pandas/core/window/ewm.py
def mean(self, *args, **kwargs):
        """
        Exponential weighted moving average.

        Parameters
        ----------
        *args, **kwargs
            Arguments and keyword arguments to be passed into func.
        """
        nv.validate_window_func("mean", args, kwargs)
        if self.times is not None:
            window_func = window_aggregations.ewma_time
            window_func = partial(
                window_func,
                times=self.times,
                halflife=self.halflife,
            )
        else:
            window_func = window_aggregations.ewma
            window_func = partial(
                window_func,
                com=self.com,
                adjust=self.adjust,
                ignore_na=self.ignore_na,
            )
        return self._apply(window_func)

        Exponential weighted moving average.

        Parameters
        ----------
        *args, **kwargs
            Arguments and keyword arguments to be passed into func.
        
Exponential weighted moving average.
Parameters

args, **kwargs
Arguments and keyword arguments to be passed into func.
Exponential weighted moving average . Parameters args ** kwargs Arguments and keyword arguments to be passed into func .
def mean(self, *args, **kwargs):
        nv.validate_window_func("mean", args, kwargs)
        if self.times is not None:
            window_func = window_aggregations.ewma_time
            window_func = partial(
                window_func,
                times=self.times,
                halflife=self.halflife,
            )
        else:
            window_func = window_aggregations.ewma
            window_func = partial(
                window_func,
                com=self.com,
                adjust=self.adjust,
                ignore_na=self.ignore_na,
            )
        return self._apply(window_func)
def mean ( self , * args , ** kwargs ) : nv . validate_window_func ( "mean" , args , kwargs ) if self . times is not None : window_func = window_aggregations . ewma_time window_func = partial ( window_func , times = self . times , halflife = self . halflife , ) else : window_func = window_aggregations . ewma window_func = partial ( window_func , com = self . com , adjust = self . adjust , ignore_na = self . ignore_na , ) return self . _apply ( window_func )
Exponential weighted moving average.
Exponential weighted moving average .
"""
        Exponential weighted moving average.

        Parameters
        ----------
        *args, **kwargs
            Arguments and keyword arguments to be passed into func.
        """
self