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