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A heap is a specialized tree-based data structure that satisfies the heap property. It is a complete binary tree, meaning all levels are fully filled except possibly the last, which is filled from left to right. Heaps are commonly used to implement priority queues and for efficient sorting algorithms like heap sort.
Max Heap
In a Max Heap, the key at the root node is always greater than or equal to the keys of its children, and the same property must be recursively true for all sub-trees in that binary tree. This ensures that the maximum element is always at the root1.
Operations on Max Heap
Insertion: Add the new element at the end of the heap and then "bubble up" to maintain the heap property.
Deletion: Remove the root element, replace it with the last element, and then "bubble down" to maintain the heap property.
Heapify: Convert an unsorted array into a heap by repeatedly performing the "bubble down" operation.
Example Code for Max Heap in Python
class MaxHeap:def __init__(self): Introduction to Max-Heap – Data Structure and Algorithm Tutorials
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Discover the essentials of Max Heap data structures. Explore how Max Heaps work, their key properties, and learn how to perform operations like insertion, deletion, and heapify with step-by-step examples.
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