Rolling.
max
Calculate the rolling maximum.
Note
the current implementation of this API uses Spark’s Window without specifying partition specification. This leads to move all data into single partition in single machine and could cause serious performance degradation. Avoid this method against very large dataset.
Return type is determined by the caller.
See also
Series.rolling
Series rolling.
DataFrame.rolling
DataFrame rolling.
Series.max
Similar method for Series.
DataFrame.max
Similar method for DataFrame.
Examples
>>> s = ps.Series([4, 3, 5, 2, 6]) >>> s 0 4 1 3 2 5 3 2 4 6 dtype: int64
>>> s.rolling(2).max() 0 NaN 1 4.0 2 5.0 3 5.0 4 6.0 dtype: float64
>>> s.rolling(3).max() 0 NaN 1 NaN 2 5.0 3 5.0 4 6.0 dtype: float64
For DataFrame, each rolling maximum is computed column-wise.
>>> df = ps.DataFrame({"A": s.to_numpy(), "B": s.to_numpy() ** 2}) >>> df A B 0 4 16 1 3 9 2 5 25 3 2 4 4 6 36
>>> df.rolling(2).max() A B 0 NaN NaN 1 4.0 16.0 2 5.0 25.0 3 5.0 25.0 4 6.0 36.0
>>> df.rolling(3).max() A B 0 NaN NaN 1 NaN NaN 2 5.0 25.0 3 5.0 25.0 4 6.0 36.0