title: Is there an efficient way to merge two sorted dataframes in pandas, maintaing sortedness?
body: <p>If I have two dataframes (or series) that are already sorted on compatible keys, I'd like to be able to cheaply merge them together and maintain sortedness.  I can't see a way to do that other than via concat() and explicit sort()</p>
  
  <pre><code>a = pd.DataFrame([0,1,2,3], index=[1,2,3,5], columns=['x'])
  b = pd.DataFrame([4,5,6,7], index=[0,1,4,6], columns=['x'])
  print pd.concat([a,b])
  print pd.concat([a,b]).sort()
  
     x
  1  0
  2  1
  3  2
  5  3
  0  4
  1  5
  4  6
  6  7
  
     x
  0  4
  1  0
  1  5
  2  1
  3  2
  4  6
  5  3
  6  7
  </code></pre>
  
  <p>It looks like there has been a bit of related discussion with numpy arrays, suggesting an 'interleave' method, but I haven't found a good answer.</p>