title: pandas index.asof with multiindex
body: <p>I have data with a time series for each entity: </p>
  
  <pre><code>id  event_date  value
  1   2013-12-21  3.82
  1   2013-12-22  2.47
  1   2013-12-25  2.13
  1   2014-01-03  3.92
  1   2014-01-04  2.48
  2   2014-10-16  3.96
  2   2014-10-17  3.61
  2   2014-10-29  2.59
  2   2014-11-05  3.64
  2   2014-11-15  2.85
  </code></pre>
  
  <p>I've put it in a dataframe with a multiindex: </p>
  
  <pre><code>               value
  id event_date
  1  2013-12-21   3.82
     2013-12-22   2.47
     2013-12-25   2.13
     2014-01-03   3.92
     2014-01-04   2.48
  2  2014-10-16   3.96
     2014-10-17   3.61
     2014-10-29   2.59
     2014-11-05   3.64
     2014-11-15   2.85
  </code></pre>
  
  <p>I'm trying to find the latest date before an arbitrary cut off (say before 2014-10-31 or 2014-09-30) in the series for each id. index.asof or Series.asof seems to be what I want but I can't figure out how to use it with multiple indices. For a date of '2014-10-30' I want this output:</p>
  
  <pre><code>id  event_date
  1   2014-01-04 00:00:00
  2   2014-10-29 00:00:00
  </code></pre>
  
  <p>I can get there by looping over the first level index but it seems like there should be a better more pandonic way (the full data set is pretty large) and I'm just missing it. </p>
  
  <pre><code>In [10]: for idx in df.index.levels[0]:
     ....:     print idx, df.loc[idx].index.asof('2014-10-30')
     ....:
  1 2014-01-04 00:00:00
  2 2014-10-29 00:00:00
  </code></pre>
  
  <p>There is no reason the data has to be in this multiindex structure, just seems to make sense given I have a timeseries for each id. The times are sorted and there are no duplicates. </p>
  
  <p>versions:
  pandas: 0.15.0
  numpy: 1.9.0</p>