ENH: expanding_max/min for datetime types
Docs currently explicitly mention float64 as the type of columns for `expanding_max` and `expanding_min`, and indeed, it does a conversion to float64 for other types:

```
In [6]: x = pd.date_range('2008/01/01', periods=3).to_series()

In [7]: x
Out[7]: 
2008-01-01   2008-01-01
2008-01-02   2008-01-02
2008-01-03   2008-01-03
Freq: D, dtype: datetime64[ns]

In [8]: pd.expanding_min(x)
Out[8]: 
2008-01-01    1.199146e+18
2008-01-02    1.199146e+18
2008-01-03    1.199146e+18
Freq: D, dtype: float64

In [9]: pd.expanding_max(x)
Out[9]: 
2008-01-01    1.199146e+18
2008-01-02    1.199232e+18
2008-01-03    1.199318e+18
Freq: D, dtype: float64    
```

It would probably be a good idea to implement this for other supported dtypes. Not all expanding functions will work with any dtype, but at least things like max/min for orderable types are pretty straightforward.
