Hash Tables

Master hash table usage for fast lookups, frequency counting, and deduplication.

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Showing: Python

Overview

Hash tables provide O(1) average-case lookup, insertion, and deletion. This section covers efficient use of hash tables for solving common interview problems.

Key Concepts

  • Hash function design
  • Collision resolution
  • Load factor and resizing
  • Hash sets vs hash maps
  • Frequency counting
  • Deduplication

Common Problems

Easy

  • Two Sum
  • Contains Duplicate
  • Valid Anagram
  • Intersection of Two Arrays

Medium

  • Group Anagrams
  • Top K Frequent Elements
  • Subarray Sum Equals K
  • Longest Consecutive Sequence

Hard

  • LRU Cache
  • All O`one Data Structure
  • Substring with Concatenation of All Words

Practice Tips

  1. Choose the right structure: Set for existence, map for counting
  2. Time-space trade-off: Hash tables trade space for time
  3. Key design: Consider what makes a good hash key
  4. Collision handling: Understand chaining and open addressing

Resources