title: Selecting Pandas DataFrame records for many years based on month & day range
body: <p>I've got some daily data in a Pandas DataFrame and it has a nice index. Something like this:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  
  rng = pd.date_range('1/1/2010', periods=1000, freq='D')
  ts = pd.DataFrame(randn(len(rng)), index=rng, columns=['vals'])
  print ts.head()
  
                  vals
  2010-01-01  1.098302
  2010-01-02 -1.384821
  2010-01-03 -0.426329
  2010-01-04 -0.587967
  2010-01-05 -0.853374
  </code></pre>
  
  <p>I'd like to subset my DataFrame to only the records that fall between February 2 &amp; March 3 <strong>for all years</strong>. </p>
  
  <p>It seems there should be a very Pandas-esque way of doing this but I'm struggling to find it. Any help?</p>