pandas Cross sections of different axes with MultiIndex Using .loc and slicers

Example

Unlike the .xs method, this allows you to assign values. Indexing using slicers is available since version 0.14.0.

In [1]:
import pandas as pd
import numpy as np
arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
          ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]
idx_row = pd.MultiIndex.from_arrays(arrays, names=['Row_First', 'Row_Second'])
idx_col = pd.MultiIndex.from_product([['A','B'], ['i', 'ii']], names=['Col_First','Col_Second'])
df = pd.DataFrame(np.random.randn(8,4), index=idx_row, columns=idx_col)

Out[1]:
Col_First                    A                   B          
Col_Second                   i        ii         i        ii
Row_First Row_Second                                        
bar       one        -0.452982 -1.872641  0.248450 -0.319433
          two        -0.460388 -0.136089 -0.408048  0.998774
baz       one         0.358206 -0.319344 -2.052081 -0.424957
          two        -0.823811 -0.302336  1.158968  0.272881
foo       one        -0.098048 -0.799666  0.969043 -0.595635
          two        -0.358485  0.412011 -0.667167  1.010457
qux       one         1.176911  1.578676  0.350719  0.093351
          two         0.241956  1.082138 -0.516898 -0.196605

Selection on rows:

In [2]: df.loc[(slice(None),'two'),:]
Out[2]: 
Col_First                    A                   B          
Col_Second                   i        ii         i        ii
Row_First Row_Second                                        
bar       two        -0.460388 -0.136089 -0.408048  0.998774
baz       two        -0.823811 -0.302336  1.158968  0.272881
foo       two        -0.358485  0.412011 -0.667167  1.010457
qux       two         0.241956  1.082138 -0.516898 -0.196605

Selection on columns:

In [3]: df.loc[:,(slice(None),'ii')]
Out[3]: 
Col_First                    A         B
Col_Second                  ii        ii
Row_First Row_Second                    
bar       one        -1.872641 -0.319433
          two        -0.136089  0.998774
baz       one        -0.319344 -0.424957
          two        -0.302336  0.272881
foo       one        -0.799666 -0.595635
          two         0.412011  1.010457
qux       one         1.578676  0.093351
          two         1.082138 -0.196605

Selection on both axis::

In [4]: df.loc[(slice(None),'two'),(slice(None),'ii')]
Out[4]: 
Col_First                    A         B
Col_Second                  ii        ii
Row_First Row_Second                    
bar       two        -0.136089  0.998774
baz       two        -0.302336  0.272881
foo       two         0.412011  1.010457
qux       two         1.082138 -0.196605

Assignment works (unlike .xs):

In [5]: df.loc[(slice(None),'two'),(slice(None),'ii')]=0
         df
Out[5]: 
Col_First                    A                   B          
Col_Second                   i        ii         i        ii
Row_First Row_Second                                        
bar       one        -0.452982 -1.872641  0.248450 -0.319433
          two        -0.460388  0.000000 -0.408048  0.000000
baz       one         0.358206 -0.319344 -2.052081 -0.424957
          two        -0.823811  0.000000  1.158968  0.000000
foo       one        -0.098048 -0.799666  0.969043 -0.595635
          two        -0.358485  0.000000 -0.667167  0.000000
qux       one         1.176911  1.578676  0.350719  0.093351
          two         0.241956  0.000000 -0.516898  0.000000