CSV Validator

About this tool

Check a CSV for structural problems: rows that have more or fewer columns than the header row, which usually indicate missing commas or stray delimiters.

Example

Input: name,age\nAlice,30,extra

Output: Row 2 has 3 columns (expected 2)

Privacy

This tool runs entirely in your browser. Your data is processed locally and never uploaded to a server.

How to use this tool

1. Paste your CSV text into the input box.
2. Run the validator to check the row structure.
3. Review any rows that have too few or too many columns.
4. Fix missing commas, extra commas, or stray delimiters in the source data.

Step by step, what happens

1. The tool reads the first row and treats it as the header row.
2. It counts how many columns the header has and compares every later row against that count.
3. Rows with fewer or more fields are flagged as structural problems.
4. You use the row-by-row results to spot missing commas, accidental extra commas, or broken quoting in the CSV source.

Worked example

Here is a small CSV where one data row is missing a value and another row has an extra comma.

Input: name,age,city Alice,30,Paris Bob,Seattle Cara,25,Rome,Extra

1. The validator sees that the header row has three columns: name, age, and city.
2. It checks each following row against that three-column structure.
3. It flags Bob's row because it has only two columns, and Cara's row because it has four columns.

Tips and common mistakes

• If a row is flagged, look for a missing comma or an extra comma near that row first.
• Quoted fields can contain commas, so make sure text with commas is wrapped correctly in quotes.
• Keep the header row clean and consistent, because every other row is checked against it.
• A CSV can look fine in a text editor but still fail here if one line has a different number of fields.

Frequently asked questions