👀 Views: 76 💬 Answers: 1 📅 Created: 2025-09-07

react arrays data-merging javascript

I'm wondering if anyone has experience with I've looked through the documentation and I'm still confused about This might be a silly question, but Building an application that aggregates data from various APIs, I've run into some unexpected behavior when merging arrays from different sources. The goal is to unify the user data coming from two endpoints – one for basic info and the other for additional preferences. After fetching the data, I attempt to combine them into a single array of user objects. Here's a simplified example of what I'm working with: ```javascript const basicInfo = [ { id: 1, name: 'Alice' }, { id: 2, name: 'Bob' } ]; const preferences = [ { id: 1, likes: 'Cats' }, { id: 3, likes: 'Dogs' } ]; const combinedData = basicInfo.map(user => { const pref = preferences.find(p => p.id === user.id); return { ...user, preferences: pref ? pref.likes : null }; }); console.log(combinedData); ``` Currently, the merged `combinedData` results in an array that only includes Alice correctly, while Bob is showing up with `null` preferences. This is likely due to the missing ID in the `preferences` array. However, I want to ensure that `combinedData` represents all users, ideally defaulting missing preference data to an empty string or a specific message. I've tried using `reduce()` instead, which seems a bit more elegant: ```javascript const combinedData = basicInfo.reduce((acc, user) => { const pref = preferences.find(p => p.id === user.id); acc.push({ ...user, preferences: pref ? pref.likes : 'No preferences found' }); return acc; }, []); ``` Yet, the challenge persists. If a user exists in `basicInfo` but not in `preferences`, I would expect the output to still reflect that user, which is not happening. Would leveraging a more functional approach, such as using `flatMap()`, be beneficial here? Or should I consider a different strategy entirely, perhaps with a more robust merging function that accounts for missing entries? Also, I'm concerned about performance as this application is expected to scale up to hundreds of user records, and I want to avoid any bottlenecks in data processing. Any insights or best practices for optimizing this merging logic would be greatly appreciated. My development environment is Linux. Is there a better approach? My development environment is Linux. What am I doing wrong? What are your experiences with this?