How to Query CSV Files with SQL in Your Browser

CSV is easy to export but awkward to inspect once files grow beyond a few thousand rows. SQL gives you a direct way to filter, group, sort, and join CSV data without first importing it into a spreadsheet or database server.

• Filter rows with WHERE instead of manual spreadsheet filters.
• Summarize numeric columns with COUNT, SUM, AVG, MIN, and MAX.
• Join multiple CSV files when IDs or names connect them.
• Export a smaller result set after the query is finished.

1. Open the SQL for Files editor.
2. Drag a CSV file into the Add Data area, or choose it from your file picker.
3. Review the detected table name in the Database sidebar.
4. Expand the table to inspect column names before writing a query.

Begin with a small preview query so you can verify column names and row shape before running larger aggregations.

SELECT *
FROM sales
LIMIT 20;

Then filter, sort, or select only the columns that matter for your analysis.

SELECT order_date, region, revenue
FROM sales
WHERE revenue > 1000
ORDER BY revenue DESC;

SQL is especially useful when you want totals by category, region, month, customer segment, or another repeated value in the CSV file.

SELECT
  region,
  COUNT(*) AS order_count,
  SUM(revenue) AS total_revenue,
  AVG(revenue) AS average_revenue
FROM sales
GROUP BY region
ORDER BY total_revenue DESC;

Add more than one CSV when your analysis needs lookup data, product names, account metadata, or another table that connects through a shared key.

SELECT
  orders.order_id,
  customers.customer_name,
  orders.revenue
FROM orders
JOIN customers
  ON orders.customer_id = customers.customer_id
ORDER BY orders.revenue DESC;

SQL for Files runs the CSV import and query execution in your browser with DuckDB WASM. The app does not upload your files, SQL, or result rows to a backend service.

After a query finishes, use CSV export for the result set, or save the local database in your browser if you want to keep working across sessions.