API/BUG: should df.loc[:,'col'] be the same as df['col'] for assignment
see also: http://stackoverflow.com/questions/21415432/pandas-v0-13-0-setting-dataframe-values-of-type-datetime64ns

~~I believe this changed from 0.12.~~ was the same in 0.12

Boils down to if the row indexer is a null-slice (IOW all rows are selected), should
dtype conversion be done or not (as it current)

```
In [45]: df = pd.DataFrame({'date':pd.date_range('2000-01-01','2000-01-5'),'val' : np.arange(5)})

In [46]: df
Out[46]: 
        date  val
0 2000-01-01    0
1 2000-01-02    1
2 2000-01-03    2
3 2000-01-04    3
4 2000-01-05    4

[5 rows x 2 columns]

In [47]: df['date'] = 0

In [48]: df
Out[48]: 
   date  val
0     0    0
1     0    1
2     0    2
3     0    3
4     0    4

[5 rows x 2 columns]

In [49]: df = pd.DataFrame({'date':pd.date_range('2000-01-01','2000-01-5'),'val' : np.arange(5)})

In [53]: df.loc[:,'date'] = np.array([0])

In [54]: df
Out[54]: 
        date  val
0 1970-01-01    0
1 1970-01-01    1
2 1970-01-01    2
3 1970-01-01    3
4 1970-01-01    4

[5 rows x 2 columns]
```
