CSV Deduplicator

The CSV Deduplicator is a free online tool that remove duplicate rows from csv files. deduplicate by exact match or selected columns with case-insensitive and whitespace trimming options.. It runs entirely in your browser with no installation or sign-up needed.

Exact row match (all columns) or selected-columns mode. Rows matching on all selected columns are duplicates.

Yes — toggle to treat "Alice" and "alice" as same value. Whitespace trimming also available.

Yes. Download the cleaned CSV or a separate file with only the removed duplicate rows for review.

Yes, the CSV Deduplicator is 100% free with no registration, no hidden fees, and no usage limits. All processing happens locally in your browser, ensuring complete privacy.

Absolutely. The CSV Deduplicator processes everything client-side in your browser. No data is uploaded to or stored on any server. Your content remains private on your device at all times.

Yes, the CSV Deduplicator is fully responsive and works on smartphones and tablets. You can use it on any device with a modern web browser -- no app download required.

No account or registration is needed. Simply open the CSV Deduplicator in your browser and start using it immediately. There are no sign-up walls or usage restrictions.

Simply enter your input in the provided field, adjust any settings to your preference, and the tool will process it instantly. You can then copy the result to your clipboard or download it.

The CSV Deduplicator works in all modern browsers including Chrome, Firefox, Safari, Edge, and Opera. For the best experience, use the latest version of your preferred browser.

Both options remove the same duplicate rows; they only change which copy of each matching set survives. Keep First retains the earliest occurrence in the file and drops every later match, which is best when the top of your data holds the original or authoritative record. Keep Last retains the final occurrence and drops the earlier ones, which matters when newer rows hold the most recent version of a record — for example, an updated address or order status appended at the bottom of an export. The choice has no effect on how many rows are removed, only on which values you end up keeping, so it is worth thinking about before exporting. Toggle Keep First or Keep Last in the deduplication settings and watch the Duplicate Groups tab mark exactly which row stays.

Use exact row match when you only want to remove perfect copies — rows are duplicates only if every column is identical, so anything that differs in any field is kept. This is the safest option for stripping out accidental full-row repeats. Use selected columns when you want to collapse records that represent the same entity even though some fields differ: pick a unique field like an email address or order ID, and rows matching on just those columns are treated as duplicates regardless of the other values. For example, two rows with the same email but a different signup date would survive exact match but merge under column mode. Pick the mode that matches your definition of a duplicate, then check the Duplicate Groups tab here to confirm the right rows were flagged before you export.

Switch the deduplication mode to Selected Columns Only, then tick just the column you care about — for instance an Email or Customer ID column — and leave the rest unchecked. The tool then treats two rows as duplicates whenever those chosen fields match, even if every other column is different. This is exactly how you collapse multiple records for the same person or order down to one. Pair it with the case-insensitive option so Alice@Example.com and alice@example.com count as the same address, and trim whitespace so a stray leading space does not split an otherwise identical value. The Duplicate Groups view shows each matching set together with the kept row marked, so you can verify the logic. Select your key column above and the duplicate count updates instantly.

Those two options redefine what counts as identical, so flipping them naturally changes how many duplicates are found. By default the tool compares values literally, meaning Alice and alice, or bob@example.com and a copy with a leading space, are treated as different and kept apart. Turning on case-insensitive match lowercases values before comparing, so entries that differ only in capitalization collapse into one group. Turning on trim whitespace strips leading and trailing spaces, so values that differ only by stray padding from a sloppy export also merge. Real-world data full of inconsistent casing and spacing will show more duplicates once these are enabled. If your count looks too low or too high, adjust these toggles and read the duplicate rate in the summary panel to confirm the match rules fit your data.

Yes. The tool auto-detects the delimiter from your data, recognizing commas, semicolons, tabs, and pipes, so European-style semicolon CSVs and .tsv exports are parsed without any manual setting — the detected delimiter is shown above the results. It also parses fields correctly when they are wrapped in double quotes or contain commas, line breaks, or escaped quotation marks inside them, so a value like a full address or a quoted note will not be split apart or shift your columns. On export, the cleaned file is always written as standard comma-separated values with proper quoting applied where needed, giving you a clean, portable result regardless of the original format. Drop a .csv or .tsv file or paste your data above and the delimiter, column count, and row count appear immediately.