title: Group by Date and count of unique users as column name
body: <p>Dataframe</p>
  <pre><code>d = {'logdate': ['2022-06-20' , '2022-06-21' , '2022-06-22' , '2022-06-23' , '2022-06-24' , '2022-06-25' , '2022-06-26' , '2022-06-27' , '2022-06-28' , '2022-06-29' , '2022-06-30' , '2022-07-01' , '2022-06-20' , '2022-06-21' , '2022-06-22' , '2022-06-23' , '2022-06-24' , '2022-06-25' , '2022-06-26' , '2022-06-27' , '2022-06-28' , '2022-06-29' , '2022-06-30' , '2022-07-01'], 'Username': [ 'UserA' , 'UserA' , 'UserB' , 'UserF' , 'UserA' , 'UserA' , 'UserC' , 'UserA' , 'UserA' , 'UserE' , 'UserA' , 'UserD' , 'UserA' , 'UserE' , 'UserB' , 'UserA' , 'UserF' , 'UserE' , 'UserA' , 'UserA' , 'UserB' , 'UserB' , 'UserA' , 'UserD']}
  df = pd.DataFrame(data=d)
  df
  </code></pre>
  <p>Output:</p>
  <pre><code>| logdate    | Username |
  |------------|----------|
  | 2022-06-20 | UserA    |
  | 2022-06-21 | UserA    |
  | 2022-06-22 | UserB    |
  | 2022-06-23 | UserF    |
  | 2022-06-24 | UserA    |
  | 2022-06-25 | UserA    |
  </code></pre>
  <p>I want to achieve the following, group by date and count of each users as individual columns</p>
  <p><strong>Expected</strong>:</p>
  <pre><code>| logdate    | UserA | UserB | UserC | UserD | UserE | UserF |
  |------------|-------|-------|-------|-------|-------|-------|
  | 2022-06-20 | 2     | 0     | 0     | 0     | 0     | 0     |
  | 2022-06-21 | 1     | 0     | 0     | 0     | 1     | 0     |
  | 2022-06-22 | 0     | 2     | 0     | 0     | 0     | 0     |
  | 2022-06-23 | 1     | 0     | 0     | 0     | 0     | 1     |
  </code></pre>
  <p>All I could try was to group by logdate and count Username</p>
  <pre><code>df.groupby('logdate')[['Username']].count()
  </code></pre>
  <p>Any suggestions would be helpful, Thanks.</p>