skipna keyword not yet available in groupby for 2.3

Author: jorisvandenbossche

pandas/core/arrays/base.py

@@ -2391,8 +2391,7 @@ def _groupby_op(
             if op.how == "sum":
                 # https://github.com/pandas-dev/pandas/issues/60229
                 # All NA should result in the empty string.
-                assert "skipna" in kwargs
-                if kwargs["skipna"] and min_count == 0:
+                if min_count == 0:
                     arr = arr.fillna("")
             npvalues = arr.to_numpy(object, na_value=np.nan)
         else:

pandas/tests/groupby/test_reductions.py

@@ -711,13 +711,13 @@ def test_min_empty_string_dtype(func, string_dtype_no_object):
 
 
 @pytest.mark.parametrize("min_count", [0, 1])
-def test_string_dtype_empty_sum(string_dtype_no_object, skipna, min_count):
+def test_string_dtype_empty_sum(string_dtype_no_object, min_count):
     # https://github.com/pandas-dev/pandas/issues/60229
     dtype = string_dtype_no_object
     df = DataFrame({"a": ["x"], "b": [pd.NA]}, dtype=dtype)
     gb = df.groupby("a")
-    result = gb.sum(skipna=skipna, min_count=min_count)
-    value = "" if skipna and min_count == 0 else pd.NA
+    result = gb.sum(min_count=min_count)
+    value = "" if min_count == 0 else pd.NA
     expected = DataFrame(
         {"b": value}, index=pd.Index(["x"], name="a", dtype=dtype), dtype=dtype
     )