title: Pandas Concat Giving "InvalidIndexError: Reindexing only valid with uniquely valued Index objects" Error
body: <p>I have two different dfs that I want to combine using:</p>
  
  <pre><code>pd.concat([df1, df2], 1)
  </code></pre>
  
  <p>The end result being a df with the date as the index and all of the cols.</p>
  
  <p><a href="http://pandas.pydata.org/pandas-docs/stable/merging.html#set-logic-on-the-other-axes" rel="nofollow noreferrer">According to pandas documentation</a>, this should work. And it was working. But now it's not and I have no idea why.</p>
  
  <p>df1:</p>
  
  <pre><code>        gbp_open  gbp_high gbp_low gbp_close gbp_volume
  date                    
  2017-03-13  0.8217  0.82246 0.81627 0.8216  000
  2017-03-10  0.8224  0.82366 0.82055 0.82255 000
  2017-03-09  0.82139 0.82364 0.82    0.8212  000
  2017-03-08  0.81943 0.82372 0.8186  0.81937 000
  2017-03-07  0.817   0.82163 0.8163  0.8168  000
  2017-03-06  0.81351 0.81659 0.8132  0.813   000
  2017-03-03  0.8147  0.81854 0.8141  0.81468 000
  2017-03-02  0.81492 0.81561 0.81264 0.81485 000
  2017-03-01  0.80779 0.81402 0.80629 0.80788 000
  2017-02-28  0.80403 0.8059  0.80183 0.8039  000
  </code></pre>
  
  <p>And df2:</p>
  
  <pre><code>          inr_open  inr_high inr_low inr_close inr_volume
  date                    
  2017-03-13  66.485  66.58   66.11   66.485  000
  2017-03-10  66.71   66.77   66.5398 66.6805 000
  2017-03-09  66.815  66.853  66.60   66.765  000
  2017-03-08  66.625  66.83   66.613  66.6162 000
  2017-03-07  66.645  66.695  66.58   66.6647 000
  2017-03-06  66.71   66.78   66.60   66.773  000
  2017-03-03  66.845  66.885  66.74   66.8451 000
  2017-03-02  66.69   66.858  66.67   66.858  000
  2017-03-01  66.705  66.89   66.7046 66.7051 000
  2017-02-28  66.735  66.808  66.59   66.6932 000
  </code></pre>
  
  <p>I've tried several different solutions but none of them do what I need, which is combine the two on the date.</p>
  
  <p>Edit: And strangely enough, I'm using pretty much the exact same code on a different dataset (but same operation) and it is working with no issues.</p>
  
  <p>Edit 2: Maybe this will help. I used df1.join(df2, how = 'outer') and it worked fine. Well <em>almost</em> fine. When I checked for any repeat values, there was one date which showed four (and it happens to be yesterday - which would explain why it's a recent issue).</p>
  
  <p>How might this contribute to the problem?</p>
  
  <pre><code>xdf.index.value_counts()
  
  2017-04-24    4
  2016-11-14    1
  2011-03-28    1
  2011-09-19    1
  2011-09-13    1
  2013-12-25    1
  2012-07-12    1
  2011-08-08    1
  2016-11-22    1
  </code></pre>
  
  <p>Any thoughts?</p>