Backport PR #36950: REGR: Allow positional arguments in DataFrame.agg (#37005)

Co-authored-by: Paul Ganssle <[email protected]>

Author: meeseeksmachine

doc/source/whatsnew/v1.1.4.rst

@@ -15,6 +15,7 @@ including other versions of pandas.
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Fixed regression where attempting to mutate a :class:`DateOffset` object would no longer raise an ``AttributeError`` (:issue:`36940`)
+- Fixed regression where :meth:`DataFrame.agg` would fail with :exc:`TypeError` when passed positional arguments to be passed on to the aggregation function (:issue:`36948`).
 - Fixed regression in :class:`RollingGroupby` with ``sort=False`` not being respected (:issue:`36889`)
 
 .. ---------------------------------------------------------------------------

pandas/core/frame.py

@@ -7359,7 +7359,7 @@ def aggregate(self, func=None, axis=0, *args, **kwargs):
 
         result = None
         try:
-            result, how = self._aggregate(func, axis=axis, *args, **kwargs)
+            result, how = self._aggregate(func, axis, *args, **kwargs)
         except TypeError as err:
             exc = TypeError(
                 "DataFrame constructor called with "

pandas/tests/frame/apply/test_frame_apply.py

@@ -1480,6 +1480,34 @@ def test_agg_cython_table_raises(self, df, func, expected, axis):
         with pytest.raises(expected, match=msg):
             df.agg(func, axis=axis)
 
+    @pytest.mark.parametrize("axis", [0, 1])
+    @pytest.mark.parametrize(
+        "args, kwargs",
+        [
+            ((1, 2, 3), {}),
+            ((8, 7, 15), {}),
+            ((1, 2), {}),
+            ((1,), {"b": 2}),
+            ((), {"a": 1, "b": 2}),
+            ((), {"a": 2, "b": 1}),
+            ((), {"a": 1, "b": 2, "c": 3}),
+        ],
+    )
+    def test_agg_args_kwargs(self, axis, args, kwargs):
+        def f(x, a, b, c=3):
+            return x.sum() + (a + b) / c
+
+        df = pd.DataFrame([[1, 2], [3, 4]])
+
+        if axis == 0:
+            expected = pd.Series([5.0, 7.0])
+        else:
+            expected = pd.Series([4.0, 8.0])
+
+        result = df.agg(f, axis, *args, **kwargs)
+
+        tm.assert_series_equal(result, expected)
+
     @pytest.mark.parametrize("num_cols", [2, 3, 5])
     def test_frequency_is_original(self, num_cols):
         # GH 22150