python - Groupby Pandas 抛出 ValueError : Grouper and axis must be same length

Question

我有下面的csv

ID,PR_No,PMO,PRO,REV,COST
111,111,AB,MA,2575,2575
111,111,AB,MA,-1137,-1137
112,112,CD,KB,1134,3334
111,111,AB,MA,100,100

输出如下

ID,PR_No,PMO,PRO,REV,COST
111,111,AB,MA,1538,1538
112,112,CD,KB,1134,3334

1538=2575-1137+100

我的代码抛出值错误

df_n = df.groupby([['ID','PR_No','PMO','PRO']]).agg({'REV':sum,'COST':sum})

Answer 1

删除嵌套 []对于列名称列表:

df_n = df.groupby(['ID','PR_No','PMO','PRO']).agg({'REV':sum,'COST':sum})
print (df_n)
                    REV  COST
ID  PR_No PMO PRO            
111 111   AB  MA   1538  1538
112 112   CD  KB   1134  3334

因为相同的聚合函数可以在 groupby 之后使用 .sum 创建列表:

df_n = df.groupby(['ID','PR_No','PMO','PRO'])['REV','COST'].sum()

ValueError: Grouper and axis must be same length

这是什么意思？

如果使用示例数据运行它可以工作，因为嵌套列表的长度与示例数据的长度相同:

df_n = df.groupby([['ID','PR_No','PMO','PRO']]).agg({'REV':sum,'COST':sum})
print (df_n)
        REV  COST
ID     2575  2575
PMO    1134  3334
PRO     100   100
PR_No -1137 -1137

如果创建具有重复项的列表，它会聚合示例数据:

df_n = df.groupby([['ID','ID','PRO','PRO']]).agg({'REV':sum,'COST':sum})
print (df_n)
      REV  COST
ID   1438  1438
PRO  1234  3434

但如果长度不同，则失败:

print (df)
    ID  PR_No PMO PRO   REV  COST
0  111    111  AB  MA  2575  2575
1  111    111  AB  MA -1137 -1137
2  112    112  CD  KB  1134  3334
3  111    111  AB  MA   100   100
4  111    111  AB  MA   100   100 <- added new row

df_n = df.groupby([['ID','ID','PRO','PRO']]).agg({'REV':sum,'COST':sum})
print (df_n)

ValueError: Grouper and axis must be same length