What if my JSON is nested?

The converter supports one level of nesting via dot notation ('user.name' becomes a column). Deeper nesting is flattened using the same convention. For complex nested structures, consider preprocessing with jq first.

Will it export Excel-compatible CSVs?

Yes — by default it uses CRLF line endings and comma separators, which Excel opens cleanly. Switch to semicolon separator for European Excel locales.

What about arrays inside fields?

Arrays are serialized as JSON strings and quoted. If you want one row per array element, restructure the JSON first — flatten the array at the top level.

Does it escape special characters?

Yes — RFC 4180-compliant escaping. Commas, quotes, and newlines inside field values are handled correctly.

How do I import the CSV into Excel?

Two approaches: (1) Open Excel, then File → Open → select the CSV file → Excel uses Get Data wizard for proper field handling. (2) Drag-drop the CSV into Excel — usually works for clean CSVs but may misinterpret encoding. For UTF-8 CSVs (with non-ASCII characters), use the Get Data wizard and explicitly select 'UTF-8' encoding to preserve special characters. European Excel locales: change separator to semicolon. Common gotcha: Excel auto-converts long numeric strings to scientific notation (e.g., '1234567890123' becomes 1.23457E+12); pre-format columns as Text before pasting to preserve.

Can I convert CSV back to JSON?

Yes — use our CSV to JSON tool for the reverse direction. Round-tripping JSON → CSV → JSON usually preserves data, but watch for: (1) Type loss — CSV has no native types, all values become strings (true/false/numbers become text). (2) Nested objects flatten to dot-notation, then need to be re-nested. (3) Empty values may convert from null to empty string and back. For lossless round-trips, JSON-only formats (JSONL, NDJSON) preserve all types and nesting.

Developer Utilities · Free tool

JSON to CSV Converter

Turn JSON arrays into CSV with auto-detected headers and nested field flattening instantly in your browser—free, no-sign-up converter.

Updated June 2026

JSON (array of objects)

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What it does

A free JSON to CSV converter. Paste an array of JSON objects; get a downloadable CSV with all keys as headers. Handles nested strings, commas, and quotes correctly using RFC 4180-compliant escaping. Output uses CRLF line endings by default for Excel compatibility; switch to LF for Unix-style consumers.

Useful for migrating data between APIs, importing into spreadsheets, handing data to non-technical colleagues who live in Excel, or building CSV exports from JSON-first databases (MongoDB, Firestore, DynamoDB). The tool flattens one level of nesting using dot notation: a JSON property ‘user.email’ becomes a column named ‘user.email’. Deeper nesting requires preprocessing with jq or similar.

Common gotchas: (1) Excel auto-converts long numeric strings to scientific notation (e.g., ‘1234567890123’ becomes ‘1.23457E+12’) — pre-format columns as Text before pasting to preserve. (2) UTF-8 encoding required for non-ASCII characters; use the Get Data wizard with explicit UTF-8 selection. (3) European Excel locales need semicolon separator instead of comma. (4) Arrays inside fields are serialized as JSON strings and quoted — restructure the source data if you need one row per array element.

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How to use it

Paste a JSON array of objects into the input.
Click Convert.
Copy the CSV output or download as a file.
Use the output in Excel, Google Sheets, or your database.

When to use this tool

Exporting API data (REST, GraphQL responses) for a non-technical analyst to review.
Migrating data from a JSON-first database into a SQL system that imports CSV better.
Converting NoSQL exports (MongoDB, Firestore) to spreadsheet-friendly format.
Generating bulk-import files for legacy systems that only accept CSV.

When not to use it

Heavily nested JSON (3+ levels deep) — flattening loses meaning; consider keeping JSON.
Data with mixed schemas where every record has different keys — CSV requires consistent columns.
Very large files (10M+ rows) — browser conversion may timeout; use a streaming converter.

Common use cases

User export from analytics API (1,000 user objects with consistent fields) → CSV for marketing team.
Product catalog JSON from headless CMS → CSV import to legacy retail system.
Developer survey responses from JSON-storing form tool → CSV for manager's Excel analysis.
Test data fixture (JSON in your code repo) → CSV for QA team to verify in Excel.

Frequently asked questions

What if my JSON is nested?: The converter supports one level of nesting via dot notation ('user.name' becomes a column). Deeper nesting is flattened using the same convention. For complex nested structures, consider preprocessing with jq first.
Will it export Excel-compatible CSVs?: Yes — by default it uses CRLF line endings and comma separators, which Excel opens cleanly. Switch to semicolon separator for European Excel locales.
What about arrays inside fields?: Arrays are serialized as JSON strings and quoted. If you want one row per array element, restructure the JSON first — flatten the array at the top level.
Does it escape special characters?: Yes — RFC 4180-compliant escaping. Commas, quotes, and newlines inside field values are handled correctly.
How do I import the CSV into Excel?: Two approaches: (1) Open Excel, then File → Open → select the CSV file → Excel uses Get Data wizard for proper field handling. (2) Drag-drop the CSV into Excel — usually works for clean CSVs but may misinterpret encoding. For UTF-8 CSVs (with non-ASCII characters), use the Get Data wizard and explicitly select 'UTF-8' encoding to preserve special characters. European Excel locales: change separator to semicolon. Common gotcha: Excel auto-converts long numeric strings to scientific notation (e.g., '1234567890123' becomes 1.23457E+12); pre-format columns as Text before pasting to preserve.
Can I convert CSV back to JSON?: Yes — use our CSV to JSON tool for the reverse direction. Round-tripping JSON → CSV → JSON usually preserves data, but watch for: (1) Type loss — CSV has no native types, all values become strings (true/false/numbers become text). (2) Nested objects flatten to dot-notation, then need to be re-nested. (3) Empty values may convert from null to empty string and back. For lossless round-trips, JSON-only formats (JSONL, NDJSON) preserve all types and nesting.

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