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BUG: Pandas Series.str.contains with StringDtype("pyarrow") returns pd.BooleanDtype() instead of Arrow bool type #52156
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Thanks for the report.
If you use
|
@mroeschke What is the difference between "string[pyarrow]" and pd.ArrowDtype(pa.string()? I thought it was 2 equivalent ways of specifying an arrow datatype. Also, just wanted to also mention that regex flags with arrow backend are not implemented yet:
Since my understanding is that arrow uses a different regex engine than the python re module, will arrow datatype regex support the same regex flags that work with the string pandas ea type? |
This will first depend whether pyarrow will support this functionality in the future. If not, then there will need to be custom implementation in pandas. |
Should we close this @mroeschke? I guess there is nothing to do now |
Yeah I'm not sure if |
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
An ea type is returned from an arrow series.
Expected Behavior
I expect an arrow type to be returned. There is a warning present:
:1: PerformanceWarning: Falling back on a non-pyarrow code path which may decrease performance.
But I thought that once data is in arrow it should stay in arrow. So will this eventually use arrow code or will it leverage the python re module?
Installed Versions
INSTALLED VERSIONS
commit : 1a2e300
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 : 2.0.0rc0
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 67.2.0
pip : 22.3.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : None
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 : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : None
qtpy : None
pyqt5 : None
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