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JSON ⇄ CSV

Two-way conversion between JSON arrays and CSV

Input
JSON ArrayJSON
Lines: 0Chars: 0
Output
CSVCSV
Lines: 0Chars: 0

Overview: JSON ⇄ CSV is a two-way tool built for tabular structured data. It can export a JSON array of objects to a standard CSV file, or parse CSV back into a JSON array. The tool follows RFC 4180, automatically escaping commas, newlines and double quotes, and is fully compatible with Excel, Google Sheets, Numbers and other mainstream spreadsheet software.

How to use: Step 1 — paste a JSON array (each element is an object representing a record) into the left panel, or click "Sample" to load an example. Step 2 — the tool extracts the union of all object keys as the header row, fills missing fields with empty values, and emits CSV. Step 3 — to go the other way, paste CSV on the right; the first row is treated as the header, and the remaining rows are converted into an array of objects. Step 4 — copy or download the converted result. Nested objects or arrays are serialised as JSON strings inside the cell.

Typical scenarios: Data analysts import back-end API JSON into Excel for pivot analysis; operations teams convert CSV user lists exported from business systems into JSON for bulk CMS imports; QA engineers turn CSV test data into JSON fixtures; product managers exchange back-office reports between CSV and JSON to share with different colleagues; data engineers preview data during ETL debugging.

Technical notes: The tool expects JSON with a top-level array of objects; non-arrays or empty arrays trigger a warning. Values containing commas, double quotes or newlines are automatically wrapped in double quotes and internal double quotes are escaped by doubling. CSV output uses CRLF newlines to stay compatible with the Windows version of Excel. Headers are the union of every object key, preserving the order in which they first appear; numbers and booleans in JSON become strings in CSV and stay strings on the way back.

Privacy: All conversion happens locally. User lists, order data, tracking data and other sensitive tables are never uploaded, so your privacy is fully protected.

Frequently Asked Questions

How do I use JSON ⇄ CSV?
Step 2 — the tool extracts the union of all object keys as the header row, fills missing fields with empty values, and emits CSV. Step 3 — to go the other way, paste CSV on the right; the first row is treated as the header, and the remaining rows are converted into an array of objects.
What can JSON ⇄ CSV do?
Typical scenarios: Data analysts import back-end API JSON into Excel for pivot analysis; operations teams convert CSV user lists exported from business systems into JSON for bulk CMS imports; QA engineers turn CSV test data into JSON…
Is my data private when I use JSON ⇄ CSV?
User lists, order data, tracking data and other sensitive tables are never uploaded, so your privacy is fully protected. User lists, order data, tracking data and other sensitive tables are never uploaded, so your privacy is fully protected.
What technical details should I know about JSON ⇄ CSV?
Values containing commas, double quotes or newlines are automatically wrapped in double quotes and internal double quotes are escaped by doubling. CSV output uses CRLF newlines to stay compatible with the Windows version of Excel.