Prepare imports
Normalize supplier files before importing them into databases, CRMs, analytics tools, or ETL jobs.
Convert CSV to TSV, add or remove column names, and control output quoting from one browser-based workspace.
If the input has no header row and you keep headers enabled, blank names are auto-generated as column0, column1, and so on.
Header names keep normal minimal quoting. Data values can be fully quoted or stripped of optional quotes where valid.
Columns
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Data rows
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Output rows
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Waiting for CSV or TSV input.
A quick workflow so you can get the result you need without guesswork.
Paste CSV or TSV content, or upload a local file into the editor.
Set whether the input already includes a header row, then choose whether to keep, remove, or replace column names.
Pick CSV or TSV output, decide how value quotes should be handled, and run the transformation.
Practical cases where this utility saves time and reduces mistakes.
Normalize supplier files before importing them into databases, CRMs, analytics tools, or ETL jobs.
Generate column0, column1, and similar names for raw extracts, then edit them into something meaningful.
Quote every value for downstream systems that expect strict CSV formatting, or strip optional quotes from cleaner exports.
Short answers to the most common questions about the calculator above.
Yes. Choose TSV as the output format and the tool will rewrite the same rows with tab separators.
If you leave headers enabled in the output, the tool generates names such as column0, column1, and column2. You can also override them with your own custom names.
The quote setting targets data values. Header names use normal minimal quoting so the output stays readable while remaining valid.
No. Parsing and transformation happen locally in your browser.
This CSV manipulator handles common spreadsheet-export cleanup tasks directly in the browser. You can switch between CSV and TSV output, drop header rows, generate missing column names, and control whether values are quoted in the final file.
That makes it useful when a vendor export, legacy system, or quick spreadsheet save leaves you with data that is structurally close to what you need but not quite ready to use.
Developers, analysts, and operations teams often need to reformat delimited text before passing it into a database loader, warehouse job, marketing platform, or internal script. A focused browser tool is faster than spinning up a one-off parser for small cleanup work.
Because everything runs locally, it is also practical for internal datasets that should stay on your machine while you inspect and transform them.
Keep moving with other free browser-based utilities on HandyUtils.