inconsistant result shape from dataframe.apply depending on if a date column is present
#### A small, complete example of the issue

``` python
import pandas as pd
df1 = pd.DataFrame.from_items([('A', [1,2,3]), ('B', [4, 5, 6])])
df2 = pd.DataFrame.from_items([('A', [pd.datetime(1970,1,1), pd.datetime(1970,1,1), pd.datetime(1970,1,1)]), ('B', [4, 5, 6])])
f = lambda row: [row.B + 3]
r1 = df1.apply(f, axis=1)
r2 = df2.apply(f, axis=1)
# bug: r1 and r2 are different and different in shape.
# expect: r1 and r2 to be the same values and shape.
r1
r2
# a clue to the difference:
(df1._is_mixed_type,df1._is_datelike_mixed_type)
(df2._is_mixed_type,df2._is_datelike_mixed_type)

```
#### Expected Output

``` python
0    [7]
1    [8]
2    [9]
```
#### Output of `pd.show_versions()`

<details>
## INSTALLED VERSIONS

commit: None
python: 3.5.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.1
nose: None
pip: 8.1.2
setuptools: 20.3
Cython: None
numpy: 1.11.1
scipy: None
statsmodels: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: None
tables: None
numexpr: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
boto: None
pandas_datareader: None
</details>
