error_bad_lines is ignored if names argument is used in read_csv function

Code Sample, a copy-pastable example if possible

#example taken from #20573
import io
import numpy as np
import pandas as pd
buf = io.StringIO("0,1,Amigo,3\n1,1,Inimigo,amigo,9\n2,1,Cowboy,42\n")
names = ['ID','X1','X2','X3']
dtypes = {"X3": int}
pd.read_csv(buf, names=names, error_bad_lines=False, dtype=dtypes, header=None)

Problem description

Bad lines option (error_bad_lines=False) is ignored when using the names argument. When omitting the names option everything works fine with pandas 0.23.3 (see issue #20573), but when names is used a ValueError is raised (ValueError: invalid literal for int() with base 10: ‘amigo’).

Expected Output

b’Skipping line 3: expected 4 fields, saw 5\n’

ID	X1	X2	X3
0	1	Amigo	3
2	1	Cowboy	42

Output of pd.show_versions()

[paste the output of pd.show_versions() here below this line] INSTALLED VERSIONS

commit: None python: 3.6.4.final.0 python-bits: 64 OS: Linux OS-release: 4.15.0-24-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8

pandas: 0.23.3 pytest: 3.4.2 pip: 9.0.2 setuptools: 38.5.2 Cython: 0.27.3 numpy: 1.13.3 scipy: 1.0.0 pyarrow: 0.8.0 xarray: None IPython: 6.2.1 sphinx: 1.7.1 patsy: 0.5.0 dateutil: 2.6.1 pytz: 2018.3 blosc: None bottleneck: 1.2.1 tables: 3.4.2 numexpr: 2.6.4 feather: None matplotlib: 2.2.0 openpyxl: 2.5.1 xlrd: 1.1.0 xlwt: 1.3.0 xlsxwriter: 1.0.2 lxml: 4.1.1 bs4: 4.6.0 html5lib: 0.9999999 sqlalchemy: 1.2.5 pymysql: None psycopg2: None jinja2: 2.10 s3fs: None fastparquet: 0.1.4 pandas_gbq: None pandas_datareader: None

[louis-red]

Will try to have a look at this one !

[WillAyd]

Sorry I thought you were addressing the issue with the names argument as outlined by OP. If that’s not the case then yes open a separate issue