CSV β JSON Converter
Convert between CSV and JSON instantly β paste, upload, transform, download.
What is it?
CSV (Comma-Separated Values) and JSON (JavaScript Object Notation) are the two most widely used formats for structured data exchange. CSV is the format of choice for spreadsheets, database exports, and data analysis pipelines β it is human-readable, compact and universally supported by tools like Excel, Google Sheets, and pandas. JSON is the lingua franca of APIs, web applications, and NoSQL databases β it natively supports nested objects, arrays, and typed values. Converting between the two formats is a common task for developers, data analysts, and business users alike. You might receive a CSV export from a CRM and need it as JSON to feed into a REST API. Or you might get a JSON response from an endpoint and need it flattened into CSV for a business report in Excel. Either direction requires parsing logic that can be tedious to write manually every time. This converter handles both directions with configurable options. For CSV to JSON, you can choose the field delimiter (comma, semicolon, pipe, or tab), decide whether to use the first row as field names, and control how numeric values are treated. For JSON to CSV, you can choose the output delimiter and control how nested objects or arrays are handled. Both modes support file upload (CSV or JSON files) as well as direct paste. The output can be downloaded as a file or copied to clipboard instantly.
How to use it
- Select the conversion direction: "CSV β JSON" or "JSON β CSV" using the mode toggle.
- Paste your CSV or JSON data into the text area, or click "Upload file" to load a .csv or .json file.
- Configure the options: for CSV input, set the delimiter and whether the first row contains headers.
- Click "Convert" to process the data.
- Review the output in the result panel β the converted data appears formatted and ready to use.
- Click "Copy" to copy the result to your clipboard, or "Download" to save it as a .json or .csv file.
Why use this tool
Almost every developer and data professional has needed to quickly convert between CSV and JSON at some point. The alternatives are slow: writing a Python script, opening a Jupyter notebook, running a Node.js one-liner in the terminal, or using a general-purpose tool that requires five steps to do something that should take ten seconds. This tool makes the conversion instant and configurable β with no server upload, no account creation, and no file size anxiety. All processing runs in JavaScript directly in your browser, which means conversions happen in milliseconds even for files with tens of thousands of rows. The file upload feature makes it practical for real workloads β drag a 10 MB CSV export from your database tool, convert it to JSON in one click, and download the result. The delimiter options (comma, semicolon, pipe, tab) cover every CSV dialect you are likely to encounter in practice, from standard US exports to European semicolon-delimited files.
Frequently asked questions
What delimiters are supported for CSV input?
The tool supports comma (,), semicolon (;), pipe (|) and tab delimiters. Semicolon is common in European CSV files because commas are used as decimal separators in many European locales.
What happens with nested JSON objects when converting to CSV?
Nested objects are flattened using dot notation (e.g. "address.city" becomes a column header). Arrays of primitive values are joined with a semicolon. Deeply nested structures may not convert to a clean CSV β in those cases, consider flattening your JSON first.
What is the maximum file size?
There is no hard limit β the processing runs entirely in your browser. In practice, files up to 50β100 MB convert quickly. Very large files may take a few seconds depending on your browser and device.
Are my files uploaded to a server?
No. All conversion logic runs in JavaScript in your browser. Files are read using the File Reader API and processed locally β nothing is ever sent to an external server.
What if my CSV has inconsistent columns?
The converter will still process the file, using the first row's column count as the reference. Rows with fewer columns will have missing fields set to null or empty string in the JSON output.