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Convert JSON arrays into downloadable CSV tables for easy viewing and editing in Excel
Supports objects, arrays of objects, and arrays of primitive values. Nested objects are flattened as “parent.field,” while arrays remain as text within cells.
Paste your JSON and select Convert & Preview to view and download the table.
Overview
Understand what the tool solves, how it works, and the boundaries of its data.
JSON is a text format for structured values. In a JSON object, property names pair with values; an array is an ordered list. This converter turns an object array into rows and uses discovered property paths as columns. A single object becomes one row. Arrays of primitive values and a single primitive value use a “Value” column.
For example, an object with a nested address such as {"customer":{"name":"Ari","city":"Denver"}} produces columns named customer.name and customer.city. Nested objects are flattened into dotted paths; nested arrays stay as JSON text within a cell. The converter gathers columns from keys it encounters across the rows. The preview shows up to eight rows, while the downloaded file includes the converted rows.
Choose XLSX when you want a workbook with one worksheet named Data. Choose CSV when you need plain tabular text for another system. Both formats can be opened in Excel, but CSV does not carry workbook features such as multiple sheets or cell formatting. The download choice affects the file format, not the values inferred from your JSON.
The format references below define JSON and describe Excel's supported file types; the column layout comes from the input you provide.
Guide
Follow the workflow and verify inputs and outputs with practical examples.
Paste valid JSON: an array of records, a single object, an array of primitive values, or one primitive value. Property names and string values must follow JSON syntax, including double quotes.
Enter a file name and select XLSX or CSV. Use Load Example if you want to see a sample object structure.
Select Convert & Preview. Check detected row and column counts, then compare the headers and several cells with the source.
Download the file when the preview matches your intended table. The first eight rows are only a preview; the export contains all converted rows.
Example input: [{"Name":"Ari","Team":"Design"},{"Name":"Sam","Team":"Support"}] gives two data rows and the columns Name and Team. A nested object such as {"contact":{"city":"Denver"}} becomes the contact.city column.
Use cases
See how the tool fits into real work and everyday tasks.
An operations analyst can turn a consistently shaped order or signup array into rows, then compare record counts and key fields before filtering in a spreadsheet.
A developer can convert a short response sample to see flattened property paths and spot missing or newly named fields.
Q&A
Find concise answers to common questions and confusing cases.
Yes. One object becomes a single row, with its properties as columns.
No. Nested objects are flattened into dotted column names; arrays within a value remain JSON text in one cell.
The on-page table displays at most the first eight rows. The downloaded file contains all rows produced from the input.
Represent identifiers as quoted strings in the source JSON, then inspect how your spreadsheet imports that column. Spreadsheet software may otherwise interpret long digit strings as numbers.
Notes
Review scope, result limitations, and important precautions before use.
Parsing, preview, and file generation happen in your browser. Large JSON inputs can still consume substantial browser memory, and this page does not state a fixed maximum record count. Very long numbers may lose precision during numeric parsing; account codes, phone numbers, and IDs are usually better represented as quoted strings when their digits must be preserved exactly. The converter rearranges data but does not validate whether values are complete, correct, or unique. Keep the original JSON and spot-check important fields after export.
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