How to Export Excel Data to JSON: Complete Guide

How to Export Excel Data to JSON: Complete Guide

JSON (JavaScript Object Notation) is the standard format for web APIs, databases, and modern applications.
Converting Excel data to JSON enables:

• API integrations: Send data to web services
• Database imports: Load data into NoSQL databases
• Web applications: Use Excel data in JavaScript apps
• Data exchange: Share structured data easily

This guide shows you multiple methods to export Excel data to JSON format.

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🚨 Why Export Excel to JSON?

Common Use Cases:

• API integration: Send Excel data to REST APIs
• Web development: Use Excel data in web apps
• Database import: Load into MongoDB, Firebase, etc.
• Data sharing: Exchange structured data
• Automation: Integrate with modern systems

JSON Format Example:

[
  {
    "name": "John Smith",
    "email": "john@email.com",
    "age": 30
  },
  {
    "name": "Jane Doe",
    "email": "jane@email.com",
    "age": 25
  }
]

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🛠 Method 1: Online Converters (Quick & Easy)

When to Use

• One-time conversion
• Small files (< 10MB)
• No technical skills needed

Popular Tools

• ConvertCSV.com: Excel to JSON converter
• Zamzar: File conversion service
• CloudConvert: Supports many formats

Steps

1. Upload Excel file
2. Select JSON output format
3. Click convert
4. Download JSON file

Pros:

• ✅ No installation needed
• ✅ User-friendly
• ✅ Quick results

Cons:

• ❌ File size limits
• ❌ Privacy concerns (uploads data)
• ❌ Limited customization

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🛠 Method 2: Excel Formulas (Basic)

Problem: Manual JSON Creation

Solution: Build JSON with Formulas

Sample Data:

Name	Email	Age
John	john@email.com	30
Jane	jane@email.com	25

JSON Formula:

="{" & CHAR(34) & "name" & CHAR(34) & ":" & CHAR(34) & A2 & CHAR(34) & "," & 
 CHAR(34) & "email" & CHAR(34) & ":" & CHAR(34) & B2 & CHAR(34) & "," & 
 CHAR(34) & "age" & CHAR(34) & ":" & C2 & "}"

Result:

{"name":"John","email":"john@email.com","age":30}

For Array:

="[" & TEXTJOIN(",", TRUE, JSONRows) & "]"

Limitations:

• Complex for large datasets
• Manual formatting
• Not ideal for nested structures

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🛠 Method 3: VBA Macro (Automated)

Problem: Need Automated Conversion

Solution: VBA Script

VBA Code:

Sub ExportToJSON()
    Dim ws As Worksheet
    Set ws = ActiveSheet
    
    Dim lastRow As Long
    lastRow = ws.Cells(ws.Rows.Count, 1).End(xlUp).Row
    
    Dim json As String
    json = "["
    
    Dim i As Long
    For i = 2 To lastRow
        json = json & "{"
        json = json & """name"":""" & ws.Cells(i, 1) & ""","
        json = json & """email"":""" & ws.Cells(i, 2) & ""","
        json = json & """age"":" & ws.Cells(i, 3)
        json = json & "}"
        
        If i < lastRow Then
            json = json & ","
        End If
    Next i
    
    json = json & "]"
    
    ' Save to file
    Dim filePath As String
    filePath = ThisWorkbook.Path & "\output.json"
    
    Open filePath For Output As #1
    Print #1, json
    Close #1
    
    MsgBox "JSON exported to " & filePath
End Sub

How to Use:

1. Press Alt+F11 to open VBA editor
2. Insert > Module
3. Paste code
4. Modify column references
5. Run macro (F5)

Pros:

• ✅ Automated
• ✅ Handles large datasets
• ✅ Customizable

Cons:

• ❌ Requires VBA knowledge
• ❌ Excel-specific

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🛠 Method 4: Python Script (Most Flexible)

Problem: Need Advanced Control

Solution: Python with pandas

Python Code:

import pandas as pd
import json

# Read Excel file
df = pd.read_excel('data.xlsx')

# Convert to JSON
json_data = df.to_json(orient='records', indent=2)

# Save to file
with open('output.json', 'w') as f:
    f.write(json_data)

print("JSON exported successfully!")

