JSON to Excel Converter
Convert JSON array of objects to Excel (.xlsx) and Excel back to JSON. Support multi-sheet workbooks, nested object flattening, and full Excel compatibility.
About JSON to Excel Converter
Our free online JSON to Excel Converter is a powerful utility that transforms JSON arrays of objects into Excel (.xlsx) workbooks and converts Excel files back into JSON format. This bidirectional conversion tool is essential for data analysts, developers, and business professionals who need to exchange data between web APIs and spreadsheet applications.
The JSON to Excel conversion handles flat and nested objects. When flattening is enabled, nested objects like `｛"address": ｛"city": "NY"｝｝` become `address.city` columns in the Excel sheet. Arrays are serialized as JSON strings within the cell. The tool creates a proper Excel workbook with a single worksheet by default, with a customizable sheet name.
The Excel to JSON conversion reads the active worksheet and reconstructs JSON objects from each row, using the header row as keys. It supports multiple Excel formats including .xlsx, .xls, .xlsb, .xlsm, and .ods. The output is a clean array of JSON objects ready for use in APIs, databases, or applications.
Powered by the SheetJS (xlsx) library, this tool provides reliable and accurate conversion between JSON and Excel formats. All processing happens directly in your browser, so your data never leaves your device. This ensures complete privacy and security for your sensitive data, including customer information, financial records, and confidential datasets.
Related JSON Tools
Features
Bidirectional Conversion
Convert JSON to Excel and Excel back to JSON with a single click. Perfect for data transformation workflows.
Nested Object Flattening
Automatically flatten nested JSON objects into dot-separated column headers for tabular representation.
Full Excel Support
Support .xlsx, .xls, .xlsb, .xlsm, and .ods formats for reading and writing Excel workbooks.
Custom Sheet Name
Set a custom worksheet name when generating Excel files for organized workbook management.
Header Row Control
Optionally include or exclude the header row in the Excel output for flexible data export options.
Upload & Download
Upload Excel files directly or download converted data as .xlsx or .json files for local use.
Auto-Convert
Enable auto-convert mode to transform your data automatically as you type in real-time.
Statistics
View input/output character counts, row count, column count, and sheet count for quick data overview.
Privacy First
All conversion happens in your browser. Your data never leaves your device, ensuring complete security.
How to Use
Paste Your Data
Paste JSON array of objects into the left input editor, or click "Upload Excel" to load an Excel file. Click "Sample JSON" to load example data.
Configure Options
Choose your nested key separator, whether to flatten nested objects, include a header row, and set the worksheet name.
Convert
Click "JSON to Excel" to generate an Excel file, or "Excel to JSON" to convert uploaded Excel data to JSON.
Copy or Download
Click Copy to copy the converted JSON to clipboard, or Download JSON/Excel to save as files for local use.
Frequently Asked Questions
What JSON format does this tool expect?
The tool expects a JSON array of objects, where each object represents a row and each key represents a column. For example: `[｛"name": "John", "age": 30｝, ｛"name": "Jane", "age": 25｝]`. If your JSON is a single object or a nested structure, you may need to restructure it first. The tool handles objects with different keys - columns are generated from all unique keys across all objects.
How does nested object flattening work?
When flattening is enabled, nested objects are converted to flat key paths. For example, `｛"user": ｛"name": "John", "address": ｛"city": "NY"｝｝｝` becomes `｛"user.name": "John", "user.address.city": "NY"｝`. The dot separator can be changed to an underscore in the settings. Arrays within nested objects are serialized as JSON strings in the Excel cell.
What Excel formats are supported?
The tool supports reading .xlsx (Excel 2007+), .xls (Excel 97-2003), .xlsb (Excel Binary), .xlsm (Excel with Macros), .ods (OpenDocument Spreadsheet), and .csv files. For output, it generates .xlsx format which is compatible with all modern versions of Microsoft Excel, Google Sheets, LibreOffice, and other spreadsheet applications.
Can it handle multiple sheets?
Currently, the JSON to Excel conversion creates a single worksheet. When reading multi-sheet Excel files, it reads the first (active) worksheet by default. The sheet name can be customized when generating new Excel files. If you need multi-sheet support, consider converting each sheet separately.
How are data types preserved?
SheetJS automatically detects and preserves common data types including strings, numbers, booleans, and dates. When converting from JSON to Excel, numeric values are written as Excel numbers, booleans as Excel booleans, and strings as Excel strings. When converting from Excel to JSON, the same type detection is applied in reverse.
Is this JSON to Excel converter free?
Yes, it is completely free to use with no registration, sign-up, or limits. You can use it as many times as you need for personal, educational, or commercial projects without any restrictions.
Does it work offline?
Yes, once the page is loaded, all JSON and Excel conversion happens entirely in your browser using JavaScript and the SheetJS library. No server communication is needed, so you can use it even without an internet connection after the initial page load.
Can it handle large datasets?
Yes, this tool can handle large datasets efficiently. Since all processing is done client-side, the performance depends on your device's capabilities. For very large datasets (hundreds of thousands of rows), conversion may take a few extra moments, but the results are just as accurate.
Is my data secure?
Absolutely. All JSON and Excel conversion happens directly in your browser using JavaScript. Your data is never sent to any server, stored, or logged. This ensures complete privacy and security for sensitive information like customer data, financial records, and confidential datasets.