title: Add new rows to a pandas dataframe
body: <p>I have two dataframes <code>df1</code> and <code>df2</code> that that were computed from the same source, but with different methods, thus most of the values are same, with some differences. Now, I want to update <code>df1</code> based on values in <code>df2</code>.</p>
  
  <p>For example:</p>
  
  <pre><code>df1 = pd.DataFrame({'name':['john','deb','john','deb'], 'col1':[490,500,425,678], 'col2':[456,625,578,789],'col3':['TN','OK','OK','NY']})
   name col1 col2 col3
   john  490  456  TN
   deb   500  625  OK
   john  425  578  OK
   deb   678  789  NY
  
  df2 = pd.DataFrame({'name':['deb','john','deb','john','deb'], 'col1':[400,490,500,425,678], 'col2':[225,456,625,578,789],'col3':['TN','TN','OK','OK','NY']})
   name col1 col2 col3
    deb  400  225  TN
   john  490  456  TN
    deb  500  625  OK
   john  425  578  OK
   deb   678  789  NY
  </code></pre>
  
  <p>So, in this case <code>.append</code> should append only the first row from <code>df2</code> to <code>df1</code>. So, only if there is a new row in <code>df2</code> that is not present in <code>df1</code> (based on name and <code>col3</code>) that column will be added/updated, else it wont be.</p>
  
  <p>This almost seems like something that <code>concat</code> should do.</p>