python - 2 groupby 在同一个数据框中，可能吗？

Question

我想要以下 df，制作一个 df = df.groupby(['id','quarter'])['jobs].mean() 但同时数据框必须具有另一列中按 ID 和年份列出的职位的平均值。

 id    year   quarter    month    jobs
  1    2007      1         1        10      
  1    2007      1         2        12    
  1    2007      1         3        12 
  1    2007      2         4        12      
  1    2007      2         5        12
  1    2007      2         6        13
  1    2007      3         7        14
  1    2007      3         8         9
  1    2007      3         9        12
  1    2007      4         10       15
  1    2007      4         12       18
  2    2007      1         1        15
  2    2007      1         2        15
  2    2007      1         3        16
  2    2007      2         4        17
  2    2007      2         5        18
  2    2007      2         6        10      
  2    2007      3         7        12    
  2    2007      3         8        12 
  2    2007      3         9        12      
  2    2007      4         10       12
  2    2007      4         11       13
  2    2007      4         12       14

结果应该是这样的

 id    year   quarter         jobs         jobs_year
  1    2007      1       (mean quarter)   (mean year)    
  1    2007      2       (mean quarter)   (mean year)    
  1    2007      3       (mean quarter)   (mean year) 
  1    2007      4       (mean quarter)   (mean year) 
  2    2007      1       (mean quarter)   (mean year) 
  2    2007      2       (mean quarter)   (mean year) 
  2    2007      3       (mean quarter)   (mean year) 
  2    2007      4       (mean quarter)   (mean year) 

Answer 1

使用transform然后drop_duplicates

df['jobs1']=df.groupby(['id','quarter'])['jobs'].transform('mean')
df['jobs_year']=df.groupby(['id','year'])['jobs'].transform('mean')
df=df.drop_duplicates(['id','year','quarter'])
df
Out[305]: 
    id  year  quarter  month  jobs      jobs1  jobs_year
0    1  2007        1      1    10  11.333333  12.636364
3    1  2007        2      4    12  12.333333  12.636364
6    1  2007        3      7    14  11.666667  12.636364
9    1  2007        4     10    15  16.500000  12.636364
11   2  2007        1      1    15  15.333333  13.833333
14   2  2007        2      4    17  15.000000  13.833333
17   2  2007        3      7    12  12.000000  13.833333
20   2  2007        4     10    12  13.000000  13.833333