GroupBy aggregation fails if DataFrame has CategoricalIndex 
#### Code Sample, a copy-pastable example if possible

```python
ids = pd.Categorical([0, 1, 2])
df = pd.DataFrame({
    'id': ids,
    'groups': [1, 1, 2],
    'value': [0, 1, 0]
}).set_index('id')

df.groupby('groups').agg({'value': pd.Series.nunique})

```
#### Problem description
The above works in v. `0.25.3` but not in `1.0.0rc0`. It fails with: `TypeError: Cannot convert Categorical to numpy.ndarray` 

Full stack trace:
```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "~/.virtualenvs/3.6-test-pd-1.0.0/lib/python3.6/site-packages/pandas/core/groupby/generic.py", line 940, in aggregate
    result, how = self._aggregate(func, *args, **kwargs)
  File "~/.virtualenvs/3.6-test-pd-1.0.0/lib/python3.6/site-packages/pandas/core/base.py", line 430, in _aggregate
    result = _agg(arg, _agg_1dim)
  File "~/.virtualenvs/3.6-test-pd-1.0.0/lib/python3.6/site-packages/pandas/core/base.py", line 397, in _agg
    result[fname] = func(fname, agg_how)
  File "~/.virtualenvs/3.6-test-pd-1.0.0/lib/python3.6/site-packages/pandas/core/base.py", line 381, in _agg_1dim
    return colg.aggregate(how)
  File "~/.virtualenvs/3.6-test-pd-1.0.0/lib/python3.6/site-packages/pandas/core/groupby/generic.py", line 265, in aggregate
    return self._python_agg_general(func, *args, **kwargs)
  File "~/.virtualenvs/3.6-test-pd-1.0.0/lib/python3.6/site-packages/pandas/core/groupby/groupby.py", line 935, in _python_agg_general
    result, counts = self.grouper.agg_series(obj, f)
  File "~/.virtualenvs/3.6-test-pd-1.0.0/lib/python3.6/site-packages/pandas/core/groupby/ops.py", line 624, in agg_series
    return self._aggregate_series_fast(obj, func)
  File "~/.virtualenvs/3.6-test-pd-1.0.0/lib/python3.6/site-packages/pandas/core/groupby/ops.py", line 648, in _aggregate_series_fast
    grouper = libreduction.SeriesGrouper(obj, func, group_index, ngroups, dummy)
  File "pandas/_libs/reduction.pyx", line 329, in pandas._libs.reduction.SeriesGrouper.__init__
TypeError: Cannot convert Categorical to numpy.ndarray
```
#### Expected Output
The correct result applying the aggregation function to the DataFrameGroupBy

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


<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.9.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.0.0rc0
numpy            : 1.18.1
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.1
setuptools       : 45.1.0
Cython           : None
pytest           : 5.2.0
hypothesis       : None
sphinx           : 2.0.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.2.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : 0.3.2
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.0.2
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : 5.2.0
s3fs             : 0.4.0
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : 0.47.0
</details>
