JSON to CSV Converter

Convert JSON data to CSV format for Excel, Google Sheets, and data analysis. Handles nested objects and arrays with proper flattening.

JSON Input(Array of objects)

CSV Output

JSON to CSV Converter

Why Convert JSON to CSV?

  • • Excel Compatibility: Open JSON data in Excel and spreadsheet apps
  • • Data Analysis: Use with analytics tools and BI platforms
  • • Reporting: Create reports and visualizations from JSON
  • • Database Import: Import JSON data into relational databases
  • • Data Sharing: Share data with non-technical team members
  • • Backup Format: CSV is widely supported and readable

Perfect For

  • • Data Analysts: Converting API data for analysis
  • • Business Users: Working with data in familiar spreadsheet format
  • • Developers: Exporting application data for reporting
  • • Researchers: Converting survey data for statistical analysis
  • • Marketers: Analyzing customer data and metrics
  • • Administrators: Creating data backups and exports

Conversion Features

Data Handling

  • • Nested Objects: Flattens nested objects using dot notation
  • • Arrays: Converts arrays to indexed columns or JSON strings
  • • Mixed Types: Handles strings, numbers, booleans, and null values
  • • Missing Fields: Fills empty cells for missing properties
  • • Special Characters: Properly escapes commas, quotes, and newlines

Output Options

  • • Custom Delimiters: Comma, semicolon, tab, or pipe separated
  • • Excel Compatible: Proper CSV formatting for Excel import
  • • Header Row: Automatic column headers from object keys
  • • UTF-8 Encoding: Supports international characters
  • • RFC 4180 Compliant: Follows CSV standard specifications

Conversion Examples

JSON Input

[
  {
    "name": "John",
    "age": 30,
    "address": {
      "city": "NYC",
      "state": "NY"
    },
    "skills": ["JS", "Python"]
  },
  {
    "name": "Jane",
    "age": 25,
    "address": {
      "city": "LA", 
      "state": "CA"
    },
    "skills": ["Python", "SQL"]
  }
]

CSV Output

name,age,address.city,address.state,skills
John,30,NYC,NY,"[""JS"",""Python""]"
Jane,25,LA,CA,"[""Python"",""SQL""]"

Best Practices

Input Guidelines

  • • Array Format: Provide JSON as array of objects for best results
  • • Consistent Structure: Objects should have similar properties
  • • Flat Objects: Minimize nesting for cleaner CSV output
  • • Valid JSON: Ensure proper JSON syntax before conversion
  • • Data Types: Keep consistent data types in columns

Output Optimization

  • • Choose Delimiter: Use semicolon for European Excel versions
  • • Handle Arrays: Consider if arrays should be JSON strings or separate columns
  • • Column Order: Most important fields will appear first
  • • Data Validation: Check CSV in target application
  • • Encoding: Ensure proper character encoding for international data

Use Cases & Applications

Business Applications

  • • Sales Reports: Export customer and transaction data
  • • User Analytics: Convert web analytics to spreadsheet format
  • • Inventory Management: Export product catalogs and stock data
  • • Financial Data: Convert accounting data for analysis
  • • Survey Results: Transform survey responses for reporting

Technical Applications

  • • API Data Export: Convert REST API responses to CSV
  • • Database Migration: Prepare JSON data for SQL import
  • • Log Analysis: Convert structured logs for analysis
  • • Configuration Export: Export app settings and configurations
  • • Data Backup: Create readable backups of JSON databases

Privacy & Security

Data Protection

  • • Client-Side Processing: All conversion happens in your browser
  • • No Server Upload: Your JSON data never leaves your device
  • • No Storage: No data is saved or logged anywhere
  • • Secure Connection: HTTPS encryption for website access
  • • Privacy First: No tracking or analytics on sensitive data

Technical Features

  • • Real-time Conversion: Instant transformation without delays
  • • Large File Support: Handles large JSON datasets efficiently
  • • Error Handling: Comprehensive JSON validation and error reporting
  • • Multiple Formats: Support for different CSV delimiter options
  • • Cross-Platform: Works on all devices and browsers

Frequently Asked Questions

What JSON format works best for CSV conversion?
JSON arrays of objects work best for CSV conversion. Each object becomes a row, and object properties become columns. For example: [{"name": "John", "age": 30}, {"name": "Jane", "age": 25}]. Single objects are automatically wrapped in an array.
How are nested objects handled in the conversion?
Nested objects are flattened using dot notation. For example, {"user": {"name": "John", "address": {"city": "NYC"}}} becomes columns like "user.name" and "user.address.city". This preserves the hierarchical structure in a flat CSV format.
What happens to arrays in JSON objects?
Arrays are converted to JSON strings within CSV cells. For example, ["JavaScript", "Python"] becomes a single CSV cell containing the JSON array. This preserves all array data while maintaining CSV compatibility.
Which delimiter should I choose for my CSV?
Use comma (,) for most applications and English Excel versions. Use semicolon (;) for European Excel versions that use comma as decimal separator. Tab is good for data analysis tools, and pipe (|) works when your data contains many commas.
Can I convert large JSON datasets?
Yes, our converter handles large JSON datasets efficiently since all processing happens in your browser. There are no file size limits, and your data stays completely private. Large datasets may take a moment to process depending on complexity.
Will the CSV file open correctly in Excel?
Yes, our CSV output follows RFC 4180 standards and is fully compatible with Excel, Google Sheets, and other spreadsheet applications. Special characters, commas, and quotes are properly escaped to ensure clean import.