How to Fix Pandas' 'pandas.parser.CParserError: Error tokenizing data' in CSV Files?

How to Resolve "pandas.parser.CParserError: Error tokenizing data" When Reading a CSV File

When working with a CSV file using Pandas, you may encounter the error "pandas.parser.CParserError: Error tokenizing data." This specific error occurs when the CSV file has an unequal number of fields in a line, causing a parsing error.

Understanding the Cause:

The error message indicates that the parser expected two fields in a particular line but found 12 instead. This mismatch between the expected and actual number of fields leads to the error.

Resolving the Issue:

There are two primary ways to resolve this issue:

1. Handling Bad Lines:

   • on_bad_lines='skip': This option instructs Pandas to skip the offending lines with invalid data, allowing you to read the rest of the file without errors.
   • on_bad_lines='warn': This option generates warnings for the invalid lines, indicating their presence and allowing you to assess the extent of the problem. For advanced handling, you can pass a callable function.

2. Error Handling:

   • error_bad_lines=False: (for Pandas versions less than 1.3.0) This option suppresses the error entirely, allowing you to read the entire file, including the invalid lines. However, it does not provide any information about the invalid lines.

Example Code:

As an example, if you had the following code:

path = 'GOOG Key Ratios.csv'
data = pd.read_csv(path)

To handle the error, you could modify the code as follows:

path = 'GOOG Key Ratios.csv'
data = pd.read_csv(path, on_bad_lines='skip')

By using one of these approaches, you can read the CSV file despite the presence of invalid lines, ensuring your Pandas operations proceed smoothly

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