JSON to CSV Converter Online Free

How to convert JSON to CSV

Start by pasting a JSON array or object into the left panel. The converter accepts a single object, an array of objects, or a simple array of arrays, then normalizes the structure for spreadsheet use. If your data contains nested objects, you can flatten them with dot notation such as user.address.city so each field lands in its own CSV column. If you have arrays as values, choose whether to combine them into one cell or expand them into indexed columns like tags.0 and tags.1.

Next, adjust the options for your workflow: set the delimiter to comma, semicolon, tab, or pipe; choose whether the first row should be a header; decide whether to quote every field; and enable formula protection if you are sending the CSV to Excel or Google Sheets. The browser runs the conversion locally, so you can preview the output before downloading the finished file.

Once the output looks right, copy it or download it as a .csv file. Because the conversion happens entirely on your device, there is no server round trip and no risk of exposing sensitive data in transit. This is especially useful when exporting customer records, analytics rows, or API payloads into a format that spreadsheet tools can open quickly.

Before and after example

Imagine a JSON payload from an API that returns a list of employees with nested profile details. The source might contain a name, department, and a nested address object. After conversion, the CSV creates a row for each employee and separate columns for name, department, and address.city. That makes it easy to sort records, import into Excel, or feed them into a report generator with little cleanup.

Common use cases

CSV remains the universal format for spreadsheets, dashboards, and bulk data import. Marketing teams often convert JSON from a CMS or form endpoint to CSV for analysis in Google Sheets. Finance teams export structured records to CSV for monthly reconciliation. Developers also use it to inspect API responses in a tabular format, especially when debugging fields or preparing sample data for Excel-based reporting.

If you are preparing data for a CRM, migration task, or batch import, CSV is easy to validate, edit, and share with non-technical collaborators. The tool handles nested data, quoting, and row normalization so the output stays clean and readable.

Things to watch out for

Nested JSON is not always a perfect match for a flat spreadsheet. If you flatten arrays or objects without naming the output carefully, columns may become difficult to read. For example, a tags array might become tags.0, tags.1, and tags.2 or a single comma-separated string depending on your chosen style. CSV also has limited support for data types; numbers are stored as text unless a spreadsheet tool interprets them. Use column headers and consistent field naming to make imports simpler later on.

Frequently asked questions

Related tools

• CSV to JSON
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• JSON to YAML
• JSON Formatter
• JSON Validator
• YAML to JSON (coming soon)