Reindexing/resampling a level in a multi-index dataframe
I was wondering if, given the recent set of developments and improvements to `asfreq` and `resample`, we now have a more efficient method for solving [this problem](http://stackoverflow.com/questions/29356412/efficiently-re-indexing-one-level-with-forward-fill-in-a-multi-index-dataframe) [from SO].

Example:

```
item_uid   created_at     value     
0S0099v8iI 2015-03-25  10652.79
0F01ddgkRa 2015-03-25   1414.71
0F02BZeTr6 2015-03-20  51505.22
0F02BZeTr6 2015-03-23  51837.97
0F02BZeTr6 2015-03-24  51578.63
0F02BZeTr6 2015-03-25       NaN
0F02BZeTr6 2015-03-26       NaN
0F02BZeTr6 2015-03-27  50893.42
0F02BcIzNo 2015-03-17   1230.00
0F02BcIzNo 2015-03-23   1130.00
0F02F4gAMs 2015-03-25   1855.96
0F02Vwd6Ou 2015-03-19   5709.33
0F04OlAs0R 2015-03-18    321.44
0F05GInfPa 2015-03-16    664.68
0F05PQARFJ 2015-03-18   1074.31
0F05PQARFJ 2015-03-26   1098.31
0F06LFhBCK 2015-03-18    211.49
0F06ryso80 2015-03-16     13.73
0F06ryso80 2015-03-20     12.00
0F07gg7Oth 2015-03-19   2325.70
```

which, if we were to resample with a daily frequency, would return (e.g. for `item_uid = 0F02BZeTr6`):

```
item_uid   created_at     value     
0F02BZeTr6 2015-03-20  51505.22
0F02BZeTr6 2015-03-21  51505.22
0F02BZeTr6 2015-03-22  51505.22
0F02BZeTr6 2015-03-23  51837.97
0F02BZeTr6 2015-03-24  51578.63
0F02BZeTr6 2015-03-25  51578.63
0F02BZeTr6 2015-03-26  51578.63
0F02BZeTr6 2015-03-27  50893.42
0F02BZeTr6 2015-03-28  50893.42
0F02BZeTr6 2015-03-29  50893.42
```

I mention this partly because `unstacking` can be very slow when our index is huge. Any thoughts here are welcome!
