title: Convert pandas datetime objects
body: <p>I have a column in a pandas data frame that contains datetime objects after applying the pd.to_datetime() method.
  So far so good. Now the column contains the dates in a the form '2016-02-08 09:59:00.510'.
  However, I would like to somehow 'drop' the date information, producing input in the form HH:MM:SS, like this:</p>
  
  <p>2016-02-08 09:59:00.510 --> 09:59:00</p>
  
  <p>I was wondering, if that is possible and if so, I would really appreciate some hints to the right way to do that.</p>
  
  <p>Below there is a small working example. I was able to convert the datetime objects to integers (ns?) but I couldn't find out how to convert the objects in column 'Date' to the format I want.</p>
  
  <p>As mentioned: Any help is highly appreciated! </p>
  
  <pre><code>import pandas as pd
  import time
  
  s1 = {'Timestamp' : ['20160208_095900.51','20160208_095901.51','20160208_095902.51','20160208_095903.51',
                       '20160208_095904.51','20160208_095905.51','20160208_095906.51','20160208_095907.51',
                       '20160208_095908.51','20160208_095909.51']}
  
      df = pd.DataFrame(s1)
  
      df['Date'] = pd.to_datetime(df['Timestamp'], format =  '%Y%m%d_%H%M%S.%f')
      df['ns'] = (df['Date'].astype(np.int64) / int(1e6))
      print df
  </code></pre>