DEPR: Enforce deprecation of args/kwargs in Window (#50338)

Author: rhshadrach

doc/source/whatsnew/v2.0.0.rst

@@ -721,6 +721,7 @@ Removal of prior version deprecations/changes
 - When providing a list of columns of length one to :meth:`DataFrame.groupby`, the keys that are returned by iterating over the resulting :class:`DataFrameGroupBy` object will now be tuples of length one (:issue:`47761`)
 - Removed deprecated methods :meth:`ExcelWriter.write_cells`, :meth:`ExcelWriter.save`, :meth:`ExcelWriter.cur_sheet`, :meth:`ExcelWriter.handles`, :meth:`ExcelWriter.path` (:issue:`45795`)
 - The :class:`ExcelWriter` attribute ``book`` can no longer be set; it is still available to be accessed and mutated (:issue:`48943`)
+- Removed unused ``*args`` and ``**kwargs`` in :class:`Rolling`, :class:`Expanding`, and :class:`ExponentialMovingWindow` ops (:issue:`47851`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/compat/numpy/function.py

@@ -335,51 +335,6 @@ def validate_take_with_convert(convert: ndarray | bool | None, args, kwargs) ->
 )
 
 
-def validate_window_func(name, args, kwargs) -> None:
-    numpy_args = ("axis", "dtype", "out")
-    msg = (
-        f"numpy operations are not valid with window objects. "
-        f"Use .{name}() directly instead "
-    )
-
-    if len(args) > 0:
-        raise UnsupportedFunctionCall(msg)
-
-    for arg in numpy_args:
-        if arg in kwargs:
-            raise UnsupportedFunctionCall(msg)
-
-
-def validate_rolling_func(name, args, kwargs) -> None:
-    numpy_args = ("axis", "dtype", "out")
-    msg = (
-        f"numpy operations are not valid with window objects. "
-        f"Use .rolling(...).{name}() instead "
-    )
-
-    if len(args) > 0:
-        raise UnsupportedFunctionCall(msg)
-
-    for arg in numpy_args:
-        if arg in kwargs:
-            raise UnsupportedFunctionCall(msg)
-
-
-def validate_expanding_func(name, args, kwargs) -> None:
-    numpy_args = ("axis", "dtype", "out")
-    msg = (
-        f"numpy operations are not valid with window objects. "
-        f"Use .expanding(...).{name}() instead "
-    )
-
-    if len(args) > 0:
-        raise UnsupportedFunctionCall(msg)
-
-    for arg in numpy_args:
-        if arg in kwargs:
-            raise UnsupportedFunctionCall(msg)
-
-
 def validate_groupby_func(name, args, kwargs, allowed=None) -> None:
     """
     'args' and 'kwargs' should be empty, except for allowed kwargs because all

pandas/core/window/common.py

@@ -3,12 +3,9 @@
 
 from collections import defaultdict
 from typing import cast
-import warnings
 
 import numpy as np
 
-from pandas.util._exceptions import find_stack_level
-
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
     ABCSeries,
@@ -172,38 +169,3 @@ def prep_binary(arg1, arg2):
     X = arg1 + 0 * arg2
     Y = arg2 + 0 * arg1
     return X, Y
-
-
-def maybe_warn_args_and_kwargs(cls, kernel: str, args, kwargs) -> None:
-    """
-    Warn for deprecation of args and kwargs in rolling/expanding functions.
-
-    Parameters
-    ----------
-    cls : type
-        Class to warn about.
-    kernel : str
-        Operation name.
-    args : tuple or None
-        args passed by user. Will be None if and only if kernel does not have args.
-    kwargs : dict or None
-        kwargs passed by user. Will be None if and only if kernel does not have kwargs.
-    """
-    warn_args = args is not None and len(args) > 0
-    warn_kwargs = kwargs is not None and len(kwargs) > 0
-    if warn_args and warn_kwargs:
-        msg = "args and kwargs"
-    elif warn_args:
-        msg = "args"
-    elif warn_kwargs:
-        msg = "kwargs"
-    else:
-        msg = ""
-    if msg != "":
-        warnings.warn(
-            f"Passing additional {msg} to {cls.__name__}.{kernel} has "
-            "no impact on the result and is deprecated. This will "
-            "raise a TypeError in a future version of pandas.",
-            category=FutureWarning,
-            stacklevel=find_stack_level(),
-        )

