BUG: concat series with NA in multiindex fail to combine rows of same index

[hdou]

• 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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Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.

Code Sample, a copy-pastable example

# Your code here
import pandas as pd

names=['A1','A2']

idx1 = pd.MultiIndex.from_tuples([(1,1), (2, pd.NA)], names=names)
idx2 = pd.MultiIndex.from_tuples([(2, pd.NA), (3,3)], names=names)

s1 = pd.Series([11,12], index=idx1)
s2 = pd.Series([13,14], index=idx2)
s3 = pd.concat([s1, s2], axis=1)
print (s3)
# s3 fails to combine the two rows with index (2, NaN)
#            0     1
# A1 A2
# 1  1.0  11.0   NaN
# 2  NaN  12.0  13.0
#    NaN  12.0  13.0
# 3  3.0   NaN  14.0


# Workaround is to use merge after reset index
s1 = s1.reset_index()
s2 = s2.reset_index()
s3 = pd.merge(s1,s2,on=names,how='outer')
s3 = s3.set_index(names)
print (s3)
# Now the result is expected
# A1 A2
# 1  1.0  11.0   NaN
# 2  NaN  12.0  13.0
# 3  3.0   NaN  14.0

Problem description

[this should explain why the current behaviour is a problem and why the expected output is a better solution]

Expected Output

Output of pd.show_versions()

[paste the output of pd.show_versions() here leaving a blank line after the details tag]
INSTALLED VERSIONS

commit : 2a7d332
python : 3.8.5.final.0
python-bits : 64
OS : Darwin
OS-release : 18.7.0
Version : Darwin Kernel Version 18.7.0: Thu Jun 18 20:50:10 PDT 2020; root:xnu-4903.278.43~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.1.2
numpy : 1.19.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1.1
setuptools : 47.1.0
Cython : 0.29.21
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
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.3.1
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pytables : None
pyxlsb : None
s3fs : None
scipy : 1.5.2
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

[dsaxton]

See @phofl's response to your other issue #36479. Also #30750 #36060 #36470, etc.

[kidrahahjo]

@hdou are you still having trouble with this?

[mroeschke]

Thanks for the report. Agreed, this issue seems overlap/be address from the linked issues so closing.