When is this useful?
It is useful when the same email, SKU, or order appears more than once. The hardest part is not the removal algorithm—it is deciding what “the same record” means for your dataset.
Free web tool
Remove duplicate CSV rows by selected key columns, keeping the first or last occurrence.
Use this to reduce repeated customer, product, or order rows based on one or more key columns. You can keep the first or last occurrence, so it works best when you understand both the key definition and the current row order.
It is useful when the same email, SKU, or order appears more than once. The hardest part is not the removal algorithm—it is deciding what “the same record” means for your dataset.
Keys can be composite, such as store_id,sku. A SKU might be duplicated globally but unique within each store. Choosing the key based on business identity changes which rows are considered duplicates.
If a customer file is already sorted oldest-to-newest and later rows contain the latest data, using email + “keep last” can work. If the file is not reliably sorted, “last” does not mean “latest,” so sort or verify the order first.
“Duplicates removed” is source rows minus kept rows. With “keep last,” the value from the last occurrence is kept, but key output order follows when each key was first seen. If row order has business meaning, review that detail before using the output.