BUG: Outer join on multiple date time columns results in nan keys
I have tried to reduce this problem as small as possible, two data frames attached each with 291 rows.

[pickles.zip](https://github.com/pydata/pandas/files/424538/pickles.zip)

```
df1 = pd.read_pickle('df1.pkl')
df2 = pd.read_pickle('df2.pkl')

merged = df1.merge(df2, how='outer', on=['DateTime', 'valid_datetime'])
#this results in nan values on the join keys
merged.shape[0] == merged[['DateTime', 'valid_datetime']].dropna().shape[0]
```

Note that if the DateTime and valid_datetime columns are converted to strings then this works fine.
