CSV to JSON Converter

The CSV to JSON Converter turns tabular spreadsheet data — Excel exports, database dumps, analytics reports — into clean, API-ready JSON arrays of objects. Paste CSV with any delimiter, and the parser detects header rows, quoted fields, and value types automatically, so you get JSON your code can consume immediately.

• •Header row detection: the first CSV row becomes your JSON object keys automatically
• •Custom delimiter support: comma, semicolon, tab, pipe, or any single custom character
• •Quoted-field parsing: correctly handles commas and newlines embedded inside quoted values
• •Automatic type inference: numeric strings, true/false, and empty values convert to numbers, booleans, and null
• •Pretty-print output: indented JSON for readability, or compact JSON for smaller payloads
• •Runs entirely in your browser: your CSV data is never uploaded to a server

• •Turning an Excel or Google Sheets export into a JSON payload for a REST API request
• •Feeding a CSV database dump into a JavaScript or Node.js data pipeline
• •Converting a CSV analytics report (Google Analytics, Mixpanel) into JSON for a custom dashboard
• •Preparing JSON test fixtures by editing tabular data in a spreadsheet first
• •Importing CSV survey or form responses into a JSON-based statistics tool

1. 1.Paste your CSV data into the input editor, or upload a .csv file
2. 2.Confirm the delimiter (comma, semicolon, tab, pipe, or custom) matches your file
3. 3.Toggle 'First row is header' on if your CSV includes column names
4. 4.Enable Auto Convert for live output, or click Convert
5. 5.Copy the JSON output or download it as a .json file

• •Rows with a different column count than the header row still convert, but keys may be missing or misaligned — verify output for irregular CSV
• •Values like '00123' are detected as numeric and lose their leading zero; disable type inference if you need to preserve ID-like strings
• •Multi-line values wrapped in quotes are supported but can be fragile with malformed quoting
• •Non-UTF-8 encoded files (Latin-1, Windows-1252) may display garbled characters — re-save as UTF-8 first

• •Very large CSV files (over ~50MB) may exceed browser memory — use a command-line tool such as csvkit or pandas for huge datasets
• •The tool does not validate CSV schema consistency across rows
• •For production ETL pipelines, a dedicated tool with error handling and logging (Airflow, Fivetran) is more appropriate than browser-based conversion

If you're starting from JSON and need spreadsheet-friendly CSV — for example, exporting an API response for a non-technical stakeholder to open in Excel — use the JSON to CSV Converter instead. It flattens nested objects into columns and lets you choose delimiter and quoting style for the output file.