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Reproducible Example

importpandasaspdimportiocsv_text="column1,column2,column3\n1,2,3\nIAMAWRONGLINE\na,4,5"buffer=io.StringIO(csv_text) df=pd.read_csv(buffer, header=0, on_bad_lines="skip", dtype={"column1": int, "column2": int, "column3": int}) """Output:Traceback (most recent call last): File "pandas/_libs/parsers.pyx", line 1161, in pandas._libs.parsers.TextReader._convert_tokensTypeError: Cannot cast array data from dtype('O') to dtype('int64') according to the rule 'safe'During handling of the above exception, another exception occurred:Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/snelleman/.venv/sparkle/lib/python3.10/site-packages/pandas/io/parsers/readers.py", line 1026, in read_csv return _read(filepath_or_buffer, kwds) File "/home/snelleman/.venv/sparkle/lib/python3.10/site-packages/pandas/io/parsers/readers.py", line 626, in _read return parser.read(nrows) File "/home/snelleman/.venv/sparkle/lib/python3.10/site-packages/pandas/io/parsers/readers.py", line 1923, in read ) = self._engine.read( # type: ignore[attr-defined] File "/home/snelleman/.venv/sparkle/lib/python3.10/site-packages/pandas/io/parsers/c_parser_wrapper.py", line 234, in read chunks = self._reader.read_low_memory(nrows) File "pandas/_libs/parsers.pyx", line 838, in pandas._libs.parsers.TextReader.read_low_memory File "pandas/_libs/parsers.pyx", line 921, in pandas._libs.parsers.TextReader._read_rows File "pandas/_libs/parsers.pyx", line 1066, in pandas._libs.parsers.TextReader._convert_column_data File "pandas/_libs/parsers.pyx", line 1167, in pandas._libs.parsers.TextReader._convert_tokensValueError: invalid literal for int() with base 10: 'IAMAWRONGLINE'"""

Issue Description

I would expect in this case that the line would be skipped as it does not comply with the formatting. In a similar situation I got the error message:

" raise ValueError("Trying to coerce float values to integers")
ValueError: Trying to coerce float values to integers"

or

" raise IntCastingNaNError(
pandas.errors.IntCastingNaNError: Cannot convert non-finite values (NA or inf) to integer"

Am I misunderstanding how this argument works? In my case it would be very useful to skip these bad lines as well! :)

Expected Behavior

I would expect the on_bad_lines callable to be triggered by these issues, as not complying with the dtypes is in my opinion a bad line. Perhaps the Pandas team has a different view?

Installed Versions

INSTALLED VERSIONS

commit : 9c8bc3e
python : 3.10.8
python-bits : 64
OS : Linux
OS-release : 5.14.0-427.16.1.el9_4.x86_64
Version : #1 SMP PREEMPT_DYNAMIC Wed May 8 17:48:14 UTC 2024
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_GB.UTF-8
LOCALE : en_GB.UTF-8

pandas : 2.3.3
numpy : 1.26.4
pytz : 2025.2
dateutil : 2.9.0.post0
pip : 22.2.2
Cython : None
sphinx : None
IPython : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2025.9.0
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.6
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.15.3
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.2
qtpy : None
pyqt5 : None