Description
Pandas version checks
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
x = pd.DataFrame({"a": ["a1", "a1", "a2"], "b": ["b1", "b2", "b3"]}, dtype=pd.StringDtype())
x = x.set_index(["a", "b"])
y = pd.DataFrame({"a": ["a1"], "c": ["c1"]}, dtype=pd.StringDtype())
y = y.set_index(["a", "c"])
z = x.join(y, how="inner")Issue Description
When joining 2 data frames with the StringDtype dtype index, the inner join gives incorrect results. The outcome of z returns a multi-index with only 1 row:
"a1", "b1", "c1"
It does work when I don't explicitly set the dtype. In that case the index dtypes are object.
Expected Behavior
The expected result for data frame z is 2 rows (just like in Pandas 1.4.x), namely:
"a1", "b1", "c1"
"a1", "b2", "c1"
Installed Versions
INSTALLED VERSIONS
commit : 91111fd
python : 3.10.8.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 85 Stepping 7, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252
pandas : 1.5.1
numpy : 1.23.4
pytz : 2022.5
dateutil : 2.8.2
setuptools : 65.3.0
pip : 22.3
Cython : None
pytest : 7.1.3
hypothesis : None
sphinx : 5.3.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : 1.0.9
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 1.4.42
tables : None
tabulate : 0.8.10
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None