GroupBy(..., as_index=True).agg() drops index when 
#### Code Sample, a copy-pastable example if possible

```ipython
In [1]: import pandas as pd

In [2]: pd.DataFrame({"A": [1997], "B": pd.Series(["b"], dtype="category").cat.as_ordered()}).groupby("A", as_index=True).agg({"B": "size"})
Out[2]:
      B
A
1997  1

In [3]: pd.DataFrame({"A": [1997], "B": pd.Series(["b"], dtype="category").cat.as_ordered()}).groupby("A", as_index=True).agg({"B": "min"})
Out[3]:
   B
0  b
```
#### Problem description

When aggregating `min`, `max` or `first` of a categorical column, `.agg()` returns a dataframe with a default index instead of the index returned by `groupby()`.

(This may be related to #13416 ... but I think it's a clear, well-defined bug so maybe easier to resolve?)

In my case, I think I can work around this problem with a hack: if I `.agg({"B": ["min", "size"]})` and then ignore the `("B", "size")` output column, Pandas will output a dataframe with the correct index.

#### Expected Output

```
Out[3]:
      B
A
1997  b
```

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

<details>
INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.2.11-200.fc30.x86_64
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 0.25.0
numpy            : 1.16.1
pytz             : 2018.9
dateutil         : 2.8.0
pip              : 19.0.3
setuptools       : 40.8.0
Cython           : 0.29.5
pytest           : 4.5.0
hypothesis       : None
sphinx           : 2.1.1
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.2.5
html5lib         : 1.0.1
pymysql          : None
psycopg2         : 2.8.3 (dt dec pq3 ext lo64)
jinja2           : 2.10.1
IPython          : 7.2.0
pandas_datareader: None
bs4              : 4.6.3
bottleneck       : None
fastparquet      : 0.2.1
gcsfs            : None
lxml.etree       : 4.2.5
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.14.1
pytables         : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
</details>
