[FEA] Support GroupBy aggregations on DecimalColumn

[ChrisJar]

Is your feature request related to a problem? Please describe.
I wish I could perform groupby aggregations on columns with type decimal

Describe the solution you'd like
I would like to mimic what happens when calling a groupby aggregation on columns with type float. For example:

df = cudf.DataFrame({'id': [0, 1, 1], 'val': [1.00, 1.01, 1.02]})
df.groupby('id').agg('mean')

returns

id | val
-- | --
0  |  1.000
1  |  1.015

However, if I convert the float column to decimal

df['val'] = cudf.Series([decimal.Decimal(x) for x in [1.00, 1.01, 1.02]], dtype=cudf.Decimal64Dtype(7,3))
df.groupby('id').agg('mean')

it returns:

---------------------------------------------------------------------------
DataError                                 Traceback (most recent call last)
<ipython-input-20-2a197b045ee3> in <module>
----> 1 df.groupby('id').agg('mean')

~/anaconda3/envs/cudf_dev/lib/python3.7/contextlib.py in inner(*args, **kwds)
     72         def inner(*args, **kwds):
     73             with self._recreate_cm():
---> 74                 return func(*args, **kwds)
     75         return inner
     76 

~/anaconda3/envs/cudf_dev/lib/python3.7/site-packages/cudf/core/groupby/groupby.py in agg(self, func)
    169         # a Float64Index, while Pandas returns an Int64Index
    170         # (GH: 6945)
--> 171         result = self._groupby.aggregate(self.obj, normalized_aggs)
    172 
    173         result = cudf.DataFrame._from_table(result)

cudf/_lib/groupby.pyx in cudf._lib.groupby.GroupBy.aggregate()

cudf/_lib/groupby.pyx in cudf._lib.groupby._drop_unsupported_aggs()

DataError: No numeric types to aggregate

[github-actions]

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[ChrisJar]

Closed with #7731