What this tool is for
CSV cleanup can improve consistency before importing a file into another program. Trimming whitespace and removing blank rows are useful, but aggressive normalization can erase meaningful spaces or alter intentionally empty records.
How to use it
- Import the original CSV and inspect a few problematic rows.
- Run the supported cleanup operations, then compare counts and important columns.
- Download the cleaned copy while preserving the original for rollback.
Example workflow
For a mailing list, removing completely empty rows is helpful, but trimming spaces inside a product description may not be appropriate.
Important limitations
- Row-width normalization can expose malformed data rather than automatically correct its meaning.
- Cleaning does not prove that a record is accurate or that two similar names refer to the same person.