Learn and practice the Hash Maps, Knowing What to Track, Top K Elements, and the Heaps patterns to solve coding interview problems.

Grokking Grind 75 in Python: Mastery through Coding Patterns

Efficient data management, information tracking, element identification, and value optimization are crucial to problem-solving, particularly for challenges that involve handling, analyzing, and extracting meaningful insights from data. This module teaches essential coding patterns for all such coding challenges. It covers Hash Maps for storing and retrieving data, Knowing What to Track for identifying and managing key information, Top K Elements for extracting significant data points, and Heaps for efficiently handling extreme values in datasets. These techniques are valuable for solving various data-centric challenges, optimizing algorithms, and data manipulation.

Heaps, Hashing and Tracking

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## Statement

Given an array, `nums`, having $n$ integers, return the majority element. An element will be considered a majority element if it occurs more than $⌊n / 2⌋$ times in the array.

> **Note:** It is safe to assume that the majority element always exists in the array.




**Constraints**
- $n ==$ `nums.length`
- $1\leq n\leq 5* 10^4$
- $−10^9 \leq$ `nums[i]` $\leq10^9$

Let's solve the Majority Element problem using the Knowing What To Track pattern.

Hash Maps

Knowing What to Track

Top K Elements

Heaps

Conclusion

Solution: Majority Element

Statement