How to remove duplicate rows from a spreadsheet
Duplicate rows inflate counts, totals and averages. Removing them sounds simple, but deleting the wrong rows is worse than leaving them in. Omixa separates duplicates that are safe to remove from those that need a person to decide.
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Exact duplicates, removed
An exact duplicate is a row where every cell matches an earlier row. When you choose to remove duplicates, Omixa keeps the first occurrence, removes the repeats, and records each removal in the change log with the row it came from.
Near-duplicates, reviewed
Some rows look like duplicates but are not. Omixa reports two kinds for review and never removes them automatically: rows that match on the key columns you choose but differ elsewhere, and rows that share an email address or phone number but are not exact copies.
A shared name is never treated as proof of identity. Two people called Ada Okafor are not one person, so a name match alone is not a duplicate.
Checking the result
The quality report counts duplicates found and removed, so you can see how much of the file they affected. Duplicates also lower the data-quality score, which is why an exact-repeat share is part of how the score is calculated.
Steps
- Upload your CSV or Excel file.
- Check how many exact duplicates were found.
- Leave "Remove duplicates" on to keep the first occurrence of each row.
- Review the near-duplicate flags and decide each one yourself.
Common questions
Which duplicate is kept?
The first occurrence stays. Later identical rows are removed and logged.
Will Omixa remove people who share a name?
No. Matching names are not treated as duplicates. Only exact repeated rows are removed automatically.
Can I see what was removed?
Yes. The change log lists each rule that ran and how many cells or rows it changed, and removals are recorded individually.
Related guides
- Clean CSV filesClean a messy CSV file: stray spaces, duplicate rows, inconsistent dates and placeholders. Review the changes and download a cleaned copy. Free, no account.
- Data quality assessmentGet a data-quality score and report for a spreadsheet: what was found, what was fixed, and what still needs review. Practical, explainable, no guesswork.
- Standardize spreadsheet dataMake spreadsheet values consistent: dates, phone numbers, emails, countries, categories and capitalisation. Ambiguous values are flagged, not guessed.