REGR: fix df.apply with keyword non-zero axis

doc/source/whatsnew/v1.5.1.rst

@@ -78,6 +78,8 @@ Fixed regressions
 - Fixed regression causing an ``AttributeError`` during warning emitted if the provided table name in :meth:`DataFrame.to_sql` and the table name actually used in the database do not match (:issue:`48733`)
 - Fixed :meth:`.DataFrameGroupBy.size` not returning a Series when ``axis=1`` (:issue:`48738`)
 - Fixed Regression in :meth:`DataFrameGroupBy.apply` when user defined function is called on an empty dataframe (:issue:`47985`)
+- Fixed regression in :meth:`DataFrame.apply` when passing non-zero ``axis`` via keyword argument (:issue:`48656`)
+-
 
 .. ---------------------------------------------------------------------------
 

pandas/core/apply.py

@@ -552,10 +552,11 @@ def apply_str(self) -> DataFrame | Series:
         if callable(func):
             sig = inspect.getfullargspec(func)
             if self.axis != 0 and (
-                "axis" not in sig.args or f in ("corrwith", "mad", "skew")
+                ("axis" not in sig.args and "axis" not in sig.kwonlyargs)
+                or f in ("corrwith", "mad", "skew")
             ):
                 raise ValueError(f"Operation {f} does not support axis=1")
-            elif "axis" in sig.args:
+            elif "axis" in sig.args or "axis" in sig.kwonlyargs:
                 self.kwargs["axis"] = self.axis
         return self._try_aggregate_string_function(obj, f, *self.args, **self.kwargs)
 

pandas/tests/groupby/test_any_all.py

@@ -83,6 +83,23 @@ def test_any_non_keyword_deprecation():
     tm.assert_equal(result, expected)
 
 
+def test_any_apply_keyword_non_zero_axis_regression():
+    # https://github.com/pandas-dev/pandas/issues/48656
+    df = DataFrame({"A": [1, 2], "B": [0, 2], "C": [0, 0]})
+    expected = df.any(axis=1)
+    result = df.apply("any", axis=1)
+    tm.assert_series_equal(result, expected)
+
+    msg = (
+        "In a future version of pandas all arguments of "
+        "DataFrame.any and Series.any will be keyword-only."
+    )
+    with tm.assert_produces_warning(FutureWarning, match=msg):
+        expected = df.any(1)
+    result = df.apply("any", 1)
+    tm.assert_series_equal(result, expected)
+
+
 @pytest.mark.parametrize("bool_agg_func", ["any", "all"])
 def test_bool_aggs_dup_column_labels(bool_agg_func):
     # 21668