title: Extracting hour, date and month from a pandas (python) DataFrame object
body: <p>With a pandas DataFrame <code>df</code>:</p>
  
  <pre><code>         x                   y
  0   29-04-2014 07:40:52     07:40:52
  1   29-04-2014 07:59:25     07:15:00
  2                NaN             NaN
  3   29-04-2014 08:16:12     07:45:00
  4   09-05-2014 08:19:14     07:30:00
  5   23-04-2014 08:27:16     08:30:00
  6   29-04-2014 08:37:16     07:00:00
  7                NaN             NaN
  8   29-04-2014 08:41:16     07:30:00
  9   25-03-2014 08:42:16     07:30:00
  </code></pre>
  
  <p>where columns <code>x</code> contains the <code>Date-Month-Year Hour:Minute:Second</code> and <code>y</code> stores the <code>Hour:Minute:Second</code>, how can one extract only:</p>
  
  <ol>
  <li>the date [<code>29</code> from row 0] of column <code>x</code>, </li>
  <li>the month [<code>04</code> or <code>April</code> from row 0] of column <code>x</code>,</li>
  <li>the month and date [<code>29-04</code> or <code>29-April</code> from row 0] of column <code>x</code>,</li>
  <li>the hour and minute [<code>07-40</code> from row 0] of columns <code>x</code> and <code>y</code></li>
  </ol>
  
  <p>I imported the DataFrame from a text file using </p>
  
  <p><code>df = pd.read_table("C:\data.txt, sep= '\t'")</code> </p>
  
  <p>but it was originally from MS Excel or MS Access.</p>
  
  <p>When I run <code>df.dtypes</code>, I got </p>
  
  <pre><code>   x    object
     y    object
     dtype: object
  </code></pre>
  
  <p>I am working of Pandas version <code>0.14.1</code> in Python <code>3.4</code>.</p>
  
  <p><strong>Example DataFrame</strong></p>
  
  <pre><code>import numpy as np
  import pandas a pd
  
  df = pd.DataFrame({'x': ['29-04-2014 07:40:52', np.nan, '29-04-2014 08:16:16','29-04-2014 08:19:56', '29-04-2014 08:27:20'],
                     'y': ['07:40:52', '07:15:00', np.nan, '07:45:00', '07:30:00']})
  </code></pre>