Pandas: How to avoid FutureWarning when setting bool value to NaN (missing)?

Question

I want to apply comparison operator to Pandas DataFrame. In case the source data value is missing then my result bool table should contain missing values as well. My code:

>>> pd.__version__
'2.1.1'
>>> df = pd.DataFrame([[1.2, 2.2, np.nan], [1.1, np.nan, 3.3]], columns=['A', 'B', 'C'])
>>> res = df.gt(1.0)
>>> res
res
    A      B      C
0  True   True  False
1  True  False   True

Attempt to assign NaN value to original missing positions yields FutureWarning

>>> res[df.isna()]=pd.NA
FutureWarning: Setting an item of incompatible dtype is deprecated and will raise in a future error of pandas. Value 'nan' has dtype incompatible with bool, please explicitly cast to a compatible dtype first.

How to get the results correctly without warning?

Note: this question is unrelated as it does not solve entering of missing values.

Answer 1

I think problem is combinations boolean with missing values, so convert mask to Nullable Boolean:

res = df.gt(1.0).astype('boolean')

res[df.isna()]=pd.NA
print (res)
      A     B     C
0  True  True  <NA>
1  True  <NA>  True

res = df.gt(1.0).astype('boolean').mask(df.isna())
print (res)
      A     B     C
0  True  True  <NA>
1  True  <NA>  True