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BUG: Multiplying strings by int fails with ArrowNotImplementedError: #51970
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Another NotImlemented error: dec = pd.Series([decimal.Decimal("12.123")], dtype=pd.ArrowDtype(pa.decimal128(5, 3)))
This error, unlike the above, is coming from Pandas, not pyarrow. Will modulus support be added in the future in Pandas with decimal arrow dtype? This same code succeeds if the decimal is stored in object typed series (not using arrow dtypes). Is it planned to have parity/consistency between numpy types and the newer arrow types? The code fails with int8 pyarrow type as well, but when using an int8 from numpy, it succeeds. |
Hi, thanks for your report. Regarding modulo: We are raising NotImplemented because pyarrow does not provide a modulo function yet. |
@phofl Thanks for your response. Is the expectation, that one day, there will be parity between numpy and arrow datatypes? |
Yes. Arrow is a much newer library than NumPy, but it's actively being worked on. |
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
The operation of multiplying strings by int when the strings are stored using pd.StringDtype() is a repeat operation and succeeds, using pyarrow, it fails with ArrowNotImplementedError, does this mean that it's something that will be supported in the future? Is the expectation to have parity/consistency between the pandas backend and pyarrow backend?
Expected Behavior
I expect the behavior I get with pandas extension types:
Installed Versions
INSTALLED VERSIONS
commit : 91111fd
python : 3.8.10.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22621
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 : 2021.3
dateutil : 2.8.2
setuptools : 60.8.2
pip : 22.3.1
Cython : None
pytest : 7.0.1
hypothesis : None
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 8.1.1
pandas_datareader: None
bs4 : 4.10.0
bottleneck : None
brotli : None
fastparquet : 2023.2.0
fsspec : 2023.3.0
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 9.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : 0.8.9
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None
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