BUG: pd.DataFrame.to_hdf does not support multiindex frames with string[pyarrow_numpy]
#55088
Closed
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string[pyarrow_numpy]
#55088
Pandas version checks
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
Issue Description
Looks like using
string[pyarrow_numpy]
as dtype andto_hdf
with a multiindex frame throws a value error. The error comes frompytables.py
and more specifically the check below.pandas/pandas/io/pytables.py
Lines 2647 to 2650 in 723feb9
The
is_object_dtype
always checks againstnp.object_
.pandas/pandas/core/dtypes/common.py
Lines 137 to 165 in 723feb9
Expected Behavior
I would expect that
is_object_dtype
allows forstring[pyrrow_numpy]
(if and only if downstream behavior is supported by that dtype). If that action is not supported withstring[pyarrow_numpy]
I would expected a more informative error.Installed Versions
INSTALLED VERSIONS
commit : 723feb9
python : 3.9.13.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 165 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United States.1252
pandas : 2.2.0dev0+208.g723feb984e
numpy : 1.22.4
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 68.0.0
pip : 23.2.1
Cython : 0.29.36
pytest : 6.2.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : None
pandas_datareader : None
bs4 : None
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : 0.56.4
numexpr : 2.8.5
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 10.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.1
sqlalchemy : None
tables : 3.7.0
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None
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