pyspark.pandas.window.Rolling.min¶
-
Rolling.min() → FrameLike[source]¶ 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.
- Returns
- Series or DataFrame
Returned object type is determined by the caller of the rolling calculation.
See also
pyspark.pandas.Series.rollingCalling object with a Series.
pyspark.pandas.DataFrame.rollingCalling object with a DataFrame.
pyspark.pandas.Series.minSimilar method for Series.
pyspark.pandas.DataFrame.minSimilar 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