JSON to Excel Converter

Add your .json file to the box above or paste the JSON into the text area, check the preview, and press Convert to Excel. You get a real .xlsx workbook with one row per record and one column per field, ready to open in Excel, Google Sheets, Numbers or LibreOffice.

This is a JSON to Excel converter free of sign-ups, watermarks and limits on how often you use it. It runs in your browser, so the data is not uploaded anywhere. You can add up to 30 files at once, each up to 50 MB, or paste JSON straight from your editor, your terminal or a browser tab.

If you do not work with JSON every day, a short tour helps. JSON is plain text made of two building blocks. An object is a set of named values inside curly braces, such as a customer with a name, an email and a city. An array is an ordered list inside square brackets, such as a list of customers.

The values themselves can be text in double quotes, numbers, true or false, null for nothing, or another object or array. That nesting is what makes JSON flexible, and also what makes it awkward in a spreadsheet, which only has rows and columns.

The mapping used here is simple. Each object in the list of records becomes a row. Each named value becomes a column, and the column name is the key. When a value is itself an object, its keys become extra columns with the parent name in front. When a value is a list, it goes into one cell.

JSON is the language of web apps and APIs, but it is hard to read when there are hundreds of records. Excel is where most people sort, filter, total and share data. Turning the JSON into a spreadsheet lets anyone on your team work with it, without writing code.

Common reasons are reviewing an export from a web app, checking the output of an API, sharing data with a colleague who does not use a code editor, building a quick report, or comparing two datasets side by side. In each case you want clean rows and columns, not brackets and quotes.

Nothing to install: no add-in, no Power Query steps, no script. Open the page in any modern browser on Windows, Mac, Linux or a Chromebook, add the file and download the workbook.

Even though it is a web page, the conversion itself happens on your own device. The page loads once, and after that the reading, the flattening and the writing of the Excel file all run in your browser. That makes it quick for small files and private for every file.

The simplest case for a JSON array to Excel conversion is a file that is just a list of objects, such as [ { ... }, { ... } ]. Every object in the list becomes one row, in the same order as in the file.

Many files wrap the list in an outer object. The tool looks inside and picks the largest list of objects it can find, up to a few levels deep, and the file line in the tool tells you where it came from, for example Records from data or Records from response.items. If a file holds a single object and no list, you get one row.

A list of plain values, such as a list of names or numbers, also works: each value becomes a row in a column called value.

Real JSON is rarely flat. A customer has an address, the address has a city, an order has a total with a currency. To handle this, the tool opens up every nested object and gives each inner field its own column, named with dots: address.city, address.zip, total.amount, total.currency.

This works at any depth, so a field three levels down becomes a column such as customer.address.city. You can then sort and filter by city in Excel like any other column, and the nested JSON to Excel table stays one clean row per record.

Lists inside a record are handled in one of two ways, which you choose under Nested data. Join with commas turns a list of simple values such as [ new, vip ] into one cell that reads new, vip. Keep as JSON text writes the list exactly as JSON, brackets and all. A list that contains objects is always kept as JSON text, so no information is lost.

The tool reads every record and collects every key that appears in any of them. Each key becomes a column, in the order it was first seen. A record that lacks a key simply gets an empty cell in that column, so records with different shapes still line up.

Values keep their type. Numbers in the JSON become real Excel numbers you can add up, and strings stay text, even when they look like numbers. That means IDs, postcodes and phone numbers written as strings keep their leading zeros. true and false become Excel TRUE and FALSE values, and null becomes an empty cell.

JSON has no date type, so dates arrive as strings such as 2026-10-14 or 2026-10-14T09:30:00Z, or as numbers that count seconds or milliseconds since 1970. Strings stay text in the workbook, exactly as written, so nothing is changed behind your back.

