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When I use Pandas 2.0 with pyarrow engine to read CSV file, if the file get some bad lines, it will raise a error such as "pyarrow.lib.ArrowInvalid: CSV parse error: Expected 1 columns, got 2: ".
Then I added the argument '', it will raise another error "TypeError: read_csv() got an unexpected keyword argument 'skip_bad_lines'"
So,can you add the argument like 'skip_bad_lines=True' with pyarrow engine.
@lithomas1 I've created a pull request that utilizes invalid_row_handler. However, instead of introducing a new argument, I've integrated it into the existing on_bad_lines argument to read_csv when the pyarrow engine is selected. This allows for flexible handling if the invalid line has to put out a warning, be skipped, or have user-defined behavior (much like the standard implementation for the python engine).
To achieve the behavior described in the issue, the syntax would be: pd.read_csv(r"test.csv", engine='pyarrow', dtype_backend='pyarrow', on_bad_lines='skip')
Feature Type
Adding new functionality to pandas
Changing existing functionality in pandas
Removing existing functionality in pandas
Problem Description
When I use Pandas 2.0 with pyarrow engine to read CSV file, if the file get some bad lines, it will raise a error such as "pyarrow.lib.ArrowInvalid: CSV parse error: Expected 1 columns, got 2: ".
Then I added the argument '', it will raise another error "TypeError: read_csv() got an unexpected keyword argument 'skip_bad_lines'"
So,can you add the argument like 'skip_bad_lines=True' with pyarrow engine.
Feature Description
df_arrow = pd.read_csv(r"VBAP.CSV", engine='pyarrow', dtype_backend='pyarrow', skip_bad_lines=True)
Alternative Solutions
df_arrow = pd.read_csv(r"VBAP.CSV", engine='pyarrow', dtype_backend='pyarrow', skip_bad_lines=True)
Additional Context
No response
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