BUG: Union of multi index with EA types can lose EA dtype

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Reproducible Example

>>> from cyberpandas import IPArray
>>> import pandas as pd
>>> 
>>> df1 = pd.DataFrame({
...     'address': IPArray(['192.168.1.1', '192.168.1.10']),
...     'date': ['2022-01-01', '2022-01-02'],
...     'a': [1, 2]
... })
>>> df1 = df1.set_index(['address', 'date'])
>>> 
>>> 
>>> df2 = pd.DataFrame({
...     'address': IPArray(['192.168.1.1', '192.168.1.10']),
...     'date': pd.to_datetime(['2022-01-01', '2022-01-02']),
...     'a': [1, 2]
... })
>>> df2 = df2.set_index(['address', 'date'])
>>> 
>>> df1.index.dtypes
address        ip
date       object
dtype: object
>>> 
>>> df2.index.dtypes
address                ip
date       datetime64[ns]
dtype: object
>>> 
>>> df1.index.union(df2.index).dtypes
address            object   # <-- should be type "ip", not "object"
date       datetime64[ns]
dtype: object

Issue Description

The ExtensionType can get lost when two MultiIndex objects are combined by .union() (which becomes a problem when using df.combine_first(...) which relies on index.union(...)).

The problem occurs when both MIs share the same EA series, but the other series (assuming only 2-series MI) has a different type. In that case, the former EA dimension of the joined MI is losing its EA dtype.

Expected Behavior

EA type can be maintained after index.union(...).

Installed Versions

INSTALLED VERSIONS

commit : e8093ba372f9adfe79439d90fe74b0b5b6dea9d6 python : 3.8.13.final.0 python-bits : 64 OS : Darwin OS-release : 21.5.0 Version : Darwin Kernel Version 21.5.0: Tue Apr 26 21:08:22 PDT 2022; root:xnu-8020.121.3~4/RELEASE_X86_64 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : en_AU.UTF-8 LOCALE : en_AU.UTF-8

pandas : 1.4.3 numpy : 1.23.1 pytz : 2022.1 dateutil : 2.8.2 setuptools : 62.3.2 pip : 22.1.1 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 brotli : None fastparquet : None fsspec : None gcsfs : None markupsafe : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pyreadstat : None pyxlsb : None s3fs : None scipy : None snappy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlwt : None zstandard : None

[phofl]

Hi, thanks for your report. As a note: This also happens for our own extension arrays.

[phofl]

We did a couple of prs in that are. You can check the whatsnew for 2.0, they are documented there