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Reproducible Example

a = pd.Series(
    data = [7575709, 7600316, 7537176, 7526456, 7174444, 7548816, 7474075, 7636965, 7526409, 7636980],
    name = 'ArticleID',
    dtype = "uint64[pyarrow]",
)
b = pd.Series(
    data = [3, 3, 3, 3, 3, 0, 3, 16, 3, 8],
    name = 'Delivery_Quantity_Base_Unit',
    dtype = "uint8[pyarrow]",
)
index = pd.Series(
    data = [7526409, 7600316, 7474075, 7575709, 7174444, 7526456, 7537176, 7548816, 7636965, 7636980],
    name = "ArticleID",
    dtype= 'int64[pyarrow]'
)
ip = pd.Series(
    data = [3, 3, 3, 3, 3, 3, 3, 10, 16, 8],
    index = index,
    name = "IP/CV",
    dtype= 'uint8[pyarrow]'
)
df = pd.concat([a, b], axis=1)

df.join(ip, on="ArticleID")

Issue Description

Join fails because of a keyerror. It does work with a numpy backend.

--------------------------------------------------------------------------- KeyError Traceback (most recent call last) Cell In[152], line 1 ----> 1 df.join(ip, on="ArticleID") File [c:\ProgramData\Miniconda3\envs\DLL_ETL\lib\site-packages\pandas\core\frame.py:9729](file:///C:/ProgramData/Miniconda3/envs/DLL_ETL/lib/site-packages/pandas/core/frame.py:9729), in DataFrame.join(self, other, on, how, lsuffix, rsuffix, sort, validate) [9566] def join( [9567] self, [9568] other: DataFrame | Series | Iterable[DataFrame | Series], (...) [9574] validate: str | None = None, [9575] ) -> DataFrame: [9576] """ [9577] Join columns of another DataFrame. [9578] (...) [9727] 5 K1 A5 B1 [9728] """ -> [9729] return self._join_compat( [9730] other, [9731] on=on, [9732] how=how, [9733] lsuffix=lsuffix, [9734] rsuffix=rsuffix, [9735] sort=sort, [9736] validate=validate, [9737] ) File [c:\ProgramData\Miniconda3\envs\DLL_ETL\lib\site-packages\pandas\core\frame.py:9768](file:///C:/ProgramData/Miniconda3/envs/DLL_ETL/lib/site-packages/pandas/core/frame.py:9768), in DataFrame._join_compat(self, other, on, how, lsuffix, rsuffix, sort, validate) [9758] if how == "cross": [9759] return merge( [9760] self, [9761] other, (...) [9766] validate=validate, [9767] ) -> [9768] return merge( [9769] self, [9770] other, [9771] left_on=on, [9772] how=how, [9773] left_index=on is None, [9774] right_index=True, [9775] suffixes=(lsuffix, rsuffix), [9776] sort=sort, [9777] validate=validate, [9778] ) [9779] else: [9780] if on is not None: File [c:\ProgramData\Miniconda3\envs\DLL_ETL\lib\site-packages\pandas\core\reshape\merge.py:156](file:///C:/ProgramData/Miniconda3/envs/DLL_ETL/lib/site-packages/pandas/core/reshape/merge.py:156), in merge(left, right, how, on, left_on, right_on, left_index, right_index, sort, suffixes, copy, indicator, validate) [125]@Substitution("\nleft : DataFrame or named Series") [126]@Appender(_merge_doc, indents=0) [127]def merge( (...) [140] validate: str | None = None, [141]) -> DataFrame: [142] op = _MergeOperation( [143] left, [144] right, (...) [154] validate=validate, [155] ) --> [156] return op.get_result(copy=copy) File [c:\ProgramData\Miniconda3\envs\DLL_ETL\lib\site-packages\pandas\core\reshape\merge.py:803](file:///C:/ProgramData/Miniconda3/envs/DLL_ETL/lib/site-packages/pandas/core/reshape/merge.py:803), in _MergeOperation.get_result(self, copy) [800]if self.indicator: [801] self.left, self.right = self._indicator_pre_merge(self.left, self.right) --> [803]join_index, left_indexer, right_indexer = self._get_join_info() [805]result = self._reindex_and_concat( [806] join_index, left_indexer, right_indexer, copy=copy [807]) [808]result = result.__finalize__(self, method=self._merge_type) File [c:\ProgramData\Miniconda3\envs\DLL_ETL\lib\site-packages\pandas\core\reshape\merge.py:1042](file:///C:/ProgramData/Miniconda3/envs/DLL_ETL/lib/site-packages/pandas/core/reshape/merge.py:1042), in _MergeOperation._get_join_info(self) [1037] join_index, left_indexer, right_indexer = left_ax.join( [1038] right_ax, how=self.how, return_indexers=True, sort=self.sort [1039] ) [1041] elif self.right_index and self.how == "left": -> [1042] join_index, left_indexer, right_indexer = _left_join_on_index( [1043] left_ax, right_ax, self.left_join_keys, sort=self.sort [1044] ) [1046] elif self.left_index and self.how == "right": [1047] join_index, right_indexer, left_indexer = _left_join_on_index( [1048] right_ax, left_ax, self.right_join_keys, sort=self.sort [1049] ) File [c:\ProgramData\Miniconda3\envs\DLL_ETL\lib\site-packages\pandas\core\reshape\merge.py:2281](file:///C:/ProgramData/Miniconda3/envs/DLL_ETL/lib/site-packages/pandas/core/reshape/merge.py:2281), in _left_join_on_index(left_ax, right_ax, join_keys, sort) [2278] else: [2279] jkey = join_keys[0] -> [2281] left_indexer, right_indexer = _get_single_indexer(jkey, right_ax, sort=sort) [2283] if sort or len(left_ax) != len(left_indexer): [2284] # if asked to sort or there are 1-to-many matches [2285] join_index = left_ax.take(left_indexer) File [c:\ProgramData\Miniconda3\envs\DLL_ETL\lib\site-packages\pandas\core\reshape\merge.py:2220](file:///C:/ProgramData/Miniconda3/envs/DLL_ETL/lib/site-packages/pandas/core/reshape/merge.py:2220), in _get_single_indexer(join_key, index, sort) [2217] def _get_single_indexer( [2218] join_key, index: Index, sort: bool = False [2219] ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: -> [2220] left_key, right_key, count = _factorize_keys(join_key, index._values, sort=sort) [2222] return libjoin.left_outer_join(left_key, right_key, count, sort=sort) File [c:\ProgramData\Miniconda3\envs\DLL_ETL\lib\site-packages\pandas\core\reshape\merge.py:2382](file:///C:/ProgramData/Miniconda3/envs/DLL_ETL/lib/site-packages/pandas/core/reshape/merge.py:2382), in _factorize_keys(lk, rk, sort, how) [2378] # error: Item "ndarray" of "Union[Any, ndarray]" has no attribute [2379] # "_values_for_factorize" [2380] rk, _ = rk._values_for_factorize() # type: ignore[union-attr] -> [2382] klass, lk, rk = _convert_arrays_and_get_rizer_klass(lk, rk) [2384] rizer = klass(max(len(lk), len(rk))) [2386] if isinstance(lk, BaseMaskedArray): File [c:\ProgramData\Miniconda3\envs\DLL_ETL\lib\site-packages\pandas\core\reshape\merge.py:2449](file:///C:/ProgramData/Miniconda3/envs/DLL_ETL/lib/site-packages/pandas/core/reshape/merge.py:2449), in _convert_arrays_and_get_rizer_klass(lk, rk) [2447] klass = _factorizers[lk.dtype.type] # type: ignore[index] [2448] else: -> [2449] klass = _factorizers[lk.dtype.type] [2451] else: [2452] klass = libhashtable.ObjectFactorizer KeyError:

