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Copulas is a Python library for modeling multivariate distributions and sampling from them using copula functions. Given a table containing numerical data, we can use Copulas to learn the distribution and later on generate new synthetic rows following the same statistical properties.

Some of the features provided by this library include:

  • A variety of distributions for modeling univariate data.

  • Multiple Archimedean copulas for modeling bivariate data.

  • Gaussian and Vine copulas for modeling multivariate data.

  • Automatic selection of univariate distributions and bivariate copulas.

Supported Distributions


  • Beta

  • Gamma

  • Gaussian

  • Gaussian KDE

  • Log-Laplace

  • Student T

  • Truncated Gaussian

  • Uniform

Archimedean Copulas (Bivariate)

  • Clayton

  • Frank

  • Gumbel


  • Gaussian Copula

  • D-Vine

  • C-Vine

  • R-Vine

Indices and tables