Rolling.
min
Calculate the rolling minimum.
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.
Returned object type is determined by the caller of the rolling calculation.
See also
pyspark.pandas.Series.rolling
Calling object with a Series.
pyspark.pandas.DataFrame.rolling
Calling object with a DataFrame.
pyspark.pandas.Series.min
Similar method for Series.
pyspark.pandas.DataFrame.min
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).min() 0 NaN 1 3.0 2 3.0 3 2.0 4 2.0 dtype: float64
>>> s.rolling(3).min() 0 NaN 1 NaN 2 3.0 3 2.0 4 2.0 dtype: float64
For DataFrame, each rolling minimum 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).min() A B 0 NaN NaN 1 3.0 9.0 2 3.0 9.0 3 2.0 4.0 4 2.0 4.0
>>> df.rolling(3).min() A B 0 NaN NaN 1 NaN NaN 2 3.0 9.0 3 2.0 4.0 4 2.0 4.0