Backport PR pandas-dev#43709: REGR: Passing args/kwargs to Series.agg fails (pandas-dev#43716)

Co-authored-by: Richard Shadrach <[email protected]>

Author: meeseeksmachine

doc/source/whatsnew/v1.3.4.rst

@@ -20,7 +20,7 @@ Fixed regressions
 - Fixed regression in :meth:`Series.cat.reorder_categories` failing to update the categories on the ``Series`` (:issue:`43232`)
 - Fixed regression in :meth:`Series.cat.categories` setter failing to update the categories on the ``Series`` (:issue:`43334`)
 - Fixed regression in :meth:`pandas.read_csv` raising ``UnicodeDecodeError`` exception when ``memory_map=True`` (:issue:`43540`)
--
+- Fixed regression in :meth:`Series.aggregate` attempting to pass ``args`` and ``kwargs`` multiple times to the user supplied ``func`` in certain cases (:issue:`43357`)
 
 .. ---------------------------------------------------------------------------
 
@@ -29,6 +29,7 @@ Fixed regressions
 Bug fixes
 ~~~~~~~~~
 - Fixed bug in :meth:`.GroupBy.mean` with datetimelike values including ``NaT`` values returning incorrect results (:issue:`43132`)
+- Fixed bug in :meth:`Series.aggregate` not passing the first ``args`` to the user supplied ``func`` in certain cases (:issue:`43357`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/apply.py

@@ -1046,7 +1046,6 @@ def agg(self):
         result = super().agg()
         if result is None:
             f = self.f
-            args = self.args
             kwargs = self.kwargs
 
             # string, list-like, and dict-like are entirely handled in super
@@ -1065,9 +1064,9 @@ def agg(self):
             # then .agg and .apply would have different semantics if the
             # operation is actually defined on the Series, e.g. str
             try:
-                result = self.obj.apply(f, *args, **kwargs)
+                result = self.obj.apply(f)
             except (ValueError, AttributeError, TypeError):
-                result = f(self.obj, *args, **kwargs)
+                result = f(self.obj)
 
         return result
 

pandas/tests/apply/test_series_apply.py

@@ -103,6 +103,21 @@ def test_apply_args():
     assert isinstance(result[0], list)
 
 
+@pytest.mark.parametrize(
+    "args, kwargs, increment",
+    [((), {}, 0), ((), {"a": 1}, 1), ((2, 3), {}, 32), ((1,), {"c": 2}, 201)],
+)
+def test_agg_args(args, kwargs, increment):
+    # GH 43357
+    def f(x, a=0, b=0, c=0):
+        return x + a + 10 * b + 100 * c
+
+    s = Series([1, 2])
+    result = s.agg(f, 0, *args, **kwargs)
+    expected = s + increment
+    tm.assert_series_equal(result, expected)
+
+
 def test_series_map_box_timestamps():
     # GH#2689, GH#2627
     ser = Series(pd.date_range("1/1/2000", periods=10))