Read SAS  (sas7bdat)
Very excited to have this new feature in Pandas. I have a few comments to share:
1. `pd.read_sas()` doesn't read SAS date variable correctly (this is noted in the doc). Dates are read as `numpy.float64`. Note in SAS, dates are recorded as numbers relative to 1960-1-1. It would be helpful to allow some sort of arguments to parse the date variable correctly. 
2. Moreover, SAS has some special missing variables such as `.B` or `.R`. I wonder how are these cases treated? 
3. Not nearly as fast as `read_csv()`. To read a 700MB SAS data. The time is

```
CPU times: user 1min 47s, sys: 955 ms, total: 1min 48s
Wall time: 1min 48s
```

The time for the same CSV file (I covered the same file to CSV using SAS) is 

```
CPU times: user 3.93 s, sys: 343 ms, total: 4.28 s
Wall time: 4.29 s
```
