title: Combine dataframe values based on repeated index labels
body: <p>I've got a single-column dataframe with an index of integers represented as strings that has repeated values in it. The values are integers and I would like to have a dataframe with an index with no repeats in it and whose values are the sum of all the values that originally had the given index label. Here's a sample of the data I'm working with:</p>
  
  <pre><code>&gt;&gt;&gt;  verts
  3    54
  3    34
  0    33
  4    28
  4    23
  2    22
  2    15
  5    15
  5    15
  0     9
  1     2
  6     1
  1     1
  6     1
  </code></pre>
  
  <p>I could do it this way, but it doesn't seem like good pandas syntax:</p>
  
  <pre><code>new_index = set(verts.index)
  new_vals = [verts[x].sum() for x in new_index]
  new_df = pd.DataFrame({'Counts': new_vals}, index=new_index)
  new_df
     Counts
  1       3
  0      42
  3      88
  2      37
  5      30
  4      51
  6       2
  </code></pre>
  
  <p>Is there something more straight-forward? Thanks.</p>