>>> import numpy as np
>>> import pandas as pd
>>> pd.__version__
u'0.23.4'
>>> index = pd.MultiIndex(levels=[[u'bar', u'baz', u'foo', u'qux'],
                                  [u'one', u'two', u'three', u'four']],
                          labels=[[0, 0, 1, 1, 2, 2, 3, 3],
                                  [0, 0, 1, 1, 2, 2, 3, 3]],
                          names=[u'first', u'second'])
>>> df = pd.DataFrame(np.random.randn(8, 4), index=index)
>>> df.columns = ['c0', 'c1', 'c2', 'c3']
>>> df
                    c0        c1        c2        c3
first second
bar   one    -2.366973 -0.887149 -0.301309  1.312207
      one     1.266500  0.864888 -1.407567  0.265077
baz   two    -1.926091 -0.671274 -0.295846  0.679759
      two    -0.212970  0.136552  0.219074  0.541827
foo   three  -0.698288 -2.059952  0.248811  0.947879
      three  -2.017481  0.163013 -0.906551 -0.102474
qux   four   -1.083530  0.097077  0.224977  0.251739
      four    0.943804  1.356789 -0.953357  0.592986

>>> two_data = df[df.index.get_level_values('second') == 'two']
>>> mask = (two_data['c1'] > 0)
>>> mask = mask.values
array([False,  True])

>>> df[df.index.get_level_values('second') == 'two'][mask].drop('two', level=1)
Empty DataFrame
Columns: [c0, c1, c2, c3]
Index: []
>>> df[df.index.get_level_values('second') == 'two'].iloc[mask].drop('two', level=1)
Empty DataFrame
Columns: [c0, c1, c2, c3]
Index: []

>>> df
                    c0        c1        c2        c3
first second
bar   one    -2.366973 -0.887149 -0.301309  1.312207
      one     1.266500  0.864888 -1.407567  0.265077
baz   two    -1.926091 -0.671274 -0.295846  0.679759
      two    -0.212970  0.136552  0.219074  0.541827
foo   three  -0.698288 -2.059952  0.248811  0.947879
      three  -2.017481  0.163013 -0.906551 -0.102474
qux   four   -1.083530  0.097077  0.224977  0.251739
      four    0.943804  1.356789 -0.953357  0.592986

>>> df[df.index.get_level_values('second') == 'two'][mask].drop('two', level=1, inplace=True)
>>> df
                    c0        c1        c2        c3
first second
bar   one    -2.366973 -0.887149 -0.301309  1.312207
      one     1.266500  0.864888 -1.407567  0.265077
baz   two    -1.926091 -0.671274 -0.295846  0.679759
      two    -0.212970  0.136552  0.219074  0.541827
foo   three  -0.698288 -2.059952  0.248811  0.947879
      three  -2.017481  0.163013 -0.906551 -0.102474
qux   four   -1.083530  0.097077  0.224977  0.251739
      four    0.943804  1.356789 -0.953357  0.592986

>>> df[df.index.get_level_values('second') == 'two'].iloc[mask].drop('two', level=1, inplace=True)
>>> df
                    c0        c1        c2        c3
first second
bar   one    -2.366973 -0.887149 -0.301309  1.312207
      one     1.266500  0.864888 -1.407567  0.265077
baz   two    -1.926091 -0.671274 -0.295846  0.679759
      two    -0.212970  0.136552  0.219074  0.541827
foo   three  -0.698288 -2.059952  0.248811  0.947879
      three  -2.017481  0.163013 -0.906551 -0.102474
qux   four   -1.083530  0.097077  0.224977  0.251739
      four    0.943804  1.356789 -0.953357  0.592986

c0        c1        c2        c3
first second
bar   one    -2.366973 -0.887149 -0.301309  1.312207
      one     1.266500  0.864888 -1.407567  0.265077
baz   two    -1.926091 -0.671274 -0.295846  0.679759
foo   three  -0.698288 -2.059952  0.248811  0.947879
      three  -2.017481  0.163013 -0.906551 -0.102474
qux   four   -1.083530  0.097077  0.224977  0.251739
      four    0.943804  1.356789 -0.953357  0.592986