SciPy
NumFOCUS Sponsored Project since 2019SciPy provides fundamental numerical algorithms for scientific computing: statistics, numerical optimization, linear algebra, special functions, integration, interpolation, signal and image processing, and more. SciPy is a foundational building block for scientific and numerical computing in Python.
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Industry
Business & Industry Applications
Higher Education Research & Teaching
Government
Language
Python
Cython
C
C++
Fortran
Features
Data Wrangling
Modeling
High Performance Computing
Statistical Computing
Numerical Computing
SciPy provides fundamental numerical algorithms for scientific computing. SciPy is built on NumPy and is an important foundation for other well-known Python packages like scikit-learn (machine learning), scikit-image (image processing) and statsmodels (statistics).
SciPy is used in virtually all fields of science and engineering. From major scientific endeavors like the LIGO project detecting gravitational waves and the first ever image of a black hole to individual scientists and teams in fields as diverse as economics, biology, and psychology.
