BUG: Pie chart with categorical values fails

[darkdragon-001]

• I have checked that this issue has not already been reported.
• 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.

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Code Sample, a copy-pastable example

import pandas as pd
pd.Series(pd.Categorical(['cat'], categories=['cat'], ordered=True)).plot.pie()

Problem description

It should be possible to plot a pie chart with categorical values.

Traceback:

Traceback (most recent call last):
  File "", line 1, in 
  File "/usr/lib/python3/dist-packages/pandas/plotting/_core.py", line 1528, in pie
    return self(kind="pie", **kwargs)
  File "/usr/lib/python3/dist-packages/pandas/plotting/_core.py", line 949, in __call__
    return plot_backend.plot(data, kind=kind, **kwargs)
  File "/usr/lib/python3/dist-packages/pandas/plotting/_matplotlib/__init__.py", line 60, in plot
    plot_obj = PLOT_CLASSES[kind](data, **kwargs)
  File "/usr/lib/python3/dist-packages/pandas/plotting/_matplotlib/core.py", line 1506, in __init__
    data = data.fillna(value=0)
  File "/usr/lib/python3/dist-packages/pandas/core/series.py", line 4530, in fillna
    return super().fillna(
  File "/usr/lib/python3/dist-packages/pandas/core/generic.py", line 6061, in fillna
    new_data = self._mgr.fillna(
  File "/usr/lib/python3/dist-packages/pandas/core/internals/managers.py", line 594, in fillna
    return self.apply(
  File "/usr/lib/python3/dist-packages/pandas/core/internals/managers.py", line 409, in apply
    applied = getattr(b, f)(**kwargs)
  File "/usr/lib/python3/dist-packages/pandas/core/internals/blocks.py", line 1779, in fillna
    values = values.fillna(value=value, limit=limit)
  File "/usr/lib/python3/dist-packages/pandas/core/arrays/categorical.py", line 1721, in fillna
    raise ValueError("fill value must be in categories")
ValueError: fill value must be in categories

Expected Output

It should generate pie chart without errors.

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit : b5958ee python : 3.9.5.final.0 python-bits : 64 OS : Linux OS-release : 5.8.0-50-generic Version : #56-Ubuntu SMP Mon Apr 12 17:18:36 UTC 2021 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8

pandas : 1.1.5
numpy : 1.19.5
pytz : 2021.1
dateutil : 2.8.1
pip : 20.3.4
setuptools : 52.0.0
Cython : 0.29.21
pytest : 6.0.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.3
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : None
pandas_datareader: None
bs4 : 4.9.3
bottleneck : 1.2.1
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.4
numexpr : 2.7.2
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.6.0
sqlalchemy : None
tables : 3.6.1
tabulate : None
xarray : None
xlrd : None
xlwt : 1.3.0
numba : None

Additional context

Might be linked to #39320 and #32414

[darkdragon-001]

I was using it wrongly. Correct way:

import pandas as pd
pd.Categorical(['cat'], categories=['cat'], ordered=True).value_counts().plot.pie()