BUG: Unable to create a MultiIndex with `nan` values in nullable `Float` dtypes
- [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.

---

**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
>>> df = pd.DataFrame({'a':pd.Series([1, 2, None], dtype='Int64'), 'b':pd.Float64Dtype().__from_arrow__(pa.array([0.2, np.nan, None]))})
>>> df
      a     b
0     1   0.2
1     2   NaN
2  <NA>  <NA>
>>> pd.MultiIndex.from_frame(df)
Traceback (most recent call last):
  File "<input>", line 1, in <module>
  File "/Users/pgali/PycharmProjects/del/venv1/lib/python3.7/site-packages/pandas/core/indexes/multi.py", line 662, in from_frame
    return cls.from_arrays(columns, sortorder=sortorder, names=names)
  File "/Users/pgali/PycharmProjects/del/venv1/lib/python3.7/site-packages/pandas/core/indexes/multi.py", line 462, in from_arrays
    codes, levels = factorize_from_iterables(arrays)
  File "/Users/pgali/PycharmProjects/del/venv1/lib/python3.7/site-packages/pandas/core/arrays/categorical.py", line 2632, in factorize_from_iterables
    return map(list, zip(*(factorize_from_iterable(it) for it in iterables)))
  File "/Users/pgali/PycharmProjects/del/venv1/lib/python3.7/site-packages/pandas/core/arrays/categorical.py", line 2632, in <genexpr>
    return map(list, zip(*(factorize_from_iterable(it) for it in iterables)))
  File "/Users/pgali/PycharmProjects/del/venv1/lib/python3.7/site-packages/pandas/core/arrays/categorical.py", line 2604, in factorize_from_iterable
    cat = Categorical(values, ordered=False)
  File "/Users/pgali/PycharmProjects/del/venv1/lib/python3.7/site-packages/pandas/core/arrays/categorical.py", line 359, in __init__
    dtype = CategoricalDtype(categories, dtype.ordered)
  File "/Users/pgali/PycharmProjects/del/venv1/lib/python3.7/site-packages/pandas/core/dtypes/dtypes.py", line 160, in __init__
    self._finalize(categories, ordered, fastpath=False)
  File "/Users/pgali/PycharmProjects/del/venv1/lib/python3.7/site-packages/pandas/core/dtypes/dtypes.py", line 314, in _finalize
    categories = self.validate_categories(categories, fastpath=fastpath)
  File "/Users/pgali/PycharmProjects/del/venv1/lib/python3.7/site-packages/pandas/core/dtypes/dtypes.py", line 508, in validate_categories
    raise ValueError("Categorical categories cannot be null")
ValueError: Categorical categories cannot be null
```

#### Problem description
Should `nan` be allowed in the first place while creating a nullable floating array? If yes, then we have an issue while creating a mulit-index from the dataframe.



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

<details>

INSTALLED VERSIONS
------------------
commit           : 7d32926db8f7541c356066dcadabf854487738de
python           : 3.7.3.final.0
python-bits      : 64
OS               : Darwin
OS-release       : 20.3.0
Version          : Darwin Kernel Version 20.3.0: Thu Jan 21 00:07:06 PST 2021; root:xnu-7195.81.3~1/RELEASE_X86_64
machine          : x86_64
processor        : i386
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : en_US.UTF-8
pandas           : 1.2.2
numpy            : 1.19.2
pytz             : 2020.1
dateutil         : 2.8.1
pip              : 20.2.3
setuptools       : 50.3.0
Cython           : None
pytest           : None
hypothesis       : 5.29.0
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.11.2
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 1.0.1
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
