DEPR: non-keyword arguments in any (pandas-dev#44896)

* tighten return type in any

* correct overload definitions

* add overload def for NDFrame input

* remove overload defs and define function any in sub-classes

* add overload defs for level

* correct default val in overload defs

* deprecate non-keyword args

* add whatsnew note

* modify return types and add tests

* move non-keyword deprecation to generic

* correct deprecation decorators

* remove imports in test assertions

* place deprecate_nonkeyword at correct place

* remove changes from frame.py, series.py

* readd changes in frame, series without actual implementations

* place deprecate_nonkeyword at other place

* add name argument to deprecate_non_keyword_args decorator

* add test for name in deprecate_nonkeyword_args

* remove changes from frame.py, series.py

* correct stacklevel in warning

* correct stacklevel

* set stacklevel to default

* move deprecation message to whatsnew v1.5.0.rst

* add name parameter in deprecate_non_keyword_args docstring

* correct whitespace in deprecate_nonkeyword_args docstring

* update any non-keyword args in other tests

* update any in doc

* update remaining any() calls in pandas/core

* correct docstring of isocalendar in pandas/core/indexes/accessors.py

Co-authored-by: Marco Edward Gorelli <marcogorelli@protonmail.com>

doc/source/whatsnew/v0.13.0.rst

@@ -664,7 +664,7 @@ Enhancements
      other = pd.DataFrame({'A': [1, 3, 3, 7], 'B': ['e', 'f', 'f', 'e']})
      mask = dfi.isin(other)
      mask
-     dfi[mask.any(1)]
+     dfi[mask.any(axis=1)]
 
 - ``Series`` now supports a ``to_frame`` method to convert it to a single-column DataFrame (:issue:`5164`)
 

doc/source/whatsnew/v1.5.0.rst

@@ -429,6 +429,7 @@ Other Deprecations
 - Deprecated behavior of method :meth:`DataFrame.quantile`, attribute ``numeric_only`` will default False. Including datetime/timedelta columns in the result (:issue:`7308`).
 - Deprecated :attr:`Timedelta.freq` and :attr:`Timedelta.is_populated` (:issue:`46430`)
 - Deprecated :attr:`Timedelta.delta` (:issue:`46476`)
+- Deprecated passing arguments as positional in :meth:`DataFrame.any` and :meth:`Series.any` (:issue:`44802`)
 - Deprecated the ``closed`` argument in :meth:`interval_range` in favor of ``inclusive`` argument; In a future version passing ``closed`` will raise (:issue:`40245`)
 - Deprecated the methods :meth:`DataFrame.mad`, :meth:`Series.mad`, and the corresponding groupby methods (:issue:`11787`)
 

pandas/core/generic.py

@@ -7224,7 +7224,7 @@ def asof(self, where, subset=None):
         if not isinstance(where, Index):
             where = Index(where) if is_list else Index([where])
 
-        nulls = self.isna() if is_series else self[subset].isna().any(1)
+        nulls = self.isna() if is_series else self[subset].isna().any(axis=1)
         if nulls.all():
             if is_series:
                 self = cast("Series", self)
@@ -10517,7 +10517,7 @@ def any(
         skipna: bool_t = True,
         level: Level | None = None,
         **kwargs,
-    ) -> Series | bool_t:
+    ) -> DataFrame | Series | bool_t:
         return self._logical_func(
             "any", nanops.nanany, axis, bool_only, skipna, level, **kwargs
         )
@@ -10941,6 +10941,12 @@ def _add_numeric_operations(cls):
         """
         axis_descr, name1, name2 = _doc_params(cls)
 
+        @deprecate_nonkeyword_arguments(
+            version=None,
+            allowed_args=["self"],
+            stacklevel=find_stack_level() - 1,
+            name="DataFrame.any and Series.any",
+        )
         @doc(
             _bool_doc,
             desc=_any_desc,

pandas/core/missing.py

@@ -191,7 +191,7 @@ def find_valid_index(values, *, how: str) -> int | None:
     is_valid = ~isna(values)
 
     if values.ndim == 2:
-        is_valid = is_valid.any(1)  # reduce axis 1
+        is_valid = is_valid.any(axis=1)  # reduce axis 1
 
     if how == "first":
         idxpos = is_valid[::].argmax()

pandas/tests/frame/test_reductions.py

@@ -1066,11 +1066,11 @@ def test_any_all_extra(self):
             },
             index=["a", "b", "c"],
         )
-        result = df[["A", "B"]].any(1)
+        result = df[["A", "B"]].any(axis=1)
         expected = Series([True, True, False], index=["a", "b", "c"])
         tm.assert_series_equal(result, expected)
 
-        result = df[["A", "B"]].any(1, bool_only=True)
+        result = df[["A", "B"]].any(axis=1, bool_only=True)
         tm.assert_series_equal(result, expected)
 
         result = df.all(1)
@@ -1119,7 +1119,7 @@ def test_any_datetime(self):
         ]
         df = DataFrame({"A": float_data, "B": datetime_data})
 
-        result = df.any(1)
+        result = df.any(axis=1)
         expected = Series([True, True, True, False])
         tm.assert_series_equal(result, expected)
 

pandas/tests/groupby/test_any_all.py

@@ -61,6 +61,28 @@ 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

pandas/tests/util/test_deprecate_nonkeyword_arguments.py

@@ -9,7 +9,9 @@
 import pandas._testing as tm
 
 
-@deprecate_nonkeyword_arguments(version="1.1", allowed_args=["a", "b"])
+@deprecate_nonkeyword_arguments(
+    version="1.1", allowed_args=["a", "b"], name="f_add_inputs"
+)
 def f(a, b=0, c=0, d=0):
     return a + b + c + d
 
@@ -44,6 +46,19 @@ def test_four_arguments():
         assert f(1, 2, 3, 4) == 10
 
 
+def test_three_arguments_with_name_in_warning():
+    with warnings.catch_warnings(record=True) as w:
+        warnings.simplefilter("always")
+        assert f(6, 3, 3) == 12
+        assert len(w) == 1
+        for actual_warning in w:
+            assert actual_warning.category == FutureWarning
+            assert str(actual_warning.message) == (
+                "Starting with pandas version 1.1 all arguments of f_add_inputs "
+                "except for the arguments 'a' and 'b' will be keyword-only."
+            )
+
+
 @deprecate_nonkeyword_arguments(version="1.1")
 def g(a, b=0, c=0, d=0):
     with tm.assert_produces_warning(None):

pandas/util/_decorators.py

@@ -261,6 +261,7 @@ def deprecate_nonkeyword_arguments(
     version: str | None,
     allowed_args: list[str] | None = None,
     stacklevel: int = 2,
+    name: str | None = None,
 ) -> Callable[[F], F]:
     """
     Decorator to deprecate a use of non-keyword arguments of a function.
@@ -281,6 +282,11 @@ def deprecate_nonkeyword_arguments(
 
     stacklevel : int, default=2
         The stack level for warnings.warn
+
+    name : str, optional
+        The specific name of the function to show in the warning
+        message. If None, then the Qualified name of the function
+        is used.
     """
 
     def decorate(func):
@@ -296,7 +302,7 @@ def decorate(func):
         num_allow_args = len(allow_args)
         msg = (
             f"{future_version_msg(version)} all arguments of "
-            f"{func.__qualname__}{{arguments}} will be keyword-only."
+            f"{name or func.__qualname__}{{arguments}} will be keyword-only."
         )
 
         @wraps(func)