CSV Validator
Validate CSV structure and check for errors
CSV Input
Validation Result
What is CSV Validation?
A CSV validator checks if your CSV (Comma-Separated Values) file follows proper formatting rules. It detects structural errors, inconsistent column counts, malformed headers, and delimiter issues that cause import failures.
According to RFC 4180, the official CSV specification, valid CSV files must have consistent column counts per row and properly escaped special characters. IANA defines CSV as a registered MIME type (text/csv), making validation crucial for data exchange across systems.
Validation happens entirely in your browser. Your data remains private—no server uploads, no external processing.
Why Validate CSV Files?
Prevent Import Errors
Invalid CSV causes database imports to fail, Excel errors, and broken data pipelines. Validation catches these issues before they break your workflow.
Check Column Consistency
Every row must have the same number of columns. Validation detects missing or extra fields that corrupt data imports.
Detect Structure Issues
Unescaped quotes, wrong delimiters, and line break problems—validation finds them all with detailed error messages.
Real-Time Feedback
Instant validation results as you type or upload. See exactly what's wrong and where, with line numbers and error descriptions.
Standards Compliant
Follows RFC 4180 specifications. Ensures your CSV works across databases, spreadsheets, and programming libraries.
Sample Data Included
Test with valid and invalid CSV examples. Learn what passes validation and what fails, with clear explanations.
How to Validate CSV
Input Your CSV
Paste CSV data, upload a file, or click "Valid Sample" or "Invalid Sample" to see examples. The validator accepts various CSV formats and encodings.
Instant Validation
Validation runs automatically. The right panel shows whether your CSV is valid or invalid, with a detailed breakdown of any errors found.
Fix Issues
Review error messages, fix problems in your CSV, and revalidate. Continue until your CSV passes validation and is ready for import.
Common Questions
What makes a CSV invalid?
Common errors include: inconsistent column counts per row, unescaped quotes, wrong delimiters, missing headers, and improper line breaks. The validator detects all these issues.
Does this support different delimiters?
Yes. The validator handles commas, semicolons, tabs, and pipes. It auto-detects the delimiter or you can specify it. Works with both US and European CSV formats.
Can I validate large CSV files?
Absolutely. Upload CSV files of any size. Validation happens in your browser using JavaScript, so file size only affects your computer's memory, not server limits.
How do I fix invalid CSV?
The validator shows specific error messages with line numbers. Fix those issues in a text editor or use our CSV Formatter to clean up structure automatically. Then revalidate.
Is validation the same as formatting?
No. Validation checks if CSV is correct. Formatting fixes structure and makes it readable. Use validation first to find errors, then formatting to clean them up.
Where can I learn more about CSV standards?
Read RFC 4180 for official CSV specifications. The W3C Tabular Data Model provides modern recommendations for CSV structure and metadata.
Related CSV Tools
Validation is one step in the CSV workflow. Explore related tools:
For more CSV resources, check CSVLint for best practices and CSVKit documentation for advanced CSV processing tools.