title: Pandas rolling on a shifted dataframe
body: <p>Here's a piece of code, I don't get why on the last column rm-5, I get NaN for the first 4 items.</p>
  
  <p>I understand that for the rm columns the 1st 4 items aren't filled because there is no data available, but if I shift the column calculation should be made, shouldn't it ?</p>
  
  <p>Similarly I don't get why there are 5 and not 4 items in the rm-5 column that are NaN</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  
  index = pd.date_range('2000-1-1', periods=100, freq='D')
  df = pd.DataFrame(data=np.random.randn(100), index=index, columns=['A'])
  
  df['rm']=pd.rolling_mean(df['A'],5)
  df['rm-5']=pd.rolling_mean(df['A'].shift(-5),5)
  
  print df.head(n=8)
  print df.tail(n=8)
  
                     A        rm      rm-5
  2000-01-01  0.109161       NaN       NaN
  2000-01-02 -0.360286       NaN       NaN
  2000-01-03 -0.092439       NaN       NaN
  2000-01-04  0.169439       NaN       NaN
  2000-01-05  0.185829  0.002341  0.091736
  2000-01-06  0.432599  0.067028  0.295949
  2000-01-07 -0.374317  0.064222  0.055903
  2000-01-08  1.258054  0.334321 -0.132972
                     A        rm      rm-5
  2000-04-02  0.499860 -0.422931 -0.140111
  2000-04-03 -0.868718 -0.458962 -0.182373
  2000-04-04  0.081059 -0.443494 -0.040646
  2000-04-05  0.500275 -0.093048       NaN
  2000-04-06 -0.253915 -0.008288       NaN
  2000-04-07 -0.159256 -0.140111       NaN
  2000-04-08 -1.080027 -0.182373       NaN
  2000-04-09  0.789690 -0.040646       NaN
  </code></pre>