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JSON to CSV Converter

Convert simple JSON arrays into CSV rows for spreadsheets, exports, and quick tabular review.

Convert JSON arrays into CSV instantly. Useful for exports, spreadsheets, and quick data transformation workflows.

Explore more tools that work well with this page.

Json Formatter Beautify JSON for easier reading, debugging, and review. Regex Tester Test regular expressions in a focused browser workflow. Base64 Encoder Encode and decode Base64 text instantly in your browser.

FAQ

Common questions about this tool.

What does the JSON to CSV tool do?

It turns JSON records into CSV output so you can move structured data into spreadsheet-friendly rows.

Is the JSON to CSV tool free to use?

Yes. It runs in the browser for quick exports and review work.

How to use

Paste your input, run the tool, then copy the result you need.

  1. Paste or type the text or data you want to work with.
  2. Click the main action button to generate the result.
  3. Review the output and copy it into your next step.

Use cases

This helps when structured data needs to move into a spreadsheet quickly.

  • Turn API responses or exported objects into CSV files for spreadsheet review and handoff.
  • Flatten simple JSON arrays before sharing data with non-technical teammates.
  • Prepare structured records for CSV imports, audits, or manual data checks.

When this tool is useful

Convert simple JSON arrays into CSV rows for spreadsheets, exports, and quick tabular review. JSON to CSV sits in the json & data part of the site, which focuses on format, validate, and convert structured data for development work.

Open it when raw JSON, copied records, or lightweight data transforms are slowing down debugging, QA, or documentation work. Within that group, it leans toward data conversion tasks, so the page is tuned for quick single-purpose use rather than a long multi-step workflow. If this step is only part of the job, the most relevant follow-up tools are Json Formatter and Regex Tester.

Before you copy the result

  • Validate the structure after processing, especially when the source came from logs, APIs, or spreadsheet exports.
  • Compare the first object or row before copying large results into another system.
  • If the output is valid but still hard to review, switch to a related comparison or extraction tool next.

Example

A quick example of how this tool works.

Input

[{"name":"Alex","age":30},{"name":"Sam","age":28}]

Output

name,age\nAlex,30\nSam,28