pyspark.pandas.groupby.GroupBy.cummax#
- GroupBy.cummax()[source]#
- Cumulative max for each group. - Returns
- Series or DataFrame
 
 - See also - Series.cummax
- DataFrame.cummax
 - Examples - >>> df = ps.DataFrame( ... [[1, None, 4], [1, 0.1, 3], [1, 20.0, 2], [4, 10.0, 1]], ... columns=list('ABC')) >>> df A B C 0 1 NaN 4 1 1 0.1 3 2 1 20.0 2 3 4 10.0 1 - By default, iterates over rows and finds the sum in each column. - >>> df.groupby("A").cummax().sort_index() B C 0 NaN 4 1 0.1 4 2 20.0 4 3 10.0 1 - It works as below in Series. - >>> df.C.groupby(df.A).cummax().sort_index() 0 4 1 4 2 4 3 1 Name: C, dtype: int64