Enhancement Proposals; Versions: Numpy 2.2 Manual [Reference Guide PDF] [User Guide PDF] Numpy 2.1 Manual [Reference Guide PDF] [User Guide PDF] Numpy 2.0 Manual [Reference Guide PDF] [User Guide PDF] Numpy 1.26 ...

Dec 14, 2024 · NumPy reference# Release: 2.2. Date: December 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. Python API#