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

Standard expanding window functions

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

Exponentially-weighted moving window functions

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