Tech

JSON to Excel: A Complete Guide to Converting JSON Data

Editorial Team 2 hours agoLast Updated: November 7, 2026

12 minutes read

JSON is a common format used by websites, apps, and APIs to store and share data. But raw JSON can be hard to read, especially when the file has a lot of information.

Converting JSON to Excel puts the data into simple rows and columns. This makes it easier to read, edit, sort, filter, and analyze. This guide explains what JSON to Excel is and the easiest ways to convert your data.

What Is JSON to Excel?

JSON to Excel means changing data from a JSON file into an Excel spreadsheet.

JSON stands for JavaScript Object Notation. It is a text format used by websites, servers, APIs, mobile apps, and other software to store and share data.

Excel works differently. It organizes information into rows, columns, tables, and worksheets. This format is usually easier for people to read and work with.

During conversion, JSON fields can become Excel columns. Each record can become a new row. For example, names, ages, countries, and IDs can appear in separate columns.

The converted file is usually saved as .xlsx. You can also convert JSON to .csv if you only need a simple table.

JSON to Excel is not one specific tool or website. It is simply the process of changing JSON data into a spreadsheet format.

Understanding JSON Data

Before converting a file, it helps to know how JSON stores information.

JSON mainly uses objects and arrays. It can store text, numbers, true or false values, empty values, objects, and lists.

A JSON object uses curly brackets { }. For example:

{
  "name": "Ali",
  "age": 25,
  "city": "Karachi"
}

Here, name, age, and city are fields. Each field has its own value.

A JSON array uses square brackets [ ]. It can hold several records.

[
  {
    "name": "Ali",
    "age": 25,
    "city": "Karachi"
  },
  {
    "name": "Ahmed",
    "age": 28,
    "city": "Lahore"
  }
]

After conversion, the Excel table could look like this:

Name	Age	City
Ali	25	Karachi
Ahmed	28	Lahore

Simple JSON data is usually easy to convert. More complex files may need extra steps.

What Is Nested JSON?

Nested JSON means that one object or list is stored inside another object.

For example:

{
  "name": "Ali",
  "contact": {
    "email": "ali@example.com",
    "city": "Karachi"
  }
}

Here, contact contains more information inside it.

A converter may create separate Excel columns such as contact.email and contact.city.

Turning nested JSON into simple rows and columns is often called flattening.

Nested arrays can be harder to convert. For example, one customer may have several phone numbers or orders. The converter may need to create extra rows, columns, or tables.

For deeply nested JSON, Excel Power Query or Python can give you more control.

Why Convert JSON to Excel?

JSON works well for software, but it is not always easy for people to read.

Excel makes the information easier to view and manage. You can sort records, search for information, filter columns, edit values, and make calculations.

You can also use Excel formulas, charts, PivotTables, and other tools to study the data.

For example, a business may receive order data from an API in JSON format. After converting it to Excel, the business can easily review products, customers, sales, and dates.

JSON to Excel conversion can be useful for:

API and software data
Business reports
Online store orders
Inventory records
Marketing and SEO reports
Financial information
Research and education
Employee records
Customer information
Website data

It is also useful when you need to share JSON information with someone who is more comfortable using spreadsheets.

How to Convert JSON to Excel Using an Online Converter

An online converter is one of the easiest ways to convert JSON to Excel.

You normally do not need to install software or write any code. The conversion happens through your web browser.

The basic steps are:

Open a JSON to Excel converter.
Upload your .json file or paste the JSON data.
Start the conversion.
Check the preview if the tool provides one.
Download the .xlsx file.

Some tools also support drag-and-drop uploads or importing JSON from a URL.

Other features may include JSON error checking, table previews, different output formats, and table styles.

Some online tools mentioned in our research include Minifier.org, json-csv.com, and Aspose.Cells. Their features and limits can change over time.

Online tools are useful for small and simple files. They can also help if you do not have Excel installed.

However, most online tools need an internet connection. Some may also have limits on file size.

Be careful when uploading private information. Do not upload passwords, customer details, financial records, or other sensitive data unless you trust the service and understand how it handles your files.

How to Convert JSON to Excel Using Microsoft Excel

Microsoft Excel can import JSON using Power Query, also known as Get & Transform.

This method gives you more control over the data. You can check, clean, and organize it before adding it to your worksheet.

The usual steps are:

Open Microsoft Excel.
Go to Data.
Click Get Data.
Choose From File > From JSON.
Select your JSON file.
The data will open in Power Query.
Convert the data into a table if needed.
Expand the records into columns.
Choose the columns you want.
Arrange or edit the data if needed.
Click Close & Load.

Your JSON data will then appear in the Excel worksheet.

