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() |
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. |