BUG: maximum of pd.Series([np.nan],dtype=ordered_category) raise
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample, a copy-pastable example

```python
In [1]: pd.__version__
Out[1]: '1.0.3'

In [2]: pd.Series([np.nan],dtype=pd.CategoricalDtype([0,1],ordered=True)).max()
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-2-5a47d189b696> in <module>
----> 1 pd.Series([np.nan],dtype=pd.CategoricalDtype([0,1],ordered=True)).max()

~/.pyenv/versions/3.7.4/lib/python3.7/site-packages/pandas/core/generic.py in stat_func(self, axis, skipna, level, numeric_only, **kwargs)
  11213             return self._agg_by_level(name, axis=axis, level=level, skipna=skipna)
  11214         return self._reduce(
> 11215             f, name, axis=axis, skipna=skipna, numeric_only=numeric_only
  11216         )
  11217

~/.pyenv/versions/3.7.4/lib/python3.7/site-packages/pandas/core/series.py in _reduce(self, op, name, axis, skipna, numeric_only, filter_type, **kwds)
   3870
   3871         if isinstance(delegate, Categorical):
-> 3872             return delegate._reduce(name, skipna=skipna, **kwds)
   3873         elif isinstance(delegate, ExtensionArray):
   3874             # dispatch to ExtensionArray interface

~/.pyenv/versions/3.7.4/lib/python3.7/site-packages/pandas/core/arrays/categorical.py in _reduce(self, name, axis, **kwargs)
   2123         if func is None:
   2124             raise TypeError(f"Categorical cannot perform the operation {name}")
-> 2125         return func(**kwargs)
   2126
   2127     @deprecate_kwarg(old_arg_name="numeric_only", new_arg_name="skipna")

~/.pyenv/versions/3.7.4/lib/python3.7/site-packages/pandas/util/_decorators.py in wrapper(*args, **kwargs)
    212                 else:
    213                     kwargs[new_arg_name] = new_arg_value
--> 214             return func(*args, **kwargs)
    215
    216         return cast(F, wrapper)

~/.pyenv/versions/3.7.4/lib/python3.7/site-packages/pandas/core/arrays/categorical.py in max(self, skipna)
   2188         if not good.all():
   2189             if skipna:
-> 2190                 pointer = self._codes[good].max()
   2191             else:
   2192                 return np.nan

~/.pyenv/versions/3.7.4/lib/python3.7/site-packages/numpy/core/_methods.py in _amax(a, axis, out, keepdims, initial, where)
     28 def _amax(a, axis=None, out=None, keepdims=False,
     29           initial=_NoValue, where=True):
---> 30     return umr_maximum(a, axis, None, out, keepdims, initial, where)
     31
     32 def _amin(a, axis=None, out=None, keepdims=False,

ValueError: zero-size array to reduction operation maximum which has no identity
```

In the older version, the same code didn't raise an error.

```python
In [10]: pd.__version__
Out[10]: '0.25.3'

In [11]: pd.Series([np.nan],dtype=pd.CategoricalDtype([0,1],ordered=True)).max()
    ...:
Out[11]: nan
```

#### Problem description

Because of this behavior, I failed to df.groupby().max() for ordered categories.

#### Expected Output

Expected output should be np.nan

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 18.7.0
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_US.UTF-8

pandas           : 1.0.3
numpy            : 1.17.3
pytz             : 2019.3
dateutil         : 2.8.0
pip              : 20.0.2
setuptools       : 40.8.0
Cython           : None
pytest           : 5.2.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : 1.2.2
lxml.etree       : 4.4.2
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : 7.8.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.4.2
matplotlib       : 3.1.1
numexpr          : None
odfpy            : None
openpyxl         : 3.0.0
pandas_gbq       : None
pyarrow          : 0.15.0
pytables         : None
pytest           : 5.2.1
pyxlsb           : None
s3fs             : 0.2.2
scipy            : 1.3.1
sqlalchemy       : None
tables           : None
tabulate         : 0.8.5
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : 1.2.2
numba            : None

</details>
