title: Getting the non common elements from the two columns in two dataframes
body: <pre><code>data1 = {'date': ['1998', '1999','1999','2000','1999'], 
          'node1': [1,1,2,3,3],
       'node2': [3,4,3,4,8],
       'weight': [1,1,1,1,1], }
  df1 = pd.DataFrame(data1, columns = ['date', 'node1','node2','weight'])
  
  data2 = {'date': ['2002','2001','2003','2002','2002','2001'], 
          'node1': [1,1,1,2,2,3],
       'node2': [2,3,4,3,5,4],
       'weight': [1,1,1,1,1,1], }
  df2= pd.DataFrame(data2, columns = ['date', 'node1','node2','weight'])
  </code></pre>
  
  <p>I would like to search both the columns in each dataframe and then output the row which has the non common element in it.</p>
  
  <p>Output for this data would be:</p>
  
  <p>dataframe1: 3 8 1999</p>
  
  <p>dataframe2: 2 5 2002</p>
  
  <p>Output explanation-By searching across the two rows in the two dataframes we find that 5 and 8 are the non common elements therefore the row containing them are printed.</p>
  
  <p>Edit-Data corrected.</p>