title: Panda group dataframes into user specified time period
body: <p>Probably related: <a href="https://stackoverflow.com/questions/17764619/pandas-dataframe-group-year-index-by-decade">pandas dataframe group year index by decade</a></p>
  
  <p>For example if I have data as follows</p>
  
  <pre><code>                     status  bytes_sent upstream_cache_status  \
  timestamp                                                       
  2014-05-26 23:56:30     200         356                  MISS   
  2014-05-26 23:56:30     200       10517                     -   
  2014-05-26 23:57:05     200        6923                  MISS   
  2014-05-26 23:57:14     200         323                     -   
  2014-05-26 23:57:30     200         356                  MISS   
  2014-05-26 23:57:38     200        8107                   HIT   
  2014-05-26 23:57:43     200         369                  MISS   
  2014-05-26 23:57:56     304         401                   HIT   
  2014-05-26 23:57:56     304         401                   HIT   
  2014-05-26 23:57:56     304         387                  MISS   
  2014-05-26 23:57:57     304         401                   HIT   
  2014-05-26 23:57:58     304         401                   HIT   
  2014-05-26 23:58:08     200         507               EXPIRED   
  2014-05-26 23:58:29     304         338                   HIT   
  2014-05-26 23:58:31     400         409                     -   
  2014-05-26 23:58:45     200         425                  MISS   
  </code></pre>
  
  <p>if let say I want to group them such that each group contains logs within 30 seconds (time is user-specified), how do I do that? I have seen this</p>
  
  <pre><code>df.groupby(lambda x: x.hour)
  </code></pre>
  
  <p>but I highly doubt it is relevant in my case</p>