COMPAT: .map iterates over python types rather than storage type
#### Code Sample, a copy-pastable example if possible

```
import pandas as P
S=P.Series([0.6,0.2,15])
```

**pandas 0.18+numpy 0.10**:

```
In [1]: print S.dtype
float64

In [2]: print S.values.dtype
float64

In [3]: print S.map(type)
0    <type 'numpy.float64'>
1    <type 'numpy.float64'>
2    <type 'numpy.float64'>
dtype: object
```

**pandas 0.18.1+numpy 0.11.0**:

```
In [5]: print S.dtype
float64

In [6]: print S.values.dtype
float64

In [7]: print S.map(type)
0    <type 'float'>
1    <type 'float'>
2    <type 'float'>
dtype: object
```

I expect to get the same dtype for the 3 print, why this is changed in last version?
#### output of `pd.show_versions()`

```
pandas: 0.18.1
nose: 1.3.7
pip: 1.5.4
setuptools: 21.0.0
Cython: 0.24
numpy: 1.11.0
scipy: 0.17.0
statsmodels: 0.6.1
xarray: None
IPython: 4.2.0
sphinx: 1.3.5
patsy: 0.4.1
dateutil: 2.4.2
pytz: 2016.4
blosc: 1.2.7
bottleneck: None
tables: 3.2.2
numexpr: 2.5.2
matplotlib: 1.5.1
openpyxl: 2.3.5
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: None
lxml: 3.4.0
bs4: 4.4.1
html5lib: 0.9999999
httplib2: None
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None
```

Thank you
Gla
