Description
Pandas version checks
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I have checked that this issue has not already been reported.
-
I have confirmed this bug exists on the latest version of pandas.
-
I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
pytest --pdb pandas/tests/test_multilevel.pyIssue Description
The unit-test
pandas/pandas/tests/test_multilevel.py
Line 138 in 65af4ef
does not pass.
I am using VSCode with the .devcontainer file (thus in a container), with a linux distribution (pop-os).
Stack trace:
self = <pandas.tests.test_multilevel.TestMultiLevel object at 0x7fc319bae370>
def test_alignment(self):
x = Series(
data=[1, 2, 3], index=MultiIndex.from_tuples([("A", 1), ("A", 2), ("B", 3)])
)
y = Series(
data=[4, 5, 6], index=MultiIndex.from_tuples([("Z", 1), ("Z", 2), ("B", 3)])
)
> res = x - y
pandas/tests/test_multilevel.py:147:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
pandas/core/ops/common.py:72: in new_method
return method(self, other)
pandas/core/arraylike.py:111: in __sub__
return self._arith_method(other, operator.sub)
pandas/core/series.py:6273: in _arith_method
self, other = ops.align_method_SERIES(self, other)
pandas/core/ops/__init__.py:168: in align_method_SERIES
left, right = left.align(right, copy=False)
pandas/core/series.py:4865: in align
return super().align(
pandas/core/generic.py:9478: in align
return self._align_series(
pandas/core/generic.py:9585: in _align_series
join_index, lidx, ridx = self.index.join(
pandas/util/_decorators.py:317: in wrapper
return func(*args, **kwargs)
pandas/core/indexes/base.py:230: in join
join_index, lidx, ridx = meth(self, other, how=how, level=level, sort=sort)
pandas/core/indexes/base.py:4725: in join
return self._join_via_get_indexer(other, how, sort)
pandas/core/indexes/base.py:4747: in _join_via_get_indexer
join_index = self.union(other)
pandas/core/indexes/base.py:3351: in union
result = self._union(other, sort=sort)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = MultiIndex([('A', 1),
('A', 2),
('B', 3)],
)
other = MultiIndex([('Z', 1),
('Z', 2),
('B', 3)],
), sort = None
def _union(self, other, sort) -> MultiIndex:
other, result_names = self._convert_can_do_setop(other)
if (
any(-1 in code for code in self.codes)
and any(-1 in code for code in other.codes)
or other.has_duplicates
):
# This is only necessary if both sides have nans or other has dups,
# fast_unique_multiple is faster
result = super()._union(other, sort)
if isinstance(result, MultiIndex):
return result
return MultiIndex.from_arrays(
zip(*result), sortorder=None, names=result_names
)
else:
rvals = other._values.astype(object, copy=False)
> right_missing = lib.fast_unique_multiple(self._values, rvals)
E TypeError: Argument 'arrays' has incorrect type (expected list, got numpy.ndarray)
pandas/core/indexes/multi.py:3655: TypeErrorExpected Behavior
The test should pass
Installed Versions
pandas : 1.6.0.dev0+119.gaea824f9aa.dirty
numpy : 1.22.4
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 65.3.0
pip : 22.2.2
Cython : 0.29.32
pytest : 7.1.3
hypothesis : 6.54.5
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.9.1
html5lib : 1.1
pymysql : 1.0.2
psycopg2 : 2.9.3
jinja2 : 3.0.3
IPython : 8.5.0
pandas_datareader: 0.10.0
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : 0.8.3
fsspec : 2021.11.0
gcsfs : 2021.11.0
matplotlib : 3.5.3
numba : 0.55.2
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.8
pyarrow : 9.0.0
pyreadstat : 1.1.9
pyxlsb : 1.0.9
s3fs : 2021.11.0
scipy : 1.9.1
snappy :
sqlalchemy : 1.4.41
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.6.0
xlrd : 2.0.1
xlwt : 1.3.0
zstandard : 0.18.0
tzdata : None