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Messy Data Cleaner

ExcelFree · Private

Paste messy tabular data and get consistent values, sensible headers, and duplicate-row flags — reviewed in a before/after preview, exported as .xlsx. Nothing uploaded.

Nothing is uploaded — all processing happens on your device. No pasted data is ever sent to a server — parsing, cleaning suggestions, and export all run in this browser tab.

Paste Messy Data
Accepts tab-separated (paste from Excel/Sheets) or comma-separated text

How cleaning works

  1. Paste data copied straight from Excel/Sheets (tab-separated), or comma-separated text.
  2. Click Clean Data. Values that are clearly the same thing in different casing ("Sydney" / "sydney" / "SYDNEY") are normalized instantly, no AI involved.
  3. If a value looks like it might be an abbreviation of another value in the same column (like "SYD" for "Sydney"), or if a header row is missing, the local AI model is asked — a small model download happens once, the first time this is needed.
  4. Review the before/after preview, then export as .xlsx or continue straight to Data → Chart.

What the AI is (and isn't) responsible for

The model only ever suggests a header name or answers "is this value the same as that one, written differently" — a yes/no classification. Duplicate-row flagging is plain pattern matching on the normalized values, not AI, so it stays fast and predictable even for large pastes. Nothing here performs any calculation on your data.

Privacy

Parsing, cleaning suggestions, and the .xlsx export all happen locally. Nothing is uploaded.

Frequently Asked Questions

What kind of data can I paste in?
Tab-separated (copied straight from Excel/Sheets) or comma-separated text. Parsing is handled by PapaParse, the same library used across the site for CSV handling.
What does "cleaning" actually change?
Inconsistent values that clearly mean the same thing (like "Sydney", "sydney", and "SYD") get normalized to one consistent value, missing column headers get sensible suggested names, and rows that look like duplicates are flagged — all shown in a before/after preview so you can review every change before exporting.
Does the AI do the duplicate detection or the math?
No — duplicate-row flagging is plain pattern matching on the normalized values, not AI, so it stays predictable. The AI model is only used to suggest header names and value normalizations; it never performs any calculation on your data.
Is my data uploaded anywhere?
No. Parsing, cleaning suggestions, and the .xlsx export all happen locally in your browser.

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