CSV ⇄ JSON Converter
Two-way CSV ↔ JSON conversion that handles commas and newlines inside quoted fields, with delimiter and header options.
>_ USAGE GUIDE
Paste CSV and get structured JSON, or convert a JSON array back into CSV — both directions in real time. Parsing follows the CSV standard (RFC 4180), which means commas and newlines inside quoted fields are handled correctly. This is exactly where hand-written split(',') logic breaks and where simplistic converters scramble your rows.
- Paste your data: CSV text, or a JSON array of objects
- Set the options: pick the delimiter — comma, semicolon, or tab (European Excel exports often use semicolons) — and whether the first row is a header
- Copy the result: JSON for your program, CSV for your spreadsheet
The common flows: convert a JSON response to CSV and open it in Excel as a report, or convert an Excel-exported CSV to JSON and feed it straight into your code. All conversion runs locally in the browser — business data never leaves your device, and the tool works offline.
>_ FAQ
Q1 · What if a CSV field contains commas or line breaks?
The CSV standard wraps such fields in double quotes, and a double quote inside a field is escaped as two consecutive quotes (""). Excel and mainstream tools follow this convention. This parser implements the standard, so quoted fields with embedded commas or newlines survive intact; if your data source did not escape properly, fix it at the source before converting.
Q2 · Why do non-ASCII characters turn garbled when I open the CSV in Excel?
Excel reads CSV using the system's legacy ANSI encoding by default, so UTF-8 content shows as mojibake. The standard fix is to save the file as UTF-8 with BOM. Paste the converted output into a text editor, save it with UTF-8 BOM encoding, and Excel will display the characters correctly.
Q3 · What if the first row is data, not a header?
Turn off the "first row is header" option. The first row is then treated as data and the JSON output is an array of arrays; with the option on, the first row becomes field names and the output is an array of objects keyed by the header columns. Switch as your data requires.
Q4 · What if the JSON objects have inconsistent fields?
Real-world data often has optional fields — some records carry email, others do not. The conversion uses the union of all field names as columns and emits empty cells for missing values. If your source JSON is deeply nested, flatten it first: CSV is a two-dimensional table format and cannot represent nesting.
Q5 · Can it convert very large CSV files?
CSV of a few dozen megabytes parses fine locally in the browser. For files in the hundreds of megabytes, browser memory can become a constraint — use command-line tools such as Python's pandas instead. Reports, exports, and configuration-scale data are exactly what this tool is built for.