title: Merge rows with same date and add counter column in pandas
body: <p>I have a simple DataFrame that looks like this:</p>
  
  <pre><code>               date
  0   2018-08-28 13:13:37
  1   2018-08-28 13:43:31
  2   2018-08-28 15:23:25
  3   2018-08-28 15:23:30
  4   2018-08-28 15:23:33
  5   2018-08-28 15:23:34
  ...
  790 2018-09-04 10:45:38
  791 2018-09-04 10:45:38
  792 2018-09-04 11:13:16
  793 2018-09-04 12:12:09
  794 2018-09-04 14:01:54
  </code></pre>
  
  <p>I want to group all rows with same date (hour, minute and seconds is not important) and create a new column with the sum (number of merged rows with same date).</p>
  
  <p>The output I'm trying to work out is:</p>
  
  <pre><code>          date         sum
  0   2018-08-28         6
  1   2018-08-29         100
  2   2018-08-30         100
  3   2018-08-31         100
  4   2018-09-01         100
  5   2018-09-02         100
  6   2018-09-03         100
  7   2018-09-04         100
  </code></pre>
  
  <p>I've tried to play around with the <a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html#pandas-dataframe-groupby" rel="nofollow noreferrer">groupby function</a> but I'm not able to get the correct output</p>