How to Solve the Pandas `pandas.parser.CParserError: Error tokenizing data` Error When Reading CSV Files?

Troubleshooting 'pandas.parser.CParserError: Error tokenizing data' for Pandas CSV Parsing

One may encounter the 'pandas.parser.CParserError: Error tokenizing data' error while utilizing the pd.read_csv function of the Pandas library, indicating a discrepancy between the expected and encountered number of fields in a given line of the CSV file.

The error message implies that the library anticipated two fields in a particular line (line 3 in this case) but encountered 12 instead. This disparity can arise due to malformed data, such as missing values or extra commas within a field.

To resolve the issue and proceed with the CSV parsing, consider the following approach:

Utilize the on_bad_lines parameter:

data = pd.read_csv(path, on_bad_lines='skip')

This method skips the offending lines with unexpected fields, allowing the reading process to continue.

For more advanced handling of invalid lines, implement a custom callable that defines actions to be taken when bad lines are detected.

If your Pandas version is less than 1.3.0, you can substitute the on_bad_lines parameter with error_bad_lines:

data = pd.read_csv("file1.csv", error_bad_lines=False)

This option also skips the problematic lines, but without the need for a customcallable.

As an alternative to Pandas, you can explore using the CSV module in Python, which provides basic utilities for parsing CSV files. However, it may not offer the same level of flexibility and features as Pandas.

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