Pandas BUG: NaN vs NA in mixed reduction

df = pd.DataFrame(
    {
        "B": [1, None, 3],
        "C": pd.array([1, None, 3], dtype="Int64"),
    }
)
result = df.skew()

>>> result
B    <NA>
C    <NA>
dtype: Float64

>>> df[["B"]].skew()
B   NaN
dtype: float64

Based on test_mixed_reductions. The presence of column "C" shouldn't affect the result we get for column "B".

Comment From: rhshadrach

Expected Behavior

NA

I would expect Float64 dtype with NaN and NA. One might also argue object, but so far it appears we coerce to the nullable dtypes.

df = pd.DataFrame(
    {
        "B": [1, 2, 3],
        "C": pd.array([1, 2, 3], dtype="Float64"),
    }
)
print(df.sum())
# B    6.0
# C    6.0
# dtype: Float64

Comment From: jbrockmendel

Hah, in the expected behavior section i put "NA" to mean "I'm not writing anything here", not pd.NA.