#### 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.
Preface
Free Chapter
Python Data Types and Structures
Introduction to Algorithm Design
Algorithm Design Techniques and Strategies
Stacks and Queues
Trees
Heaps and Priority Queues
Hash Tables
Graphs and Algorithms
Searching
Sorting
Selection Algorithms
String Matching Algorithms
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Index

# Selection Algorithms

One interesting set of algorithms related to finding elements in an unordered list of items is selection algorithms. Given a list of elements, selection algorithms are used to find the `k`th smallest or largest element from the list. So given a list of data elements and a number (`k`), the aim is to find the `k`th smallest or largest element. The simplest case of selection algorithms is to find the minimum or maximum data element from the list. However, sometimes, we may need to find the `k`th smallest or largest element in the list. The simplest way is to first sort the list using any sorting algorithm, and then we can easily obtain the `k`th smallest (or largest) element. However, when the list is very large, then it is not efficient to sort the list to get the `k`th smallest or largest element. In that case, we can use different selection algorithms that can efficiently produce the `k`th smallest or largest element.

In this chapter, we will cover the following topics...