title: Pandas: Return Hour from Datetime Column Directly
body: <p>Assume I have a DataFrame <code>sales</code> of timestamp values:</p>
  
  <pre><code>timestamp               sales_office
  2014-01-01 09:01:00     Cincinnati
  2014-01-01 09:11:00     San Francisco
  2014-01-01 15:22:00     Chicago
  2014-01-01 19:01:00     Chicago
  </code></pre>
  
  <p>I would like to create a new column <code>time_hour</code>. I can create it by writing a short function as so and using <code>apply()</code> to apply it iteratively:</p>
  
  <pre><code>def hr_func(ts):
      return ts.hour
  
  sales['time_hour'] = sales['timestamp'].apply(hr_func)
  </code></pre>
  
  <p>I would then see this result:</p>
  
  <pre><code>timestamp               sales_office         time_hour
  2014-01-01 09:01:00     Cincinnati           9
  2014-01-01 09:11:00     San Francisco        9
  2014-01-01 15:22:00     Chicago              15
  2014-01-01 19:01:00     Chicago              19
  </code></pre>
  
  <p>What I'd <em>like</em> to achieve is some shorter transformation like this (which I know is erroneous but gets at the spirit):</p>
  
  <pre><code>sales['time_hour'] = sales['timestamp'].hour
  </code></pre>
  
  <p>Obviously the column is of type <code>Series</code> and as such doesn't have those attributes, but it seems there's a simpler way to make use of matrix operations.</p>
  
  <p>Is there a more-direct approach?</p>