Subtract values in a data frame ignoring specific keys - python-2.7

Question

I have two data frames as such:
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'])
Formatted:
>>> 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
I would like to subtract df2 from df1 on the lforce and rforce columns for each speed to get the resulting data frame df3.
My problem is that I need to ignore the pressure and load in df2 during the subtraction, but retain the originals from df1.
Desired result:
>>> 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)
output:
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

Answer 2

May be somehing like this:
>>> df3 = df1.reset_index(level=[0,1])
>>> df4 = df2.reset_index(level=[0,1])
>>> df4['pressure'] = 0
>>> df4['load'] = 0
>>> df3 - df4
pressure load lforce rforce
speed
10 42 350 1.7 1.0
10 36 700 4.9 4.2
20 42 350 1.8 1.0
20 36 700 5.1 4.4
30 42 350 1.6 0.9
30 36 700 5.0 4.3
40 42 350 1.5 0.8
40 36 700 5.1 4.4
50 42 350 1.4 0.7
50 36 700 5.1 4.5
60 42 350 1.4 0.6
60 36 700 5.2 4.6
70 42 350 1.1 0.6
70 36 700 5.2 4.8
Now you just have to move pressure and load back to index

Answer 3

Is this what you're looking for?
d1 = df1.reset_index(['pressure','load'])
d2 = df2.reset_index(['pressure','load'])
r0 = d1.merge(d2, left_index=True, right_index=True)
r1 = r0.set_index(['pressure_x','load_x'], drop=False)
r1['lforce'] = r1.lforce_x - r1.lforce_y
r1['rforce'] = r1.rforce_x - r1.rforce_y
df3 = r1[['lforce','rforce']]
df3