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JSON To CSV

The input must be an array of objects where each object represents one row. The keys of the first object become the CSV header, and subsequent rows fill values in matching columns. A bare object, a string, or a deeply nested array of arrays cannot be flattened automatically. If y

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The input must be an array of objects where each object represents one row. The keys of the first object become the CSV header, and subsequent rows fill values in matching columns. A bare object, a string, or a deeply nested array of arrays cannot be flattened automatically. If y

This free JSON To CSV from KX Toolkit is part of our all-in-one online toolkit. It runs entirely in your browser, so your data never leaves your device for client-side operations. 100% free, forever - no paywall, no credit card, no trial.

How to use the JSON To CSV

  1. Paste your input - JSON, regex pattern, JWT, URL etc.
  2. Pick any flags or options the tool supports.
  3. Click the action button (Format, Test, Decode).
  4. Copy the result or download it as a file.

What you can do with the JSON To CSV

  • Format and validate API responses while debugging.
  • Test regex patterns against real input before deploying.
  • Decode JWTs to inspect claims and expiry.
  • Generate UUIDs for migrations, tests and seeders.

Why use KX Toolkit's JSON To CSV

  • Browser-based: Works on Windows, macOS, Linux, iOS and Android - no install, no extension.
  • Privacy-first: Client-side tools never upload your data; server-side tools delete files right after processing.
  • Mobile-friendly: Full feature parity on phones and tablets - not a stripped-down view.
  • Fast: Optimised for instant feedback. No artificial waiting screens, no email-gated downloads.
  • One hub for everything: 300+ tools across SEO, text, image, PDF, code, color, calculators and more - skip switching between sites.

Tips for the best results

Bookmark the most-used tools - your browser bookmark bar is faster than retyping the URL every time.

Related Developer Tools

If you find this tool useful, explore the full Developer Tools collection or browse our complete tool directory. KX Toolkit is built for marketers, developers, designers, students and anyone who needs a quick utility without signing up for yet another SaaS.

What shape does my JSON need to be for CSV conversion?
The input must be an array of objects where each object represents one row. The keys of the first object become the CSV header, and subsequent rows fill values in matching columns. A bare object, a string, or a deeply nested array of arrays cannot be flattened automatically. If your data is wrapped in an outer object, point the converter at the inner array.
How are nested objects and arrays handled?
Nested values are typically serialized as JSON strings inside a single CSV cell, since CSV is a flat tabular format with no native nesting. Some converters offer dot-notation flattening that produces columns like address.city or tags.0. Pick the option that matches your downstream consumer - spreadsheets prefer flat columns, while data pipelines often re-parse the JSON-in-cell format.
Why are some of my CSV cells wrapped in double quotes?
CSV requires quoting when a cell contains a comma, a double quote, or a line break. The converter quotes those values automatically and doubles any internal double quotes, which is the standard RFC 4180 escape. Cells without special characters are left unquoted to keep the output compact. This makes the CSV safe to open in Excel, Numbers, and any compliant parser.
What delimiter and line ending should I use?
The default delimiter is a comma, but you can switch to semicolon, tab, or pipe if your locale or downstream tool expects it. European Excel installations, for example, use semicolons because comma is the decimal separator. Line endings default to CRLF for maximum compatibility with Windows tools, though Unix-only pipelines work fine with LF. UTF-8 with BOM helps Excel detect non-ASCII characters correctly.
How do I handle objects with different keys across the array?
The converter scans every object to compute the union of keys, so missing fields appear as empty cells rather than being dropped. This avoids data loss but produces wide rows when the schema is inconsistent. If your records vary widely, consider splitting them into separate CSV files per shape, or normalize the JSON first so every object has the same keys.
Are dates and numbers preserved correctly in CSV?
CSV is text-only, so types are lost - every value becomes a string. Dates are written exactly as they appear in the JSON, typically ISO 8601 strings. Numbers keep their digits but lose any indication that they were numeric until a parser interprets them again. When importing into a spreadsheet, be ready to set column types manually or use a typed format like Parquet for analytics workloads.

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