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