Read a JSON array as rows and columns
The table viewer turns record-shaped JSON into columns and rows for quick inspection. It helps spot missing fields and compare values across records.
When should you use it?
- Scan a list of API users or products.
- Find a record with a particular cell value.
- Decide whether the data can be exported to CSV or Excel.
Example: compare two records
Each object becomes a row. The source remains available in the formatted and tree views.
[{"name":"Alex","role":"Developer"},{"name":"Sam","role":"Designer"}]name | role
Alex | Developer
Sam | DesignerRecognize record-shaped JSON
A table works best when each object describes the same kind of entity: a customer, an event, or an order. Property names become columns and records become rows. Missing fields and nested values need more care than a flat spreadsheet suggests. A blank-looking cell does not prove that a property was present with an empty string; inspect the original record when that distinction matters.
Use a preview for inspection, then choose an export
The table viewer is designed for browsing and searching a bounded set of rows and columns. It is useful for spotting inconsistent names, unexpected types, or an outlying record. Use JSON to CSV for a portable text table, JSON to Excel for a workbook, or JSON to Markdown for documentation. Review nested objects before exporting, since a cell cannot express every relationship as clearly as the original tree.
Read JSON records like a table.
A row view helps you compare fields across records. Paste an array of objects, inspect the first 500 rows, and search within the bounded preview.
Paste JSON records
Use an array of objects, or open a local JSON file.
Inspect the table
Columns are gathered from the record keys; paging keeps the view responsive.
Return to source
Switch to formatted text or tree view whenever you need full nested detail.
How can I inspect an array of JSON objects as rows and columns?
Paste a record array into Table Viewer. The union of top-level property names becomes columns, so a field missing from one record remains visible as an empty position rather than shifting cells. Search and paging help scan the preview without changing the underlying JSON.
JSON: records with different fields
json[
{"id":1,"name":"Alex"},
{"id":2,"name":"Sam","role":"reviewer"}
]The table has id, name, and role columns. The first row has no role value; the second has reviewer.
Why does the table stop before the end of my file?
The table is a bounded preview of up to 500 rows and 50 columns. The JSON source remains available in other views. For a file containing all supported records, use JSON to CSV or JSON to Excel.
What should you check before using the result?
This is an inspection view, not a full spreadsheet export. Preview and cell text are bounded; use JSON to CSV or JSON to Excel to create a file.
Preview boundaries
The table shows at most 500 rows and 50 columns, with cell previews shortened after 240 characters. The source JSON is kept separately and is never truncated by the table preview.
When a table is useful
Use the table to compare record fields and spot missing values. Nested objects and arrays remain JSON text within cells. For a downloadable spreadsheet or Markdown table, use the dedicated conversion tools.
Technical reference: JSON syntax and interoperability · RFC 8259