Excel to JSON Converter

What Is Excel to JSON Conversion

Converting Excel spreadsheets (XLS/XLSX) to JSON transforms tabular data into the structured format used by web APIs, databases, and modern applications. Excel remains the most common format for business data — financial reports, inventory lists, customer databases, and project plans — but developers need this data in JSON for integration with web services, NoSQL databases, and configuration systems.

This tool converts Excel files to JSON directly in your browser with no server uploads, supporting multiple sheets, data type preservation, and customizable output structures.

Output Format Options

Format	Structure	Best For
Array of objects	[{col1: val, col2: val}, ...]	API payloads, MongoDB imports
Array of arrays	[[val, val], [val, val], ...]	Raw data processing, matrix operations
Nested objects	{key: {col1: val, col2: val}}	Lookup tables, configuration data
Keyed by column	{col1: [vals], col2: [vals]}	Column-oriented analytics

Data Type Handling

Excel Type	JSON Mapping	Considerations
Text	String	Direct mapping
Number	Number	Preserve precision for financial data
Date	ISO 8601 string	Excel stores dates as serial numbers; convert to ISO format
Boolean	true/false	Excel TRUE/FALSE → JSON true/false
Empty cell	null or omitted	Decide whether to include null values or skip empty cells
Formula	Computed value	Convert the formula result, not the formula itself

Common Use Cases

• API data migration: Convert Excel-managed data into JSON for import into REST APIs, GraphQL endpoints, or NoSQL databases like MongoDB and CouchDB
• Configuration generation: Transform Excel-based configuration tables into JSON config files for applications and services
• Web application data: Convert spreadsheet data for use in client-side web applications, dashboards, and data visualizations
• ETL pipelines: Use as the first step in Extract-Transform-Load pipelines that start with Excel exports from business systems
• Test data preparation: Convert Excel test case definitions into JSON fixtures for automated testing frameworks

Best Practices

1. Clean data before converting — Remove empty rows, merged cells, and formatting-only content. Merged cells produce unpredictable results in JSON conversion.
2. Use the first row as headers — Ensure column headers are valid JSON key names: no spaces (use camelCase or snake_case), no special characters, and unique names.
3. Validate JSON output — After conversion, validate the JSON with a schema validator to ensure data types and structure match your target system's expectations.
4. Handle dates explicitly — Excel date serial numbers (like 45292) are meaningless in JSON. Convert to ISO 8601 strings (2024-01-15) or Unix timestamps based on your application's needs.
5. Consider file size — JSON is typically 2-3x larger than the equivalent Excel file because it includes repeated key names. For large datasets, consider streaming or pagination.