pyspark.pandas.groupby.GroupBy.rank¶
-
GroupBy.rank(method: str = 'average', ascending: bool = True) → FrameLike[source]¶ Provide the rank of values within each group.
- Parameters
- method{‘average’, ‘min’, ‘max’, ‘first’, ‘dense’}, default ‘average’
average: average rank of group
min: lowest rank in group
max: highest rank in group
first: ranks assigned in order they appear in the array
dense: like ‘min’, but rank always increases by 1 between groups
- ascendingboolean, default True
False for ranks by high (1) to low (N)
- Returns
- DataFrame with ranking of values within each group
Examples
>>> df = ps.DataFrame({ ... 'a': [1, 1, 1, 2, 2, 2, 3, 3, 3], ... 'b': [1, 2, 2, 2, 3, 3, 3, 4, 4]}, columns=['a', 'b']) >>> df a b 0 1 1 1 1 2 2 1 2 3 2 2 4 2 3 5 2 3 6 3 3 7 3 4 8 3 4
>>> df.groupby("a").rank().sort_index() b 0 1.0 1 2.5 2 2.5 3 1.0 4 2.5 5 2.5 6 1.0 7 2.5 8 2.5
>>> df.b.groupby(df.a).rank(method='max').sort_index() 0 1.0 1 3.0 2 3.0 3 1.0 4 3.0 5 3.0 6 1.0 7 3.0 8 3.0 Name: b, dtype: float64