Power Query is also helpful for nested JSON. You can expand objects and lists to show their information in separate columns.

You can remove unwanted fields, rename columns, move columns, and change data types.

Power Query also saves the steps you used to prepare the data. This can make it easier to refresh the data later.

Importing JSON from a Web Source

JSON can also come directly from websites or APIs.

Excel Power Query can connect to supported web sources. In some cases, you can go to Data > Get Data > From Web and enter the web address.

A public source may work directly. Other APIs may require an API key, login, or other settings.

After Excel receives the JSON data, you can use Power Query to turn it into rows and columns.

How to Convert JSON to Excel Using Python

Python is another way to convert JSON to Excel. It is mainly useful for developers and people who work with data often.

The pandas library can read JSON data and place it into a table called a DataFrame.

For simple JSON, you can use:

import pandas as pd

df = pd.read_json("data.json")
df.to_excel("output.xlsx", index=False)

This method works well when the JSON already has a simple structure.

Nested JSON may need to be flattened first. Pandas provides json_normalize() for this.

import json
import pandas as pd

with open("data.json", encoding="utf-8") as file:
    data = json.load(file)

df = pd.json_normalize(data)
df.to_excel("output.xlsx", index=False)

Complex JSON may need more code to organize objects and arrays correctly.

Pandas may also use an Excel-writing library such as openpyxl or XlsxWriter when creating an .xlsx file.

Python requires some coding knowledge. However, it gives you more control. You can clean the data, rename columns, remove unwanted fields, convert many files, and automate the process.

Online Converter vs. Excel vs. Python

The best method depends on your file and what you want to do with it.

Feature	Online Converter	Excel	Python
Easy to use	Very easy	Easy	Coding needed
Installation	Usually no	Excel needed	Python needed
Internet	Usually yes	No for local files	No for local files
Quick conversion	Very good	Good	Good after setup
Nested JSON	Depends on tool	Good	Very good
Data cleaning	Limited	Good	Very good
Automation	Limited	Possible	Very good
Privacy	Depends on tool	Good for local files	Good for local files
Best for	Quick tasks	Reports and spreadsheets	Complex or repeated work

An online converter is a good choice for a quick and simple task.

Excel is useful when you want to view, clean, and organize the information without coding.

Python is better for complex files, automation, and repeated conversions.

For private files, local tools such as Excel or Python can help you avoid uploading data to a third-party website.

JSON to Excel vs. JSON to CSV

JSON can also be converted to CSV instead of Excel.

CSV stands for Comma-Separated Values. It is a simple text format that stores information in rows and columns.

Feature	Excel (XLSX)	CSV
Rows and columns	Yes	Yes
Multiple worksheets	Yes	No
Formatting	Yes	No
Formulas	Yes	No built-in workbook formulas
Charts	Yes	No
Best for	Reports and analysis	Simple data

Excel is better when you need formatting, charts, formulas, or several worksheets.

CSV is useful when you only need simple rows and columns or want to move data between different programs.

Complex nested JSON may need to be flattened before it can be saved properly in either format.

Benefits of Converting JSON to Excel

JSON to Excel makes data easier to read. Instead of looking through raw JSON text, you can see the information in clear rows and columns.

Excel also makes it easy to sort and filter information. You can quickly find records by date, country, product, customer, or another field.

You can use formulas, charts, and PivotTables to study the data and create reports.

It also makes sharing easier. Developers may prefer JSON, while other team members may prefer Excel.

Tools such as Power Query and Python can also save time by converting data automatically instead of copying it by hand.

Limitations of JSON to Excel Conversion

JSON and Excel store data in different ways. Because of this, some files are harder to convert than others.

Nested JSON may contain many levels of objects and arrays. Excel mainly uses rows and columns, so complex data often needs to be flattened first.

Excel also has size limits. One worksheet can contain up to 1,048,576 rows and 16,384 columns.

Long numbers can also cause problems. Excel normally keeps up to 15 significant digits for numbers. Long IDs and reference numbers should often be stored as text.

Leading zeros can disappear too. For example, 001245 may become 1245.

Dates may also appear in the wrong format. Always check date columns after conversion.

JSON null values or missing fields may appear as empty cells.

For important data, check the finished Excel file against the original JSON file.

Is JSON to Excel Conversion Safe?

JSON to Excel conversion itself is a normal process. The main concern is how your data is handled.

Using Excel or Python locally can keep the file on your computer. This can be a better choice for private or business data.

Online converters need more care. Some services upload your file to their servers. Others may process some data inside your browser.

Check the website’s privacy policy before uploading sensitive information. Also check whether it explains how long uploaded files are stored.

Avoid uploading passwords, API keys, financial information, private customer details, or confidential business records to unknown websites.

