BUG: groupby.transform with a reducer and unobserved categories coerces dtype

[rhshadrach]

The implementation of groupby.transform with a reduction like sum or min calls the corresponding reduction and then reindexes the output to the input's index in _wrap_transform_fast_result. However, when there are unobserved categories, their presence can induce NA values in the reduction, coercing the dtype to float. This results in unnecessarily coercing the result to float as well.

df = pd.DataFrame({'a': pd.Categorical([1, 1, 2], categories=[1, 2, 3]), 'b': [3, 4, 5]})
gb = df.groupby('a', observed=False)
result = gb.transform('min')
print(result)
#      b
# 0  3.0
# 1  3.0
# 2  5.0

The expected output of column b here should be [3, 3, 5] rather than floats.

[banorton]

take

[banorton]

@rhshadrach Did you mean, b should be [3, 3, 5] rather than floats? Instead of [3, 5, 5].

[rhshadrach]

Yes - thanks. I've updated the OP.