title: Pandas merge tables: only distinct Ids from second table
body: <p>I am trying to figure out if it's possible to join/merge/concat two tables and just instead of 'outer' I'd like to pick the distinct Ids from the second table with the pandas built-in options. </p>
  
  <p>Right now I am doing something along the lines and 
  I have the feeling that my code is not very elegant:</p>
  
  <pre><code>a = [['a', '1.2', '4.2'], ['b', '70', '0.03'], ['c', '8', '1']]
  b = [['a', '52', '49'], ['b', '23', '0.05'], ['x', '5', '0']]
  df1 = pd.DataFrame(a, columns=['id_col', 'two', 'three'])
  df2 = pd.DataFrame(b, columns=['id_col', 'two', 'three'])
  
  
  # remove df2 entries also in df1
  different_ids = set(df2.id_col).difference(set(df1.id_col))
  df2 = df2[df2.id_col.isin(different_ids)]
  # merge data frames
  df_merged = pd.concat([df1,df2])
  </code></pre>
  
  <p>the merged df should have the entries a,b,c from df1 and x from df2.</p>