pandas/core/window/doc.py

@@ -40,24 +40,6 @@ def create_section_header(header: str) -> str:
     """
 ).replace("\n", "", 1)
 
-args_compat = dedent(
-    """
-    *args
-        For NumPy compatibility and will not have an effect on the result.
-
-        .. deprecated:: 1.5.0\n
-    """
-).replace("\n", "", 1)
-
-kwargs_compat = dedent(
-    """
-    **kwargs
-        For NumPy compatibility and will not have an effect on the result.
-
-        .. deprecated:: 1.5.0\n
-    """
-).replace("\n", "", 1)
-
 kwargs_scipy = dedent(
     """
     **kwargs

pandas/core/window/ewm.py

@@ -18,7 +18,6 @@
     from pandas import DataFrame, Series
     from pandas.core.generic import NDFrame
 
-from pandas.compat.numpy import function as nv
 from pandas.util._decorators import doc
 
 from pandas.core.dtypes.common import (
@@ -37,15 +36,10 @@
     get_jit_arguments,
     maybe_use_numba,
 )
-from pandas.core.window.common import (
-    maybe_warn_args_and_kwargs,
-    zsqrt,
-)
+from pandas.core.window.common import zsqrt
 from pandas.core.window.doc import (
     _shared_docs,
-    args_compat,
     create_section_header,
-    kwargs_compat,
     kwargs_numeric_only,
     numba_notes,
     template_header,
@@ -503,9 +497,7 @@ def aggregate(self, func, *args, **kwargs):
         template_header,
         create_section_header("Parameters"),
         kwargs_numeric_only,
-        args_compat,
         window_agg_numba_parameters(),
-        kwargs_compat,
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
@@ -519,12 +511,9 @@ def aggregate(self, func, *args, **kwargs):
     def mean(
         self,
         numeric_only: bool = False,
-        *args,
         engine=None,
         engine_kwargs=None,
-        **kwargs,
     ):
-        maybe_warn_args_and_kwargs(type(self), "mean", args, kwargs)
         if maybe_use_numba(engine):
             if self.method == "single":
                 func = generate_numba_ewm_func
@@ -542,7 +531,6 @@ def mean(
         elif engine in ("cython", None):
             if engine_kwargs is not None:
                 raise ValueError("cython engine does not accept engine_kwargs")
-            nv.validate_window_func("mean", args, kwargs)
 
             deltas = None if self.times is None else self._deltas
             window_func = partial(
@@ -561,9 +549,7 @@ def mean(
         template_header,
         create_section_header("Parameters"),
         kwargs_numeric_only,
-        args_compat,
         window_agg_numba_parameters(),
-        kwargs_compat,
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
@@ -577,12 +563,9 @@ def mean(
     def sum(
         self,
         numeric_only: bool = False,
-        *args,
         engine=None,
         engine_kwargs=None,
-        **kwargs,
     ):
-        maybe_warn_args_and_kwargs(type(self), "sum", args, kwargs)
         if not self.adjust:
             raise NotImplementedError("sum is not implemented with adjust=False")
         if maybe_use_numba(engine):
@@ -602,7 +585,6 @@ def sum(
         elif engine in ("cython", None):
             if engine_kwargs is not None:
                 raise ValueError("cython engine does not accept engine_kwargs")
-            nv.validate_window_func("sum", args, kwargs)
 
