[Bugs] the problem of apply method when Dataframe has a datetime type column
my dataframe below: 
```
<class 'pandas.core.frame.DataFrame'>
Int64Index: 18922 entries, 7 to 77733
Data columns (total 4 columns):
user_id       18922 non-null int64
event_id      18922 non-null int64
context       18922 non-null object
created_at    18922 non-null datetime64[ns]
dtypes: datetime64[ns](1), int64(2), object(1)
memory usage: 739.1+ KB
```
I wrote a function to transform df['context'] to a dict like: 
```python
def json_parse(json_str):
    """
    :param user_id:
    :param str:
    :return:
    """
    try:
        juxinli_report = json.loads(json_str)
    except Exception as e:
        print(e)
        juxinli_report = dict()
    if juxinli_report:
        info = {}
        data = juxinli_report.get('data', {})
        for key_1 in data.get('user_gray', {}):
            info[key_1] = data.get('user_gray', {}).get(key_1)
        return info

```
when I did:
```
jxl_report[:4].apply(lambda row: json_parse(row['context']), axis=1)
``` 
the result was strange,  it should be a Series.
```
user_id	event_id	context	created_at
7	NaN	NaN	NaN	NaN
12	NaN	NaN	NaN	NaN
15	NaN	NaN	NaN	NaN
17	NaN	NaN	NaN	NaN
```
but if I drop the column `created_at` or change its type to object, the result is expected, a Series.
```python
jxl_report = jxl_report.drop(['created_at'], axis=1)
# or
# jxl_report['created_at'] = jxl_report['created_at'].astype('str')

```

```
7     {'contacts_class1_blacklist_cnt': 2, 'user_pho...
12    {'contacts_class1_blacklist_cnt': 0, 'user_pho...
15    {'contacts_class1_blacklist_cnt': 0, 'user_pho...
17    {'contacts_class1_blacklist_cnt': 0, 'user_pho...
```


#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.20.3
pytest: None
pip: 9.0.1
setuptools: 28.8.0
Cython: None
numpy: 1.13.3
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: 1.1.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: 1.1.9
pymysql: 0.7.11.None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None

</details>
