setitem type coercion fails when setting a datetime column in a single row dataframe
xref #6942
xref #12499

``` python
import datetime
import pandas as pd
df1 = pd.DataFrame({'a': [0,1], 'b': [datetime.datetime.now(), datetime.datetime.now()]})
# next line works as expected
df1.loc[:,'b'] = [datetime.datetime.now(), datetime.datetime.now()]
df1 = pd.DataFrame({'a': [0], 'b': [datetime.datetime.now()]})
# next line blows up 
df1.loc[:,'b'] = [datetime.datetime.now()]
```

Exception:
/Users/<snip>/anaconda/lib/python2.7/site-packages/pandas/core/internals.py in _try_coerce_args(self, values, other)
   2103                 other_mask = isnull(other)
   2104 
-> 2105                 other = other.astype('i8', copy=False).view('i8')
   2106             except ValueError:
   2107 

TypeError: long() argument must be a string or a number, not 'datetime.datetime'

Incidentally, df1['b'] = [datetime.datetime.now()] will work, but i'm avoiding that as the performance is so poor when it's a copy (in my particular case the copy is dead and gc.collect(2) gets called for each column set operation, blowing out the runtime to 3x what it was pre-copy checking - should I open a separate issue for that?). 

pd.show_versions():
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Darwin
OS-release: 12.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.1
setuptools: 20.3
Cython: 0.23.4
numpy: 1.10.4
scipy: 0.17.0
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.3.5
patsy: 0.4.0
dateutil: 2.5.1
pytz: 2016.2
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.5
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.8.4
lxml: 3.6.0
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.39.0
pandas_datareader: None
