JSON to CSV Converter
Convert JSON arrays to CSV spreadsheets and CSV back to JSON instantly
What is JSON to CSV Converter?
JSON and CSV are the two most common formats for exchanging structured data — JSON dominates in APIs and web applications, while CSV dominates in spreadsheets, data analytics, business intelligence tools, and database imports. The need to convert between them arises constantly: an API returns product data as JSON that needs to go into a Google Sheet, a database export as CSV needs to be transformed to JSON for a REST API, or a data analyst needs to share API data in a format their non-technical colleagues can open in Excel. Our free JSON to CSV Converter handles both directions. It takes a JSON array of objects and flattens it into a properly formatted CSV with column headers derived from the object keys. Nested objects are handled by flattening to dot-notation keys (address.city, address.postcode). Conversion also works in reverse — paste a CSV and receive a clean JSON array. All conversion happens in your browser; your data files are never uploaded to any server.
How to Use JSON to CSV Converter
- 1
Paste Your JSON or CSV
Paste a JSON array of objects (e.g., [{"name":"Alice","age":30}, ...]) or a CSV file with a header row. The tool detects the format automatically.
- 2
Convert
Click "JSON to CSV" or "CSV to JSON". Nested JSON objects are flattened to dot-notation column names. Arrays within objects are stringified. CSV headers become JSON object keys.
- 3
Copy or Download
Copy the converted output to clipboard, or download it as a .csv or .json file ready to open in Excel, import into a database, or pass to an API.
Use Cases
Exporting API Data to Google Sheets
A common workflow for non-technical stakeholders is reviewing API data in a spreadsheet. Fetch the JSON response from an API, paste it here, convert to CSV, and upload the downloaded file to Google Sheets or Excel. The column headers are automatically derived from the JSON keys, producing a clean, importable table without any manual formatting.
Importing CSV Data into a JSON-Based System
Client-supplied data often arrives as Excel exports or CSV files — contact lists, product catalogues, inventory updates. Convert the CSV to JSON here to get a properly structured array of objects that can be posted directly to a REST API, inserted into MongoDB, or processed by a Node.js script without a CSV parsing library.
Transforming Database Exports for Analysis
Database query results exported as CSV can be converted to JSON here for use with data transformation scripts, JavaScript array methods, or tools like jq. The reverse is equally useful: convert a JSON API response to CSV for import into a relational database using LOAD DATA INFILE or PostgreSQL's COPY command.
Features
Bidirectional Conversion
Convert JSON arrays to CSV and CSV tables back to JSON array format — both directions in one tool.
Automatic Header Detection
Extracts column headers from JSON object keys (JSON→CSV) and uses the first CSV row as JSON property names (CSV→JSON).
Nested Object Flattening
Flattens nested JSON objects to dot-notation CSV columns (address.city, address.postcode) for formats that do not support nesting.
Custom Delimiter Support
Choose comma, semicolon, or tab as the CSV delimiter to match regional Excel defaults or specific import tool requirements.
Download as File
Download the converted output as a properly named .csv or .json file ready for immediate use without extra copy-paste steps.
Frequently Asked Questions
The converter expects a JSON array of objects where every object has the same (or similar) keys. For example: [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]. Each object becomes a CSV row; the keys of the first object become the column headers. JSON with a single object at the root (not an array) must be wrapped in an array first.
Nested objects are flattened using dot notation: {"address": {"city": "London", "postcode": "SW1A"}} becomes two columns: address.city and address.postcode. This makes the data usable in a flat CSV format. Arrays within objects are typically serialised as JSON strings within the CSV cell, since CSV has no native representation of arrays.
Excel has long-standing issues with CSV encoding. If your CSV contains non-ASCII characters (accented letters, Arabic, Chinese), Excel may display garbled characters when opening a UTF-8 CSV. Solutions: (1) Import the CSV through Excel's data import wizard and specify UTF-8 encoding. (2) Add a UTF-8 BOM (byte order mark) to the start of the file — some converters do this automatically. (3) Save as .xlsx instead of .csv after import.
CSV files are typically comma-delimited, but in many European countries where the comma is used as the decimal separator (1.234,56 instead of 1,234.56), semicolons are used instead. Excel on European Windows installs defaults to semicolon-delimited CSV. If your CSV opens in Excel with all data in one column, try switching the delimiter from comma to semicolon in this converter.
The tool handles CSV files of typical data export sizes (up to tens of thousands of rows) quickly. Very large files (millions of rows, hundreds of MB) may be slow depending on your browser and device. For production data pipelines with large files, use server-side tools like Papa Parse (JavaScript), pandas (Python), or built-in database COPY/LOAD commands.
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