Remove Duplicate Rows
Processing entirely on your device — large files may take a moment.
Exported data loves duplicates: double-submitted forms, re-run exports, merged lists. This tool compares every row as a whole — all columns must match exactly for a row to count as a duplicate — and keeps the first occurrence, so your data order tells the same story with the repeats gone.
If nothing is duplicated the tool tells you outright instead of handing back an identical file — no guessing whether it ran.
How to remove duplicate rows
- 1
Select your files
Drag & drop your CSV files onto the area above, or click to browse. You can add multiple files at once for batch conversion.
- 2
Convert instantly
Click "Convert to CSV". The conversion runs entirely inside your browser using WebAssembly — no upload, no queue, no waiting.
- 3
Download results
Download each converted CSV file individually, or grab everything at once as a ZIP archive.
About the CSV format
CSV (comma-separated values) is the lowest common denominator of tabular data: one table, rows as lines, columns separated by commas, everything plain text. Excel, Google Sheets, every database importer, every data-science library and every scripting language read it, which is why it has survived fifty years of format fashion.
Its weaknesses come from the same minimalism. There are no types (everything is a string until you decide otherwise), no formulas, one table per file, and dialect quirks are legendary: comma vs semicolon locales, quoting rules, and Excel's insistence on re-opening UTF-8 files without a BOM as mojibake. Clean, well-formed UTF-8 CSV with a BOM sidesteps nearly all of it.
+Strengths
- ✓Universal: Excel, Sheets, databases and code all read it
- ✓Human-readable and diff-friendly
- ✓Streams well — process giant files line by line
!Limitations
- −No types, no formulas, no multiple sheets
- −Dialect chaos: delimiters, quoting, encoding
- −Nested or hierarchical data does not fit
Frequently asked questions
Does "duplicate" mean the whole row?
Yes — every column must match exactly. Rows sharing an ID but differing elsewhere are kept; that is a data problem to resolve deliberately, not silently.
Is the first or last occurrence kept?
The first — order is fully preserved, so if your rows are chronological the earliest record of each duplicate survives.
Are near-duplicates (extra spaces) removed too?
No — comparison is exact. Whitespace differences count as different rows, which protects legitimate data. Clean the file first if trailing spaces are the issue.