Installation:

pip install pandas openpyxl

Advanced Options:

# Custom JSON structure
json_data = df.to_json(
    orient='records',  # Array of objects
    indent=2,          # Pretty print
    date_format='iso'  # Date formatting
)

# Nested JSON
json_data = df.groupby('category').apply(
    lambda x: x.to_dict('records')
).to_json(indent=2)

Pros:

• ✅ Very flexible
• ✅ Handles complex structures
• ✅ Can process large files

Cons:

• ❌ Requires Python knowledge
• ❌ Need to install libraries

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🛠 Method 5: Power Query (Excel Built-in)

Problem: Need Regular Exports

Solution: Power Query Transformation

Steps:

1. Load Data to Power Query

   • Data > Get Data > From File > From Workbook
   • Select your Excel file

2. Transform Data

   • Apply any needed transformations
   • Clean and structure data

3. Export to JSON

   • Use M code to convert to JSON
   • Or use Power Automate for automation

M Code Example:

let
    Source = Excel.CurrentWorkbook(){[Name="Table1"]}[Content],
    ToJson = Json.FromValue(Source)
in
    ToJson

Pros:

• ✅ Built into Excel
• ✅ Can automate
• ✅ Handles transformations

Cons:

• ❌ Requires Power Query knowledge
• ❌ More complex setup

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🛠 Method 6: Node.js Script (For Developers)

Problem: Web Development Integration

Solution: Node.js with exceljs

Installation:

npm install exceljs

Code:

const ExcelJS = require('exceljs');
const fs = require('fs');

async function excelToJson() {
    const workbook = new ExcelJS.Workbook();
    await workbook.xlsx.readFile('data.xlsx');
    
    const worksheet = workbook.getWorksheet(1);
    const jsonData = [];
    
    worksheet.eachRow((row, rowNumber) => {
        if (rowNumber === 1) return; // Skip header
        
        const rowData = {};
        row.eachCell((cell, colNumber) => {
            const header = worksheet.getRow(1).getCell(colNumber).value;
            rowData[header] = cell.value;
        });
        jsonData.push(rowData);
    });
    
    fs.writeFileSync('output.json', JSON.stringify(jsonData, null, 2));
    console.log('JSON exported successfully!');
}

excelToJson();

Pros:

• ✅ Great for web development
• ✅ Handles large files
• ✅ Integrates with Node.js apps

Cons:

• ❌ Requires Node.js knowledge
• ❌ Need to install packages

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🤖 Advanced: AI-Powered Excel to JSON Conversion

For complex conversions, RowTidy can automatically:

1. Detect Data Structure

   • Identifies nested relationships
   • Suggests optimal JSON structure
   • Handles complex Excel layouts

2. Intelligent Conversion

   • Preserves data types
   • Handles dates and numbers correctly
   • Maintains relationships

3. Custom JSON Formats

   • Array of objects
   • Nested structures
   • Custom key names

4. Validation

   • Validates JSON syntax
   • Checks data integrity
   • Ensures proper formatting

Benefits:

• ✅ Handles complex structures automatically
• ✅ Preserves data types correctly
• ✅ Validates output JSON
• ✅ Saves time on manual conversion

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📊 JSON Format Options

Option 1: Array of Objects

[
  {"name": "John", "age": 30},
  {"name": "Jane", "age": 25}
]

Option 2: Object with Keys

{
  "users": [
    {"name": "John", "age": 30},
    {"name": "Jane", "age": 25}
  ]
}

Option 3: Nested Structure

[
  {
    "name": "John",
    "contact": {
      "email": "john@email.com",
      "phone": "555-1234"
    }
  }
]

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✅ Best Practices

1. Validate JSON

   • Use JSON validator tools
   • Check syntax before using
   • Test with sample data

2. Handle Data Types

   • Numbers as numbers (not strings)
   • Dates in ISO format
   • Booleans as true/false

3. Escape Special Characters

   • Handle quotes, newlines, etc.
   • Use proper escaping
   • Validate special cases

4. Optimize Structure

   • Choose appropriate format
   • Minimize file size
   • Consider nested vs flat

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🔗 Related Guides

1. Convert CSV to Excel Format - CSV conversion
2. Excel Data Export Best Practices - Export strategies
3. How to Prepare Data for APIs - API preparation
4. Complete Excel Data Cleaning Guide - Comprehensive guide
5. Excel Automation Techniques - Automation methods

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📌 Conclusion

Exporting Excel to JSON opens up many possibilities for integration and data sharing. The methods in this guide will help you:

• Convert Excel data to JSON format
• Choose the right method for your needs
• Handle complex data structures
• Validate and optimize JSON output

For quick conversions: Use online tools
For automation: Use VBA or Python
For complex structures: Use RowTidy or specialized tools

Remember: Choose the method that matches your technical skills and requirements. Start simple and upgrade as needed.

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✍️ Ready to convert Excel to JSON automatically?

👉 Try RowTidy today for intelligent Excel to JSON conversion with proper data type handling and validation. Get started with a free trial and see how AI-powered conversion can streamline your data exports.

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This guide is part of our comprehensive series on Excel data management. Check out our other tutorials on data conversion, data export, and API integration for complete data solutions.