title: apply a function on rolling window in Dataframe where whole dataframe is passed to function
body: <p>I have a dataframe of 5 columns indexed by YearMo:</p>
  
  <pre><code>yearmo = np.repeat(np.arange(2000, 2010) * 100, 12) + [x for x in range(1,13)] * 10 
  rates = pd.DataFrame(data=np.random.random(120, 5)), 
                       index=pd.Series(data=yearmo, name='YearMo'), 
                       columns=['A', 'B','C', 'D', 'E'])
  
  rates.head()                       
  YearMo    A         B          C         D       E 
  200411  0.237696  0.341937  0.258713  0.569689  0.470776
  200412  0.601713  0.313006  0.221821  0.720162  0.889891
  200501  0.024379  0.761315  0.225032  0.293682  0.302431
  200502  0.996778  0.388783  0.026448  0.056188  0.744850
  200503  0.942024  0.768416  0.484236  0.102904  0.287446
  </code></pre>
  
  <p>What I would like to do is to be able to apply a rolling window and pass all five columns to a function – something like:</p>
  
  <pre><code>rates.rolling(window=60, min_periods=60).apply(lambda x: my_func(data=x, param=5)
  </code></pre>
  
  <p>but this approach applies the function to each column. Specifying <code>axis=1</code> doesn't do anything either....</p>