Description
Pandas version checks
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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
pd.set_option("mode.dtype_backend", "pyarrow")
df = pd.read_csv('flights.csv', usecols=[7,8], use_nullable_dtypes=True)
df
Issue Description
I am using the 2015 flights delay dataset: Source: https://www.kaggle.com/datasets/usdot/flight-delays.
When loading columns 7 and 8, which contains mixed types (numeric and strings), loading it using pyarrow as the backend gives this error:
TypeError: Cannot interpret 'string[pyarrow]' as a data type
Using Pandas as the backend have no issues (albeit a type warning).
Expected Behavior
It should load the two columns as string type.
Installed Versions
INSTALLED VERSIONS
commit : 1a2e300
python : 3.10.6.final.0
python-bits : 64
OS : Darwin
OS-release : 21.6.0
Version : Darwin Kernel Version 21.6.0: Mon Dec 19 20:43:09 PST 2022; root:xnu-8020.240.18~2/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : None.UTF-8
pandas : 2.0.0rc0
numpy : 1.23.5
pytz : 2022.2.1
dateutil : 2.8.2
setuptools : 65.2.0
pip : 22.2.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.0
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : 1.3.7
brotli :
fastparquet : None
fsspec : 2023.3.0
gcsfs : None
matplotlib : 3.3.2
numba : 0.56.4
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 9.0.0
pyreadstat : None
pyxlsb : None
s3fs : 2023.3.0
scipy : 1.9.1
snappy : None
sqlalchemy : 1.4.46
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
zstandard : None
tzdata : 2022.7
qtpy : None
pyqt5 : None