groupby casting to int64
#### Code Sample, a copy-pastable example if possible

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

data = "some_id,other_id,some_int\n1,234,0\n2,324,1"
dtypes = {'some_id': np.uint32, 'other_id': np.uint32, 'some_int': np.int8}
train = pd.read_csv(StringIO(data), dtype=dtypes)

print(train.dtypes) # dtypes is respected
grouped = train.groupby('some_id').some_int.agg(['sum'])
print(grouped.index.dtype) # dtype('int64')
```
#### Problem description

I am explicitly asking for uint32 but pandas coerces "some_id" column to int64 after using groupby. Is this intended? Possible duplicate of #14423 ?

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.12.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-57-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 27.2.0
Cython: 0.24.1
numpy: 1.11.1
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.4.6
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: 1.1.0
tables: 3.2.3.1
numexpr: 2.6.1
matplotlib: 1.5.3
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.42.0
pandas_datareader: None

</details>
