JSON to Excel
Paste JSON from an API response, database export, webhook, or app report and get a structured XLSX file back. Happycapy turns objects into rows, keys into column headers, nested fields into readable columns, and arrays into the layout you request. Free to start.
How JSON becomes an Excel workbook
Paste API or export data, choose how nested fields should map, and download an XLSX.
Paste your JSON
Copy your JSON array or object from an API response, database export, or any file and paste it directly into the input field. No special formatting or preparation needed.
Describe your preferences
Specify optional instructions — such as which fields to include, how to label columns, or how to handle nested keys — so the output matches exactly what you need in the spreadsheet.
The AI agent structures your data
The agent parses your JSON, maps every key to a column header, flattens nested objects using dot notation, and arranges each array item as a numbered row in the spreadsheet.
Download your Excel file
Receive a clean, ready-to-use XLSX file you can open in Excel, Google Sheets, or any spreadsheet tool — sorted, labeled, and free of the manual reformatting that would otherwise take hours.
Who converts JSON to spreadsheets
Built for people moving semi-structured data from APIs, apps, and databases into Excel.
Developers & API builders
Quickly turn API responses or database JSON exports into spreadsheets for sharing with non-technical teammates, stakeholders, or clients who work in Excel rather than code.
Data analysts & business teams
Skip manual copy-paste reformatting when working with JSON-based data sources. Get a clean, pivot-ready Excel table in seconds so you can jump straight into analysis.
Operations & project managers
Convert JSON reports, inventory exports, or CRM data dumps into structured spreadsheets for tracking, reporting, or sharing — without needing a developer to write a conversion script.
JSON to Excel mapping tips
Control arrays, nested objects, headers, and data types before generating the spreadsheet.
Specify which fields to keep
If your JSON has many keys you don't need, list only the ones you want as columns. For example: 'Include only id, name, and email columns.' This keeps your Excel sheet focused and readable.
Give columns readable names
Tell the agent to rename cryptic keys into plain language. For instance: 'Rename usr_id to User ID and ts to Timestamp.' Column headers in the final spreadsheet will match exactly what you specify.
Control nesting depth
If your JSON has deeply nested objects, indicate how far to flatten. 'Flatten only one level deep' keeps the output manageable, while 'fully flatten all nested keys' exposes every value as its own column.
Request a specific row sort order
Add a sorting instruction such as 'Sort rows by date descending' or 'Order by total_amount from highest to lowest' so the spreadsheet arrives pre-sorted and ready to review.
Handle arrays within objects explicitly
If a field contains a nested array (e.g., a list of tags per record), specify what to do: 'Join array values as a comma-separated string in one cell' or 'Expand into multiple rows — one per tag.'
Flag missing or null values
Tell the agent how to represent nulls: 'Replace null values with N/A' or 'Leave null cells blank.' This prevents ambiguous empty cells that could skew formulas or filters later in Excel.
What to expect from JSON to Excel
Review output quality, follow-up checks, and download expectations for JSON to Excel.
Most valid JSON arrays and API responses convert cleanly into Excel when the desired shape is clear. Flat arrays become one row per object, nested fields become dot-notated columns, and repeated arrays can be joined, expanded, or split into separate sheets. Very large or inconsistent JSON works best when you first request a short column mapping. Best input: valid JSON and a desired spreadsheet shape, especially rules for nested objects, repeated arrays, column names, data types, and separate sheets.
Example: Before: [{"order_id":1001,"customer":{"name":"Ana","email":"ana@example.com"},"shipping":{"city":"Austin"},"line_items":[{"sku":"TEE-1","qty":2}],"total":79.5}]. After: an Excel workbook with an Orders sheet containing order_id, customer.name, customer.email, shipping.city, total, and either a joined line_items column or a separate Line Items sheet linked by order_id.
JSON mapping notes
Review this section when source details involve: Control arrays, nested objects, headers, and data types before generating the spreadsheet.
- Nested arrays need an explicit rule: join values in one cell, expand into multiple rows, or split into a separate worksheet. The best choice depends on the data.
- Extremely large JSON files or objects with many inconsistent keys can produce very wide spreadsheets that need grouping or cleanup before analysis.
- The tool converts structure and content, but formulas, pivot tables, conditional formatting, and data validation rules should be added after the XLSX is generated.
Frequently asked questions
What JSON structures does this tool handle best?
It works best with arrays of objects — the most common JSON export format. Each object in the array becomes one row, and every unique key across all objects becomes a column. Single objects and nested structures are also supported.
Can you show a JSON to Excel before-and-after example?
Yes. A JSON record like {"order_id":1001,"customer":{"email":"ana@example.com"},"total":79.5} becomes an Excel row with columns such as order_id, customer.email, and total. If the JSON contains repeated arrays like line_items, you can ask to join them in one cell, expand them into multiple rows, or place them on a separate sheet.
How are nested objects handled in the Excel output?
Nested objects are flattened using dot notation. For example, a field like 'address.city' becomes its own column header, keeping all data in a single, readable sheet rather than splitting across multiple tabs.
What happens if different objects in my array have different keys?
The tool creates a union of all keys found across every object as column headers. Rows that lack a particular key simply show an empty cell in that column, so no data is lost.
Is there a size limit on the JSON I can convert?
Very large JSON files — typically those over a few thousand rows or with deeply nested structures spanning 5+ levels — may produce slower results or require manual cleanup. Splitting large files before converting usually gives cleaner output.
Will the Excel output preserve number and date types, or convert everything to text?
Numeric values are typically preserved as numbers in the XLSX output. Dates in ISO 8601 format (e.g., '2024-03-15') are usually recognized and formatted correctly, though custom date strings may come through as text.
Can I convert JSON that I exported from a database, API, or tool like MongoDB or Postman?
Yes — JSON exports from REST APIs, MongoDB, Firebase, Postman, and similar sources are common use cases. As long as the data follows standard JSON syntax, the conversion process treats it the same way regardless of origin.
Should nested arrays become rows, columns, or separate sheets?
It depends on the data. Tags or categories often work well as comma-separated values in one cell. Order line items, events, logs, or repeated measurements usually work better as separate rows or a second sheet linked by an ID. State your preference in the prompt for a cleaner workbook.
Do I need to clean up my JSON before pasting it in?
Minor formatting issues — trailing commas, inconsistent spacing — are often handled gracefully, but the JSON must be structurally valid. Running it through a free JSON validator first is a good habit if you are unsure about the source data.
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