concatenating frame and series with identical keys returns " int() argument must be a string"

[MarcoGorelli]

Code Sample, a copy-pastable example if possible

>>> import pandas as pd
>>> s = pd.Series([1, 2])                                                                                                                                                                                        
>>> df = pd.DataFrame([[1, 2], [3, 4]])                                                                                                                                                                          
>>> pd.concat([df, s], axis=1, keys=['a', 'a']) 

Problem description

This returns

Traceback

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-4-262b5243c6cf> in <module>
----> 1 pd.concat([df, s], axis=1, keys=['a', 'a'])

~/pandas/pandas/core/reshape/concat.py in concat(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)
    278         verify_integrity=verify_integrity,
    279         copy=copy,
--> 280         sort=sort,
    281     )
    282 

~/pandas/pandas/core/reshape/concat.py in __init__(self, objs, axis, join, keys, levels, names, ignore_index, verify_integrity, copy, sort)
    447         self.copy = copy
    448 
--> 449         self.new_axes = self._get_new_axes()
    450 
    451     def get_result(self):

~/pandas/pandas/core/reshape/concat.py in _get_new_axes(self)
    510         return [
    511             self._get_concat_axis() if i == self.axis else self._get_comb_axis(i)
--> 512             for i in range(ndim)
    513         ]
    514 

~/pandas/pandas/core/reshape/concat.py in <listcomp>(.0)
    510         return [
    511             self._get_concat_axis() if i == self.axis else self._get_comb_axis(i)
--> 512             for i in range(ndim)
    513         ]
    514 

~/pandas/pandas/core/reshape/concat.py in _get_concat_axis(self)
    566         else:
    567             concat_axis = _make_concat_multiindex(
--> 568                 indexes, self.keys, self.levels, self.names
    569             )
    570 

~/pandas/pandas/core/reshape/concat.py in _make_concat_multiindex(indexes, keys, levels, names)
    648 
    649         return MultiIndex(
--> 650             levels=levels, codes=codes_list, names=names, verify_integrity=False
    651         )
    652 

~/pandas/pandas/core/indexes/multi.py in __new__(cls, levels, codes, sortorder, names, dtype, copy, name, verify_integrity, _set_identity)
    281         # we've already validated levels and codes, so shortcut here
    282         result._set_levels(levels, copy=copy, validate=False)
--> 283         result._set_codes(codes, copy=copy, validate=False)
    284 
    285         result._names = [None] * len(levels)

~/pandas/pandas/core/indexes/multi.py in _set_codes(self, codes, level, copy, validate, verify_integrity)
    864             new_codes = FrozenList(
    865                 _coerce_indexer_frozen(level_codes, lev, copy=copy).view()
--> 866                 for lev, level_codes in zip(self._levels, codes)
    867             )
    868         else:

~/pandas/pandas/core/indexes/multi.py in <genexpr>(.0)
    864             new_codes = FrozenList(
    865                 _coerce_indexer_frozen(level_codes, lev, copy=copy).view()
--> 866                 for lev, level_codes in zip(self._levels, codes)
    867             )
    868         else:

~/pandas/pandas/core/indexes/multi.py in _coerce_indexer_frozen(array_like, categories, copy)
   3597         Non-writeable.
   3598     """
-> 3599     array_like = coerce_indexer_dtype(array_like, categories)
   3600     if copy:
   3601         array_like = array_like.copy()

~/pandas/pandas/core/dtypes/cast.py in coerce_indexer_dtype(indexer, categories)
    856     length = len(categories)
    857     if length < _int8_max:
--> 858         return ensure_int8(indexer)
    859     elif length < _int16_max:
    860         return ensure_int16(indexer)

~/pandas/pandas/_libs/algos_common_helper.pxi in pandas._libs.algos.ensure_int8()
     59             return arr
     60         else:
---> 61             return arr.astype(np.int8, copy=copy)
     62     else:
     63         return np.array(arr, dtype=np.int8)

TypeError: int() argument must be a string, a bytes-like object or a number, not 'slice'

Expected Output

I would either expect this to work, or for it to return

InvalidIndexError: Reindexing only valid with uniquely valued Index objects

, which is what happens when you do

pd.concat([df, df], axis=1, keys=['a', 'a'])

Output of pd.show_versions()

INSTALLED VERSIONS

commit : 36d6583
python : 3.7.6.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-91-generic
Version : #92-Ubuntu SMP Fri Feb 28 11:09:48 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 0.26.0.dev0+2746.g36d6583cf
numpy : 1.18.1
pytz : 2019.3
dateutil : 2.8.1
pip : 20.0.2
setuptools : 45.1.0.post20200119
Cython : 0.29.16
pytest : 5.4.1
hypothesis : 5.8.0
sphinx : 2.4.4
blosc : None
feather : None
xlsxwriter : 1.2.8
lxml.etree : 4.5.0
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.1
IPython : 7.13.0
pandas_datareader: None
bs4 : 4.8.2
bottleneck : 1.3.2
fastparquet : 0.3.3
gcsfs : None
matplotlib : 3.1.3
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.1
pandas_gbq : None
pyarrow : 0.16.0
pytables : None
pyxlsb : None
s3fs : 0.4.0
scipy : 1.4.1
sqlalchemy : 1.3.15
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.15.0
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.48.0

[MarcoGorelli]

duplicate of #33654