Try it yourself

See what a CSV check actually catches.

Run labeled CSV examples with valid rows, missing fields, embedded commas, escaped quotes, and multiline values. Inspect the results yourself.

These examples contain illustrative data, not customer records. Each link loads the input into the real validator; select Validate CSV to process it.

A valid product-order file

Three rows with four fields each. A quoted product name includes a comma, which stays inside its field.

order_id,sku,quantity,unit_price
ORD-1001,"MUG, BLUE",2,12.50
ORD-1002,NOTEBOOK-A5,5,8.00
ORD-1003,PEN-BLACK,12,1.75

Expected: 3 data rows and 4 columns, with no structural errors.

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A row with a missing field

The second data record has only three fields. The missing price does not have an empty trailing field.

order_id,sku,quantity,unit_price
ORD-1001,"MUG, BLUE",2,12.50
ORD-1002,NOTEBOOK-A5,5
ORD-1003,PEN-BLACK,12,1.75

Expected: a field-count issue for the short record.

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Quotes and a multiline value

Quotes are doubled inside a quoted field. The last value contains a newline but still belongs to one record.

record_id,description,quantity
001,"A comma, inside a field",4
002,"He said ""ready""",7
003,"First line
Second line",2

Expected: 3 data rows. Leading-zero record IDs stay as text.

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Bring your own file

Run the same check on a real import.

Keep a copy of the original file, confirm your delimiter and encoding, and review every issue before using the output. The guides explain common problems.

Open validator →