BUG: DataFrame float reductions with object input

[rhshadrach]

By "float reduction", I mean any reduction that would coerce bool or int to float - e.g. mean, std, skew, kurt.

Along with bool and int, we also coerce object to float:

print(pd.DataFrame(data=[[1]], columns=["a"], dtype=object).mean(axis=0))
# a    1.0
# dtype: float64

The reason we cast bool / int to float is to make the resulting dtype not value-dependent. However it's not clear to me if this is the correct thing to do with object. I think I would have expected to get object dtype back.

This was noticed because of the following inconsistency:

print(pd.DataFrame(columns=["a"], dtype=object).mean())
# a    NaN
# dtype: object

In the case of an empty frame with columns, we do end up with object dtype.

[jbrockmendel]

@rhshadrach im seeing object dtype on main. is this closed by one of your recent PRs?

[rhshadrach]

Thanks, closed by #51335