Convert JSON to Excel: Complete Guide with Tools 2026

Why Convert JSON to Excel?

Excel is widely used for data analysis and sharing. Converting JSON to Excel makes data accessible to non-technical users.

Online Converters

Big JSON Viewer

Upload JSON file

Click "Export to Excel"

Download XLSX file

Other Tools

• ConvertCSV.com
• JSON-to-Excel.com
• Code Beautify

Python with Pandas

Simple Conversion

import pandas as pd
import json

# Load JSON
with open('data.json') as f:
    data = json.load(f)

# Convert to DataFrame
df = pd.DataFrame(data)

# Save to Excel
df.to_excel('output.xlsx', index=False)

Nested JSON

import pandas as pd

# Flatten nested JSON
df = pd.json_normalize(data, sep='_')
df.to_excel('output.xlsx', index=False)

Multiple Sheets

with pd.ExcelWriter('output.xlsx') as writer:
    df1.to_excel(writer, sheet_name='Users', index=False)
    df2.to_excel(writer, sheet_name='Orders', index=False)

JavaScript/Node.js

Using xlsx Library

const XLSX = require('xlsx');
const fs = require('fs');

// Read JSON
const data = JSON.parse(fs.readFileSync('data.json'));

// Create worksheet
const ws = XLSX.utils.json_to_sheet(data);

// Create workbook
const wb = XLSX.utils.book_new();
XLSX.utils.book_append_sheet(wb, ws, 'Sheet1');

// Write file
XLSX.writeFile(wb, 'output.xlsx');

Command Line

Using jq and csvkit

# JSON to CSV
jq -r '(.[0] | keys_unsorted) as $keys | $keys, map([.[ $keys[] ]])[] | @csv' data.json > output.csv

# CSV to Excel (requires csvkit)
csvformat output.csv > output.xlsx

Handling Complex JSON

Arrays of Objects (Best Format)

[
  {"name": "Alice", "age": 30},
  {"name": "Bob", "age": 25}
]

Nested Objects

# Flatten before converting
df = pd.json_normalize(data, sep='.')

Excel Formatting

Python with openpyxl

from openpyxl import load_workbook
from openpyxl.styles import Font

# Convert to Excel
df.to_excel('output.xlsx', index=False)

# Add formatting
wb = load_workbook('output.xlsx')
ws = wb.active

# Bold headers
for cell in ws[1]:
    cell.font = Font(bold=True)

wb.save('output.xlsx')

Best Practices

Flatten nested JSON before conversion

Handle missing values appropriately

Validate JSON structure first

Use meaningful column names

Consider file size limits

Common Issues

Mixed Data Types

# Convert all to strings if needed
df = df.astype(str)

Large Files

Use chunking for files over 100MB:

chunks = pd.read_json('large.json', lines=True, chunksize=10000)
for i, chunk in enumerate(chunks):
    chunk.to_excel(f'output_{i}.xlsx', index=False)

Conclusion

For quick conversions, use Big JSON Viewer. For automation, use Python pandas. Both methods produce professional Excel files!