This route is for the common case where an API response or fixture list is already shaped like an array of plain objects and the next stop is a spreadsheet, CSV import, or quick table review. It is a practical browser-side export for analyst handoff, lightweight QA, and one-time reporting checks.
The converter is intentionally narrow. It does not accept a top-level object, it does not split arrays into multiple rows, and it does not try to design relational tables. Nested objects are flattened into dot-notation headers, while arrays stay inside one CSV cell as JSON text.
After you paste a JSON array, the page validates that every item is a plain object, builds one combined header row from all visible keys, flattens nested objects such as user.city, and writes CSV rows immediately. That makes it useful as a json array to csv tool, but not as a full data-modeling workflow.
| Example | Value |
|---|---|
| Input | A JSON array of objects from an API response, export preview, or test fixture. |
| Output | One flat CSV table with shared headers and dot-notation columns for nested object fields. |
If the real task is exploding arrays into child rows, normalizing multiple tables, or preserving a richer document structure, stop here. This browser json to csv route is closer to a flat export preview than to an ETL pipeline. The flatter your object array is, the more trustworthy the result becomes.
It expects a top-level JSON array whose items are plain objects.
They are flattened into headers such as address.city.
Arrays stay in one CSV cell as JSON text rather than becoming extra rows.
When you need relational expansion, schema-aware design, or anything beyond one flat table snapshot.
The input must be a JSON array of plain objects, e.g. [{"name":"A"},{"name":"B"}].
Nested objects are flattened with dot notation, and arrays stay in one CSV cell as JSON text.
Use these workflow guides when you need more context before or after running this tool.