Working with CSV and Spreadsheet Data in the Browser

CSV is the most portable data format in the world. Every database, spreadsheet, and data tool can read it. But working with CSV files often means opening Excel or Google Sheets just to do something simple — view a large file, merge two exports, or extract a few columns. Here is how to do it all in your browser.

Viewing and exploring CSV files

Large CSV files are painful to open in a text editor — 50,000 rows of comma-separated values is unreadable. A CSV viewer renders the data as an interactive table with:

• Column sorting — Click any header to sort ascending or descending
• Search and filter — Find rows matching a value across any column
• Column inspection — See data types and unique values at a glance

Our CSV Viewer & Editor loads files entirely in your browser. No upload, no size limit imposed by a server.

Running SQL queries on CSV

Sometimes you don't want to scroll — you want to ask a question. SQL on CSV lets you write queries directly against your file:

SELECT region, SUM(revenue) as total_revenue
FROM data
WHERE year = 2025
GROUP BY region
ORDER BY total_revenue DESC

This is faster than pivot tables for anyone comfortable with SQL. Our SQL on CSV tool uses an in-browser SQLite engine, so your data never leaves your machine.

Common use cases:

• Aggregating sales data by region or product
• Finding duplicates: SELECT email, COUNT(*) FROM data GROUP BY email HAVING COUNT(*) > 1
• Filtering large exports: SELECT * FROM data WHERE status = 'pending' AND amount > 1000

Merging multiple CSV files

When you have weekly exports or data from multiple sources that need combining:

1. Ensure all files have the same column headers (or map them before merging)
2. Decide whether to deduplicate rows — identical rows from different exports should usually be removed
3. Choose the column order for the merged output

Our CSV Merger handles header detection automatically, lets you reorder files, and optionally deduplicates rows.

Common gotcha: Column names that look the same but differ in case or whitespace (Name vs name vs name). Always check headers before merging.

Extracting specific columns

A raw data export often contains 30+ columns when you only need 5. Trimming the file makes it easier to share and faster to process downstream.

The CSV Column Extractor lets you check the columns you want and download the slimmed-down result. Useful for:

• Preparing data for import into another system
• Sharing only relevant fields with a colleague
• Reducing file size before running further processing

Converting between formats

Excel to CSV: XLSX files are binary — not readable in a text editor and incompatible with many data tools. Converting to CSV makes the data universally portable. Our Excel to CSV tool uses SheetJS to convert in the browser, handling multiple sheets.

JSON to Excel: API responses and data exports often arrive as JSON. Converting to Excel adds column headers, data types, and formatting that non-technical stakeholders can read immediately. The JSON to Excel tool converts JSON arrays of objects to .xlsx in one step.

CSV to Markdown Table: When writing documentation or README files, you often want to present tabular data as a Markdown table. Our CSV to Markdown Table converter handles alignment options automatically.

JSON data tools

If you work with JSON instead of CSV:

• JSON Table Viewer — Render any JSON array as a sortable, searchable table
• JSON Diff Viewer — Compare two JSON objects and see what changed
• XML to JSON — Bidirectional conversion between XML and JSON

Privacy and security

All tools on this site process data locally using WebAssembly and JavaScript — no data is sent to any server. This is critical when working with customer data, financial exports, or anything covered by GDPR or HIPAA. Your files stay on your device.

Tips for clean CSV files

1. UTF-8 encoding — Always save as UTF-8. Windows sometimes defaults to Windows-1252, which breaks special characters.
2. Consistent date formats — ISO 8601 (2026-03-23) is unambiguous across systems.
3. No merged cells — They look good in Excel but break every CSV parser.
4. Header row always first — Some tools require it; all tools benefit from it.
5. Avoid newlines in field values — They require proper quoting and confuse many parsers.

Summary

Browser-based data tools let you view, query, merge, and convert CSV and spreadsheet data without opening a desktop application or uploading files to a cloud service. For one-off tasks with sensitive data, this is both faster and more private than the traditional approach.