Bits of .NET

🔄 Data Transformation = Clean Data

Raw data needs processing. JavaScript array methods transform, filter, and aggregate data into usable formats.

📝 Data Processing Patterns

// User Data
const users = [
    { id: 1, name: 'Alice', age: 25, city: 'NYC', active: true },
    { id: 2, name: 'Bob', age: 30, city: 'LA', active: false },
    { id: 3, name: 'Charlie', age: 35, city: 'NYC', active: true },
    { id: 4, name: 'Diana', age: 28, city: 'SF', active: true },
    { id: 5, name: 'Eve', age: 22, city: 'LA', active: false }
];

// 1. Filter Active Users
const activeUsers = users.filter(u => u.active);

// 2. Map to Names and Cities
const userLocations = users.map(u => ({ name: u.name, city: u.city }));

// 3. Group by City
const groupedByCity = users.reduce((acc, user) => {
    acc[user.city] = acc[user.city] || [];
    acc[user.city].push(user);
    return acc;
}, {});

// 4. Age Statistics
const ageStats = users.reduce((acc, user) => {
    acc.sum += user.age;
    acc.count++;
    return acc;
}, { sum: 0, count: 0 });

const averageAge = ageStats.sum / ageStats.count;

// 5. Get Unique Cities
const cities = [...new Set(users.map(u => u.city))];

// 6. Sort by Age
const sortedByAge = [...users].sort((a, b) => a.age - b.age);

// 7. Find Oldest User
const oldest = users.reduce((max, user) => 
    user.age > max.age ? user : max
);

🎯 Advanced Data Processing

// Data Pipeline
const pipeline = (data) => 
    data
        .filter(item => item.active)
        .map(item => ({
            ...item,
            ageGroup: item.age < 30 ? 'Young' : 'Senior'
        }))
        .sort((a, b) => a.age - b.age);

// Chunk Data
const chunk = (array, size) => 
    array.reduce((acc, _, i) => 
        i % size === 0 ? [...acc, array.slice(i, i + size)] : acc
    , []);

// Flatten Nested Arrays
const flatten = (arr) => arr.reduce((acc, val) => 
    acc.concat(Array.isArray(val) ? flatten(val) : val), []
);

// Deep Clone Objects
const deepClone = (obj) => 
    JSON.parse(JSON.stringify(obj));

// Merge Objects
const mergeObjects = (...objs) => 
    objs.reduce((acc, obj) => ({ ...acc, ...obj }), {});

// Performance Optimization
const processData = (data) => {
    // Use single-pass when possible
    let activeCount = 0;
    let totalAge = 0;
    
    for (const user of data) {
        if (user.active) {
            activeCount++;
            totalAge += user.age;
        }
    }
    
    return {
        activeCount,
        averageAge: totalAge / activeCount
    };
};

💡 Data Processing Tips

• Use immutable operations
• Consider performance for large datasets
• Use meaningful variable names
• Document complex transformations
• Test edge cases