title: pd.concat() not merging on same index
body: <p>I have a DataFrame containing forecasts called <code>fcst</code> that looks like this:</p>
  <pre><code>             yhat        yhat_lower  yhat_upper
  ds          
  2015-08-31  -0.443522   -19.067399  17.801234
  2015-09-30  6.794625    -31.472186  46.667981
  ...
  </code></pre>
  <p>After making this transformation:</p>
  <pre><code>fcst2 = fcst[&quot;yhat&quot;].to_frame().rename(columns={&quot;yhat&quot;:&quot;test1&quot;})
  fcst3 = fcst[&quot;yhat&quot;].to_frame().rename(columns={&quot;yhat&quot;:&quot;test2&quot;})
  </code></pre>
  <p>I want to concatenate them, on the date index as such:</p>
  <pre><code>pd.concat([fcst2,fcst3])
  </code></pre>
  <p>But I receive a DataFrame that is not aligned on the index:</p>
  <pre><code>             test1     test2
  ds      
  2015-08-31  -0.443522   NaN
  2015-09-30  6.794625    NaN
  ... ... ...
  2017-05-31  NaN 95.563262
  2017-06-30  NaN 85.829916
  </code></pre>
  <p>and this despite:</p>
  <pre><code>(fcst2.index == fcst3.index).any()
  </code></pre>
  <p>returning True.</p>
  <p>My question is: why aren't the two DataFrames being concatenated on the index and what can I do to solve this?</p>
  <p>I know of the join function, but as some dates will be missing in some of the other DataFrames which I'm planning on adding I believe that the <code>concat</code> function might be better.</p>