EWMA to be Depreciated Reduces Avialable Functionality
#### Description
I have DataFrame with a datetime index and two dtype-float columns.

I wanted to use a groupby function with an EWMA such that the EWMA works on each hour of the day separately. I used the below code and all seemed to work as expected. The issue is that a warning message appeared: `FutureWarning: pd.ewm_mean is deprecated for DataFrame and will be removed in a future version, replace with DataFrame.ewm(adjust=True, min_periods=0, ignore_na=False, alpha=0.84).mean()`

My currently working code
```
data.groupby([data.index.hour]).apply(lambda x: pd.ewma(x, alpha=0.84))
```
  

The new code as kind of suggested
```
data.groupby([data.index.hour]).apply(lambda x: pd.ewm(alpha=0.84).mean(x))

AttributeError: module 'pandas' has no attribute 'ewm'
```

  
What I also tried first of all (before applying `pd.ewma`)
```
data.groupby([data.index.hour]).ewm(alpha=0.84).mean(x)

AttributeError: Cannot access callable attribute 'ewm' of 'DataFrameGroupBy' objects, try using the 'apply' method
```

Usually, with this kind of thing it is me not using the intuitive pandas functionality correctly. This time it seems that the change to `df.ewm().mean()` (which admittedly does feel much neater) is actually losing functionality or at the least, an intuitive solution to a problem. 

I think the perfect solution would be to have `df.groupby().ewm().mean()` working as this seems most intuitive as a a step onward from `df.groupby().rolling().mean()`.

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-45-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_GB.UTF-8
LOCALE: en_GB.UTF-8

pandas: 0.19.0
nose: 1.3.7
pip: 9.0.1
setuptools: 27.3.0
Cython: 0.24.1
numpy: 1.11.2
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.0.0
sphinx: 1.4.8
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.7
blosc: None
bottleneck: None
tables: 3.3.0
numexpr: 2.6.1
matplotlib: 1.5.3
openpyxl: 2.4.0
xlrd: None
xlwt: None
xlsxwriter: 0.9.3
lxml: 3.5.0
bs4: 4.4.1
html5lib: 0.999
httplib2: 0.9.1
apiclient: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.42.0
pandas_datareader: None
</details>
