Dataframe constructor does not coerce data=[None] to np.nan
#### A small, complete example of the issue

As called out in #14381, if `dtype` is not specified, values of `None` should be coerced to `np.nan`.  However, when a list of only `None` is passed to `data`, the `None` remains.

``` python
>>> pd.DataFrame([None])
      0
0  None
>>> pd.DataFrame([None, None])
      0
0  None
1  None
```
#### Expected Output

``` python
>>> pd.DataFrame([None])
      0
0  NaN
>>> pd.DataFrame([None, None])
      0
0  NaN
1  NaN
```
#### Output of `pd.show_versions()`

<details>
## INSTALLED VERSIONS

commit: None
python: 2.7.11.final.0
python-bits: 64
OS: Linux
OS-release: 3.16.0-77-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.19.0
nose: 1.3.4
pip: 8.1.2
setuptools: 5.8
Cython: 0.21
numpy: 1.11.2
scipy: 0.16.1
statsmodels: 0.6.1
xarray: None
IPython: 4.0.0
sphinx: 1.2.3
patsy: 0.3.0
dateutil: 2.5.3
pytz: 2016.7
blosc: None
bottleneck: None
tables: 3.1.1
numexpr: 2.3.1
matplotlib: 1.5.0
openpyxl: 1.8.5
xlrd: 0.9.3
xlwt: 0.7.5
xlsxwriter: 0.5.7
lxml: 3.4.0
bs4: 4.3.2
html5lib: None
httplib2: 0.9.1
apiclient: None
sqlalchemy: 0.9.7
pymysql: None
psycopg2: 2.6.1 (dt dec pq3 ext lo64)
jinja2: 2.7.3
boto: 2.32.1
pandas_datareader: None
</details>
