Inconsistent behavior of .map()
#### Code Sample, a copy-pastable example if possible

```python
pd.Series(list('abc') + [np.nan]).map({np.nan: 'bar'})
```

Result:

```
0   NaN
1   NaN
2   NaN
3   NaN
dtype: float64
```

Compare:

```python
pd.Series(list('abc') + [np.nan]).map({'a': 'foo', np.nan: 'bar'})
```

Result:

```
0    foo
1    NaN
2    NaN
3    bar
dtype: object
```

#### Problem description

If only `np.nan` is present in the mapping, then the associated mapping is not carried out. If another value is present, then it is carried out. Forgive me if this is intended behavior for some reason.

#### Expected Output

I'm not sure what is appropriate here.

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 32
OS: Linux
OS-release: 4.4.0-116-generic
machine: i686
processor: i686
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: None
pip: 8.1.1
setuptools: 20.7.0
Cython: None
numpy: 1.11.0
scipy: 0.17.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: None
patsy: 0.5.0
dateutil: 2.4.2
pytz: 2014.10
blosc: None
bottleneck: None
tables: 3.2.2
numexpr: 2.4.3
feather: None
matplotlib: 1.5.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.4.1
html5lib: 0.999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.6.0
</details>