Single-level tuple index to multi-level index on pd.concat

[harisbal]

import pandas as pd
import numpy as np

s1 = pd.Series(np.random.randn(2), index=[('a', 'b'), ('x', 'y', 'z')])
s1.index.name = 'Idx'
s1.name = 's1'

s2 = pd.Series(np.random.randn(2), index=[('a', 'b'), ('j', 'k', 'l')])
s2.index.name = 'Idx'
s2.name = 's2'

# Result
pd.concat([s1, s2], axis=1, sort=False)

Problem description

Concatenating two series with a tuple as index, results in a multi-indexed dataframe

Expected Output

s1.to_frame().join(s2)

Output of pd.show_versions()

[paste the output of pd.show_versions() here below this line]
INSTALLED VERSIONS

commit: None
python: 3.6.6.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.24.0.dev0+1028.gdb2066b7d
pytest: 3.8.1
pip: 18.1
setuptools: 40.2.0
Cython: 0.28.5
numpy: 1.15.1
scipy: 1.1.0
pyarrow: None
xarray: None
IPython: 5.0.0
sphinx: None
patsy: None
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 2.2.3
openpyxl: 2.5.6
xlrd: 1.1.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.2.11
pymysql: 0.9.2
psycopg2: 2.7.5 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None

[simonjayhawkins]

i guess the expected should be

s1.to_frame().join(s2, how='outer')

which gives

	s1	s2
Idx
(a, b)	-0.635822	0.036792
(j, k, l)	NaN	2.380095
(x, y, z)	1.149677	NaN

so pd.concat([s1, s2], axis=1, sort=False) also appears to be losing values

			s1	s2
a	b	NaN	NaN	NaN
x	y	z	1.149677	NaN
j	k	l	NaN	2.380095

[simonjayhawkins]

@WillAyd #24687 (comment). is this issue a bug?

[simonjayhawkins]

xref #24688

[summonholmes]

@WillAyd #24687 (comment). is this issue a bug?

Just closed it. This issue was more of an esoteric demonstration, where too many nested tuples results in some breakages (perhaps due to underlying bugs). There is no support for what I was doing, but how was I supposed to know? I could get away with it without raising an error, until lib.clean_index_list() started returning strangely shaped ndarrays.