Timothy Sweetser

This is a great idea! No one is actively working on it, but your contribution would be welcome.

I think we excluded this from the initial scope of the project because we felt there were already good options for fitting GLMMs in R, e.g. [lme4](https://github.com/lme4/lme4) and [mbest](https://github.com/patperry/r-mbest)

I am working on a PR for this issue and will submit this week.

what version of sklearn-pandas are you using?

The following works for me, using `sklearn-pandas==1.8.0` installed from PyPI. Can you please provide a code snippet to reproduce your issue? ``` import sklearn import pandas as pd import numpy...

Ah, I see the problem now: column B should be integer type

For comparison, using `scikit-learn` directly works just fine: ```python import pickle import numpy as np from sklearn.preprocessing import Imputer from numpy.testing import assert_array_equal arr_in = np.array([[1], [np.nan], [3]], dtype=float) expected_output...