DataFrame to_record() with string, datetime column broken in 0.11 release
Issue valid ONLY for numpy < 1.7, need to astype to object the datetime64[ns] first, then to_records

To recreate:

``` python
import pandas as pd
import datetime

current = datetime.datetime.combine(datetime.date.today(), datetime.time())
date_list = [('test{0}'.format(i), current + datetime.timedelta(days=i)) for i in xrange(5)]

# convert this to pandas df
df1 = pd.DataFrame(date_list, columns=['id', 'day1'])

print "Data Frame"
print df1
dfr = df1.to_records(index=False)
print dfr
for r in dfr:
    print r[1], type(r[1])

Output with 0.10.1 (Good)

Data Frame
      id                 day1
0  test0  2013-06-24 00:00:00
1  test1  2013-06-25 00:00:00
2  test2  2013-06-26 00:00:00
3  test3  2013-06-27 00:00:00
4  test4  2013-06-28 00:00:00
[('test0', datetime.datetime(2013, 6, 24, 0, 0))
 ('test1', datetime.datetime(2013, 6, 25, 0, 0))
 ('test2', datetime.datetime(2013, 6, 26, 0, 0))
 ('test3', datetime.datetime(2013, 6, 27, 0, 0))
 ('test4', datetime.datetime(2013, 6, 28, 0, 0))]
2013-06-24 00:00:00 <type 'datetime.datetime'>
2013-06-25 00:00:00 <type 'datetime.datetime'>
2013-06-26 00:00:00 <type 'datetime.datetime'>
2013-06-27 00:00:00 <type 'datetime.datetime'>
2013-06-28 00:00:00 <type 'datetime.datetime'>

```

Output with 0.11 (Bad)

``` python
Data Frame
      id                day1
0  test0 2013-06-24 00:00:00
1  test1 2013-06-25 00:00:00
2  test2 2013-06-26 00:00:00
3  test3 2013-06-27 00:00:00
4  test4 2013-06-28 00:00:00
[('test0', datetime.datetime(1970, 1, 16, 128, 0))
 ('test1', datetime.datetime(1970, 1, 16, 152, 0))
 ('test2', datetime.datetime(1970, 1, 16, 176, 0))
 ('test3', datetime.datetime(1970, 1, 16, 200, 0))
 ('test4', datetime.datetime(1970, 1, 16, 224, 0))]
1970-01-16 128:00:00 <type 'numpy.datetime64'>
1970-01-16 152:00:00 <type 'numpy.datetime64'>
1970-01-16 176:00:00 <type 'numpy.datetime64'>
1970-01-16 200:00:00 <type 'numpy.datetime64'>
1970-01-16 224:00:00 <type 'numpy.datetime64'>
```
1. Notice the datetime value.  This is just not a display issue.  The object has the incorrect value.
2. 0.10.1 use to return datetime.datetime type, while 0.11 returns numpy.datetime64.
