Ability to handle fractional seconds in date_converters
cc @michaelaye

```
I have a 'second' column that contains microseconds like these:
In [52]: df.second.values
Out[52]: 
array([  4.50000000e-02,   4.50000000e-02,   4.50000000e-02, ...,
         5.99920000e+01,   5.99920000e+01,   5.99920000e+01])

and had used this column to produce a DateTime index like this before:

    d = dataframe
    di = pandas.io.date_converters.parse_all_fields(
    d.year, d.month, d.date, d.hour, d.minute, d.second)

but the resulting datetime index lost the microseconds:

MultiIndex
[(1.0, 1.0, <Timestamp: 2009-07-20 00:00:00>)
 (1.0, 2.0, <Timestamp: 2009-07-20 00:00:00>)
 (1.0, 3.0, <Timestamp: 2009-07-20 00:00:00>) ...,
 (9.0, 19.0, <Timestamp: 2009-07-20 00:59:59>)
 (9.0, 20.0, <Timestamp: 2009-07-20 00:59:59>)
 (9.0, 21.0, <Timestamp: 2009-07-20 00:59:59>)]

Is there a way to keep the microseconds?
```
