Drag & drop a .json file here
or paste JSON / click Upload File above
Your data will appear here
1Paste JSON or drag a file
2Adjust options if needed
3Edit table cells, then download
Use dot notation (e.g., user.address.city) for clear column headers. For complex nested structures, consider using JSON strings or 1-level flattening.
Select delimiters based on your target application: comma for most cases, semicolon for European formats, tab for Excel, or custom for specific requirements.
Use UTF-8 BOM when exporting to Excel to ensure proper character display. For Windows systems, CRLF line endings work best.
Always validate your JSON structure before conversion. The tool automatically cleans data, but manual review ensures accuracy for critical applications.
Support for comma, semicolon, tab, pipe, and custom delimiters. Perfect for regional settings and specific data formats.
Built-in data validation and cleaning. Handles missing values, duplicate rows, and ensures proper CSV formatting.
Real-time table preview with inline editing. Double-click cells to edit, sort columns, and format data before export.
Paste your JSON data into the right input panel or drag & drop a .json file. The data is instantly converted into an editable table preview on the left. Click Download CSV to save the file. All processing happens in your browser — no signup required. For best results, ensure your JSON is valid and properly formatted.
Nested JSON objects are automatically flattened using dot notation (e.g., user.address.city becomes the column header). You can choose between three flattening modes in the config bar: Dot-separated (default, creates hierarchical columns), JSON string (keeps nested data as JSON strings), or 1 level only (flattens only top-level properties). The auto-detect feature also handles API-wrapped responses like {"data": {"items": [...]}} by extracting the nested array.
Yes. NDJSON (Newline-Delimited JSON) or JSONLines is auto-detected. Each line is treated as a separate, self-contained JSON object and converted to a table row. This format is ideal for log files, database exports, and streaming data. The converter processes each line independently, making it perfect for large datasets that don't fit in memory.
You can choose comma (default, standard CSV format), semicolon (European standard), tab (Excel-friendly TSV), pipe (alternative delimiter), or a custom delimiter for specific needs. Encoding supports UTF-8 (universal) and UTF-8 BOM (for better Excel compatibility on Windows). Line endings support CRLF (Windows) and LF (Unix/Linux). For Excel users, we recommend UTF-8 BOM with CRLF.
Yes — double-click any table cell to edit it inline. You can also sort columns by clicking headers, hide columns via right-click, insert or delete rows, and undo/redo changes with Ctrl+Z / Ctrl+Y. All edits are reflected in the final CSV output. This feature is particularly useful for cleaning data, fixing typos, or reformatting values before export.
For complex nested JSON, experiment with different flattening modes. Start with Dot-separated to see the full structure. If columns become too complex, try 1 level only for a simpler view. For preserving original structure, use JSON string mode. You can also use JSON Path to target specific nested arrays (e.g., data.items) for more precise conversion.
For large files (over 10MB), use the Upload File button instead of pasting. The tool processes files in chunks and provides better performance. For extremely large datasets, consider splitting your JSON into smaller chunks or using the NDJSON format, which the converter handles efficiently line by line.
If Excel has issues opening your CSV, try these solutions: 1) Use UTF-8 BOM encoding in the config bar, 2) Choose tab delimiter and save as .txt file, then import to Excel, 3) Ensure line endings are set to CRLF (Windows), 4) Check that your JSON data doesn't contain characters that Excel might misinterpret. The converter's UTF-8 BOM option is specifically designed to solve Excel compatibility issues.