title: Groupby agg with join not produce the expected output
body: <p>I have dataframe as below </p>
  
  <pre><code>   Wash_Month  Wash_Day
  0           3         2
  1           4         3
  </code></pre>
  
  <p>And the expected out put is </p>
  
  <pre><code>#d={'Wash_Month':'Wash_Month/Wash_Day','Wash_Day':'Wash_Month/Wash_Day'}
  
  #df.T.astype(str).groupby(d).agg(','.join)
  Out[329]: 
                         0    1
  Wash_Month/Wash_Day  3,2  4,3
  </code></pre>
  
  <p>As you saw , I first do the transpose <code>T</code>.</p>
  
  <p>If we <code>groupby</code> with <code>axis=1</code> and remove the <code>T</code>, I expected the same out put.</p>
  
  <pre><code>df.astype(str).groupby(d,axis=1).agg(','.join)
  Out[330]: 
     Wash_Month/Wash_Day
  0  Wash_Month,Wash_Day
  1  Wash_Month,Wash_Day
  </code></pre>
  
  <p>The out put is mismatched with expected output . Is there specific problem on<code>agg</code> with <code>join</code> with <code>groupby</code> of <code>axis=1</code></p>
  
  <p>Since other <code>agg</code> function like <code>sum</code> work as normal </p>
  
  <pre><code>df.astype(str).groupby({'Wash_Month':'Wash_Month/Wash_Day','Wash_Day':'Wash_Month/Wash_Day'}, axis=1).sum()
  Out[332]: 
     Wash_Month/Wash_Day
  0                 32.0 # str 3 + str 2
  1                 43.0
  </code></pre>
  
  <p>About why the result become float rather than a str check <a href="https://stackoverflow.com/questions/46751465/how-to-add-string-numbers-in-pandas">link</a> </p>
  
  <p>Appreciate your help :-)</p>