Quick Tip: Before diving into conversion methods, it's crucial to understand both formats' structures and their specific use cases. This knowledge will help you make better decisions during the conversion process.

Python Example with pandas

import pandas as pd
import xml.etree.ElementTree as ET

def xml_to_csv(xml_file, csv_file):
    # Parse XML
    tree = ET.parse(xml_file)
    root = tree.getroot()
    
    # Extract data
    data = []
    for item in root.findall('.//record'):
        row = {
            'name': item.find('name').text,
            'age': item.find('age').text,
            'email': item.find('email').text
        }
        data.append(row)
    
    # Convert to DataFrame and save as CSV
    df = pd.DataFrame(data)
    df.to_csv(csv_file, index=False)

# Usage
xml_to_csv('input.xml', 'output.csv')

JavaScript Example with xml2js

const xml2js = require('xml2js');
const fs = require('fs');

const convertXmlToCsv = async (xmlFile) => {
    try {
        // Read XML file
        const xmlData = fs.readFileSync(xmlFile, 'utf8');
        
        // Parse XML to JSON
        const parser = new xml2js.Parser({explicitArray: false});
        const result = await parser.parseStringPromise(xmlData);
        
        // Extract data and create CSV
        const records = result.root.record;
        const headers = 'name,age,email\n';
        const csvData = records.map(record => 
            `${record.name},${record.age},${record.email}`
        ).join('\n');
        
        // Write CSV file
        fs.writeFileSync('output.csv', headers + csvData);
        
        console.log('Conversion completed successfully!');
    } catch (error) {
        console.error('Error:', error);
    }
};

// Usage
convertXmlToCsv('input.xml');