Pandas : Proper way to set values based on condition for subset of multiindex dataframe

Question

I\'m not sure of how to do this without chained assignments (which probably wouldn\'t work anyways because I\'d be setting a copy).

I wan\'t to take a subset of a mu

Answer 1

This is an application of (and one of the main motivations for using MultiIndex slicers), see docs here

In [20]: df = pd.DataFrame({('A','a'): [-1,-1,0,10,12],
                   ('A','b'): [0,1,2,3,-1],
                   ('B','a'): [-20,-10,0,10,20],
                   ('B','b'): [-200,-100,0,100,200]})

In [21]: df
Out[21]: 
    A      B     
    a  b   a    b
0  -1  0 -20 -200
1  -1  1 -10 -100
2   0  2   0    0
3  10  3  10  100
4  12 -1  20  200

In [22]: idx = pd.IndexSlice

In [23]: mask = df.loc[:,idx['A',:]]<0

In [24]: mask
Out[24]: 
       A       
       a      b
0   True  False
1   True  False
2  False  False
3  False  False
4  False   True

In [25]: df[mask] = 0

In [26]: df
Out[26]: 
    A      B     
    a  b   a    b
0   0  0 -20 -200
1   0  1 -10 -100
2   0  2   0    0
3  10  3  10  100
4  12  0  20  200

Since you are working with the 1st level of the columns index, the following will work as well. The above example is more general, say you wanted to do this for 'a'.

In [30]: df[df[['A']]<0] = 0

In [31]: df
Out[31]: 
    A      B     
    a  b   a    b
0   0  0 -20 -200
1   0  1 -10 -100
2   0  2   0    0
3  10  3  10  100
4  12  0  20  200