BUG: skiprows ignored in read_csv(engine="pyarrow")

[rohanjain101]

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

>>> data = """a\nb\nc"""
>>> pd.read_csv(StringIO(data), engine="pyarrow")
   a
0  b
1  c
>>> pd.read_csv(StringIO(data), engine="pyarrow", skiprows=1)
   a
0  b
1  c
>>>

Issue Description

skiprows seems to be ignored

Expected Behavior

The first row should be skipped, and the returned df should contain same data as default csv engine.

Installed Versions

INSTALLED VERSIONS

commit : bdc79c1
python : 3.11.8.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 151 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.2.1
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.8.2
setuptools : 69.0.3
pip : 23.3.2
Cython : None
pytest : None
hypothesis : None
sphinx : 4.2.0
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.21.0
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.2.0
gcsfs : None
matplotlib : 3.8.3
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 : 1.12.0
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None

[ashorkey-umich]

take

[kymcglyn]

take

[rohanjain101]

From looking at the code, it seems skiprows is only honored if header=None for pyarrow types, but this is different from the default csv engine.

[jaketear]

I can also reproduce this issue in pandas 2.2.3. But, it seems correct when using header=1 instead of skiprows=1.

data = """a\nb\nc"""
pd.read_csv(StringIO(data), engine="pyarrow", skiprows=1)
Out[8]: 
   a
0  b
1  c
pd.read_csv(StringIO(data), engine="pyarrow", header=1)
Out[9]: 
   b
0  c

[snitish]

Any thoughts on disabling the header parameter for engine="pyarrow"? The official pyarrow.csv.read_csv documentation doesn't seem to support header anyway. That way, we only have skiprows and this issue should be fixed. @mroeschke