title: python pandas time series year extraction
body: <p>I have a DF containing timestamps:</p>
  
  <pre><code>0     2005-08-31 16:39:40
  1     2005-12-28 16:00:34
  2     2005-10-21 17:52:10
  3     2014-01-28 12:23:15
  4     2014-01-28 12:23:15
  5     2011-02-04 18:32:34
  6     2011-02-04 18:32:34
  7     2011-02-04 18:32:34
  </code></pre>
  
  <p>I would like to extract the year from each timestamp, creating additional column in the DF that would look like:</p>
  
  <pre><code>0     2005-08-31 16:39:40 2005
  1     2005-12-28 16:00:34 2005
  2     2005-10-21 17:52:10 2005
  3     2014-01-28 12:23:15 2014
  4     2014-01-28 12:23:15 2014
  5     2011-02-04 18:32:34 2011
  6     2011-02-04 18:32:34 2011
  7     2011-02-04 18:32:34 2011
  </code></pre>
  
  <p>Obviously I can go over all DF entries stripping off the first 4 characters of the date. Which is very slow. I wonder if there is a fast python-way to do this. 
  I saw that it's possible to convert the column into the datetime format by DF = pd.to_datetime(DF,'%Y-%m-%d %H:%M:%S') but when I try to then apply datetime.datetime.year(DF) it doesn't work. I will also need to parse the timestamps to months and combinations of years-months and so on...
  Help please.
  Thanks.</p>