LeetCode 274: H-Index | Python Solution | Sorting & Counting Approach
📝 In this video, I solve LeetCode's H-Index problem using sorting and counting techniques. The h-index measures a researcher's productivity and citation impact. #leetcode #sorting #arrays #pythonsolution
⏱️ **Time Complexity**: O(n log n) - dominated by the sorting operation
🗂️ **Space Complexity**: O(1) - constant extra space
Timestamps
00:00 - Understanding problem statement
00:46 - Using Brute force
01:49 - Brute Force - Big O Notation
02:16 - Using Sorting approach
04:13 - Sorting approach - Big O Notation
04:45 - Optimized solution - Using Counters
07:12 - Optimal solution - Big O Notation
07:53 - Python code walk-through
08:54 - Solution analysis - runtime + memory
🔑 **Key Concepts**:
Sorting algorithms
Binary search application
Understanding citation metrics
Array manipulation techniques
Counting sort optimization
💡 **Main Takeaways**:
How to approach problems requiring ranked metrics
Efficiently calculating bibliometric indices
Optimizing sorting-based solutions
Handling edge cases in citation counting
📚 **Related LeetCode Problems**:
LeetCode 275: H-Index II (Binary Search)
LeetCode 347: Top K Frequent Elements
LeetCode 451: Sort Characters By Frequency
LeetCode 692: Top K Frequent Words
👨💻 **Target Audience**: Software engineering candidates preparing for technical interviews, particularly those focused on algorithmic problem-solving with Python.
📋 **Prerequisites**: Basic understanding of arrays, sorting algorithms, and Python syntax.
Links
LeetCode problem: https://leetcode.com/problems/h-index/
Solution code: https://leetcode.com/problems/h-index...
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Additional Tips
Emphasize the definition of h-index, as it's not intuitive for many viewers
Discuss the O(n) counting sort solution as a follow-up optimization
Explain why sorting in descending order simplifies the solution logic