title: how to convert datetime by removing nanoseconds
body: <p>I have sample <strong>CSV</strong> data which have <strong>Time</strong> in the following format</p>
  
  <p>2014-04-29 00:00:01.933000,2014-04-29 00:00:01.933000</p>
  
  <p>I can do pd.to_datetime(data['ts']) and also pd.DatetimeIndex(data['ts'])</p>
  
  <p>but how to format the output as <strong>%Y-%m-%d %H:%M:%S</strong> or basically to be removed the nanoseconds.</p>
  
  <p>This simple dateformatter seems to be missed out from all docs, I have read in pandas. I know the alternative is to convert to the float</p>
  
  <pre><code>np.floor(pd.DatetimeIndex(pd.to_datetime(sdfeed1['ts'])).astype(int64)/1e9)
  </code></pre>
  
  <p>I don't like this ugly approach. Is there any simple way to convert array of date-times to simple format. Simply like excel does without using any lambda functions.</p>
  
  <p>pd.convert(...list of dates...,format = '....'), It should be as simple as this! Am I asking too much? Pushing np and lambda functions for this is overkill.</p>