BUG: Fix agg ingore arg/kwargs when given list like func

pandas/core/apply.py

@@ -5,6 +5,7 @@
 from contextlib import nullcontext
 from functools import partial
 import inspect
+from types import FunctionType
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -330,9 +331,18 @@ def agg_list_like(self) -> DataFrame | Series:
             # degenerate case
             if selected_obj.ndim == 1:
 
+                args_remain, kwargs_remain = self.args, self.kwargs
                 for a in arg:
                     colg = obj._gotitem(selected_obj.name, ndim=1, subset=selected_obj)
-                    new_res = colg.aggregate(a)
+                    if not isinstance(a, (np.ufunc, str)) and isinstance(
+                        a, FunctionType
+                    ):
+                        args_pass, kwargs_pass, args_remain, kwargs_remain = _map_args(
+                            a, args_remain, kwargs_remain
+                        )
+                        new_res = colg.aggregate(a, *args_pass, **kwargs_pass)
+                    else:
+                        new_res = colg.aggregate(a)
                     results.append(new_res)
 
                     # make sure we find a good name
@@ -344,7 +354,7 @@ def agg_list_like(self) -> DataFrame | Series:
                 indices = []
                 for index, col in enumerate(selected_obj):
                     colg = obj._gotitem(col, ndim=1, subset=selected_obj.iloc[:, index])
-                    new_res = colg.aggregate(arg)
+                    new_res = colg.aggregate(arg, *self.args, **self.kwargs)
                     results.append(new_res)
                     indices.append(index)
                 keys = selected_obj.columns.take(indices)
@@ -1506,3 +1516,54 @@ def validate_func_kwargs(
         no_arg_message = "Must provide 'func' or named aggregation **kwargs."
         raise TypeError(no_arg_message)
     return columns, func
+
+
+def _map_args(
+    func: AggFuncType, args: tuple, kwargs: dict
+) -> tuple[tuple, dict, tuple, dict]:
+    # GH 50624
+    """
+    Map arguments to function.
+    But for some cases with unnamed arguments, it will cause error.
+
+    Parameters
+    ----------
+    func : function
+    args : tuple
+    kwargs : dict
+
+    Returns
+    -------
+    args_pass : tuple
+        Args should be passed to func
+    kwargs_pass : dict
+        Kwargs should be passed to func
+    args_remain : tuple
+        Args should be passed to other functions
+    kwargs_remain : dict
+        Kwargs should be passed to other functions
+
+    Examples
+    --------
+    >>> def f(a=1, b=2):
+    ...     return a, b
+    >>> _map_args(f, (1,), {'b': 2, 'c': 3})
+    ((1,), {'b': 2}, (), {'c': 3})
+    >>> _map_args(f, (1, 2, 3), {'b': 4}) # maybe some unexpected results
+    ((1, 2), {}, (3,), {'b':4})
+    """
+    argspec = inspect.getfullargspec(func)
+    args_names = argspec.args + argspec.kwonlyargs
+
+    if len(args) >= len(args_names):
+        args_pass = args[: len(args_names)]
+        args_remain = args[len(args_names) :]
+        kwargs_pass = {}
+        kwargs_remain = kwargs
+    else:
+        args_pass = args
+        args_remain = ()
+        kwargs_pass = {k: v for k, v in kwargs.items() if k in args_names}
+        kwargs_remain = {k: v for k, v in kwargs.items() if k not in args_names}
+
+    return args_pass, kwargs_pass, args_remain, kwargs_remain

pandas/tests/apply/test_frame_apply.py

@@ -1623,3 +1623,22 @@ def test_any_apply_keyword_non_zero_axis_regression():
 
     result = df.apply("any", 1)
     tm.assert_series_equal(result, expected)
+
+
+def test_agg_list_like_arg():
+    # GH 50624
+    df = DataFrame({"x": [1, 2, 3]})
+
+    def foo1(x, a=1, b=2):
+        return x + a + b
+
+    def foo2(x, c=3, d=4):
+        return x + c + d
+
+    result = df.agg([foo1, foo2], 0, 5, b=6, c=7, d=8)
+    expected = DataFrame(
+        [[12, 16], [13, 17], [14, 18]],
+        columns=MultiIndex.from_tuples([("x", "foo1"), ("x", "foo2")]),
+        index=[0, 1, 2],
+    )
+    tm.assert_frame_equal(result, expected)