title: Sum the values of a column based on the timestamp
body: <p>My dataframe looks like this:</p>
  
  <pre><code>           timestamp    side    price   amount  fee
  0   2018-12-14 13:00:00 buy  0.00338508 5   0.005
  1   2018-12-14 13:00:00 buy  0.00337829 5   0.005
  2   2018-12-14 14:00:00 buy  0.00338089 5   0.005
  3   2018-12-14 14:00:00 buy  0.00338079 1   0.001
  4   2018-12-14 15:00:00 sell 0.00338838 8   0.00002711
  5   2018-12-14 15:00:00 sell 0.00339132 8   0.00002713
  6   2018-12-14 15:00:00 buy  0.00337999 5   0.005
  7   2018-12-14 16:00:00 sell 0.00339373 5   0.00001697
  </code></pre>
  
  <p>What I need to do is to create a column which would sum the values of the column 'amount' which have the same timestamp. So for the timestamp <code>2018-12-14 13:00:00</code> the new column would look like this:</p>
  
  <pre><code>          timestamp    side    price   amount  fee sum
  0   2018-12-14 13:00:00 buy  0.00338508 5   0.005 10
  1   2018-12-14 13:00:00 buy  0.00337829 5   0.005 10
  </code></pre>
  
  <p>I tried with the following code: <code>df_statistics_hour['traded_volume'] = float(df_statistics_hour['amount'].sum())</code> but of course there is the same value in each cell of the new column, any idea on how to proceed? Thanks!</p>