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
import pandas as pd
rows = []
for i in range(1_000_000):
rows.append({"text": "ab\ncd", "i": i})
df = pd.DataFrame(rows)
df.to_csv("./example.csv", index=False)
pd.read_csv("./example.csv", engine="pyarrow")Issue Description
pd.read_csv fails when reading large CSV files with engine="payarrow" if values contain newline characters. The error is
ParserError: CSV parser got out of sync with chunker. This can mean the
data file contains cell values spanning multiple lines; please consider
enabling the option 'newlines_in_values'.
Note the file must be large to trigger the error. Either pandas should enable this flag internally, or expose the option to the user.
Expected Behavior
Reading the file succeeds with engine="python" and I would expect consistency between the two options.
Installed Versions
In [7]: pd.show_versions()
INSTALLED VERSIONS
commit : d9cdd2e
python : 3.11.9.final.0
python-bits : 64
OS : Darwin
OS-release : 23.5.0
Version : Darwin Kernel Version 23.5.0: Wed May 1 20:13:18 PDT 2024; root:xnu-10063.121.3~5/RELEASE_ARM64_T6030
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.2.2
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : None
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 : 8.25.0
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 : 16.1.0
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None