BUG: pandas 1.0 dropna error with categorical data if pd.options.mode.use_inf_as_na = True
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- [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.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

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

```python
import pandas as pd
import numpy as np
from pandas.api.types import CategoricalDtype

# with categorical column and use_inf_as_na = True -> ERROR
pd.options.mode.use_inf_as_na = True
df1 = pd.DataFrame([['a1', 'good'], ['b1', 'good'], ['c1', 'good'], ['d1', 'bad']], columns=['C1', 'C2'])
df2 = pd.DataFrame([['a1', 'good'], ['b1', np.inf], ['c1', np.NaN], ['d1', 'bad']], columns=['C1', 'C2'])
categories = CategoricalDtype(categories=['good', 'bad'], ordered=True)
df1.loc[:, 'C2'] = df1['C2'].astype(categories)
df2.loc[:, 'C2'] = df2['C2'].astype(categories)
df1.dropna(axis=0)  # ERROR
df2.dropna(axis=0)  # ERROR
```

#### Problem description

With the latest version of pandas (1.0.3, installed via pip on python 3.6.8), DataFrame.dropna returns an error if a column is of type **CategoricalDtype** AND **pd.options.mode.use_inf_as_na = True**. 

Exception with traceback:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/frame.py", line 4751, in dropna
    count = agg_obj.count(axis=agg_axis)
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/frame.py", line 7800, in count
    result = notna(frame).sum(axis=axis)
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/dtypes/missing.py", line 376, in notna
    res = isna(obj)
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/dtypes/missing.py", line 126, in isna
    return _isna(obj)
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/dtypes/missing.py", line 185, in _isna_old
    return obj._constructor(obj._data.isna(func=_isna_old))
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/internals/managers.py", line 555, in isna
    return self.apply("apply", func=func)
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/internals/managers.py", line 442, in apply
    applied = getattr(b, f)(**kwargs)
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/internals/blocks.py", line 390, in apply
    result = func(self.values, **kwargs)
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/dtypes/missing.py", line 183, in _isna_old
    return _isna_ndarraylike_old(obj)
  File "/home/sbucc/miniconda3/envs/tf114/lib/python3.6/site-packages/pandas/core/dtypes/missing.py", line 283, in _isna_ndarraylike_old
    vec = libmissing.isnaobj_old(values.ravel())
TypeError: Argument 'arr' has incorrect type (expected numpy.ndarray, got Categorical)

This doesn't happen with pandas 0.24.0 or if pd.options.mode.use_inf_as_na = False (default).

#### Expected Output

no error

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

<details>

>>> pd.show_versions()

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.6.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 4.15.0-96-generic
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_GB.UTF-8
LOCALE           : en_GB.UTF-8

pandas           : 1.0.3
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.3.post20200330
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.1
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : None

</details>
