BUG: GroupBy.idxmax/idxmin with EA dtypes

pandas/core/arrays/base.py

@@ -591,7 +591,7 @@ def argsort(
             mask=np.asarray(self.isna()),
         )
 
-    def argmin(self):
+    def argmin(self, axis=None, skipna: bool = True):
         """
         Return the index of minimum value.
 
@@ -606,9 +606,11 @@ def argmin(self):
         --------
         ExtensionArray.argmax
         """
+        if not skipna:
+            raise NotImplementedError
         return nargminmax(self, "argmin")
 
-    def argmax(self):
+    def argmax(self, axis=None, skipna: bool = True):
         """
         Return the index of maximum value.
 
@@ -623,6 +625,8 @@ def argmax(self):
         --------
         ExtensionArray.argmin
         """
+        if not skipna:
+            raise NotImplementedError
         return nargminmax(self, "argmax")
 
     def fillna(self, value=None, method=None, limit=None):

pandas/tests/groupby/test_function.py

@@ -531,10 +531,16 @@ def test_idxmin_idxmax_returns_int_types(func, values):
         }
     )
     df["c_date"] = pd.to_datetime(df["c_date"])
+    df["c_date_tz"] = df["c_date"].dt.tz_localize("US/Pacific")
+    df["c_timedelta"] = df["c_date"] - df["c_date"].iloc[0]
+    df["c_period"] = df["c_date"].dt.to_period("W")
 
     result = getattr(df.groupby("name"), func)()
 
     expected = DataFrame(values, index=Index(["A", "B"], name="name"))
+    expected["c_date_tz"] = expected["c_date"]
+    expected["c_timedelta"] = expected["c_date"]
+    expected["c_period"] = expected["c_date"]
 
     tm.assert_frame_equal(result, expected)