Aggregate mean over TimeDelta column
#### Cannot compute mean of timedelta in gropuby

```python
In [1]: import pandas as pd
   ...: import numpy as np
   ...: print(pd.__version__)
   ...: 
   ...: time = pd.to_timedelta(np.random.randint(100,1000, size=10), unit='s')
   ...: cat = np.random.choice(['A','B','C'], size=10)
   ...: 
   ...: df = pd.DataFrame(dict(time=time, cat=cat))
   ...: 
   ...: print(df['time'].mean())
   ...: 
   ...: df.groupby('cat')['time'].mean()
   ...: 
0.20.3
0 days 00:07:15.800000
---------------------------------------------------------------------------
DataError                                 Traceback (most recent call last)
<ipython-input-1-b649ebd78333> in <module>()
     10 print(df['time'].mean())
     11 
---> 12 df.groupby('cat')['time'].mean()

/Users/adefusco/Applications/anaconda3/4.3/envs/module-pandas/lib/python3.6/site-packages/pandas/core/groupby.py in mean(self, *args, **kwargs)
   1035         nv.validate_groupby_func('mean', args, kwargs, ['numeric_only'])
   1036         try:
-> 1037             return self._cython_agg_general('mean', **kwargs)
   1038         except GroupByError:
   1039             raise

/Users/adefusco/Applications/anaconda3/4.3/envs/module-pandas/lib/python3.6/site-packages/pandas/core/groupby.py in _cython_agg_general(self, how, alt, numeric_only)
    834 
    835         if len(output) == 0:
--> 836             raise DataError('No numeric types to aggregate')
    837 
    838         return self._wrap_aggregated_output(output, names)

DataError: No numeric types to aggregate

```
#### Problem description
The mean of `TimeDelta` can be computed, but it is not working in GroupBy.

#### Expected Output
This is the output I would expect.

```python

In [3]: def average_time(x):
   ...:     s = x.dt.seconds
   ...:     return pd.Timedelta(s.mean(), unit='s')
   ...: 
   ...: df.groupby('cat')['time'].apply(average_time)
   ...: 
Out[3]: 
cat
A   00:09:27.666667
B   00:06:18.666667
C   00:06:19.750000
Name: time, dtype: timedelta64[ns]
```

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

<details>
              
INSTALLED VERSIONS
------------------
commit: None   
python: 3.6.1.final.0
python-bits: 64
OS: Darwin      
OS-release: 16.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None   
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.3
pytest: None
pip: 9.0.1
setuptools: 27.2.0
Cython: None
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 6.0.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: 0.2.1

</details>
