UlvixorNormalize Text Data in a CSV
Normalize the text in the columns you choose from a CSV: trim spaces, convert to uppercase or lowercase, strip accents, and collapse repeated internal spaces. Perfect for standardizing data before importing it into another system. Everything runs in your browser, with no file ever uploaded to a server.
How it works
- Paste your CSV with a header row into the input panel (or use the built-in example).
- Select one or more columns from the automatically detected list.
- Choose the normalization operations to apply: trim spaces, uppercase, lowercase, strip accents, or collapse internal spaces.
- The operations are applied in order to every value in the columns you selected.
- Copy the resulting CSV or download it as a .csv file.
Use cases
- Standardize city or category names that arrive with inconsistent capitalization.
- Strip accents from columns that will be used as identifiers or keys in another system.
- Clean up double or triple spaces introduced when copying data from a form or PDF.
- Prepare a CSV for comparison or matching against another data source that uses a different text format.
Use cases
- Standardize city or category names that arrive with inconsistent capitalization.
- Strip accents from columns that will be used as identifiers or keys in another system.
- Clean up double or triple spaces introduced when copying data from a form or PDF.
- Prepare a CSV for comparison or matching against another data source that uses a different text format.
Common mistakes
- Turning on both uppercase and lowercase at once expecting some kind of in-between result.Operations run in a fixed order, not the order you turned them on. If you enable both, the final result depends on whichever runs last; enable only the one you need.
- Expecting accent removal to also strip the Ñ.The Ñ decomposes into N plus a diacritical mark (NFD normalization), so 'Ñoño' becomes 'Nono'. Keep this in mind if you need to preserve the Ñ as-is.
- Selecting no column or no operation and still expecting a result.The tool requires at least one column and one operation selected, and shows a clear error message if either is missing.
Frequently asked questions
No. All normalization happens entirely in your browser using JavaScript. Your CSV never leaves your device or gets uploaded anywhere.
They're applied in the order they appear in the operations list (trim spaces, uppercase, lowercase, strip accents, collapse spaces), not the order you turned them on. If you select both uppercase and lowercase, the final result depends on whichever one runs last.
The tool breaks down each accented character into its base letter plus a diacritical mark (NFD normalization) and then strips those marks, so 'café' becomes 'cafe' and 'Ñoño' becomes 'Nono' (the Ñ is treated as a diacritic on the N).
The CSV Cleaner only trims spaces and removes duplicate rows across the whole file. This tool lets you pick specific columns and apply more advanced operations like changing letter case, stripping accents, and collapsing internal spaces.
Alternatives
In a spreadsheet you can combine UPPER(), LOWER(), and nested functions to strip accents, and in Python unicodedata.normalize does something similar. This tool applies several operations at once to specific columns of your CSV, with no formulas or code to write.