在Pandas中

时间:2018-05-22 15:47:23

标签: python pandas pivot aggregate

我正在使用group by来获取汇总值。 我的数据集:

df=pd.DataFrame({"A":['a','a','a','a','a','a','b','b','b','b'],
         "Sales":[2,3,7,1,4,3,5,6,9,10],
         "Units":[12,2,2,33,6,2,4,8,3,5],
         "Week":[1,2,2,1,2,1,1,2,2,1]})

在此之后,我正在应用这个功能:

def my_agg(x):
    names = {
        'Sales': x['Sales'].sum(),
        'Units': x['Sales'].sum()
             } 

    return pd.Series(names, index=['Sales','Units'])
dfA= df.groupby(['A','Week']).apply(my_agg)

给我输出:

    Sales  Units
A Week              
a 1         6      6
  2        14     14
b 1        15     15
  2        15     15

我想将一周转换成列。像这样: 需要的输出:

   Week 1              2      
A      Sales  Units   Sales  Units        
a         6     6      14     14   
b        15    15      15     15

另外,请为OUTPUT 2建议:

           Sales         Units
A  Week   1            2
a         6    14      6      14   
b        15    15     15      15

2 个答案:

答案 0 :(得分:2)

带有unstack

swaplevel

s=dfA.unstack()
s
Out[127]: 
     Sales     Units    
Week     1   2     1   2
A                       
a        6  14     6  14
b       15  15    15  15
s.swaplevel(0,1,axis=1).sort_index(level=0,axis=1)
Out[128]: 
Week     1           2      
     Sales Units Sales Units
A                           
a        6     6    14    14
b       15    15    15    15

答案 1 :(得分:1)

输出1

df.pivot_table(index='A', columns='Week', aggfunc='sum').swaplevel(1, 0, 1)

Week     1     2     1     2
     Sales Sales Units Units
A                           
a        6    14    47    10
b       15    15     9    11

输出2

df.pivot_table(index='A', columns='Week', aggfunc='sum')

     Sales     Units    
Week     1   2     1   2
A                       
a        6  14    47  10
b       15  15     9  11