auto convert from string to datetime64 in iterrows.
```python
In [1]: import pandas as pd

In [2]: pd.__version__
Out[2]: '0.20.1'

In [4]: pd.DataFrame({'symbol': ['M1609', 'M1701'], 'date': pd.to_datetime(['2016-09-01', '2017-01-01'])})
Out[4]:
        date symbol
0 2016-09-01  M1609
1 2017-01-01  M1701

In [5]: df = pd.DataFrame({'symbol': ['M1609', 'M1701'], 'date': pd.to_datetime(['2016-09-01', '2017-01-01'])})

In [6]: for i, row in df.iterrows():
   ...:     print(row)
   ...:
date      2016-09-01 00:00:00
symbol                  M1609
Name: 0, dtype: object
date     2017-01-01
symbol   1701-01-01
Name: 1, dtype: datetime64[ns]

```
#### Problem description

Hi, I found the auto convert issue in iterrows or index, the string 'M1701' is converted  to '1701-01-01', and It's not supposed to happen. So is it a bug here?

Thanks.

#### Expected Output

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.20.1
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.27.3
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.2.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: 0.7.11.None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None

</details>
