REGR: fix df.apply with keyword non-zero axis (pandas-dev#48797)

doc/source/whatsnew/v1.5.1.rst

@@ -82,6 +82,8 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.fillna` replacing wrong values for ``datetime64[ns]`` dtype and ``inplace=True`` (:issue:`48863`)
 - 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

@@ -555,11 +555,12 @@ def apply_str(self) -> DataFrame | Series:
         func = getattr(obj, f, None)
         if callable(func):
             sig = inspect.getfullargspec(func)
+            arg_names = (*sig.args, *sig.kwonlyargs)
             if self.axis != 0 and (
-                "axis" not in sig.args or f in ("corrwith", "mad", "skew")
+                "axis" not in arg_names or f in ("corrwith", "mad", "skew")
             ):
                 raise ValueError(f"Operation {f} does not support axis=1")
-            elif "axis" in sig.args:
+            elif "axis" in arg_names:
                 self.kwargs["axis"] = self.axis
         return self._try_aggregate_string_function(obj, f, *self.args, **self.kwargs)
 

pandas/tests/apply/test_frame_apply.py

@@ -1604,3 +1604,38 @@ def test_unique_agg_type_is_series(test, constant):
     result = df1.agg(aggregation)
 
     tm.assert_series_equal(result, expected)
+
+
+def test_any_non_keyword_deprecation():
+    df = DataFrame({"A": [1, 2], "B": [0, 2], "C": [0, 0]})
+    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):
+        result = df.any("index", None)
+    expected = Series({"A": True, "B": True, "C": False})
+    tm.assert_series_equal(result, expected)
+
+    s = Series([False, False, False])
+    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):
+        result = s.any("index")
+    expected = False
+    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, 0], "B": [0, 2, 0], "C": [0, 0, 0]})
+    expected = Series([True, True, False])
+    tm.assert_series_equal(df.any(axis=1), expected)
+
+    result = df.apply("any", axis=1)
+    tm.assert_series_equal(result, expected)
+
+    result = df.apply("any", 1)
+    tm.assert_series_equal(result, expected)

pandas/tests/groupby/test_any_all.py

@@ -61,28 +61,6 @@ def test_any():
     tm.assert_frame_equal(result, expected)
 
 
-def test_any_non_keyword_deprecation():
-    df = DataFrame({"A": [1, 2], "B": [0, 2], "C": [0, 0]})
-    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):
-        result = df.any("index", None)
-    expected = Series({"A": True, "B": True, "C": False})
-    tm.assert_series_equal(result, expected)
-
-    s = Series([False, False, False])
-    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):
-        result = s.any("index")
-    expected = False
-    tm.assert_equal(result, expected)
-
-
 @pytest.mark.parametrize("bool_agg_func", ["any", "all"])
 def test_bool_aggs_dup_column_labels(bool_agg_func):
     # 21668