Comparison between DataFrame and Series containing datetime and other types

```python
import pandas as pd
import datetime as dt

d = pd.DataFrame([[1, dt.datetime(1990,12,10)],
                  [2, dt.datetime(1990,12,11)]])
s = d.loc[0].copy()

d == s

```
>TypeError: int() argument must be a string, a bytes-like object or a number, not 'Timestamp'
#### Problem description

When trying to check if a series is equal to one row in a dataframe containing values of type `datetime.datetime` and values of other types, pandas breaks.
It works if the datetime values are substituted with `str` type (that's what I have tried, don't know about other types).
Also comparing the `.values` works e.g.
```
d = pd.DataFrame([[1, dt.datetime(1990,12,10)],
                  [2, dt.datetime(1990,12,11)]])
s = d.loc[0].copy()

d.values == s.values
```
Works as expected

#### Expected Output
```
       0     1
0   True  True
1  False  False

```


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

<details>
commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-93-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
pandas: 0.20.3
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 5.1.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.2
bs4: 4.5.3
html5lib: 0.9999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.4
s3fs: None
pandas_gbq: None
pandas_datareader: None

</details>
