About The CSV Profiler

CSV Profiler summarizes each column in pasted CSV data, including row count, delimiter, inferred dominant type, empty values, and approximate uniqueness. It helps you inspect data quality before import, cleanup, or analysis.

Profiling runs locally in your browser. Type detection is intentionally lightweight and best suited for quick review, not strict schema validation.

How to Profile CSV Online

1. Paste CSV text into CSV input.
2. Choose a delimiter, or leave it on Auto detect.
3. Set whether the first row should be treated as column headers.
4. Click Profile CSV.
5. Review each column's type, empty count, and unique-value count.

Choosing Options Correctly

Delimiter:
Use Auto detect for common comma, semicolon, tab, and pipe-separated data. Choose a specific delimiter when the source format is known.

First row is header:
Leave this on when row one contains names. Turn it off when every row is data and generated column names are better.

Common Use Cases

• Checking a CSV export before database import.
• Finding columns with missing values.
• Spotting likely boolean, number, date, and string fields.
• Preparing quick data-quality notes for a teammate.

Quick FAQ

Is this a full validator?
No. It profiles columns and likely types, but it does not enforce a formal schema or business rules.

Why does a mixed column show as string?
If a column contains both numbers and text, string is the safest inferred type.

Is my CSV uploaded?
No. Profiling is designed to run in the browser.

Can I analyze very large CSV files?
Browser memory and page performance are the practical limits. Sample large files if the page becomes slow.