CLN: Use kwargs instead of kwds in apply functions (#39625)

Author: rhshadrach

pandas/core/apply.py

@@ -63,7 +63,7 @@ def frame_apply(
     raw: bool = False,
     result_type: Optional[str] = None,
     args=None,
-    kwds=None,
+    kwargs=None,
 ) -> FrameApply:
     """ construct and return a row or column based frame apply object """
     axis = obj._get_axis_number(axis)
@@ -79,7 +79,7 @@ def frame_apply(
         raw=raw,
         result_type=result_type,
         args=args,
-        kwds=kwds,
+        kwargs=kwargs,
     )
 
 
@@ -88,14 +88,14 @@ def series_apply(
     func: AggFuncType,
     convert_dtype: bool = True,
     args=None,
-    kwds=None,
+    kwargs=None,
 ) -> SeriesApply:
     return SeriesApply(
         obj,
         func,
         convert_dtype,
         args,
-        kwds,
+        kwargs,
     )
 
 
@@ -109,12 +109,12 @@ def __init__(
         raw: bool,
         result_type: Optional[str],
         args,
-        kwds,
+        kwargs,
     ):
         self.obj = obj
         self.raw = raw
         self.args = args or ()
-        self.kwds = kwds or {}
+        self.kwargs = kwargs or {}
 
         if result_type not in [None, "reduce", "broadcast", "expand"]:
             raise ValueError(
@@ -126,13 +126,13 @@ def __init__(
 
         # curry if needed
         if (
-            (kwds or args)
+            (kwargs or args)
             and not isinstance(func, (np.ufunc, str))
             and not is_list_like(func)
         ):
 
             def f(x):
-                return func(x, *args, **kwds)
+                return func(x, *args, **kwargs)
 
         else:
             f = func
@@ -163,7 +163,7 @@ def agg(self) -> Tuple[Optional[FrameOrSeriesUnion], Optional[bool]]:
         obj = self.obj
         arg = self.f
         args = self.args
-        kwargs = self.kwds
+        kwargs = self.kwargs
 
         _axis = kwargs.pop("_axis", None)
         if _axis is None:
@@ -413,10 +413,10 @@ def maybe_apply_str(self) -> Optional[FrameOrSeriesUnion]:
         if callable(func):
             sig = inspect.getfullargspec(func)
             if "axis" in sig.args:
-                self.kwds["axis"] = self.axis
+                self.kwargs["axis"] = self.axis
             elif self.axis != 0:
                 raise ValueError(f"Operation {f} does not support axis=1")
-        return self.obj._try_aggregate_string_function(f, *self.args, **self.kwds)
+        return self.obj._try_aggregate_string_function(f, *self.args, **self.kwargs)
 
     def maybe_apply_multiple(self) -> Optional[FrameOrSeriesUnion]:
         """
@@ -430,7 +430,7 @@ def maybe_apply_multiple(self) -> Optional[FrameOrSeriesUnion]:
         # Note: dict-likes are list-like
         if not is_list_like(self.f):
             return None
-        return self.obj.aggregate(self.f, self.axis, *self.args, **self.kwds)
+        return self.obj.aggregate(self.f, self.axis, *self.args, **self.kwargs)
 
 
 class FrameApply(Apply):
@@ -806,7 +806,7 @@ def __init__(
         func: AggFuncType,
         convert_dtype: bool,
         args,
-        kwds,
+        kwargs,
     ):
         self.convert_dtype = convert_dtype
 
@@ -816,7 +816,7 @@ def __init__(
             raw=False,
             result_type=None,
             args=args,
-            kwds=kwds,
+            kwargs=kwargs,
         )
 
     def apply(self) -> FrameOrSeriesUnion:
@@ -877,17 +877,17 @@ def __init__(
         obj: Union[SeriesGroupBy, DataFrameGroupBy],
         func: AggFuncType,
         args,
-        kwds,
+        kwargs,
     ):
-        kwds = kwds.copy()
-        self.axis = obj.obj._get_axis_number(kwds.get("axis", 0))
+        kwargs = kwargs.copy()
+        self.axis = obj.obj._get_axis_number(kwargs.get("axis", 0))
         super().__init__(
             obj,
             func,
             raw=False,
             result_type=None,
             args=args,
-            kwds=kwds,
+            kwargs=kwargs,
         )
 
