BUG: concat series returns error result when indexes use tuples with NA in them

[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 = [(1,1), (2, pd.NA)]
idx2 = [(2, pd.NA), (3,3)]

s1 = pd.Series([11,12], index=idx1)
s2 = pd.Series([13,14], index=idx2)
s3 = pd.concat([s1, s2], axis=1)
print (s3)
#           0     1
# 1 1    11.0   NaN
# 2 NaN   NaN   NaN     <= expect 12.0 13.0 as the values
# 3 3     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.

[ivanovmg]

Probably because pd.NA is not comparable (no equal, not not equal) with pd.NA?
I am not sure, but I guess index values have to be comparable with each other.

Similar cases (or maybe not).

This works.

df1 = pd.DataFrame({'a': [1, 2]}, index=[pd.NA, 1])
df2 = pd.DataFrame({'b': [4, 5]}, index=[1, pd.NA])
df = pd.concat([df1, df2], axis=1)
print(df)

producing

     a  b
NaN  1  5
1    2  4

This - does not.

df1 = pd.DataFrame({'a': [1, 2, 3]}, index=[pd.NA, 1, pd.NA])
df2 = pd.DataFrame({'b': [4, 5, 6]}, index=[1, pd.NA, pd.NA])
df = pd.concat([df1, df2], axis=1)
print(df)

Traceback (most recent call last):
  File "temp/formatters.py", line 29, in <module>
    df = pd.concat([df1, df2], axis=1)
  File "/workspaces/pandas/pandas/core/reshape/concat.py", line 288, in concat
    return op.get_result()
  File "/workspaces/pandas/pandas/core/reshape/concat.py", line 504, in get_result
    mgrs_indexers, self.new_axes, concat_axis=self.bm_axis, copy=self.copy
  File "/workspaces/pandas/pandas/core/internals/concat.py", line 85, in concatenate_block_managers
    return BlockManager(blocks, axes)
  File "/workspaces/pandas/pandas/core/internals/managers.py", line 142, in __init__
    self._verify_integrity()
  File "/workspaces/pandas/pandas/core/internals/managers.py", line 319, in _verify_integrity
    raise construction_error(tot_items, block.shape[1:], self.axes)
ValueError: Shape of passed values is (3, 2), indices imply (2, 2)

[mroeschke]

Thanks for the report. Agreed that this seem to overlap/be related to linked issues so going to close in favor of those issues.