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🔧 Programming ✅ 100% Free ⚡ Instant

CSV Formatter & Table Viewer

Paste CSV data and instantly see it as a formatted table. Supports comma, semicolon, tab and pipe delimiters with automatic header detection.

Delimiter:
Input
Output
Ready — paste your input and click Format
Try a sample: Users Table Products Sales Data
📊 Stats
Rows
Columns
Total Cells
Size
⌨️ Shortcuts
Ctrl+EnterFormat CSV
Ctrl+Shift+CCopy output
Ctrl+LClear all
TabInsert indent in editor
💡 Tips
📊
Header row — the first row is treated as column headers and highlighted.
🔤
Quoted fields — values with commas or newlines should be wrapped in double quotes.
↔️
Auto-delimiter — change the delimiter dropdown if your data uses semicolons or tabs.
🔒
100% private — all processing runs in your browser. Nothing is uploaded.

What is a CSV Formatter?

A CSV formatter parses comma-separated values and displays them in a clean, aligned table view. It handles quoted fields, multiple delimiters, and messy data — making it easy to inspect the structure of any CSV file before importing it into a database or spreadsheet.

CSV Best Practices

  • Always include a header row as the first line with descriptive column names
  • Wrap values containing commas or newlines in double quotes
  • Use consistent encoding (UTF-8) for international characters
  • Avoid trailing commas at the end of rows

Frequently Asked Questions

The CSV Formatter supports comma (,), semicolon (;), tab (\t), and pipe (|) as delimiters. Select the correct one from the Delimiter dropdown before formatting. European spreadsheet software (Excel, LibreOffice in some locales) often exports with semicolons.
Fields wrapped in double quotes are parsed correctly, including those that contain the delimiter character or newlines. A double quote inside a quoted field should be escaped as two consecutive double quotes ("").
Yes, but very large files (100,000+ rows) may be slow in the browser. For large files, consider using Python's pandas library or command-line tools like csvkit.
Done!