Window

Rolling objects are returned by .rolling calls: pyspark.pandas.DataFrame.rolling(), pyspark.pandas.Series.rolling(), etc.

Expanding objects are returned by .expanding calls: pyspark.pandas.DataFrame.expanding(), pyspark.pandas.Series.expanding(), etc.

ExponentialMoving objects are returned by .ewm calls: pyspark.pandas.DataFrame.ewm(), pyspark.pandas.Series.ewm(), etc.

Standard moving window functions

Rolling.count()	The rolling count of any non-NaN observations inside the window.
Rolling.sum()	Calculate rolling summation of given DataFrame or Series.
Rolling.min()	Calculate the rolling minimum.
Rolling.max()	Calculate the rolling maximum.
Rolling.mean()	Calculate the rolling mean of the values.
Rolling.quantile(quantile[, accuracy])	Calculate the rolling quantile of the values.

Standard expanding window functions

Expanding.count()	The expanding count of any non-NaN observations inside the window.
Expanding.sum()	Calculate expanding summation of given DataFrame or Series.
Expanding.min()	Calculate the expanding minimum.
Expanding.max()	Calculate the expanding maximum.
Expanding.mean()	Calculate the expanding mean of the values.
Expanding.quantile(quantile[, accuracy])	Calculate the expanding quantile of the values.

Exponential moving window functions

ExponentialMoving.mean()

Calculate an online exponentially weighted mean.

pyspark.pandas.TimedeltaIndex.microseconds pyspark.pandas.window.Rolling.count