#### 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
Other Books You May Enjoy
Index

# Selection sort algorithm

Another popular sorting algorithm is selection sort. The selection sort algorithm begins by finding the smallest element in the list and interchanges it with the data stored at the first position in the list. Thus, it sorts the sublist sorted up to the first element. This process is repeated for (n-1) times to sort n items.

Next, the second smallest element, which is the smallest element in the remaining list, is identified and interchanged with the second position in the list. This makes the initial two elements sorted. The process is repeated, and the smallest element remaining in the list is swapped with the element in the third index on the list. This means that the first three elements are now sorted.

Let’s look at an example to understand how the algorithm works. We’ll sort the following list of four elements {15, 12, 65, 10, 7}, as shown in Figure 11.14, along with their index positions using the selection sort algorithm:

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