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