title: How to create specific time buckets from time column in pandas
body: <p>I have a dataframe which has a column <code>time</code> with these unique values</p>
  
  <pre><code>0      15:54:16
  1      16:25:24
  2      16:54:40
  3      17:27:16
  4      18:23:30
  5      18:48:38
  6      10:24:45
  7      11:25:41
  8      12:26:42
  9      13:29:11
  10     14:32:45
  11     15:32:00
  12     16:30:19
  13     17:33:04
  14     18:31:15
           ...   
  450    06:18:34
  451    18:47:22
  452    07:43:53
  453    08:37:06
  454    09:27:41
  455    13:26:42
  456    10:57:58
  457    11:59:33
  458    12:58:45
  459    14:28:37
  460    16:28:10
  461    07:58:07
  462    19:59:23
  463    20:31:53
  464    09:58:47
  </code></pre>
  
  <p>I want to transform this column to time buckets. I would like the buckets to be specific: <code>0to6, 6to10, 10to14, 14to16, 16to19 and 19to0</code></p>
  
  <p>Is there a way to do this without using the <code>numpy.where</code> ?</p>