scikit-fda: Functional Data Analysis in Python

Welcome to scikit-fda’s documentation!#

This package offers classes, methods and functions to give support to Functional Data Analysis in Python. Includes a wide range of utils to work with functional data, and its representation, exploratory analysis, or preprocessing, among other tasks such as inference, classification, regression or clustering of functional data.

In the project page hosted by Github you can find more information related to the development of the package.

An exhaustive list of all the contents of the package can be found in the Index.


Currently, scikit-fda is available in Python versions above 3.8, regardless of the platform. The stable version can be installed via PyPI:

pip install scikit-fda

It is also available from conda-forge:

conda install -c conda-forge scikit-fda

It is possible to install the latest version of the package, available in the develop branch, by cloning this repository and doing a manual installation.

git clone
pip install ./scikit-fda

In this type of installation make sure that your default Python version is currently supported, or change the python and pip commands by specifying a version, such as python3.6.

How do I start?#

If you want a quick overview of the package, we recommend you to try the new tutorial. For articles about specific topics, feel free to explore the examples. Want to check the documentation of a particular class or function? Try searching for it in the API list.


All contributions are welcome. You can help this project grow in multiple ways, from creating an issue, reporting an improvement or a bug, to doing a repository fork and creating a pull request to the development branch. The people involved at some point in the development of the package can be found in the contributors page.


The package is licensed under the BSD 3-Clause License. A copy of the license can be found along with the code or in the project page.