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BUG: CSV C engine raises an error on single line CSV with no header when passing extra names #47566
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This issue was sort of similar but it's not the same since the example no longer raises an error. #26218 |
Hi, thanks for the report. this is the same cause as #40587 |
Okay, thanks. Not sure how it relates to that other issue especially since the C engine works as expected for 2 rows. I think I'm documenting an explicit case with 1 row where it has incorrect behavior. |
Files are read in chunks, and if the first line of any chunk is off, we get an error. |
Okay. I will close the issue since it's a duplicate. |
…hen passing extra names (pandas-dev#47566) * Expect the provided number of columns when the names property is set * Add tests to demonstrate handling of files with a single row with fewer columns.
…hen passing extra names (pandas-dev#47566) * Expect the provided number of columns when the names property is set * Add tests to demonstrate handling of files with a single row with fewer columns.
Pandas version checks
I have checked that this issue has not already been reported.
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
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 with
NaN
) 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
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