title: Access last elements of inner multiindex level in pandas dataframe
body: <p>In a <code>multi index</code> pandas dataframe I want to access the <strong>last</strong> element of the second index for all values of the first index. The number of levels in the second index vary depending on the value of the first index. I went through the <a href="http://pandas.pydata.org/pandas-docs/stable/advanced.html" rel="noreferrer">pandas multi index documentation</a> but could not find anything that does that.</p>
  
  <p>For example, for the data frame below:</p>
  
  <pre><code>arrays = [ ['bar', 'bar', 'baz', 'foo', 'foo', 'foo',   'qux'],
             ['one', 'two', 'one', 'one', 'two', 'three', 'one']]
  tuples = list(zip(*arrays))
  index = pd.MultiIndex.from_tuples(tuples, names=['first', 'second'])
  df = pd.DataFrame(np.random.randn(7, 3), index=index, columns=['A', 'B', 'C'])
  df
                   A         B         C
  first second
  bar   one     0.289163 -0.464633 -0.060487
        two     0.224442  0.177609  2.156436
  baz   one    -0.262329 -0.248384  0.925580
  foo   one     0.051350  0.452014  0.206809
        two     2.757255 -0.739196  0.183735
        three  -0.064909 -0.963130  1.364771
  qux   one    -1.330857  1.881588 -0.262170
  </code></pre>
  
  <p>I want to get:</p>
  
  <pre><code>                 A         B         C
  first second
  bar   two     0.224442  0.177609  2.156436
  baz   one    -0.262329 -0.248384  0.925580
  foo   three  -0.064909 -0.963130  1.364771
  qux   one    -1.330857  1.881588 -0.262170
  </code></pre>
  
  <p>The <code>dataframes</code> I am working with have over <code>10M</code> lines so I want to avoid explicit looping.</p>