JSON to CSV Converter
Drop a JSON array, get a spreadsheet-ready CSV — ready for Excel, Google Sheets, Tableau, or any BI tool that speaks CSV.
Drop your JSON file here
Converts to .csv — stays on your device
Why convert JSON to CSV?
- Turning a REST API response or Postman export into a CSV for your finance or ops team.
- Converting a Node/Python script's JSON output into a CSV for Google Sheets analysis.
- Exporting MongoDB or DynamoDB query results (as JSON) to CSV for a BI import.
- Turning a Stripe or Shopify API dump into CSV for accounting reconciliation.
- Preparing JSON data for a CSV-only ingestion pipeline (Snowflake COPY, BigQuery load, SFTP drop).
- Making structured log data or event streams reviewable in Excel.
How our converter works
Your JSON must be an array of flat objects (that's the whole point of CSV — it's flat). PapaParse infers the column headers from all keys across all objects, then writes one row per array element. Missing keys become empty cells. Values with commas or newlines are quoted per RFC 4180. Types survive — numbers stay unquoted, strings get quoted when needed. Runs entirely in your browser; JSON containing customer data, financial records, or API keys never leaves your device.
JSON vs CSV — what's gained, what's lost
| Feature | JSON | CSV |
|---|---|---|
| Nested data | Objects + arrays at any depth | Flat only — nested fields are stringified or error |
| Types | Native types (number, bool, null) | All strings on read-back |
| Readability | Requires a viewer | Opens in any spreadsheet |
| Best for | APIs, programs | Humans, spreadsheets, BI tools |
| Compression-friendly | Moderate | Excellent — repetitive |
Frequently asked questions
What shape does my JSON need to be in?
A JSON array of flat objects: `[{...}, {...}, {...}]`. Each object's keys become columns; each object becomes a row. The tool will error clearly if you feed it a single object or an array with nested objects.
What if some objects have keys others don't?
All keys from all objects are unioned into the header row. Objects missing a key get an empty cell in that column. This is the standard "sparse array" handling.
How are nested objects or arrays handled?
Nested values are JSON.stringify'd and written as quoted strings in the cell. CSV is a flat format — there's no native way to represent nesting. If you need true flattening (e.g. `user.name` → `user_name`), flatten the JSON first with jq or a small script.
Will Excel or Sheets auto-parse the output?
Yes — the output is RFC 4180 CSV, which Excel, Sheets, Numbers, and every BI tool open correctly. Unicode works (UTF-8). For Excel's dialect-specific quirks (semicolons in European locales), open via Data → Import Text instead of double-clicking.
Are my files uploaded?
No. The conversion is entirely client-side. JSON containing customer records, financial data, or internal API payloads stays on your device.
About the JSON format
JSON is the default format for APIs and programs — structured, typed, nested, machine-readable. CSV is the default format for spreadsheets and analysis tools — flat, simple, human-editable, universally supported. Converting JSON to CSV is the standard bridge when structured data needs to be reviewed, filtered, or reported on by a human with Excel, Google Sheets, or a BI tool. The conversion is lossy by design: CSV can't represent nested objects or arrays, so the source JSON must be a flat array of objects. The output follows RFC 4180 — proper quoting, escaped quotes, UTF-8 encoding — so it opens cleanly in every spreadsheet application and loads into every BI tool, database COPY command, or SFTP pipeline.