Free CSV to JSON Converter Online
Convert CSV data to JSON instantly. Paste your CSV with headers and get a JSON array of objects. Handles quoted fields and commas inside values.
CSV (comma-separated values) is the universal export format for spreadsheets and databases, but most APIs and web applications expect JSON. Converting between them by writing a parser is repetitive work; this tool does it instantly. Paste any CSV with a header row and click Convert — each row becomes a JSON object, with the column headers as keys. The output is a JSON array ready to paste into an API call, a seed file, or a configuration. The parser handles quoted fields, commas inside quoted values, and Windows line endings.
CSV to JSON
How to use this csv to json converter
- Paste your CSV data into the input box. The first row must be the header row — its values become the JSON keys.
- Click Convert to produce the JSON array.
- Each row in the CSV becomes one object in the array. Empty fields become empty strings.
- Click Copy to put the JSON on your clipboard.
Common use cases
- Exporting a spreadsheet from Excel or Google Sheets and converting it to JSON for an API payload
- Seeding a database from a CSV export by converting to a format a migration script can consume
- Transforming a product catalog CSV into a JSON array for a web storefront
- Converting exported contact data (CSV) into JSON for import into a CRM or email tool
- Prototyping with a static JSON dataset that was originally maintained as a spreadsheet
Frequently asked questions
Does this handle quoted commas inside fields?
Yes. Fields that contain commas must be wrapped in double quotes in standard CSV. The parser recognizes these quoted fields and preserves the contents, including embedded commas.
What if my CSV uses a semicolon or tab as the delimiter?
The tool defaults to comma as the delimiter. For semicolon-delimited files (common in European locales), do a find-and-replace before pasting.
Are all values returned as strings?
Yes. CSV has no type system — everything is text. If your application needs typed values, add a post-processing step to cast fields to the correct types.
What happens if rows have different numbers of columns?
If a row has fewer columns than the header, the missing fields are omitted. If a row has more columns, the extra values are ignored.