How to Convert JSON to Table - Step by Step Guide
Transform complex nested JSON, hierarchical data structures, and deeply nested objects into readable HTML tables. Supports unlimited nesting depth, recursive JSON structures, JSON arrays, and tree visualization for API responses, database exports, and configuration files.
Input Your JSON Data
Alright, let's get your JSON data into the converter! Whether it's a complex nested JSON structure, API response with deep hierarchy, or database export with multiple levels, you've got three super easy options:
Example: Try This Simple JSON
Copy and paste this JSON example to see how it works:
{ "name": "Maeve Winters", "email": "[email protected]", "age": 28, "department": "Engineering", "active": true }
See Automatic Table Generation
Here's where things get cool! The moment you paste or type JSON, the tool springs into action with real-time parsing. No "convert" button to click, no waiting around - it just works! Instantly handles multi-level nested JSON, recursive data structures, and hierarchical relationships. Here's what happens behind the scenes:
Single Object → Key-Value Table
Input JSON (single object):
{ "name": "Maeve Winters", "email": "[email protected]", "age": 28, "department": "Engineering", "active": true }
Output table (key-value pairs):
| key | value |
|---|---|
| name | Maeve Winters |
| [email protected] | |
| age | 28 |
| department | Engineering |
| active | true |
Array of Objects → Column-Based Table
Input JSON (array of objects):
[ { "id": 1, "product": "Laptop", "price": 999.99, "category": "Electronics", "inStock": true }, { "id": 2, "product": "Mouse", "price": 29.99, "category": "Accessories", "inStock": false }, { "id": 3, "product": "Monitor", "price": 299.50, "category": "Electronics", "inStock": true }, { "id": 4, "product": "Keyboard", "price": 79.99, "category": "Accessories", "inStock": true } ]
Output table (column-based):
| id | product | price | category | inStock |
|---|---|---|---|---|
| 1 | Laptop | 999.99 | Electronics | true |
| 2 | Mouse | 29.99 | Accessories | false |
| 3 | Monitor | 299.50 | Electronics | true |
| 4 | Keyboard | 79.99 | Accessories | true |
Perfect for spreadsheet-like data! Arrays become columns automatically.
Customize and Filter Your Table
Now we're getting to the fun stuff! Once your hierarchical JSON table is generated from your nested data structures, you've got powerful data manipulation and visualization options:
Example: Nested Objects → Tables Within Tables
Try this nested JSON:
{ "company": "TechCorp Inc", "employees": [ { "id": 101, "name": "Sarah Wilson", "department": "Engineering", "contact": { "email": "[email protected]", "phone": "+1-555-0123", "address": { "street": "123 Main St", "city": "San Francisco", "state": "CA" } }, "projects": [ { "name": "Mobile App", "status": "active", "budget": 50000 }, { "name": "Website Redesign", "status": "completed", "budget": 25000 } ] } ], "totalEmployees": 150 }
Creates nested tables:
| key | value | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| company | TechCorp Inc | ||||||||||
| employees |
| ||||||||||
| totalEmployees | 150 |
* Nested objects and arrays appear as sub-tables within cells
Step 4: Edit Data Directly in the Table
This is where things get really handy! Want to tweak your hierarchical data structure but don't want to manually edit deeply nested JSON paths? Our inline editing feature lets you modify complex nested objects and arrays directly in the table view:
Example: Edit Mode in Action
When you click "Edit" and then click on a cell, you can change values directly. For example, change John's department from "Engineering" to "Marketing" and watch the JSON update automatically! 🪄
Step 5: Export and Share Your Results
Time to export your organized hierarchical data! Whether you're exporting complex nested JSON for analysis, sharing API response visualizations with your team, or archiving database dumps, here are your options:
Example: Real API Response
Perfect for complex API responses from REST APIs, GraphQL endpoints, or microservices like this e-commerce order data with nested arrays:
{ "orders": [ { "orderId": "ORD-2024-001", "customer": "Tech Solutions Inc", "amount": 1299.99, "status": "shipped", "items": ["Laptop", "Mouse", "Keyboard"] }, { "orderId": "ORD-2024-002", "customer": "Digital Marketing Co", "amount": 599.50, "status": "processing", "items": ["Monitor", "Webcam"] } ], "totalRevenue": 1899.49, "orderCount": 2 }
Frequently Asked Questions
How do I convert complex nested JSON to a table?
Simply paste your JSON data (including deeply nested structures, recursive objects, or multi-level arrays) into the input area or upload a JSON file. The tool instantly parses and converts it to a hierarchical table format with tree visualization. For nested JSON objects and arrays at any depth level, it automatically creates sub-tables within cells to maintain the complete data structure and parent-child relationships.
Can I download the table as Excel or CSV?
Yes! Click the "Export to Excel" button to download as .xlsx file, or use "Copy" to get the data for pasting into spreadsheets. The export preserves your table structure including nested data.
Can it handle large, deeply nested JSON files with unlimited nesting depth?
Yes! The tool efficiently handles large JSON files with complex hierarchical structures and unlimited nesting levels. Whether you have 5, 10, or 20+ levels of nested objects and arrays, our recursive parser processes them all. Use the search box to find specific data across all nesting levels, navigate through tree structures, or use the filter feature to flip rows and columns for better viewing. Very large datasets (100MB+) are processed in chunks with optimized memory management for smooth performance.
My JSON has errors - can this tool validate and fix malformed JSON?
Yes! The tool includes a robust JSON validator that shows exactly where syntax errors occur with line numbers and context. It can auto-fix common issues like missing commas, trailing commas, unquoted keys, and improperly escaped characters even in deeply nested structures. The validator works at all nesting levels. For more complex JSON repair needs (like fixing corrupted API responses or malformed database exports), try the JSON Fixer tool.
How do I visualize nested JSON data as a tree structure online?
Paste your nested JSON into the converter, and it automatically creates a hierarchical tree structure view. You can expand and collapse nested objects and arrays to navigate through multiple levels of data. The tree visualization makes it easy to understand complex parent-child relationships in deeply nested JSON structures.
Can I convert API response JSON to HTML table with nested objects?
Yes! The tool is designed specifically for API responses from REST APIs, GraphQL endpoints, and microservices. It handles nested objects, arrays, and complex hierarchical data structures automatically. Simply paste your API response, and it will create organized tables with sub-tables for nested data.
How to export complex nested JSON to Excel with preserved structure?
Click the "Export to Excel" button to download a .xlsx file that maintains all nested relationships. Nested objects and arrays are preserved as sub-tables within cells, keeping the hierarchical structure intact. This is perfect for sharing API data or database exports with team members who need to analyze nested data in Excel.
Can I edit nested JSON directly in table view and update the source?
Yes! Enable edit mode by clicking the "Edit" button, then click any cell to modify values even in deeply nested structures. The source JSON updates automatically in real-time with proper JSON path preservation. This makes it easy to fix data, update values, or remove unwanted information without manually editing complex JSON syntax.
How to search and filter across multiple levels of nested JSON?
Use the search box to find specific values across all nesting levels instantly. The search works through deeply nested objects, arrays, and hierarchical structures, highlighting matching results throughout the entire JSON tree. You can also use the filter feature to narrow down data and focus on specific sections of your nested structure.