title: Joining Multiple Dataframes with Pandas with overlapping Column Names?
body: <p>I have multiple (more than 2) dataframes I would like to merge. They all share the same value column:</p>
  
  <pre><code>In [431]: [x.head() for x in data]
  Out[431]: 
  [                     AvgStatisticData
  DateTime                             
  2012-10-14 14:00:00         39.335996
  2012-10-14 15:00:00         40.210110
  2012-10-14 16:00:00         48.282816
  2012-10-14 17:00:00         40.593039
  2012-10-14 18:00:00         40.952014,
                        AvgStatisticData
  DateTime                             
  2012-10-14 14:00:00         47.854712
  2012-10-14 15:00:00         55.041512
  2012-10-14 16:00:00         55.488026
  2012-10-14 17:00:00         51.688483
  2012-10-14 18:00:00         57.916672,
                        AvgStatisticData
  DateTime                             
  2012-10-14 14:00:00         54.171233
  2012-10-14 15:00:00         48.718387
  2012-10-14 16:00:00         59.978616
  2012-10-14 17:00:00         50.984514
  2012-10-14 18:00:00         54.924745,
                        AvgStatisticData
  DateTime                             
  2012-10-14 14:00:00         65.813114
  2012-10-14 15:00:00         71.397868
  2012-10-14 16:00:00         76.213973
  2012-10-14 17:00:00         72.729002
  2012-10-14 18:00:00         73.196415,
  ....etc
  </code></pre>
  
  <p>I read that join can handle multiple dataframes, however I get:</p>
  
  <pre><code>In [432]: data[0].join(data[1:])
  ...
  Exception: Indexes have overlapping values: ['AvgStatisticData']
  </code></pre>
  
  <p>I have tried passing <code>rsuffix=["%i" % (i) for i in range(len(data))]</code> to join and still get the same error. I can workaround this by building my <code>data</code> list in a way where the column names don't overlap, but maybe there is a better way?  </p>