title: how to add a dataframe with another dataframe and updated common values based on a column
body: <p>my first data frame-</p>
  <pre><code>df1 = pd.DataFrame({'CONTRACT':['Tom', 'nick', 'krish', 'jack'],
          'Net_Qty':[20, 21, 19, 18]})
  
      CONTRACT    Net_Qty
  0   Tom       20
  1   nick      21
  2   krish     19
  3   jack      18
  </code></pre>
  <p>second data frame-</p>
  <pre><code>df2 = pd.DataFrame({'CONTRACT':['Tom', 'nick', 'amit', 'joy'],
          'Net_Qty':[30, 40, 45, 54]})
      CONTRACT    Net_Qty
  0   Tom         30
  1   nick        40
  2   amit        45
  3   joy         54
  </code></pre>
  <p>I want dataframe dataframe Like this (all values of df2 and <em>uncommon</em> values of df1)-</p>
  <pre><code>        CONTRACT    Net_Qty
      0   Tom         30
      1   nick        40
      2   krish       19
      4   jack        18
      2   amit        45
      3   joy         54
  </code></pre>
  <p>I tried like this-</p>
  <pre><code>cols = list(df1.columns)
              df1.loc[df1.CONTRACT.isin(
                  df2.CONTRACT), cols] = df2[cols]
              print(df1)
  </code></pre>
  <p>but its not working fine.......</p>
  <p>Can anyone please suggest a better way-</p>