Data Structures and Algorithms in Python | 40. Search trees - Part B by Abraham | Learn Smarter
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40. Search trees - Part B

The chapter discusses the intricacies of deletion in binary search trees, detailing various scenarios based on the structure of the node being deleted. It outlines the processes required when deleting leaf nodes, nodes with one child, and nodes with two children. Implementation aspects are covered, including the necessary functions to maintain tree integrity and the importance of balancing trees for efficient operations such as insertion, deletion, and search.

Sections

  • 40.1

    Deletion In A Binary Search Tree

    This section covers the process of deleting nodes in a binary search tree (BST), detailing different scenarios and the techniques used to maintain tree properties.

    Learning Practice

  • 40.1.1

    Deleting A Leaf Node

    This section covers the process of deleting a leaf node from a binary search tree, including scenarios of nodes with one or two children.

    Learning Practice

  • 40.1.2

    Deleting A Node With One Child

    This section discusses the key techniques for deleting a node with one child in a binary search tree.

    Learning Practice

  • 40.1.3

    Deleting A Node With Two Children

    This section discusses the complexities involved in deleting a node with two children in a binary search tree.

    Learning Practice

  • 40.1.4

    Handling Missing Values In Deletion

    This section discusses the complexities involved in deleting values from a tree structure, detailing the various scenarios that arise during deletion.

    Learning Practice

  • 40.2

    Time Complexity Of Deletion Operations

    This section discusses the complexities and methods involved in deleting nodes from a binary search tree.

    Learning Practice

  • 40.2.1

    Balanced Trees And Their Properties

    This section discusses deletion operations in balanced trees, outlining the steps and cases involved in maintaining tree structure.

    Learning Practice

  • 40.2.2

    Avl Trees As An Example

    This section focuses on deleting nodes in AVL trees, explaining the intricacies involved, and the procedures to maintain tree balance.

    Learning Practice

  • 40.3

    Implementation Of Deletion In Python

    This section discusses how to implement the delete operation in a binary search tree, covering various cases based on the node's children.

    Learning Practice

  • 40.3.1

    Tree Class And Node Structure

    This section discusses the operations involved in deleting nodes from a binary search tree, including handling cases of leaf, single-child, and two-child nodes.

    Learning Practice

  • 40.3.2

    Utility Functions

    This section discusses the complexities and processes associated with deleting nodes from binary search trees, specifically focusing on various scenarios such as leaf nodes, nodes with one child, and nodes with two children.

    Learning Practice

  • 40.4

    Demonstration Of Tree Operations

    This section covers the delete operation in binary search trees, explaining various scenarios and their implementations.

    Learning Practice

  • 40.4.1

    Inserting Values Into The Tree

    In this section, we discuss the complexities of deleting a node from a binary search tree, including various scenarios based on the node's structure.

    Learning Practice

  • 40.4.2

    Deleting Values From The Tree

    This section explains the algorithm and process of deleting values from a binary search tree, addressing various scenarios such as deleting leaf nodes, nodes with one child, and nodes with two children.

    Learning Practice

  • 40.5

    Challenges With Tree Balancing

    This section discusses the complexities of deleting nodes from a binary search tree, outlining various scenarios and their implications for tree structure.

    Learning Practice

  • 40.6

    Conclusion And Summary Of Tree Operations

    This section summarizes tree operations, focusing on the complexities of deletion and the significance of maintaining tree balance.

    Learning Practice

References

Chapter 40 part-B.pdf

Class Notes

Memorization

What we have learnt

  • Deletion in binary search t...
  • Nodes can be deleted by pro...
  • Maintaining balance in a bi...

Final Test

Revision Tests