BUG: CSV C engine raises an error on single line CSV with no header when passing extra names · Issue #47566 · pandas-dev/pandas (original) (raw)

Pandas version checks

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• 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

import io import pandas as pd

stream_without_header = io.StringIO("1,2")

pd.read_csv(stream_without_header, header=None, names=["a", "b"]) stream_without_header.seek(0)

pd.read_csv( stream_without_header, header=None, names=["a", "b", "c"], engine="python", ) stream_without_header.seek(0)

this will raise an error

pd.read_csv( stream_without_header, header=None, names=["a", "b", "c"], engine="c", )

add another line and read_csv works fine

stream_with_2lines_without_header = io.StringIO("1,2\n3,4") pd.read_csv( stream_with_2lines_without_header, header=None, names=["a", "b", "c"], engine="c", )

Issue Description

The C engine for parsing CSV does not behave the same as the Python engine when it comes to reading single line CSV files without a header row. The example shows how the Python engine behaves as expected (the extra specified row is returned withNaN) while the C engine raises an error.

Expected Behavior

The two engines should behave the same and given the behavior for 2+ lines, the 1 line example should work correctly.

Installed Versions

In [2]: pd.show_versions()

INSTALLED VERSIONS

commit : e8093ba
python : 3.8.5.final.0
python-bits : 64
OS : Darwin
OS-release : 21.5.0
Version : Darwin Kernel Version 21.5.0: Tue Apr 26 21:08:22 PDT 2022; root:xnu-8020.121.3~4/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.4.3
numpy : 1.22.4
pytz : 2022.1
dateutil : 2.8.2
setuptools : 47.1.0
pip : 22.1.2
Cython : 0.29.30
pytest : 7.1.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.0
html5lib : None
pymysql : 1.0.2
psycopg2 : 2.9.3
jinja2 : 3.1.2
IPython : 8.4.0
pandas_datareader: None
bs4 : 4.11.1
bottleneck : None
brotli : 1.0.9
fastparquet : None
fsspec : 2022.5.0
gcsfs : None
markupsafe : 2.1.1
matplotlib : 3.5.2
numba : None
numexpr : None
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 7.0.0
pyreadstat : None
pyxlsb : None
s3fs : 2022.5.0
scipy : 1.8.1
snappy : None
sqlalchemy : 1.4.37
tables : None
tabulate : 0.8.9
xarray : 2022.3.0
xlrd : 2.0.1
xlwt : None
zstandard : None