title: Python & Pandas - Group by day and count for each day
body: <p>I am new on pandas and for now i don't get how to arrange my time serie, take a look at it :</p>
  
  <pre><code>date &amp; time of connection
  19/06/2017 12:39
  19/06/2017 12:40
  19/06/2017 13:11
  20/06/2017 12:02
  20/06/2017 12:04
  21/06/2017 09:32
  21/06/2017 18:23
  21/06/2017 18:51
  21/06/2017 19:08
  21/06/2017 19:50
  22/06/2017 13:22
  22/06/2017 13:41
  22/06/2017 18:01
  23/06/2017 16:18
  23/06/2017 17:00
  23/06/2017 19:25
  23/06/2017 20:58
  23/06/2017 21:03
  23/06/2017 21:05
  </code></pre>
  
  <p>This is a sample of a dataset of 130 k raws,I tried :
  <code>df.groupby('date &amp; time of connection')['date &amp; time of connection'].apply(list)</code></p>
  
  <p>Not enough i guess</p>
  
  <p>I think i should :</p>
  
  <ul>
  <li>Create a dictionnary with index from dd/mm/yyyy to dd/mm/yyyy </li>
  <li>Convert "date &amp; time of connection" type dateTime to Date</li>
  <li>Group and count Date of "date &amp; time of connection"</li>
  <li>Put the numbers i count inside the dictionary ?</li>
  </ul>
  
  <p>What do you think about my logic ? Do you know some tutos ?
  Thank you very much</p>