title: Pandas matching datetime.datetime value against pandas date type
body: <p>I'm trying to get day ago prices from one table that match the ids and date from a second table (for a performance reporting tool).</p>
  
  <p>I'm using a pretty simple subset
  where <code>dateLoop[0]</code> is <code>datetime.datetime(2013,1,10,0,0)</code></p>
  
  <pre><code>olddate = np.datetime64(dateLoop[0])
  
  pv = dfp[dfp['instrument'].isin(dayfp.instrument.unique()) \
   &amp; dfp.date == olddate ]
  </code></pre>
  
  <p>and it raises the exception</p>
  
  <p><code>TypeError: cannot astype a datetimelike from [datetime64[ns]] to [bool]</code></p>
  
  <p>How can I get it to match a date range that hasn't been created in pandas and where its been imported as a dictionary so the datetime hasn't been indexed?</p>
  
  <pre><code>dfp = pd.DataFrame([
        dict(instrument = 'GE', price = 10, date = datetime.datetime(2013,1,10,0,0)),
        dict(instrument = 'INTC', price = 15, date = datetime.datetime(2013,1,10,0,0))
  ...]
  </code></pre>
  
  <p>and </p>
  
  <pre><code>dayfp =
  `date   id instrument portfolio  position  price            sector  \
  22 2013-01-11  153         PM  usequity     62000  82.82  Consumer Staples   
  23 2013-01-11  154        CMS  usequity    217000  23.14         Utilities   
  24 2013-01-11  155        EXC  usequity    181000  27.16         Utilities   
  25 2013-01-11  156        AES  usequity    467000  10.81         Utilities   
  26 2013-01-11  157        DOV  usequity     92000  53.95       Industrials   
  
           mv        wt  px0  
  22  5134840  0.063798  NaN  
  23  5021380  0.062389  NaN  
  24  4915960  0.061079  NaN  
  25  5048270  0.062723  NaN  
  26  4963400  0.061668  NaN  
  </code></pre>
  
  <p>I'm trying to populate px0 by searching on instrument and date from a large list of historical prices.</p>
  
  <p>Thanks</p>