Variance of nullable Int64 ignores ddof argument

[VictorDavis]

Variance calculation Series.var() is ignoring the ddof argument for nullable integer type Int64. Behavior should match that of float type.

>>> pd.__version__
'0.25.1'
>>> np.__version__
'1.17.2'
>>> s1 = pd.Series(data=[1,2,3,4,5,6,np.nan,np.nan])
>>> series.var(ddof=0)
3.5
>>> s1 = pd.Series(data=[1,2,3,4,5,6,np.nan,np.nan])
>>> s1.var(ddof=0)
2.9166666666666665
>>> s1.var(ddof=1)
3.5
>>> s2 = pd.Series(data=[1,2,3,4,5,6,np.nan,np.nan], dtype="Int64")
>>> s2.var(ddof=0)
3.5
>>> s2.var(ddof=1)
3.5 

[jorisvandenbossche]

@VictorDavis thanks for the report!
From a quick look, it seems the argument is not passed through, here:

pandas/pandas/core/arrays/integer.py

Line 655 in 6c898e6

result = op(data, axis=0, skipna=skipna, mask=mask)