     def apply(self):
@@ -903,15 +903,15 @@ def __init__(
         obj: Union[Resampler, BaseWindow],
         func: AggFuncType,
         args,
-        kwds,
+        kwargs,
     ):
         super().__init__(
             obj,
             func,
             raw=False,
             result_type=None,
             args=args,
-            kwds=kwds,
+            kwargs=kwargs,
         )
 
     def apply(self):

pandas/core/frame.py

@@ -7718,7 +7718,7 @@ def _aggregate(self, arg, axis: Axis = 0, *args, **kwargs):
             func=arg,
             axis=0,
             args=args,
-            kwds=kwargs,
+            kwargs=kwargs,
         )
         result, how = op.agg()
 
@@ -7750,7 +7750,7 @@ def apply(
         raw: bool = False,
         result_type=None,
         args=(),
-        **kwds,
+        **kwargs,
     ):
         """
         Apply a function along an axis of the DataFrame.
@@ -7798,7 +7798,7 @@ def apply(
         args : tuple
             Positional arguments to pass to `func` in addition to the
             array/series.
-        **kwds
+        **kwargs
             Additional keyword arguments to pass as keywords arguments to
             `func`.
 
@@ -7892,7 +7892,7 @@ def apply(
             raw=raw,
             result_type=result_type,
             args=args,
-            kwds=kwds,
+            kwargs=kwargs,
         )
         return op.apply()
 

pandas/core/groupby/generic.py

@@ -983,7 +983,7 @@ def aggregate(self, func=None, *args, engine=None, engine_kwargs=None, **kwargs)
                 # try to treat as if we are passing a list
                 try:
                     result, _ = GroupByApply(
-                        self, [func], args=(), kwds={"_axis": self.axis}
+                        self, [func], args=(), kwargs={"_axis": self.axis}
                     ).agg()
 
                     # select everything except for the last level, which is the one

pandas/core/resample.py

@@ -301,7 +301,7 @@ def pipe(
     def aggregate(self, func, *args, **kwargs):
 
         self._set_binner()
-        result, how = ResamplerWindowApply(self, func, args=args, kwds=kwargs).agg()
+        result, how = ResamplerWindowApply(self, func, args=args, kwargs=kwargs).agg()
         if result is None:
             how = func
             grouper = None

pandas/core/series.py

@@ -3967,7 +3967,7 @@ def aggregate(self, func=None, axis=0, *args, **kwargs):
         if func is None:
             func = dict(kwargs.items())
 
-        op = series_apply(self, func, args=args, kwds=kwargs)
+        op = series_apply(self, func, args=args, kwargs=kwargs)
         result, how = op.agg()
         if result is None:
 
@@ -4008,7 +4008,7 @@ def apply(
         func: AggFuncType,
         convert_dtype: bool = True,
         args: Tuple[Any, ...] = (),
-        **kwds,
+        **kwargs,
     ) -> FrameOrSeriesUnion:
         """
         Invoke function on values of Series.
@@ -4025,7 +4025,7 @@ def apply(
             False, leave as dtype=object.
         args : tuple
             Positional arguments passed to func after the series value.
-        **kwds
+        **kwargs
             Additional keyword arguments passed to func.
 
         Returns
@@ -4106,7 +4106,7 @@ def apply(
         Helsinki    2.484907
         dtype: float64
         """
-        op = series_apply(self, func, convert_dtype, args, kwds)
+        op = series_apply(self, func, convert_dtype, args, kwargs)
         return op.apply()
 
     def _reduce(

pandas/core/window/rolling.py

@@ -510,7 +510,7 @@ def calc(x):
             return self._apply_tablewise(homogeneous_func, name)
 
     def aggregate(self, func, *args, **kwargs):
-        result, how = ResamplerWindowApply(self, func, args=args, kwds=kwargs).agg()
+        result, how = ResamplerWindowApply(self, func, args=args, kwargs=kwargs).agg()
         if result is None:
             return self.apply(func, raw=False, args=args, kwargs=kwargs)
         return result
@@ -994,7 +994,7 @@ def calc(x):
         axis="",
     )
     def aggregate(self, func, *args, **kwargs):
-        result, how = ResamplerWindowApply(self, func, args=args, kwds=kwargs).agg()
+        result, how = ResamplerWindowApply(self, func, args=args, kwargs=kwargs).agg()
         if result is None:
 
             # these must apply directly