title: Doing a groupby and rolling window on a Pandas Dataframe with a multilevel index leads to a duplicated index entry
body: <p>If I do a groupby() followed by a rolling() calculation with a multi-level index, one of the levels in the index is repeated - most odd. I am using Pandas 0.18.1</p>
  
  <pre><code>import pandas as pd
  df = pd.DataFrame(data=[[1, 1, 10, 20], [1, 2, 30, 40], [1, 3, 50, 60],
                          [2, 1, 11, 21], [2, 2, 31, 41], [2, 3, 51, 61]],
                    columns=['id', 'date', 'd1', 'd2'])
  
  df.set_index(['id', 'date'], inplace=True)
  df = df.groupby(level='id').rolling(window=2)['d1'].sum()
  print(df)
  print(df.index)
  </code></pre>
  
  <p>The output is as follows</p>
  
  <pre><code>id  id  date
  1   1   1        NaN
          2       40.0
          3       80.0
  2   2   1        NaN
          2       42.0
          3       82.0
  Name: d1, dtype: float64
  MultiIndex(levels=[[1, 2], [1, 2], [1, 2, 3]],
             labels=[[0, 0, 0, 1, 1, 1], [0, 0, 0, 1, 1, 1], [0, 1, 2, 0, 1, 2]],
             names=[u'id', u'id', u'date'])
  </code></pre>
  
  <p>What is odd is that the id column now shows up twice in the multi-index. Moving the ['d1'] column selection around doesn't make any difference.</p>
  
  <p>Any help would be much appreciated.</p>
  
  <p>Thanks
  Paul</p>