JSON to CSV Converter
Convert a JSON object or an array of objects into reviewable CSV text in your browser, with conservative handling for merged fields and nested values.
Paste a JSON object or an array of objects, choose comma, semicolon, or tab output, and generate CSV locally. The converter merges object keys in first-seen order, writes missing fields as empty cells, and keeps nested objects or arrays as compact JSON strings instead of flattening them automatically.
Browser-local processing
JSON to CSV Converter
How to use
Finish in three steps
- 01
Paste a JSON object or an array of objects. Arrays of numbers, strings, or mixed primitives are intentionally rejected.
- 02
Choose the CSV delimiter that matches your destination system: comma, semicolon, or tab.
- 03
Convert, review the generated headers and nested JSON cells, then copy the CSV only after checking import rules.
What this converter supports
It accepts one JSON object or an array of objects, merges all top-level keys into a header row, escapes commas, quotes, and line breaks, and keeps missing fields as empty cells.
Nested JSON is kept conservative
Nested objects and arrays are serialized as compact JSON strings in a single CSV cell. The tool does not flatten address.city style paths or guess how many columns a nested structure should become.
Review before importing CSV
Check the header order, row count, delimiter, null handling, and any nested JSON cells before loading the CSV into spreadsheets, databases, API importers, or BI tools.
FAQ
About this tool
Does this JSON to CSV tool upload my data?
No. The conversion runs in your browser. Still avoid pasting confidential exports, customer records, credentials, or regulated data into pages you do not trust.
Can it flatten nested JSON automatically?
No. Nested objects and arrays are kept as JSON strings so the output stays explicit. Flattening rules are usually project-specific and should be handled by your import script or schema mapping.
Can I convert an array of strings or numbers?
No. This converter expects objects because CSV needs named columns. Wrap primitive values in objects first, such as { "value": "example" }.
How are null and missing fields handled?
Missing fields and null values become empty cells. Review those cells before importing if your destination distinguishes blank, null, and missing values.
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