pandas dataframe select columns in multiindex

I have the following pd.DataFrame:

    Name    0                       1                      ...
    Col     A           B           A            B         ...
    0       0.409511    -0.537108   -0.355529    0.212134  ...
    1       -0.332276   -1.087013    0.083684    0.529002  ...
    2       1.138159    -0.327212    0.570834    2.337718  ...

It has MultiIndex columns with names=['Name', 'Col'] and hierarchical levels. The Name label goes from 0 to n, and for each label, there are two A and B columns.

I would like to subselect all the A (or B) columns of this DataFrame.

There is a get_level_values method that you can use in conjunction with boolean indexing to get the the intended result.

    In [13]:

    df = pd.DataFrame(np.random.random((4,4)))
    df.columns = pd.MultiIndex.from_product([[1,2],['A','B']])
    print df
              1                   2          
              A         B         A         B
    0  0.543980  0.628078  0.756941  0.698824
    1  0.633005  0.089604  0.198510  0.783556
    2  0.662391  0.541182  0.544060  0.059381
    3  0.841242  0.634603  0.815334  0.848120
    In [14]:

    print df.iloc[:, df.columns.get_level_values(1)=='A']
              1         2
              A         A
    0  0.543980  0.756941
    1  0.633005  0.198510
    2  0.662391  0.544060
    3  0.841242  0.815334

From: stackoverflow.com/q/25189575