ENH: support apply method for ExtensionArray backed Series
#### Code Sample, a copy-pastable example if possible

```python
import pint
ureg = pint.UnitRegistry()
pint.PintType.ureg = ureg

def g(x):
    return x+1*ureg.day
df = pd.DataFrame({'A':pd.Series([1,2,3,4], dtype='pint[day]'),'B':pd.Series([5,6,7,8], dtype='pint[day]')})
res = df['A'].apply(g)
print(type(df['A'].values))
print(type(res.values))
```
#### Problem description

I am experimenting with the [pint-pandas](https://github.com/hgrecco/pint-pandas/issues/24) project which builds an `ExtensionArray` to be able to work with units on dataframes. The above code sample shows that `.apply` method is not implemented for _external_  extension arrays.

I am using the pint-pandas-plotting branch of the pint-pandas project as this is the one which is compatible with pandas 0.25. I installed this branch by downloading, navigating to root directory and running something along the lines of:

`python setup.py -e .`

#### Expected Output

The expected output for `print(type(res.values))` should be a `PintArray` and not a numpy array of `Quantity` objects. 

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.7.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None
pandas           : 0.25.1
numpy            : 1.17.2
pytz             : 2019.3
dateutil         : 2.8.0
pip              : 19.2.3
setuptools       : 41.4.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.8.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.1.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None

</details>
