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Getting Started with Python

You're reading from   Getting Started with Python Understand key data structures and use Python in object-oriented programming

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Product type Course
Published in Feb 2019
Publisher Packt
ISBN-13 9781838551919
Length 722 pages
Edition 1st Edition
Languages
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Authors (3):
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Benjamin Baka Benjamin Baka
Author Profile Icon Benjamin Baka
Benjamin Baka
Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
Dusty Phillips Dusty Phillips
Author Profile Icon Dusty Phillips
Dusty Phillips
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Table of Contents (31) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. A Gentle Introduction to Python FREE CHAPTER 2. Built-in Data Types 3. Iterating and Making Decisions 4. Functions, the Building Blocks of Code 5. Files and Data Persistence 6. Principles of Algorithm Design 7. Lists and Pointer Structures 8. Stacks and Queues 9. Trees 10. Hashing and Symbol Tables 11. Graphs and Other Algorithms 12. Searching 13. Sorting 14. Selection Algorithms 15. Object-Oriented Design 16. Objects in Python 17. When Objects Are Alike 18. Expecting the Unexpected 19. When to Use Object-Oriented Programming 20. Python Object-Oriented Shortcuts 21. The Iterator Pattern 22. Python Design Patterns I 23. Python Design Patterns II 24. Testing Object-Oriented Programs 1. Other Books You May Enjoy Index

Selection algorithms


Selection algorithms fall under a class of algorithms that seek to answer the problem of finding the ith-smallest element in a list. When a list is sorted in ascending order, the first element in the list will be the smallest item in the list. The second element in the list will be the second-smallest element in the list. The last element in the list will be the last-smallest element in the list but that will also qualify as the largest element in the list.

In creating the heap data structure, we have come to the understanding that a call to the pop method will return the smallest element in the heap. The first element to pop off a min heap is the first-smallest element in the list. Similarly, the seventh element to be popped off the min heap will be the seventh-smallest element in the list. Therefore, to find the ith-smallest element in a list will require us to pop the heap i number of times. That is a very simple and efficient way of finding the ith-smallest element...

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