str conversion to and comparison with datetime no longer working
It appears that appending a dataframe with a column containing string representations of dates, to a dataframe containing datetime objects now results in a column of mixed types, previously the strings were converted to datetime.  In addition filter operations using strings now no longer match the equivalent datetime objects.

This was working in 0.13.1, but no longer works in 0.16.1.
# Example

```
import pandas as pd
import datetime
import pprint
data1 = [{'a': 1, 'b': datetime.datetime(2015,06,10)},
        {'a': 2, 'b': datetime.datetime(2015,06,11)}]
df1 = pd.DataFrame(data1)

data2 = [{'a': 3, 'b': "2015-06-10"},
         {'a': 4, 'b': "2015-06-11"}]
df2 = pd.DataFrame(data2)

df = df1.append(df2)

pprint.pprint(df)
pprint.pprint(df['b'])

print("filtered table")

df = df[df['b'] == '2015-06-11']

pprint.pprint(df)
pprint.pprint(df['b'])

Output using 0.13.1
===============

   a          b
0  1 2015-06-10
1  2 2015-06-11
0  3 2015-06-10
1  4 2015-06-11

[4 rows x 2 columns]
0   2015-06-10
1   2015-06-11
0   2015-06-10
1   2015-06-11
Name: b, dtype: datetime64[ns]

filtered table
   a          b
1  2 2015-06-11
1  4 2015-06-11

[2 rows x 2 columns]
1   2015-06-11
1   2015-06-11
Name: b, dtype: datetime64[ns]

Output using 0.16.1
===============
   a                    b
0  1  2015-06-10 00:00:00
1  2  2015-06-11 00:00:00
0  3           2015-06-10
1  4           2015-06-11

0    2015-06-10 00:00:00
1    2015-06-11 00:00:00
0             2015-06-10
1             2015-06-11
Name: b, dtype: object

filtered table
   a           b
1  4  2015-06-11

1    2015-06-11
Name: b, dtype: object
```
