BUG pd.get_dummies does not propagate `NaN` correctly
#### Code Sample, a copy-pastable example if possible

```python
In [17]: s
Out[17]: 
0      a
1      b
2      c
3    NaN
dtype: object
In [18]: pd.get_dummies(s)
Out[18]: 
   a  b  c
0  1  0  0
1  0  1  0
2  0  0  1
3  0  0  0
```

#### Problem description
The current implementation does not propagate `NaN` correctly. `NaN` means the data is missing. So if you turn missing data to all zeros when one-hot encoding, you are asserting that the proper label is none of the labels you have. In reality, the proper label could be one of the labels you have, you just do not know the proper label. 

I realize people use the `dummy_na` option here, but if that option is not passed, then the output should have the `NaN`s put in the right spot.

#### Expected Output
It should propagate the NaNs.

```python
In [18]: pd.get_dummies(s)
Out[18]: 
   a  b  c
0  1  0  0
1  0  1  0
2  0  0  1
3  NaN  NaN  NaN
```

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

<details>
In [19]: pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Darwin
OS-release: 15.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.19.2
nose: 1.3.7
pip: 9.0.1
setuptools: 33.1.1.post20170320
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
statsmodels: 0.8.0
xarray: None
IPython: 5.3.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: None
tables: 3.3.0
numexpr: 2.6.2
matplotlib: 2.0.0
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999
httplib2: None
apiclient: None
sqlalchemy: 1.1.5
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext lo64)
jinja2: 2.9.5
boto: 2.46.1
pandas_datareader: None
</details>
