Python & Pandas - Group by day and count for each day : <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>
