pandas多条件分组排序问题 row_number

Question

df = pd.DataFrame({'key1' : ['a','a','a','b','b'],
    'key2' : ['c','d','c','c','d'],
    'data' : [1,10,2,3,30]})

>>> df
  key1 key2  data
0    a    c     1
1    a    d    10
2    a    c     2
3    b    c     3
4    b    d    30

目标结果
key1 key2  data  row_number
0    a    c     1     1
1    a    d    10     1
2    a    c     2     2
3    b    c     3     1
4    b    d    30     1

以key1、key2分组，按照data排序，取出序号应该怎么处理呢？搜索找到的以下方法没有成功

df['row_number'] = df['data'].groupby(df['key1','key2']).rank(ascending=True,method='first')

Answer 1

def cumsum_seq(v):
    sub = v.sort_values('data')
    sub['seq'] = sub['seq'].cumsum()
    return sub.loc[:, ['data', 'seq']]

df['seq'] = 1
df.groupby(['key1', 'key2']).apply(cumsum_seq).reset_index().drop(columns='level_2')

结果

	key1	key2	data	seq
0	a	c	1	1
1	a	c	2	2
2	a	d	10	1
3	b	c	3	1
4	b	d	30	1