title: Efficient way to add to a series without duplicates
body: <p>I need to add a to a dataframe (or series if that's more efficient) quite often, while making sure the additions don't create duplicates.  As the dataframe grows, it seems that this would get inefficient, by simply concating then calling drop_duplicates, as the whole dataset needs to be checked for duplicates for each addition.</p>
  
  <p>The data has only two columns so I am guessing turning one into an index might speed things up. (or both columns into a hierarchical index).  Do pandas has a way of disallowing duplicate indexes? </p>
  
  <p>Here is a sample problem:</p>
  
  <pre><code>print accumulating_result
    c1  c2
  0  A  x1
  1  B  x2
  2  B  x3
  3  C  x4
  
  print new
    c1  c2
  0  B  x3
  1  C  x4
  2  C  x5
  </code></pre>
  
  <p>Perform the addition of new to accumulating_result and get:</p>
  
  <pre><code>print accumulating_result
    c1  c2
  0  A  x1
  1  B  x2
  2  B  x3
  3  C  x4
  4  C  x5
  </code></pre>
  
  <p>For what's it's worth, every entry in column c2 will be unique.</p>
  
  <p>Any ideas?</p>