title: Concatenate dataframes with the same column names but different suffixes
body: <p>I have used pandas merge to bring together two dataframes (24 columns each), based on a set of condition, to generate a dataframe which contains rows which have the same values; naturally there are many  other columns in each dataframe with different values. The code used to do this is:</p>
  
  <pre><code>   Merged=pd.merge(Buy_MD,Sell_MD, on= ['ID','LocName','Sub-Group','Month'], how = 'inner' )
  </code></pre>
  
  <p>The result is a dataframe which has 48 columns, I would like to bring together these now (using melt possibly). so to visualise this:</p>
  
  <pre><code>           Deal_x        ID_x         Location_x  \... 21 other columns with _x postfix
  0        130        5845             A   
  1        155        5845             B  
  2        138        6245             C   
  3        152        7345             A 
  
           Deal_y        ID_y         Location_y \ ... 21 other columns  with _y postfix
  0        155        9545             B   
  1        155        0345             C   
  2        155        0445             D   
  </code></pre>
  
  <p>I want this to become:</p>
  
  <pre><code>           Deal        ID        Location \
  0        130        5845             A   
  1        155        5845             B  
  2        138        6245             C   
  3        152        7345             A 
  0        155        9545             B   
  1        155        0345             C   
  2        155        0445             D  
  </code></pre>
  
  <p>Please how do I do this? </p>