 .apply() for core.window.Window (feature request)
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd
import numpy as np

# create ordinary example data frame
myDf = pd.DataFrame(data={'myCol': pd.Series(np.random.randn(1000)).cumsum()})

# rolling + apply example 1: this works as expected because win_type=None returns a core.window.Rolling which provides apply functionality
myDf2 = myDf.rolling(window=50, center=True, win_type=None).apply(func=lambda x2: np.percentile(a=x2, q=50, interpolation='nearest'))
# rolling + apply example 2: this does not work because as soon as users change win_type to be anything else than None a core.window.Window is returned instead - which does *not* provide apply functionality yet
myDf3 = myDf.rolling(window=50, center=True, win_type='hamming').apply(func=lambda x2: np.percentile(a=x2, q=50, interpolation='nearest'))
```
#### Problem description

`core.window.Window` does not yet provide apply functionality like `core.window.Rolling` does, hence functions other than the readily provided ones (like `sum()`, `mean()`, etc) cannot be applied to it.

(I'm not to deep into the details, but IMHO returning different object types for just changing the window type from rectangular to some other window form seems rather unintuitive altogether. What was the reason for it being designed this way? I couldn't quickly come up with any. It leads to e.g. example 1 from above working fine as long as the `win_type` parameter is untouched - but breaks as soon as `win_type` is changed to a different-than-rectangular window, which does not semantically seem to make sense.)

#### Expected Output

`core.window.Window` should provide apply functionality, probably via `.apply()` like `core.window.Rolling`, so that example 2 from above works fine too.

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

<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.13.0-26-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: 3.2.1
pip: 9.0.1
setuptools: 36.5.0.post20170921
Cython: 0.26.1
numpy: 1.13.3
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.1.0
sphinx: 1.6.3
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.1.0
openpyxl: 2.4.8
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.0
bs4: 4.6.0
html5lib: 0.999999999
sqlalchemy: 1.1.13
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
