BUG: pyarrow stripping leading zeros with dtype=str #57666
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
import pandas as pd from io import StringIO x = """ AB|000388907|abc|0150 AB|101044572|abc|0150 AB|000023607|abc|0205 AB|100102040|abc|0205 """ df_arrow = pd.read_csv( StringIO(x), delimiter="|", header=None, dtype=str, engine="pyarrow", keep_default_na=False, ) df_python = pd.read_csv( StringIO(x), delimiter="|", header=None, dtype=str, engine="python", keep_default_na=False, ) df_arrow 0 1 2 3 0 AB 388907 abc 150 1 AB 101044572 abc 150 2 AB 23607 abc 205 3 AB 100102040 abc 205 df_python 0 1 2 3 0 AB 000388907 abc 0150 1 AB 101044572 abc 0150 2 AB 000023607 abc 0205 3 AB 100102040 abc 0205Issue Description
when I use engine=pyarrow and set dtype to str i am seeing the leading zeros in my numeric columns removed even though the resulting column type is 'O'. When I use the python engine I see that the leading zeros are still there as expected.
Expected Behavior
I would expect when treating all columns as strings that the leading zeros are retained and the data is unmodified.
Installed Versions
INSTALLED VERSIONS
commit : bdc79c1
python : 3.11.8.final.0
python-bits : 64
OS : Linux
OS-release : 6.5.0-17-generic
Version : #17-Ubuntu SMP PREEMPT_DYNAMIC Thu Jan 11 14:20:13 UTC 2024
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 2.2.1
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.8.2
setuptools : 69.1.1
pip : 24.0
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
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 15.0.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : 2.0.27
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None