title: Pandas Column differences, containing lists
body: <p>I have a data frame where the columns values are list and want to find the differences between two columns, or in other words I want to find all the elements in column A which is not there in column B.</p>
  
  <pre><code>data={'NAME':['JOHN','MARY','CHARLIE'],
    'A':[[1,2,3],[2,3,4],[3,4,5]],
    'B':[[2,3,4],[3,4,5],[4,5,6]]}
  df=pd.DataFrame(data)
  df=df[['NAME','A','B']]
  
  #I'm able to concatenate
  df['C']=df['A']+df['B']
  
      NAME    A   B   C
    0 JOHN    [1, 2, 3]   [2, 3, 4]   [1, 2, 3, 2, 3, 4]
    1 MARY    [2, 3, 4]   [3, 4, 5]   [2, 3, 4, 3, 4, 5]
    2 CHARLIE [3, 4, 5]   [4, 5, 6]   [3, 4, 5, 4, 5, 6]
  </code></pre>
  
  <p>Any way to find the differences?</p>
  
  <pre><code>df['C']=df['A']-df['B']
  </code></pre>
  
  <p>I know we can use <code>df.apply</code> to a function but row by row processing will run slow since I have around 400K rows. I'm looking for a straight forward method like </p>
  
  <pre><code>df['C']=df['A']+df['B']
  </code></pre>