title: Align two time series data sets on an hourly basis (Python, Pandas)
body: <p>I have two data sets that I am trying to compare.  One is measured meteorological values which are measured approximately every 15 minutes, but not at a consistent time each hour (i.e. 12:03, 1:05, 2:01 etc.).  The other data set is modelled data for the location on the hour exactly.  I would like to extract the value from the measured data which is occurs closest to the hour mark to join with the modelled data.</p>
  
  <p>I currently have both sets as a DataFrame format and have created an hourly time series to use as an index.  Does anyone know of an easy way to align these without looping through all the data?</p>
  
  <p>Thanks.</p>
  
  <p>Using the <code>df.resample('H', how='ohlc')</code> method, I get the following error: </p>
  
  <pre><code>Traceback (most recent call last):
    File "&lt;pyshell#81&gt;", line 1, in &lt;module&gt;
      df.resample('H', how='ohlc')
    File "C:\Python33\lib\site-packages\pandas\core\generic.py", line 290, in resample
      return sampler.resample(self)
    File "C:\Python33\lib\site-packages\pandas\tseries\resample.py", line 83, in resample
      rs = self._resample_timestamps(obj)
    File "C:\Python33\lib\site-packages\pandas\tseries\resample.py", line 226, in _resample_timestamps
      result = grouped.aggregate(self._agg_method)
    File "C:\Python33\lib\site-packages\pandas\core\groupby.py", line 1695, in aggregate
      return getattr(self, arg)(*args, **kwargs)
    File "C:\Python33\lib\site-packages\pandas\core\groupby.py", line 427, in ohlc
      return self._cython_agg_general('ohlc')
    File "C:\Python33\lib\site-packages\pandas\core\groupby.py", line 1618, in _cython_agg_general
      new_blocks = self._cython_agg_blocks(how, numeric_only=numeric_only)
    File "C:\Python33\lib\site-packages\pandas\core\groupby.py", line 1656, in _cython_agg_blocks
      result, _ = self.grouper.aggregate(values, how, axis=agg_axis)
    File "C:\Python33\lib\site-packages\pandas\core\groupby.py", line 818, in aggregate
      raise NotImplementedError
  NotImplementedError
  </code></pre>
  
  <p>A sample of my dataframe is shown below:</p>
  
  <pre><code>                              D
  2008-01-01 00:01:00  274.261108
  2008-01-01 00:11:00  273.705566
  2008-01-01 00:31:00  273.705566
  2008-01-01 00:41:00  273.705566
  2008-01-01 01:01:00  273.705566
  2008-01-01 01:11:00  273.705566
  2008-01-01 01:31:00  273.705566
  2008-01-01 01:41:00  273.705566
  2008-01-01 02:01:00  273.705566
  2008-01-01 02:11:00  273.149994
  </code></pre>
  
  <p><strong>EDIT:</strong> It appears this may be an error when using python 3.3.  Can anyone confirm this?</p>