title: Group Time Series
body: <p>Is there a way to group time series on all the dates every 30 minutes or x minutes. My question is very similar to <a href="https://stackoverflow.com/questions/16266019/python-pandas-group-datetime-column-into-hour-and-minute-aggregations">this</a> one. If I wanted to group by hours in a date, I would just need</p>
  <pre><code>data=pd.DataFrame({'Values':  1,'Date':pd.date_range('01-01-2017',periods=3600,freq='T')})
  data.set_index(['Date'],inplace=True)
  grouped=data.groupby(data.index.hour)
  </code></pre>
  <p>Running a for-loop and printing the last group give me:</p>
  <pre><code>for time,group in grouped:
      print(group)   
                       Values
  Date                       
  2017-01-01 23:00:00       1
  2017-01-01 23:01:00       1
  2017-01-01 23:02:00       1
  2017-01-01 23:03:00       1
  2017-01-01 23:04:00       1
  2017-01-01 23:05:00       1
  2017-01-01 23:06:00       1
  2017-01-01 23:07:00       1
  2017-01-01 23:08:00       1
  2017-01-01 23:09:00       1
  2017-01-01 23:10:00       1
  2017-01-01 23:11:00       1
  2017-01-01 23:12:00       1
  2017-01-01 23:13:00       1
  2017-01-01 23:14:00       1
  2017-01-01 23:15:00       1
  2017-01-01 23:16:00       1
  2017-01-01 23:17:00       1
  2017-01-01 23:18:00       1
  2017-01-01 23:19:00       1
  2017-01-01 23:20:00       1
  2017-01-01 23:21:00       1
  2017-01-01 23:22:00       1
  2017-01-01 23:23:00       1
  2017-01-01 23:24:00       1
  2017-01-01 23:25:00       1
  2017-01-01 23:26:00       1
  2017-01-01 23:27:00       1
  2017-01-01 23:28:00       1
  2017-01-01 23:29:00       1
                      ...
  2017-01-02 23:30:00       1
  2017-01-02 23:31:00       1
  2017-01-02 23:32:00       1
  2017-01-02 23:33:00       1
  2017-01-02 23:34:00       1
  2017-01-02 23:35:00       1
  2017-01-02 23:36:00       1
  2017-01-02 23:37:00       1
  2017-01-02 23:38:00       1
  2017-01-02 23:39:00       1
  2017-01-02 23:40:00       1
  2017-01-02 23:41:00       1
  2017-01-02 23:42:00       1
  2017-01-02 23:43:00       1
  2017-01-02 23:44:00       1
  2017-01-02 23:45:00       1
  2017-01-02 23:46:00       1
  2017-01-02 23:47:00       1
  2017-01-02 23:48:00       1
  2017-01-02 23:49:00       1
  2017-01-02 23:50:00       1
  2017-01-02 23:51:00       1
  2017-01-02 23:52:00       1
  2017-01-02 23:53:00       1
  2017-01-02 23:54:00       1
  2017-01-02 23:55:00       1
  2017-01-02 23:56:00       1
  2017-01-02 23:57:00       1
  2017-01-02 23:58:00       1
  2017-01-02 23:59:00       1
  </code></pre>
  <p>But there is no <code>times.30min</code> command.</p>
  <p>EDIT:
  I am trying to group every thirty minutes for all the dates. I want the output exactly like the above command but for an x minutes. The default <code>grouped = df.groupby(pd.TimeGrouper('30T'))</code> does not work, because it groups the dates individually. So if I have minute timestamps of dates say 2017-01-01 and 2017-01-02, <code>pd.TimeGrouper('30T')</code>, splits up <code>0:00-0:30 2017-01-01</code> and <code>0:00-0:30 2017-01-02</code> into seperate groups. I would like them combined.</p>