Expected Behavior

Join should just work as it does with a numpy backend. Reproducable example in details.

a = pd.Series(
    data = [7575709, 7600316, 7537176, 7526456, 7174444, 7548816, 7474075, 7636965, 7526409, 7636980],
    name = 'ArticleID',
    dtype = np.uint64,
)
b = pd.Series(
    data = [3, 3, 3, 3, 3, 0, 3, 16, 3, 8],
    name = 'Delivery_Quantity_Base_Unit',
    dtype = np.uint8,
)
index = pd.Series(
    data = [7526409, 7600316, 7474075, 7575709, 7174444, 7526456, 7537176, 7548816, 7636965, 7636980],
    name = "ArticleID",
    dtype= np.int64
)
ip = pd.Series(
    data = [3, 3, 3, 3, 3, 3, 3, 10, 16, 8],
    index = index,
    name = "IP/CV",
    dtype= np.uint8
)
df = pd.concat([a, b], axis=1)
df.join(ip, on="ArticleID")

Installed Versions

INSTALLED VERSIONS ------------------ commit : 478d340667831908b5b4bf09a2787a11a14560c9 python : 3.10.10.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19042 machine : AMD64 processor : AMD64 Family 23 Model 24 Stepping 1, AuthenticAMD byteorder : little LC_ALL : None LANG : None LOCALE : English_Netherlands.1252 pandas : 2.0.0 numpy : 1.23.5 pytz : 2023.3 dateutil : 2.8.2 setuptools : 67.6.1 pip : 23.0.1 Cython : None pytest : 7.2.2 hypothesis : None sphinx : 6.1.3 blosc : None feather : None xlsxwriter : 3.0.9 lxml.etree : 4.9.2 html5lib : 1.1 pymysql : None psycopg2 : None jinja2 : 3.1.2 IPython : 8.12.0 pandas_datareader: 0.10.0 bs4 : 4.12.0 bottleneck : None brotli : fastparquet : None fsspec : 2023.3.0 gcsfs : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : 3.1.1 pandas_gbq : None pyarrow : 11.0.0 pyreadstat : None pyxlsb : 1.0.10 s3fs : None scipy : 1.10.1 snappy : None sqlalchemy : None tables : None tabulate : 0.9.0 xarray : None xlrd : 2.0.1 zstandard : 0.19.0 tzdata : 2023.3 qtpy : 2.3.1 pyqt5 : None