title: Pandas CONCAT() with merged columns in Creation
body: <p>I am trying to create a very large dataframe, made up of one column from many smaller dataframes (renamed to the dataframe name).  I am using CONCAT() and looping through dictionary values which represent dataframes, and looping over index values, to create the large dataframe. The CONCAT() join_axes is the common index to all the dataframes. This works fine, however I then have duplicate column names.<br>
  I must be able to loop over the indexes at specifc windows as part of my final dataframe creation - so removing this step isnt an option                        </p>
  
  <p>For example, this results in the following final dataframe with duplciate columns:                      </p>
  
  <p><a href="https://i.stack.imgur.com/otW5K.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/otW5K.jpg" alt="enter image description here"></a></p>
  
  <p>Is there any way I can use CONCAT() excatly as I am, but merge the columns to produce an output like so?:</p>
  
  <p><a href="https://i.stack.imgur.com/Ex0E9.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Ex0E9.jpg" alt="enter image description here"></a></p>