Enhance Your Search Skills With Selection Sort Algorithm

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In this tutorial, you will learn how the selection sort algorithm. Also, you will find working examples of selection sort in Python.

Introduction to Selection Sort Algorithm

Selection sort is an algorithm that selects the smallest element from an unsorted list in each iteration and places that element at the beginning of the unsorted list.

How the Selection Sort Algorithm?

Set the first element as minimum.
Compare minimum with the second element. If the second element is smaller than minimum, assign the second element as minimum. Compare minimum with the third element. Again, if the third element is smaller, then assign minimum to the third element otherwise do nothing. The process goes on until the last element.
After each iteration, minimum is placed in the front of the unsorted list.
For each iteration, indexing starts from the first unsorted element. Steps 1 to 3 are repeated until all the elements are placed at their correct positions.

Selection Sort Algorithm


selectionSort(array, size)
  repeat (size - 1) times
  set the first unsorted element as the minimum
  for each of the unsorted elements
    if element < currentMinimum
      set element as new minimum
  swap minimum with first unsorted position
end selectionSort

selectionSort(array, size)

repeat (size - 1) times

set the first unsorted element as the minimum

for each of the unsorted elements

if element < currentMinimum

set element as new minimum

swap minimum with first unsorted position

end selectionSort

Python Examples


# Selection sort in Python

def selectionSort(array, size):
   
    for step in range(size):
        min_idx = step

        for i in range(step + 1, size):
         
            # to sort in descending order, change > to < in this line
            # select the minimum element in each loop
            if array[i] < array[min_idx]:
                min_idx = i
         
        # put min at the correct position
        (array[step], array[min_idx]) = (array[min_idx], array[step])

data = [-2, 45, 0, 11, -9]
size = len(data)
selectionSort(data, size)
print('Sorted Array in Ascending Order:')
print(data)

# Selection sort in Python

def selectionSort(array, size):

for step in range(size):

min_idx = step

for i in range(step + 1, size):

# to sort in descending order, change > to < in this line

# select the minimum element in each loop

if array[i] < array[min_idx]:

min_idx = i

# put min at the correct position

(array[step], array[min_idx]) = (array[min_idx], array[step])

data = [-2, 45, 0, 11, -9]

size = len(data)

selectionSort(data, size)

print('Sorted Array in Ascending Order:')

print(data)

Complexity

Cycle	Number of Comparisons
1st	(n-1)
2nd	(n-2)
3rd	(n-3)
…	…
last	1

Number of comparisons: (n – 1) + (n – 2) + (n – 3) + ….. + 1 = n(n – 1) / 2 nearly equals to n².
Complexity = O(n²)
Also, we can analyze the complexity by simply observing the number of loops. There are 2 loops so the complexity is n*n = n².

Time Complexities:

- Worst Case Complexity: O(n²) If we want to sort in ascending order and the array is in descending order then, the worst case occurs.
- Best Case Complexity: O(n²) It occurs when the array is already sorted.
- Average Case Complexity: O(n²) It occurs when the elements of the array are in jumbled order (neither ascending nor descending).

The time complexity of the selection sort is the same in all cases. At every step, you have to find the minimum element and put it in the right place. The minimum element is not known until the end of the array is not reached.

Space Complexity:

Space complexity is O(1) because an extra variable temp is used.

Selection Sort Applications

The selection sort is used when:

a small list is to be sorted
cost of swapping does not matter
checking of all the elements is compulsory
cost of writing to memory matters like in flash memory (number of writes/swaps is O(n) as compared to O(n²) of bubble sort)

The article was published on November 29, 2020 @ 4:25 PM