DataFrame.rolling.size not implemented and errors in aggregation
#### Code Sample, a copy-pastable example if possible

```python
>>> idx = pd.date_range('2012-1-1', periods=20)
>>> data = np.random.rand(len(idx))
>>> data[5] = np.nan
>>> s = pd.Series(data, idx)

>>> s.rolling('5D').size()
AttributeError: 'Rolling' object has no attribute 'size'

# no error with `agg`, but yields nonsense result
>>> s.rolling('5D').agg('size')
1

# fails when in a list
>>> s.rolling('5D').agg(['size'])
AttributeError: 'Rolling' object has no attribute 'name
```
#### Problem description

`size` should be implemented and return the size of the window. This is useful when downsampling over a larger frequency than the current. For instance, downsampling with weeks for daily data.

`'size'` yields a nonsense result when used as a string inside of `agg`.  `'count'` works but does not get the desired result as there could be missing values as there is in the above Series.

You can use `np.size` to get the desired result, but for consistency, the string `'size'` should work.

#### Expected Output

```
>>> s.rolling('5D').agg(np.size)
2012-01-01    1.0
2012-01-02    2.0
2012-01-03    3.0
2012-01-04    4.0
2012-01-05    5.0
2012-01-06    4.0
2012-01-07    4.0
2012-01-08    4.0
2012-01-09    4.0
2012-01-10    4.0
2012-01-11    5.0
2012-01-12    5.0
2012-01-13    5.0
2012-01-14    5.0
2012-01-15    5.0
2012-01-16    5.0
2012-01-17    5.0
2012-01-18    5.0
2012-01-19    5.0
2012-01-20    5.0
Freq: D, dtype: float64
```

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.7.final.0
python-bits: 64
OS: Darwin
OS-release: 18.2.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.4
pytest: 4.0.1
pip: 18.1
setuptools: 40.4.3
Cython: 0.29.1
numpy: 1.15.4
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 7.2.0
sphinx: 1.8.2
patsy: 0.5.1
dateutil: 2.7.5
pytz: 2018.7
blosc: None
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 3.0.2
openpyxl: 2.5.12
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.1.2
lxml: 4.2.5
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.2.14
pymysql: None
psycopg2: 2.7.6.1 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.7.0

</details>
