Data Structures and Algorithms in Python | 16. Selection Sort by Abraham | Learn Smarter
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16. Selection Sort

Sorting algorithms are crucial for efficient searching, particularly when using a binary search on sorted data. This chapter presents selection sort, demonstrating its step-by-step mechanism of repeatedly selecting the minimal element and placing it at the beginning of the unsorted portion. The selection sort algorithm is intuitive, although it can be inefficient for large datasets due to its O(n^2) time complexity.

Sections

  • 16.1

    Programming, Data Structures And Algorithms In Python

    This section introduces the concept of sorting algorithms, specifically focusing on the Selection Sort technique, its application, and its efficiency in organizing data.

    Learning Practice

  • 15.1.1

    Selection Sort

    Selection Sort is an intuitive and simple sorting algorithm that arranges elements in a list by repeatedly selecting the minimum value from the unsorted portion and moving it to the front.

    Learning Practice

  • 16.2

    Introduction To Sorting

    This section introduces sorting algorithms, specifically Selection Sort, highlighting its process and significance in efficient data handling.

    Learning Practice

  • 16.2.1

    Physical Task Of Sorting

    This section introduces the concept of sorting sequences, focusing on the physical task of organizing items based on their values, specifically using the Selection Sort algorithm.

    Learning Practice

  • 16.2.2

    Selection Sort Strategy

    Selection sort is an intuitive sorting algorithm where the smallest element is repeatedly selected and moved to the front of the list.

    Learning Practice

  • 16.3

    Execution Of Selection Sort

    Selection Sort is an intuitive sorting algorithm that iteratively selects the smallest element from an unsorted segment and moves it to its correct position.

    Learning Practice

  • 16.3.1

    First Steps Of Selection Sort

    This section introduces Selection Sort, a sorting technique that organizes elements by continuously selecting the minimum value and repositioning it.

    Learning Practice

  • 16.3.2

    Building Sorted Sequence

    The section introduces Selection Sort, a simple sorting algorithm that arranges elements in a sequence by repeatedly selecting the smallest element.

    Learning Practice

  • 16.4

    Modified Selection Sort Approach

    The Modified Selection Sort Approach efficiently sorts a list by repeatedly selecting the smallest element and moving it to the beginning of the unsorted section.

    Learning Practice

  • 16.4.1

    Swapping Elements

    The section explores the concept of selection sort, emphasizing how elements can be sorted by repeatedly selecting the minimum value and swapping it with the initial position of the unsorted elements.

    Learning Practice

  • 16.4.2

    Iterative Process

    The iterative process of sorting allows us to efficiently identify the arrangement of elements in a sequence and involves utilizing selection sort as a foundational algorithm.

    Learning Practice

  • 16.5

    Time Complexity Of Selection Sort

    This section discusses the concept of selection sort and its time complexity, exploring its operation and efficiency.

    Learning Practice

  • 16.5.1

    Calculating Time Complexity

    This section discusses how sorting algorithms, particularly Selection Sort, impact efficiency and highlights the calculation of time complexity.

    Learning Practice

  • 16.5.2

    Big O Notation

    Big O Notation provides a mathematical way to express the time complexity of algorithms, allowing us to evaluate their efficiency.

    Learning Practice

  • 16.5.3

    Practical Limits Of Selection Sort

    This section covers the selection sort algorithm, its implementation, and practical limitations, particularly its computational efficiency in sorting sequences.

    Learning Practice

  • 16.6

    Testing Selection Sort In Python

    This section explores the Selection Sort algorithm, its implementation in Python, and its efficiency for sorting sequences.

    Learning Practice

  • 16.6.1

    Running Python Code

    This section introduces the concept of sorting using the Selection Sort algorithm and explains its significance in searching and data management.

    Learning Practice

  • 16.6.2

    Performance Observations

    This section discusses the selection sort algorithm, highlighting its methodology and efficiency in sorting sequences.

    Learning Practice

References

chapter 16.pdf

Class Notes

Memorization

What we have learnt

  • Sorting improves search eff...
  • Selection sort operates by ...
  • The time complexity for sel...

Final Test

Revision Tests