title: Pandas rolling apply with missing data
body: <p>I want to do a rolling computation on missing data.</p>
  
  <p>Sample Code: <em>(For sake of simplicity I'm giving an example of a rolling sum but I want to do something more generic.)</em></p>
  
  <pre><code>foo = lambda z: z[pandas.notnull(z)].sum() 
  x = np.arange(10, dtype="float")    
  x[6] = np.NaN
  x2 = pandas.Series(x)    
  pandas.rolling_apply(x2, 3, foo)
  </code></pre>
  
  <p>which produces:</p>
  
  <pre><code>0   NaN    
  1   NaN
  2     3    
  3     6    
  4     9    
  5    12    
  6   NaN    
  7   NaN    
  8   NaN    
  9    24
  </code></pre>
  
  <p>I think that during the "rolling", window with missing data is being ignored for computation. I'm looking to get a result along the lines of:</p>
  
  <pre><code>0   NaN    
  1   NaN    
  2     3    
  3     6    
  4     9    
  5    12    
  6     9    
  7    12    
  8    15    
  9    24
  </code></pre>