Easy. LeetCode 1399. Count Largest Group. Algorithm: Hash Map. Python3
🚀 Count Largest Group – Hash Map Frequency Explained!
Just tackled Count Largest Group on LeetCode! This problem challenges us to group every number from 1 to n by the sum of its digits and find how many groups tie for the largest size, and I solved it using a simple Hash Map for O(n) performance.
🔹 Key Strategy:
✅ Technique: Hash Map frequency counting
✅ Optimization: Single pass digit‐sum bucketing
✅ Learning: Bucketing + aggregation is a go-to for grouping problems
Story
Imagine you’re hosting a carnival and handing out numbered tickets from 1 to n. You decide to group visitors by the “magic number” on their ticket—the sum of its digits. So ticket 4 and ticket 13 (1 + 3) both land in the “4” group. After everyone’s in their buckets, you want to know which bucket is the largest and how many share that top spot—like finding the most popular ride. You simply compute each ticket’s digit sum, tally counts in a map, grab the max count, and finally count how many buckets hit that max. Fast, fair, and perfect for real-time carnival analytics! 🎟️🎡
📌 LeetCode Solution: https://leetcode.com/problems/count-l...
📌 GitHub Repository: https://github.com/RuslanTsykaliak/Le...
Understanding Hash Map grouping is crucial for tackling real-world aggregation challenges. Would you use this technique next time? Yes or No? 🤔
#Algorithms #DataStructures #LeetCode #Programming #Coding #codinginterview #dailycoding #Python
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