# Introduction

Warning

This documentation is a work in process, and is far from complete.

Formulaic is a high-performance implementation of Wilkinson formulas for Python, which are very useful for transforming dataframes into a form suitable for ingestion into various modelling frameworks (especially linear regression).

**Source Code**: https://github.com/matthewwardrop/formulaic**Issue tracker**: https://github.com/matthewwardrop/formulaic/issues

Warning

While this project is now fully functional, the API is still subject to
change between major versions (`0.<major>.<minor>`

) as we continue to
improve things. If you are going to depend on it in another project, it is
advisable to pin formulaic to within a major version, for example:
`formulaic>=0.1.0,<0.2`

.

It provides:

- high-performance dataframe to model-matrix conversions.
- support for reusing the encoding choices made during conversion of one data-set on other datasets.
- extensible formula parsing.
- extensible data input/output plugins, with implementations for:
- input:
`pandas.DataFrame`

`pyarrow.Table`

- output:
`pandas.DataFrame`

`numpy.ndarray`

`scipy.sparse.CSCMatrix`

- support for symbolic differentiation of formulas (and hence model matrices).

with more to come!

For some examples of what Formulaic provides, and how to use it, please refer to the Concepts and User Guides documentation.