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. The purpose of this user guide is to provide an overview of the functionality of each subpackage along with some general application notes.

The following table lists the subpackages SciPy provides. The left column contains the subpackage names, whereas the right column provides a description and links to the corresponding chapter of this User Guide (if available):

Subpackage	Description (link to User Guide chapter)
`scipy.cluster`	Clustering algorithms
`scipy.constants`	Physical and mathematical constants
`scipy.differentiate`	Finite difference differentiation tools
`scipy.fft`	./fft
`scipy.fftpack`	Fast Fourier Transform routines (legacy)
`scipy.integrate`	./integrate
`scipy.interpolate`	./interpolate
`scipy.io`	./io
`scipy.linalg`	./linalg
`scipy.ndimage`	./ndimage
`scipy.optimize`	./optimize
`scipy.signal`	./signal
`scipy.sparse`	./sparse
`scipy.spatial`	./spatial
`scipy.special`	./special
`scipy.stats`	./stats

There are also additional user guides for these topics:

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