Apply mask for only the type that can become null after calculation

Author: cooolheater

Diff for: pandas/core/array_algos/masked_reductions.py

@@ -58,7 +58,8 @@ def _reductions(
         else:
             return func(values, axis=axis, **kwargs)
     else:
-        mask |= isna(values)
+        if values.dtype == np.float64:
+            mask |= isna(values)
 
         if check_below_min_count(values.shape, mask, min_count) and (
             axis is None or values.ndim == 1

Diff for: pandas/tests/series/test_reductions.py

@@ -6,7 +6,10 @@
 from pandas.compat import HAS_PYARROW
 
 import pandas as pd
-from pandas import Series
+from pandas import (
+    Series,
+    notna,
+)
 import pandas._testing as tm
 
 
@@ -230,4 +233,4 @@ def test_mean_with_skipna():
     series1 = Series({"a": 0.0, "b": 1, "c": 1})
     series2 = Series({"a": 0.0, "b": 2, "c": 2})
     result = series1.convert_dtypes() / series2.convert_dtypes()
-    assert pd.notna(result.mean(skipna=True))
+    assert notna(result.mean(skipna=True))