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# SciPy User Guide

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

SciPy is organized into subpackages covering different scientific computing domains. These are summarized in the following table:

Subpackage | Description
--- | ---
`cluster` | Clustering algorithms
`constants` | Physical and mathematical constants
`fft` | Discrete Fourier transforms
`fftpack` | Fast Fourier Transform routines (legacy)
`integrate` | Integration and ordinary differential equation solvers
`interpolate` | Interpolation and smoothing splines
`io` | Input and Output
`linalg` | Linear algebra
`ndimage` | N-dimensional image processing
`odr` | Orthogonal distance regression
`optimize` | Optimization and root-finding routines
`signal` | Signal processing
`sparse` | Sparse matrices and associated routines
`spatial` | Spatial data structures and algorithms
`special` | Special functions
`stats` | Statistical distributions and functions

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

Below, you can find the complete user guide organized by subpackages.

User guide

- Special functions (`scipy.special`)
- Integration (`scipy.integrate`)
- Optimization (`scipy.optimize`)
- Interpolation (`scipy.interpolate`)
- Fourier Transforms (`scipy.fft`)
- Signal Processing (`scipy.signal`)
- Linear Algebra (`scipy.linalg`)
- Sparse Arrays (`scipy.sparse`)
- Sparse eigenvalue problems with ARPACK
- Compressed Sparse Graph Routines (`scipy.sparse.csgraph`)
- Spatial data structures and algorithms (`scipy.spatial`)
- Statistics (`scipy.stats`)
- Multidimensional image processing (`scipy.ndimage`)
- File IO (`scipy.io`)

## Executable tutorials

Below you can also find tutorials in MyST Markdown format. These can be opened as Jupyter Notebooks with the help of the Jupytext extension.

Executable tutorials

- Interpolate transition guide