WORKLAZY TOOLS

Excel Data Cleaner

Apply 28 ordered structure, text, row-filter, and value-conversion rules to Excel and CSV files, then download cleaned XLSX, CSV, reports, and ZIP results.

Use this tool directly in your browser without installing software or signing in.

• Multiple Excel and CSV files
• 13 structure rules
• 7 text rules
• 3 row-filter rules
• 5 value-conversion rules
• Formula-reference updates and safe fallback
• XLSX, CSV, and ZIP results

Use Cases

• Formatting or fixing spaces in lists received from outside
• Cleaning up unnecessary rows and columns
• Performing repetitive data cleanup in the same order.

How to Use

• Add a file and select the sheet to clean and the row with column names.
• Add necessary rules. It is good to start with one rule to check the result first.
• Rules run from top to bottom. Check the order and settings of each rule.
• Review information about formulas, merged cells, and output formats, then run.
• Check the cleaned data as well as the change summary, errors, and excluded rows.

Example

If data looks different due to leading/trailing spaces like `Seoul` and ` Seoul `, apply Space Cleanup first, and then decide whether to apply Duplicate Cleanup. The result may vary depending on the rule order.

Should I remove spaces or duplicates first?

The same name doesn't always mean the same person, and the same product name with a different order number could be a different transaction. Decide which columns will be used as criteria for identical data before applying duplicate cleanup or row deletion.

Try applying just one rule with a minor change first, like whitespace cleanup. Since rules are executed from top to bottom, the result of cleaning up whitespace followed by removing duplicates can differ from the reverse order. Check not only the result file but also the changed or excluded items in the processing report.

Examples and Selection Help

Whitespace cleanup can make "Seoul " and "Seoul" the same value. Product codes such as "0012" and "12" may be intentionally different, so review identifier columns before applying number conversion.