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How to Convert CSV to JSON
Upload CSV file with header row
Conversion creates JSON array of objects
Download .json file
Use in APIs, config files, or JavaScript applications
JSON structure produced by this tool
Output format is array of objects: [{"col1":"val1","col2":"val2"},{"col1":"val3","col2":"val4"}]. Each CSV row becomes one object. Keys are CSV headers. If you need different structure (object with array values, nested objects, keyed by ID), post-process with JavaScript/Python after conversion.
Use cases for CSV to JSON conversion
- API request payloads—POST data from spreadsheet to REST endpoints
- Configuration files—convert settings spreadsheets to app configs
- JavaScript data imports—use JSON in web apps instead of parsing CSV
- NoSQL database seeding—import to MongoDB, CouchDB, Firebase
- Mock data generation—convert test data spreadsheets to JSON fixtures
- Static site generation—convert content spreadsheets to JSON for Jekyll/Hugo
- i18n translation files—convert translation spreadsheets to locale JSON
- GraphQL data sources—provide JSON data to GraphQL resolvers
Prepare CSV for optimal JSON output
- Headers: Use valid JavaScript identifiers. first_name good, First Name bad (spaces), 123name bad (starts with number).
- Data types: Remember all values become strings. Add type conversion in your code if needed.
- Empty values: Decide if blanks should be empty strings ("") or null. Tool outputs "". Use Find/Replace in JSON if you need null.
- Special characters: Ensure CSV is UTF-8 encoded if it contains non-ASCII characters.
- Row consistency: Verify all rows have same column count. Extra commas create phantom fields.
CSV to JSON limitations
- All values are strings—no automatic type inference
- No nested objects or arrays—flat structure only
- Empty cells become empty strings, not null
- Headers must be valid—spaces and special chars may cause issues
- Large files create large JSON—no pagination or chunking
- No schema validation—malformed CSV produces malformed JSON
- Can't preserve column order—JSON object key order isn't guaranteed
When to use JSON vs CSV
Post-processing JSON output
Tool outputs string values for everything. To add types: use JavaScript map() to convert fields, JSON.parse() with reviver function, or libraries like ajv for schema-based parsing. For nested structures: group by ID then nest related objects, or use lodash _.groupBy() and _.mapValues(). To change array-of-objects to keyed object: use Array.reduce() with ID as key. Example: arr.reduce((acc,obj)=>{acc[obj.id]=obj;return acc},{}).
Key Features
Header Row as Keys
First CSV row becomes JSON object keys. name,age,city → {"name":"...","age":"...","city":"..."}.
Array of Objects Output
Each CSV row becomes a JSON object in an array: [{...},{...},{...}]. Standard format for REST APIs.
UTF-8 Encoding
Preserves international characters. Outputs valid UTF-8 JSON.
Privacy & Security
Client-side processing via PapaParse. Files stay in browser.
Frequently Asked Questions
What if my CSV doesn't have headers?
Tool treats first row as headers. If your CSV lacks headers, add them manually in text editor first, or first row becomes keys (row1col1, row1col2, etc.).
Are numbers converted to numeric types?
No. All values export as strings. "123" not 123, "true" not true. Parse manually in your code: parseInt(obj.age) or JSON.parse() with reviver.
What happens to empty cells?
Empty cells become empty strings: "field":"". Not null or undefined. Check for empty strings in your code.
Can I create nested JSON objects?
No. Output is flat objects only. CSV structure is tabular—can't represent hierarchy. For nested data, structure CSV differently or transform JSON after conversion.
What about special characters in values?
Automatically escaped per JSON spec. Quotes become \", line breaks become \n, backslashes become \\. Output is valid JSON.