diff --git a/pandas/core/apply.py b/pandas/core/apply.py index 533190e692891..828b460f84ec6 100644 --- a/pandas/core/apply.py +++ b/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): @@ -903,7 +903,7 @@ def __init__( obj: Union[Resampler, BaseWindow], func: AggFuncType, args, - kwds, + kwargs, ): super().__init__( obj, @@ -911,7 +911,7 @@ def __init__( raw=False, result_type=None, args=args, - kwds=kwds, + kwargs=kwargs, ) def apply(self): diff --git a/pandas/core/frame.py b/pandas/core/frame.py index 6357b8feb348b..ee27e38c6f556 100644 --- a/pandas/core/frame.py +++ b/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() diff --git a/pandas/core/groupby/generic.py b/pandas/core/groupby/generic.py index 12698efa86b28..7b6eb4c8fe2f9 100644 --- a/pandas/core/groupby/generic.py +++ b/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 diff --git a/pandas/core/resample.py b/pandas/core/resample.py index 965de2e04bf40..34b7838d2280c 100644 --- a/pandas/core/resample.py +++ b/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 diff --git a/pandas/core/series.py b/pandas/core/series.py index 8bd325beede65..89ccddf4c9aa2 100644 --- a/pandas/core/series.py +++ b/pandas/core/series.py @@ -3940,7 +3940,7 @@ 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: @@ -3981,7 +3981,7 @@ def apply( func: AggFuncType, convert_dtype: bool = True, args: Tuple[Any, ...] = (), - **kwds, + **kwargs, ) -> FrameOrSeriesUnion: """ Invoke function on values of Series. @@ -3998,7 +3998,7 @@ 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 @@ -4079,7 +4079,7 @@ 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( diff --git a/pandas/core/window/rolling.py b/pandas/core/window/rolling.py index 9a68e470201c7..bec6cfb375716 100644 --- a/pandas/core/window/rolling.py +++ b/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