             deltas = None if self.times is None else self._deltas
             window_func = partial(
@@ -627,8 +609,6 @@ def sum(
         """
         ).replace("\n", "", 1),
         kwargs_numeric_only,
-        args_compat,
-        kwargs_compat,
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
@@ -637,9 +617,7 @@ def sum(
         aggregation_description="(exponential weighted moment) standard deviation",
         agg_method="std",
     )
-    def std(self, bias: bool = False, numeric_only: bool = False, *args, **kwargs):
-        maybe_warn_args_and_kwargs(type(self), "std", args, kwargs)
-        nv.validate_window_func("std", args, kwargs)
+    def std(self, bias: bool = False, numeric_only: bool = False):
         if (
             numeric_only
             and self._selected_obj.ndim == 1
@@ -649,7 +627,7 @@ def std(self, bias: bool = False, numeric_only: bool = False, *args, **kwargs):
             raise NotImplementedError(
                 f"{type(self).__name__}.std does not implement numeric_only"
             )
-        return zsqrt(self.var(bias=bias, numeric_only=numeric_only, **kwargs))
+        return zsqrt(self.var(bias=bias, numeric_only=numeric_only))
 
     @doc(
         template_header,
@@ -661,8 +639,6 @@ def std(self, bias: bool = False, numeric_only: bool = False, *args, **kwargs):
         """
         ).replace("\n", "", 1),
         kwargs_numeric_only,
-        args_compat,
-        kwargs_compat,
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
@@ -671,9 +647,7 @@ def std(self, bias: bool = False, numeric_only: bool = False, *args, **kwargs):
         aggregation_description="(exponential weighted moment) variance",
         agg_method="var",
     )
-    def var(self, bias: bool = False, numeric_only: bool = False, *args, **kwargs):
-        maybe_warn_args_and_kwargs(type(self), "var", args, kwargs)
-        nv.validate_window_func("var", args, kwargs)
+    def var(self, bias: bool = False, numeric_only: bool = False):
         window_func = window_aggregations.ewmcov
         wfunc = partial(
             window_func,
@@ -708,7 +682,6 @@ def var_func(values, begin, end, min_periods):
         """
         ).replace("\n", "", 1),
         kwargs_numeric_only,
-        kwargs_compat,
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
@@ -723,11 +696,9 @@ def cov(
         pairwise: bool | None = None,
         bias: bool = False,
         numeric_only: bool = False,
-        **kwargs,
     ):
         from pandas import Series
 
-        maybe_warn_args_and_kwargs(type(self), "cov", None, kwargs)
         self._validate_numeric_only("cov", numeric_only)
 
         def cov_func(x, y):
@@ -783,7 +754,6 @@ def cov_func(x, y):
         """
         ).replace("\n", "", 1),
         kwargs_numeric_only,
-        kwargs_compat,
         create_section_header("Returns"),
         template_returns,
         create_section_header("See Also"),
@@ -797,11 +767,9 @@ def corr(
         other: DataFrame | Series | None = None,
         pairwise: bool | None = None,
         numeric_only: bool = False,
-        **kwargs,
     ):
         from pandas import Series
 
-        maybe_warn_args_and_kwargs(type(self), "corr", None, kwargs)
         self._validate_numeric_only("corr", numeric_only)
 
         def cov_func(x, y):
@@ -940,7 +908,6 @@ def corr(
         other: DataFrame | Series | None = None,
         pairwise: bool | None = None,
         numeric_only: bool = False,
-        **kwargs,
     ):
         raise NotImplementedError("corr is not implemented.")
 
@@ -950,11 +917,10 @@ def cov(
         pairwise: bool | None = None,
         bias: bool = False,
         numeric_only: bool = False,
-        **kwargs,
     ):
         raise NotImplementedError("cov is not implemented.")
 
-    def var(self, bias: bool = False, *args, **kwargs):
+    def var(self, bias: bool = False, numeric_only: bool = False):
         raise NotImplementedError("var is not implemented.")
 
     def mean(self, *args, update=None, update_times=None, **kwargs):