JSON to Table

How to review and edit JSON in table view

1. 01

   Tutorial Step

   Step 1 – Load your JSON

   Paste or import valid JSON and the editor immediately turns raw text into rows, columns, or a key-value grid that is easier to read.

   • Paste raw JSON directly into the tool, or click Import to load it from a local file, a URL, or sample data.
   • After import, the editor detects the structure automatically and switches the view by node type: arrays become rows and columns, while objects become key-value pairs.
   • If your JSON is large, import the full payload first and then inspect it section by section from the tree instead of staring at the entire document at once.
   • If you hit a syntax problem, fix it first in the formatter or validator, then return to the table editor for a smoother workflow.
2. 02

   Tutorial Step

   Step 2 – Use the tree to find the right branch

   Once the data is loaded, use the hierarchy first so you can focus the correct branch before making changes.

   • Expand objects and arrays level by level in the sidebar so you can confirm the main structure, such as `users`, `items`, or `settings`.
   • Click any tree node and the main area will focus on that specific branch instead of showing the entire JSON document.
   • If every item inside an array has a similar schema, select the array node first; if you only need one record, drill further into that entry.
   • For deeply nested JSON, identify the business field you actually need before editing in the main table so you do not make broad changes at the root by mistake.
3. 03

   Tutorial Step

   Step 3 – Edit the table view

   Once the right node is open, you can edit cells directly instead of fixing commas and braces by hand.

   • Double-click any cell to update strings, numbers, booleans, and other simple values without manually handling commas, quotes, or indentation.
   • For objects and arrays, use the context menu to add, delete, or duplicate properties and rows when you need to clean up repeated data quickly.
   • When you are working with list data, combine sorting, filtering, and search to isolate the target records before you edit them.
   • Every change updates both the table view and the underlying JSON in real time; after important edits, jump back to the root and verify that the overall structure still makes sense.
4. 04

   Tutorial Step

   Step 4 – Export the final result

   Once you finish the local edits, validate the result and take the cleaned-up JSON back into your workflow.

   • Before exporting, switch back to the root node and make sure the full JSON is still intact, especially parent fields and array items.
   • If everything looks right, copy the final JSON to your clipboard and paste it into your API client, code editor, or documentation.
   • If you need a saved artifact, download the result as a JSON file so you can archive it, roll it back, or hand it off to another teammate.
   • If you still need formatting, validation, or conversion to CSV or Schema, move into the related tools and keep the workflow going.
   • If the next step is restructuring fields, rewriting nesting, or turning the current data into a different JSON shape, continue with the AI JSON Transform tool and let the AI assistant draft the transformation logic first.

This approach is faster and safer than editing raw JSON by hand when you want a readable table, quick checks, and local changes that stay under control.