python-2.7 - 在忽略特定键的数据框中减去值

Question

我有两个数据框:

df1 = pd.DataFrame({ 'pressure' : [42,42,42,42,42,42,42,36,36,36,36,36,36,36], 
                     'load' : [350,350,350,350,350,350,350,700,700,700,700,700,700,700], 
                     'speed' : [70,60,50,40,30,20,10,70,60,50,40,30,20,10], 
                     'lforce' : [3.6,3.5,3.3,3.2,3.1,3.1,2.9,7.7,7.3,7.0,6.8,6.5,6.4,6.1],
                     'rforce' : [3.4,3.2,3.1,3.0,2.9,2.8,2.7,7.6,7.2,6.9,6.6,6.3,6.2,5.9]
                     }).set_index(['pressure','load','speed'])

df2 = pd.DataFrame({ 'pressure' : [47,47,47,47,47,47,47], 
                     'load' : [20,20,20,20,20,20,20], 
                     'speed' : [70,60,50,40,30,20,10], 
                     'lforce' : [2.5,2.1,1.9,1.7,1.5,1.3,1.2],
                     'rforce' : [2.8,2.6,2.4,2.2,2.0,1.8,1.7]
                     }).set_index(['pressure','load','speed'])

格式化:

>>> df1
                     lforce  rforce
pressure load speed                
42       350  70        3.6     3.4
              60        3.5     3.2
              50        3.3     3.1
              40        3.2     3.0
              30        3.1     2.9
              20        3.1     2.8
              10        2.9     2.7
36       700  70        7.7     7.6
              60        7.3     7.2
              50        7.0     6.9
              40        6.8     6.6
              30        6.5     6.3
              20        6.4     6.2
              10        6.1     5.9
>>> df2
                     lforce  rforce
pressure load speed                
47       20   70        2.5     2.8
              60        2.1     2.6
              50        1.9     2.4
              40        1.7     2.2
              30        1.5     2.0
              20        1.3     1.8
              10        1.2     1.7

我想减去 df2来自 df1在 lforce和 rforce每个列 speed获取结果数据框 df3 .

我的问题是我需要忽略 pressure和 load在 df2在减法期间，但保留来自 df1 的原件.

想要的结果:

>>> df3
                     lforce  rforce
pressure load speed                
42       350  70        1.1     0.6
              60        1.3     0.6
              50        1.4     0.7
              40        1.5     0.8
              30        1.6     0.9
              20        1.7     1.0
              10        1.7     1.0
36       700  70        5.2     4.8
              60        5.1     4.6
              50        5.1     4.4
              40        5.1     4.4
              30        5.0     4.3
              20        5.0     4.3
              10        4.9     4.2

Answer 1

df1.sub(df2.reset_index([0, 1], drop=True), level=2)

输出:

                    lforce  rforce
pressure load speed                
42       350  70        1.1     0.6
              60        1.4     0.6
              50        1.4     0.7
              40        1.5     0.8
              30        1.6     0.9
              20        1.8     1.0
              10        1.7     1.0
36       700  70        5.2     4.8
              60        5.2     4.6
              50        5.1     4.5
              40        5.1     4.4
              30        5.0     4.3
              20        5.1     4.4
              10        4.9     4.2