title: Interpolating one time series onto another in pandas
body: <p>I have one set of values measured at regular times. Say:</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  rng = pd.date_range('2013-01-01', periods=12, freq='H')
  data = pd.Series(np.random.randn(len(rng)), index=rng)
  </code></pre>
  
  <p>And another set of more arbitrary times, for example, (in reality these times are not a regular sequence)</p>
  
  <pre><code>ts_rng = pd.date_range('2013-01-01 01:11:21', periods=7, freq='87Min')
  ts = pd.Series(index=ts_rng)
  </code></pre>
  
  <p>I want to know the value of data interpolated at the times in ts.<br>
  I can do this in numpy:</p>
  
  <pre><code>x = np.asarray(ts_rng,dtype=np.float64)
  xp = np.asarray(data.index,dtype=np.float64)
  fp = np.asarray(data)
  ts[:] = np.interp(x,xp,fp)
  </code></pre>
  
  <p>But I feel pandas has this functionality somewhere in  <code>resample</code>, <code>reindex</code> etc. but I can't quite get it.</p>