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SciPy User Guide

docs/tutorial:index

SciPy is a collection of mathematical algorithms and convenience functions built on NumPy . It adds significant power to Python by providing the user with high-level commands and classes for manipulating and visualizing data.

Subpackages and User Guides

SciPy is organized into subpackages covering different scientific computing domains. These are summarized in the following table, with their user guide linked in the Description and User Guide column (if available):

==================    ========================================
Subpackage            Description and User Guide
==================    ========================================
``cluster``           Clustering algorithms
``constants``         Physical and mathematical constants
``differentiate``     Finite difference differentiation tools
``fft``               :doc:`./fft`
``fftpack``           Fast Fourier Transform routines (legacy)
``integrate``         :doc:`./integrate`
``interpolate``       :doc:`./interpolate`
``io``                :doc:`./io`
``linalg``            :doc:`./linalg`
``ndimage``           :doc:`./ndimage`
``odr``               Orthogonal distance regression
``optimize``          :doc:`./optimize`
``signal``            :doc:`./signal`
``sparse``            :doc:`./sparse`
``spatial``           :doc:`./spatial`
``special``           :doc:`./special`
``stats``             :doc:`./stats`
==================    ========================================

There are also additional user guides for these topics:

./arpack - Eigenvalue problem solver using iterative methods
./csgraph - Compressed Sparse Graph Routines

For guidance on organizing and importing functions from SciPy subpackages, refer to the Guidelines for Importing Functions from SciPy.

For information on support for parallel execution and thread safety, see scipy_parallel_execution and scipy_thread_safety.