title: Combining the values of the two columns upon which 'outer' 'merge'-ing is applied
body: <p>I am trying to perform a<code>pd.merge</code> with an <code>outer</code> manner upon two columns. But I need the output dataframe to have the two columns actually merged together, so that there are no Nan values.</p>
  
  <p>I give an example. Assume the following dataframes that will merge on the timestamp columns:</p>
  
  <pre><code>a1=['2019-09-01 00:00:00', '2019-09-01 01:00:00', '2019-09-01 03:00:00', '2019-09-10 01:00:00']
  a2=['a','c_1','d','f_1']
  b1=['2019-09-01 00:10:00', '2019-09-01 01:00:00', '2019-09-01 03:07:00', '2019-09-10 01:00:00']
  b2=['b','c_2', 'e', 'f_2']
  A=pd.DataFrame({'a1':a1, 'a2':a2})
  A.a1=pd.to_datetime(A.a1)
  B=pd.DataFrame({'b1':b1, 'b2':b2})
  B.b1=pd.to_datetime(B.b1)
  </code></pre>
  
  <p>The merged dataframe I wish to get is close to this:</p>
  
  <pre><code>merged=pd.merge(A,B, left_on='a1', right_on='b1', how='outer', sort=True)
  print(merged)
  &gt;&gt;&gt;
                     a1   a2                  b1   b2
  0 2019-09-01 00:00:00    a                 NaT  NaN
  1                 NaT  NaN 2019-09-01 00:10:00    b
  2 2019-09-01 01:00:00  c_1 2019-09-01 01:00:00  c_2
  3 2019-09-01 03:00:00    d                 NaT  NaN
  4                 NaT  NaN 2019-09-01 03:07:00    e
  5 2019-09-10 01:00:00  f_1 2019-09-10 01:00:00  f_2
  </code></pre>
  
  <p>except that the desired output should have 'a1' and 'b1' merged. It should look like:</p>
  
  <pre><code>             datetime   a2    b2  #datetime column has 'a1' and 'b1' merged
  0 2019-09-01 00:00:00    a   NaN
  1 2019-09-01 00:10:00  NaN     b
  2 2019-09-01 01:00:00  c_1   c_2
  3 2019-09-01 03:00:00    d   NaN
  4 2019-09-01 03:07:00  NaN     e
  5 2019-09-10 01:00:00  f_1   f_2
  </code></pre>
  
  <p>Any thoughts how I can perform that in pythonic/pandaic way?</p>
  
  <p>Thank you in advance :-)</p>