title: Is it possible to use cut on a collection of datetimes?
body: <p>Is it possible to use <code>pandas.cut</code> to make bins out of <code>datetime</code> stamps?</p>
  
  <p>The following code:</p>
  
  <pre><code>import pandas as pd
  import StringIO
  
  contenttext = """Time,Bid
  2014-03-05 21:56:05:924300,1.37275
  2014-03-05 21:56:05:924351,1.37272
  2014-03-05 21:56:06:421906,1.37275
  2014-03-05 21:56:06:421950,1.37272
  2014-03-05 21:56:06:920539,1.37275
  2014-03-05 21:56:06:920580,1.37272
  2014-03-05 21:56:09:071981,1.37275
  2014-03-05 21:56:09:072019,1.37272"""
  
  content = StringIO.StringIO(contenttext)
  df = pd.read_csv(content, header=0)
  df['Time'] = pd.to_datetime(df['Time'], format='%Y-%m-%d %H:%M:%S:%f')
  
  pd.cut(df['Time'], 5)
  </code></pre>
  
  <p>Throws the following error:</p>
  
  <pre><code>---------------------------------------------------------------------------
  TypeError                                 Traceback (most recent call last)
  &lt;ipython-input-3-f5387a84c335&gt; in &lt;module&gt;()
       16 df['Time'] = pd.to_datetime(df['Time'], format='%Y-%m-%d %H:%M:%S:%f')
       17 
  ---&gt; 18 pd.cut(df['Time'], 5)
  
  /home/???????/sites/varsite/venv/local/lib/python2.7/site-packages/pandas/tools/tile.pyc in cut(x, bins, right, labels, retbins, precision, include_lowest)
       80         else:
       81             rng = (nanops.nanmin(x), nanops.nanmax(x))
  ---&gt; 82         mn, mx = [mi + 0.0 for mi in rng]
       83 
       84         if mn == mx:  # adjust end points before binning
  
  TypeError: unsupported operand type(s) for +: 'Timestamp' and 'float'
  </code></pre>