BUG: interchange buffer show bytemask (instead of bitmask) validity for 'string[pyarrow]' #57762
Description
Pandas version checks
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I have checked that this issue has not already been reported.
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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
df = pd.DataFrame({"a": ["x", None]}, dtype="large_string[pyarrow]")
print(df.__dataframe__().get_column_by_name('a').get_buffers())
print(df['a'].array._pa_array.chunks[0].buffers())
print(pai.from_dataframe(df))Issue Description
This shows
{'data': (PandasBuffer({'bufsize': 1, 'ptr': 140019260284416, 'device': 'CPU'}), (<DtypeKind.UINT: 1>, 8, 'C', '=')), 'validity': (PandasBuffer({'bufsize': 2, 'ptr': 94883712583296, 'device': 'CPU'}), (<DtypeKind.BOOL: 20>, 8, 'b', '=')), 'offsets': (PandasBuffer({'bufsize': 24, 'ptr': 94883723016784, 'device': 'CPU'}), (<DtypeKind.INT: 0>, 64, 'l', '='))}
[<pyarrow.Buffer address=0x7f58c8608040 size=1 is_cpu=True is_mutable=True>, <pyarrow.Buffer address=0x7f58c8608000 size=24 is_cpu=True is_mutable=True>, <pyarrow.Buffer address=0x7f58c8608080 size=1 is_cpu=True is_mutable=True>]
Expected Behavior
I think
{'data': (PandasBuffer({'bufsize': 1, 'ptr': 140019260284416, 'device': 'CPU'}), (<DtypeKind.UINT: 1>, 8, 'C', '=')), 'validity': (PandasBuffer({'bufsize': 1, 'ptr': 94883712583296, 'device': 'CPU'}), (<DtypeKind.BOOL: 20>, 1, 'b', '=')), 'offsets': (PandasBuffer({'bufsize': 24, 'ptr': 94883723016784, 'device': 'CPU'}), (<DtypeKind.INT: 0>, 64, 'l', '='))}
[<pyarrow.Buffer address=0x7f58c8608040 size=2 is_cpu=True is_mutable=True>, <pyarrow.Buffer address=0x7f58c8608000 size=24 is_cpu=True is_mutable=True>, <pyarrow.Buffer address=0x7f58c8608080 size=1 is_cpu=True is_mutable=True>]
Installed Versions
INSTALLED VERSIONS
commit : b033ca9
python : 3.10.12.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.146.1-microsoft-standard-WSL2
Version : #1 SMP Thu Jan 11 04:09:03 UTC 2024
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.1.0.dev0+761.gb033ca94e7
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.8.2
setuptools : 69.1.1
pip : 24.0
Cython : 3.0.8
pytest : 8.0.2
hypothesis : 6.98.15
sphinx : 7.2.6
blosc : None
feather : None
xlsxwriter : 3.2.0
lxml.etree : 5.1.0
html5lib : 1.1
pymysql : 1.4.6
psycopg2 : 2.9.9
jinja2 : 3.1.3
IPython : 8.22.1
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : 1.3.8
fastparquet : 2024.2.0
fsspec : 2024.2.0
gcsfs : 2024.2.0
matplotlib : 3.8.3
numba : 0.59.0
numexpr : 2.9.0
odfpy : None
openpyxl : 3.1.2
pyarrow : 15.0.0
pyreadstat : 1.2.6
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2024.2.0
scipy : 1.12.0
sqlalchemy : 2.0.27
tables : 3.9.2
tabulate : 0.9.0
xarray : 2024.2.0
xlrd : 2.0.1
zstandard : 0.22.0
tzdata : 2024.1
qtpy : 2.4.1
pyqt5 : None