Open Duncan-Hunter opened 3 months ago
Hey @Duncan-Hunter ,
good catch, good suggestion. I'll take a look into the np.issubdtype
function for a cleaner solution.
Worst case scenario we can always add the extension dtypes to the list above.
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Describe the bug Pandas has extension DTypes. When you fit a Univariate calculator, or presumably anything that else that checks for dtypes using
_split_features_by_type
, columns are dropped becauseInt64
is not inTo Reproduce Using an environment with
nannyml=0.10.7
Expected behavior There should be support for these dtypes, and columns shouldn't be dropped without the user knowing.
Additional context I'm going to work around the issue by converting my datatypes to underlying
numpy
types usingpd.Series.dtype.type
. But for a fix, I think you should usenp.issubdtype(dtype.type, np.number)
.