Window

Rolling objects are returned by .rolling calls: pandas.DataFrame.rolling(), pandas.Series.rolling(), etc.Expanding objects are returned by .expanding calls: pandas.DataFrame.expanding(), pandas.Series.expanding(), etc.EWM objects are returned by .ewm calls: pandas.DataFrame.ewm(), pandas.Series.ewm(), etc.

Standard moving window functions

Rolling.count(self)The rolling count of any non-NaN observations inside the window.
Rolling.sum(self, *args, **kwargs)Calculate rolling sum of given DataFrame or Series.
Rolling.mean(self, *args, **kwargs)Calculate the rolling mean of the values.
Rolling.median(self, **kwargs)Calculate the rolling median.
Rolling.var(self[, ddof])Calculate unbiased rolling variance.
Rolling.std(self[, ddof])Calculate rolling standard deviation.
Rolling.min(self, *args, **kwargs)Calculate the rolling minimum.
Rolling.max(self, *args, **kwargs)Calculate the rolling maximum.
Rolling.corr(self[, other, pairwise])Calculate rolling correlation.
Rolling.cov(self[, other, pairwise, ddof])Calculate the rolling sample covariance.
Rolling.skew(self, **kwargs)Unbiased rolling skewness.
Rolling.kurt(self, **kwargs)Calculate unbiased rolling kurtosis.
Rolling.apply(self, func[, raw, args, kwargs])The rolling function’s apply function.
Rolling.aggregate(self, arg, *args, **kwargs)Aggregate using one or more operations over the specified axis.
Rolling.quantile(self, quantile[, interpolation])Calculate the rolling quantile.
Window.mean(self, *args, **kwargs)Calculate the window mean of the values.
Window.sum(self, *args, **kwargs)Calculate window sum of given DataFrame or Series.

Standard expanding window functions

Expanding.count(self, **kwargs)The expanding count of any non-NaN observations inside the window.
Expanding.sum(self, *args, **kwargs)Calculate expanding sum of given DataFrame or Series.
Expanding.mean(self, *args, **kwargs)Calculate the expanding mean of the values.
Expanding.median(self, **kwargs)Calculate the expanding median.
Expanding.var(self[, ddof])Calculate unbiased expanding variance.
Expanding.std(self[, ddof])Calculate expanding standard deviation.
Expanding.min(self, *args, **kwargs)Calculate the expanding minimum.
Expanding.max(self, *args, **kwargs)Calculate the expanding maximum.
Expanding.corr(self[, other, pairwise])Calculate expanding correlation.
Expanding.cov(self[, other, pairwise, ddof])Calculate the expanding sample covariance.
Expanding.skew(self, **kwargs)Unbiased expanding skewness.
Expanding.kurt(self, **kwargs)Calculate unbiased expanding kurtosis.
Expanding.apply(self, func[, raw, args, kwargs])The expanding function’s apply function.
Expanding.aggregate(self, arg, *args, …)Aggregate using one or more operations over the specified axis.
Expanding.quantile(self, quantile[, …])Calculate the expanding quantile.

Exponentially-weighted moving window functions

EWM.mean(self, *args, **kwargs)Exponential weighted moving average.
EWM.std(self[, bias])Exponential weighted moving stddev.
EWM.var(self[, bias])Exponential weighted moving variance.
EWM.corr(self[, other, pairwise])Exponential weighted sample correlation.
EWM.cov(self[, other, pairwise, bias])Exponential weighted sample covariance.