To turn them into real Excel dates, select the column and use Data, then Text to Columns, and choose a date format, or use a formula such as =DATEVALUE(LEFT(A2,10)) for the date part. For a timestamp in milliseconds, =A2/86400000+DATE(1970,1,1) gives the date and time; for seconds, divide by 86400 instead. Then apply a date format to the cells.

A JSON to XLSX conversion here makes a genuine Office Open XML workbook, the same format Excel saves by default. It is not a CSV file with an .xlsx name, so it keeps its formatting and opens without any import dialog.

The header row is bold with a light fill, frozen so it stays in view as you scroll, and has filters switched on, so you can sort and filter any column right away. Column widths are sized to fit the content, up to a sensible maximum, so the sheet is readable as soon as it opens.

Once the workbook is open, the usual Excel tools work straight away. Click the arrow in any header cell to sort or filter that column, for example to show only orders from one city or only users who signed up this month.

Because numbers are real numbers, formulas such as SUM, AVERAGE and COUNTIF work on them without any clean-up. Select the data and choose Insert, then PivotTable, to total sales by product or count records by status in a few clicks. Charts work the same way.

If you want banded rows and a table name, select any cell and press Ctrl + T to format the range as an Excel table. Conditional formatting is handy for spotting empty cells or values out of range, and Remove Duplicates on the Data tab finds repeated records.

The workbook is a standard .xlsx file, so it is not tied to Microsoft Excel. In Google Sheets, open Drive, upload the file and open it with Google Sheets, or choose File, then Import, inside an existing sheet. The header row, the numbers and the text cells come across as they are.

On a Mac or an iPhone, Apple Numbers opens the file directly; just double-click it or tap it in the Files app. LibreOffice Calc and OnlyOffice open it too, on Windows, Mac and Linux, which makes it a good choice when you share data with people who use different programs.

Each app shows the frozen header and the filters in its own way, but the data is the same everywhere: one row per record, one column per field, and numbers you can calculate with. If someone only needs to read the data, a PDF of the sheet is often easier to send than the workbook.

Sometimes you need both formats: Excel for people and CSV for another program or a database import. This page gives you JSON to CSV and Excel from the same conversion. After you press Convert to Excel, the Also as CSV button saves the table of the first file as a comma-separated CSV file with the same columns.

The CSV is saved as UTF-8 with a byte order mark, so Excel shows accents and other alphabets correctly when you open it. If you only ever need CSV, the dedicated JSON to CSV page is a little more direct.

An API JSON to Excel conversion is one of the most common jobs. Most APIs do not return a bare list. They return an object with the records inside a field such as data, results, items or records, next to fields like status, page or total.

You do not need to dig the list out by hand. Save the response as a .json file, or copy it from your browser, Postman or the terminal and paste it in. The tool finds the largest list of records inside and shows you its path, so you can see at a glance that the rows came from results and not from somewhere else.

The tool does not call the API for you and does not fetch URLs. You bring the JSON, it makes the spreadsheet. That keeps API keys and private data out of the conversion entirely. If the API splits results into pages, save each page as its own file and add them together; each page becomes a sheet.

Excel can also read JSON itself. In Excel for Windows and recent Excel for Mac, choose Data, then Get Data, then From File, then From JSON. Power Query opens the file, and you click To Table, then expand the record columns, and expand again for each nested level, before loading the result into a sheet.

That route is worth learning if you refresh the same feed every week, because Power Query can repeat the steps for you. For a one-off file, a quick look at an export, or a computer without Power Query, this page is faster: the nested fields are expanded for you, every key becomes a column, and the header row is ready to filter.

Ordinary .json files are the main input, whether they hold a list, an object, or a response with the records tucked inside. Pasted JSON works the same way.

JSON Lines files (.jsonl or .ndjson) have one JSON object per line, which is common for logs and data exports. If a file is not one single JSON document, the tool reads it line by line, so each line becomes a row.

GeoJSON files (.geojson) are read as well. In a feature collection the features list becomes the rows, with columns such as properties.name and geometry.type. Coordinates are written as JSON text in one cell.

