Book Image

Hands-On Data Structures and Algorithms with Python - Third Edition

By : Dr. Basant Agarwal
Book Image

Hands-On Data Structures and Algorithms with Python - Third Edition

By: Dr. Basant Agarwal

Overview of this book

Choosing the right data structure is pivotal to optimizing the performance and scalability of applications. This new edition of Hands-On Data Structures and Algorithms with Python will expand your understanding of key structures, including stacks, queues, and lists, and also show you how to apply priority queues and heaps in applications. You’ll learn how to analyze and compare Python algorithms, and understand which algorithms should be used for a problem based on running time and computational complexity. You will also become confident organizing your code in a manageable, consistent, and scalable way, which will boost your productivity as a Python developer. By the end of this Python book, you’ll be able to manipulate the most important data structures and algorithms to more efficiently store, organize, and access data in your applications.
Table of Contents (17 chapters)
14
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15
Index

Amortized analysis

In the amortized analysis of an algorithm, we average the time required to execute a sequence of operations with all the operations of the algorithm. This is called amortized analysis. Amortized analysis is important when we are not interested in the time complexity of individual operations but we are interested in the average runtime of sequences of operations. In an algorithm, each operation requires a different amount of time to execute. Certain operations require significant amounts of time and resources while some operations are not costly at all. In amortized analysis, we analyze algorithms considering both the costly and less costly operations in order to analyze all the sequences of operations. So, an amortized analysis is the average performance of each operation in the worst case considering the cost of the complete sequence of all the operations. Amortized analysis is different from average-case analysis since the distribution of the input values is not...