Data from unknown sources can also contain values that spreadsheet software may treat as formulas. This is known as spreadsheet or CSV formula injection. Untrusted data should be checked before opening or sharing the final spreadsheet.

Always keep your original JSON file as a backup.

Tips for Better JSON to Excel Conversion

These simple steps can help you get a cleaner result:

Check your JSON first. Fix any errors before conversion.
Use a consistent structure. Similar records create cleaner columns.
Remove information you do not need. This keeps the spreadsheet simple.
Test a small file first. Check the result before converting a large dataset.
Check nested data. Make sure important information was not missed.
Review dates and numbers. Excel may change their format.
Keep long IDs as text. This can prevent missing or changed digits.
Check leading zeros. Some values may need text formatting.
Compare the output with the JSON. Check that the information is correct.
Keep the original file. It gives you a backup if something goes wrong.

Choose the conversion method based on your file. A small file may only need an online tool. Large or complex files may be easier to handle with Power Query or Python.

Common JSON to Excel Problems and Fixes

JSON File Will Not Import

The JSON file may have a formatting or syntax error. A missing comma, quote, bracket, or brace can stop the file from opening.

Check and validate the JSON first. Fix any errors and try again.

Everything Appears in One Column

The records may not have been expanded.

In Power Query, turn the data into a table and use the expand option to create separate columns.

Nested Information Is Missing

Nested objects and arrays may need to be expanded manually.

Use Power Query to expand them or use Python’s json_normalize() to flatten the data.

Some Columns Are Missing

Some JSON records may not contain the same fields. You may also have left out a field during conversion.

Check the original JSON and review the fields selected for the table.

Blank Cells Appear

Blank cells may mean the original JSON has missing fields or null values.

Check the original data before deciding that information was lost.

Dates Look Incorrect

Excel may read the date in a different format.

Change the column’s date type or format and check it against the original JSON.

Large Numbers Change

Excel may change very long numbers.

If a value is an ID or reference number, save it as text instead of a number.

Leading Zeros Disappear

Excel may change 00125 to 125.

Set the column to text if the zeros are important.

Conversion Is Very Slow

Large or deeply nested JSON files can take longer to process.

Remove unnecessary data, split the file into smaller parts, or use Python or another data tool for very large files.

JSONL Does Not Import Correctly

JSONL, or JSON Lines, usually stores one JSON value on each line. It is different from a normal JSON array.

Use a tool that supports JSONL or change the data into standard JSON before importing it.

Special Characters Look Wrong

The file may be using the wrong text encoding.

JSON commonly uses UTF-8. Check the file encoding if letters or symbols do not appear correctly.

Alternatives to JSON to Excel

Excel is not the only way to work with JSON data. The right option depends on what you need to do.

JSON to CSV

JSON to CSV is useful for simple data.

CSV files work with Excel, Google Sheets, databases, and many other programs. They are a good choice when you only need rows and columns.

However, CSV does not support multiple worksheets, normal Excel formatting, or charts.

Google Sheets

Google Sheets is an online spreadsheet tool.

It can be useful when several people need to view or edit the same data. JSON normally needs to be converted or imported using a script, tool, or integration before it becomes a normal table.

Python pandas

Pandas is useful for developers and data analysts.

It can read JSON, flatten nested information, clean data, select fields, combine files, and export the result to Excel or other formats.

It requires coding, but it gives users more control over the conversion.

Power BI

Power BI is mainly used for reports, dashboards, and data analysis.

It can be a better option when you want to study or visualize JSON data instead of simply creating an Excel file.

Databases

Databases can be better for very large datasets.

Instead of placing millions of records into a spreadsheet, you can store and search the information in a database. Excel or another reporting tool can then use the data you need.

This method is more technical but works better for some large projects.

JSON Viewers and Editors

You do not always need to convert JSON.

A JSON viewer can make the file easier to read by showing its objects and arrays in a clear structure.

This is useful when you only want to check or edit JSON instead of working with it as a spreadsheet.

Alternative Spreadsheet Programs

Other spreadsheet programs can open XLSX and CSV files.

They can be useful if you do not have Microsoft Excel. However, direct JSON support depends on the program and version, so check its current features first.

Bottom Line

JSON to Excel conversion makes JSON data easier to read, edit, filter, and analyze.

Online converters are useful for quick and simple tasks. Excel Power Query gives you more control without needing much coding. Python is useful for complex files, automation, and regular conversion work.

Always check your JSON before conversion. After converting it, review dates, numbers, IDs, missing values, and nested data to make sure everything is correct.

For private or sensitive information, using a trusted local tool is usually better than uploading the file to an unknown website.