For large JSON to Excel jobs, each file can be up to 50 MB, and you can add up to 30 files at a time. Because the work happens in your browser, the speed depends on your computer or phone; a few megabytes usually take a moment, and very large files take longer on older devices.

Excel itself has limits that no converter can get around: 1,048,576 rows and 16,384 columns per sheet, and 32,767 characters per cell. If your data has more rows or columns than that, the tool tells you before it starts instead of making a broken file. Very long text in a single cell is cut at the cell limit.

If a file is too big for one sheet, split it into smaller JSON files first and add them together; each one becomes its own sheet.

Add several JSON files at once and choose how they come out. One workbook, one sheet per file puts everything in a single .xlsx, with each sheet named after its file. One workbook per file gives you separate .xlsx files, downloaded together as a ZIP.

Sheet names follow Excel rules: up to 31 characters, without the characters Excel does not allow, and with a number added when two files have the same name. You can also add -excel to the end of each file name under More options.

A little preparation gives a tidier sheet. If a response holds several lists and you only want one of them, paste just that part, starting with the opening square bracket of the list. The tool always takes the largest list of objects, so trimming the input is the way to choose a smaller one.

If every record carries fields you never need, such as internal IDs or long descriptions, you can remove them in your editor first, or simply hide or delete those columns in Excel afterwards. Both give the same result; deleting columns in Excel is usually quicker.

Watch out for numbers that are sent as strings, such as prices written in quotes. They stay text on purpose, because the tool never guesses. In Excel, select the column and use the small warning icon to convert them to numbers if you want to add them up.

If the JSON is not valid, the file line in the tool says so instead of producing an empty sheet. Where your browser reports it, the message includes the character position of the problem, such as problem near character 1532, so you can jump straight to it in your editor.

The usual causes are a missing comma between records, a trailing comma after the last item, single quotes instead of double quotes, or comments, which JSON does not allow. A JSON Formatter makes the problem easy to find and fix, and then the file converts as normal.

This also works on an iPhone or Android phone, with no app to install. Open the page in Safari or Chrome, tap Select JSON files and pick the file from Files, Google Drive or your downloads, or paste JSON you copied.

Press Convert to Excel and save the workbook. It opens in the Excel app, Google Sheets or Numbers. Phones have less memory than computers, so for very large files a computer is the better choice.

Your JSON is not uploaded. Reading the file, finding the records, flattening nested data and writing the Excel file all happen in your browser, on your own device. That matters for customer lists, order exports, logs and anything else you would not want on someone else's server.

So JSON to Excel online free here does not mean trading your data for the service. There is no account, no watermark and no limit on how many times you convert.

When you add a file, the browser reads it as text. The tool first tries to read it as one JSON document; if that fails, it tries JSON Lines, one record per line. Then it looks for the list of records, flattens each record into columns with dot names, and collects every key into the header row.

The workbook is written directly as an .xlsx file in your browser, with the header styling, frozen row, filters and column widths set. Text encoding is detected automatically; if letters look wrong, you can choose UTF-8 or Windows (ANSI) under More options.

Check the preview before you convert. It shows the first rows and columns, so you can see at once whether the right list was found.

If a response has several lists and you want a smaller one, paste just that part. The tool always picks the largest list of objects.

Keep numbers as numbers in your JSON if you want to add them up in Excel, and as strings if they are codes that must keep their exact form.

Keep the original JSON. The workbook is a new file, so you can always convert again with other settings.

Once you have the workbook, you can sort, filter and chart the data in Excel. To share a read-only copy, Excel to PDF turns the sheet into a tidy PDF.

Working the other way round? CSV to Excel turns CSV files into the same kind of clean workbook, CSV to JSON goes back from rows to JSON, and PDF to Excel pulls tables out of PDF files. All of them are listed under Data Tools.