Online JSON to Excel Converter

Paste three JSON records containing names, ages, and cities to turn them into a three-row table and download a CSV file that opens in Excel.

When to use this tool

The converter includes a JSON input area, a “Delimiter” setting, and buttons for “Convert,” “Load Demo,” “Download CSV,” and “Clear.” Use it to turn consistently structured JSON records into a two-dimensional table without copying data column by column.

Note that the tool generates a CSV file, not an XLSX workbook with worksheets, formulas, or formatting. CSV is a plain-text tabular format supported by Excel, WPS Spreadsheets, and most data analysis tools.

• Business operations: Convert exported customer, order, or registration records into a table for filtering and reporting.
• Learning and development: Turn JSON API responses into rows and columns to quickly check whether all expected fields are present.
• Content management: Export article titles, publication dates, view counts, and other records into a spreadsheet for editorial planning.

How to use the converter

1. Paste the content you want to convert into the JSON input area at the top of the page. For best results, use an array at the top level, with each array item representing one object record.
2. Review the “Delimiter” setting. The default usually works for standard English and other text. If your field values contain many commas, choose a delimiter supported by the software you will use to import the file.
3. Click “Convert.” The output area below will display the data as rows and columns: object keys become column headers, and each object becomes one row.
4. Check the headers, number of records, and text content. If the output is empty or misaligned, return to the input area and check the brackets, quotation marks, and commas.
5. Once the result looks correct, click “Download CSV,” save the file locally, and open it in Excel or WPS Spreadsheets.
6. Click “Clear” to start over. If you are unsure about the required input format, click “Load Demo” to view a sample structure.

Complete example

Suppose you need to organize an event registration list. Paste the following into the JSON input area:

[
  {"Name":"Liam Chen","Age":22,"City":"Seattle"},
  {"Name":"Sophia Wang","Age":28,"City":"Austin"},
  {"Name":"Ethan Lee","Age":31,"City":"Boston"}
]

Keep the default “Delimiter” setting and click “Convert.” The converter takes the object keys Name, Age, City as the three column headers, then reads the corresponding values from each object. The output should look similar to this:

Name,Age,City
Liam Chen,22,Seattle
Sophia Wang,28,Austin
Ethan Lee,31,Boston

The result contains one header row, three data rows, and three columns. After clicking “Download CSV,” open the file in Excel to filter registrants by “City” or add a notes column. If all the data appears in one column, use Excel’s text import settings and select the same delimiter configured on this page.

More input examples

Example 1: Null values. Enter [{"Product":"Desk lamp","Stock":12},{"Product":"Bookshelf","Stock":null}] and click “Convert.” The result will usually contain “Product” and “Stock” columns, with the Bookshelf stock cell left blank or shown as null. This means the source data does not provide a usable inventory value; it should not automatically be treated as zero.

Example 2: Inconsistent fields. Enter [{"Name":"Alex Kim","Phone":"2025550147"},{"Name":"Jordan Zhou","Email":"zhou@example.com"}]. The first record lacks an “Email” field, while the second lacks a “Phone” field. Depending on how the converter determines headers, the output may contain blank cells or omit a column. Before downloading, confirm that both “Phone” and “Email” appear as headers. If either is missing, add the same fields to every record before converting.

Edge case: Empty array. The input [] contains no objects or fields, so the converter has no headers or data rows to generate. An empty result is expected.

How to interpret the results

This tool primarily flattens structured records into rows and columns. It does not verify whether names, amounts, dates, or other values are accurate. A tidy-looking output does not guarantee that the source data is complete or free of duplicates.

Common mistakes and pitfalls

• Using plain text instead of valid JSON: Keys and string values generally require double quotation marks. Trailing commas, missing brackets, and unmatched braces can cause parsing errors.
• Expecting an XLSX workbook: “Download CSV” produces a CSV file without multiple worksheets, charts, formulas, colors, or merged cells.
• Ignoring inconsistent fields: Each object should ideally use the same keys, or the output may contain blank cells or missing columns.
• Converting deeply nested data directly: Nested arrays and objects may not automatically expand into separate columns. Flatten them before conversion.
• Not checking long numbers: ID numbers, bank account numbers, order IDs, and codes beginning with zero may be reformatted by Excel or displayed in scientific notation. Set those columns to Text when importing the CSV.

Important considerations

This converter works best with small to medium-sized arrays of consistently structured objects. It is not designed for deeply nested JSON, very large data files, or tasks that require formulas, formatting, images, or multiple worksheets. Conversion reliability depends on valid source JSON, consistent fields across records, and available browser memory. Larger datasets may slow down the page or cause it to stop responding.

CSV files are sensitive to character encoding and delimiters. If text appears corrupted in Excel, try importing the file through “Data → From Text/CSV” and select UTF-8. If columns are not separated correctly, choose the same character used in the tool’s “Delimiter” setting. Before processing government IDs, contact details, customer lists, access tokens, or confidential business data, review the page’s data-handling practices and your organization’s policies. Use trusted local software when necessary. Keep a copy of the original JSON and verify the record count, key fields, and special characters after downloading.

Frequently asked questions

Why is it called a JSON to Excel converter if the download button says “Download CSV”?
“Excel” means the downloaded file can be opened and edited in Microsoft Excel. The actual output format is CSV. If you need an XLSX file, open the CSV in Excel and use “Save As” to create an Excel workbook.

What format should I paste into the tool?
For best results, paste a JSON array containing multiple objects, such as [{"Name":"Alex"},{"Name":"Taylor"}]. Click “Load Demo” to view a supported example, then replace the sample fields and values with your own.

Why does nothing happen after I click “Convert”?
Common causes include missing double quotation marks, commas, or square brackets. The input may also be an empty array. Test with a shorter sample first, then check the JSON syntax section by section.

Can nested JSON be split into multiple worksheets automatically?
The tool provides JSON-to-CSV conversion and download only; it does not create multiple worksheets. For nested objects or arrays, flatten the properties you need into a single level before converting.

Why did a phone number or order ID change in Excel?
Spreadsheet software may automatically detect and reformat data types, so this is not necessarily a conversion error. During import, set the relevant column type to “Text” to preserve leading zeros and prevent scientific notation.

Paste a small JSON sample into the input area above, click “Convert,” verify the headers and row count, then download the CSV.