The aim of library pymice is to offer the large collection of missing data methods to the Python community.

The intent is to create three packages of functions:

1. missing data exploration: offer functions to inspect missing data and its characteristics
2. multivariate amputation: implement the methodology of mice::ampute in Python
3. multiple imputation: implement the methodology of mice in Python

At the moment, the package contains class McarTests. This class of functions consists of two functions to inspect whether the nonresponse has a MCAR missingness mechanism. Little’s MCAR test is implemented in mcar_test and for each pair of variables, t-tests can be performed with function mcar_t_tests.

Obviously, a lot of development has still to be done.

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