The arrangement of data in a preferred order is called sorting in the data structure. By sorting data, it is easier to search through it quickly and easily. The simplest example of sorting is a dictionary. Before the era of the Internet, when you wanted to look up a word in a dictionary, you would do so in alphabetical order. This made it easy.
Imagine the panic if you had to go through a big book with all the English words from the world in a jumbled order! It is the same panic an engineer will go through if their data is not sorted and structured.
So, in short, sorting makes our lives easier. Check out our data science courses to learn in-depth about data science algorithms.
In this post, we will take you through the different data structures & sorting algorithms. But first, let’s understand what a sorting algorithm is and sorting in data structure.
What is a Sorting Algorithm?
A sorting algorithm is just a series of orders or instructions. In this, an array is an input, on which the sorting algorithm performs operations to give out a sorted array.
Many children would have learned to sort in data structures in their computer science classes. It is introduced at an early stage to help interested children get an idea of deeper computer science topics – divide-and-conquer methods, binary trees, heaps, etc.
Here’s an example of what sorting does.
Let’s suppose you have an array of strings: [h,j,k,i,n,m,o,l]
Now, sorting would yield an output array in alphabetical order.
Let’s learn more about sorting in data structure.
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There are two different categories in sorting:
- Internal sorting: If the input data is such that it can be adjusted in the main memory at once, it is called internal sorting.
- External sorting: If the input data is such that it cannot be adjusted in the memory entirely at once, it needs to be stored in a hard disk, floppy disk, or any other storage device. This is called external sorting.
Types of Sorting in Data Structure
Here are a few of the most common types of sorting algorithms.
1. Merge Sort
This algorithm works on splitting an array into two halves of comparable sizes. Each half is then sorted and merged back together by using the merge () function.
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Here’s how the algorithm works:
MergeSort(arr, l, r)
If r > l
- Divide the array into two equal halves by locating the middle point:
middle m = (l+r)/2
- Use the mergeSort function to call for the first half:
Call mergeSort(arr, l, m)
- Call mergeSort for the second half:
Call mergeSort(arr, m+1, r)
- Use the merge () function to merge the two halves sorted in step 2 and 3:
Call merge(arr, l, m, r)
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Check out the image below to get a clear picture of how this works.
Python program for merge sort implementation
if len(a) >1:
mid = len(a)//2
A = a[:mid]
B = a[mid:]
i = j = k = 0
while i < len(A) and j < len(B):
if A[i] < B[j]:
a[k] = A[i]
a[k] = B[j]
while i < len(A):
a[k] = A[i]
while j < len(R):
a[k] = B[j]
for i in range(len(a)):
if __name__ == ‘__main__’:
a = [12, 11, 13, 5, 6, 7]
print(“Sorted array is: “, end=”\n”)
2. Selection Sort
In this, at first, the smallest element is sent to the first position.
Then, the next smallest element is searched in the remaining array and is placed at the second position. This goes on until the algorithm reaches the final element and places it in the right position.
Look at the picture below to understand it better.
Python program for selection sort implementation
X = [6, 25, 10, 28, 11]
for i in range(len(X)):
min_idx = i
for j in range(i+1, len(X)):
if X[min_idx] > X[j]:
min_idx = j
X[i], X[min_idx] = X[min_idx], X[i]
print (“The sorted array is”)
for i in range(len(X)):
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3. Bubble Sort
It is the easiest and simplest of all the sorting algorithms. It works on the principle of repeatedly swapping adjacent elements in case they are not in the right order.
In simpler terms, if the input is to be sorted in ascending order, the bubble sort will first compare the first two elements in the array. In case the second one is smaller than the first, it will swap the two, and move on to the next element, and so on.
637124 -> 367124 : Bubble sort compares 6 and 3 and swaps them because 3<6.
367124 -> 367124 : Since 6<7, no swapping
367124 -> 361724 : Swapped 7and 1, as 7>1
361724 -> 361274 : Swapped 2 and 7, as 2<7
361274 -> 361247 : Swapped 4 and 7, as 4<7
361247 -> 361247
361274 -> 316274
316274 -> 312674
312674 -> 312674
312674 -> 312647
312647 -> 132647
132647 -> 123647
123647 -> 123647
123647 -> 123467
123467 -> 123467
As you can see, we get the ascending order result after three passes.
Python program for bubble sort implementation
n = len(a)
for i in range(n):
for j in range(0, n-i-1):
if a[j] > a[j+1] :
a[j], a[j+1] = a[j+1], a[j]
a = [64, 34, 25, 12, 22, 11, 90]
print (“The sorted array is:”)
for i in range(len(a)):
print (“%d” %a[i]),
That wraps up sorting in data structure and the most common sorting algorithms. You can choose any of the different types of sorting algorithms. However, remember that some of these can be a little tedious to write the program for. But then, they might come in handy for quick results. On the other hand, if you want to sort large datasets, you must choose the bubble sort. Not only does it yield accurate results, but is also easy to implement. Then again, it is slower than the other types. I hope you liked the article about sorting in data structure.
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Have fun coding!
What are Heap Sort and Quick Sort?
Different sorting techniques are utilized for performing the sorting procedures as per the requirements. Usually, Quick Sort is used as it is faster, but one would use Heap Sort when memory usage is the concern.
Heap Sort is a comparison-based sorting algorithm completely based on the binary heap data structure. This is why heap sort can take advantage of the heap’s properties. In the quick sort algorithm, the Divide-and-Conquer approach is utilized. Here, the entire algorithm is divided into 3 steps. The first one is to pick an element that acts as the pivot element. Next, the elements to the left of the pivot element are smaller ones and to the right are the bigger ones in value. On every partition, the previous step is repeated to sort the entire array of elements.
Which is the easiest sorting algorithm?
If you are dealing with sorting algorithms, then you will have noticed that Bubble Sort is the simplest one among all the others. The basic idea behind this algorithm is to scan the entire array of elements and compare every adjacent element. Now, the swapping action occurs only when the elements are not sorted.
With Bubble Sort, you just have to compare the adjacent elements, and the array gets sorted. This is why it is considered to be the simplest sorting algorithm.
Which is the fastest sorting algorithm in data structures?
Quicksort is considered to be the fastest one among all the other sorting algorithms. The time complexity of Quicksort is O(n log n) in its best case, O(n log n) in its average case, and O(n^2) in its worst case. Quicksort is known to be the fastest sorting algorithm because of its best performance in all the average case inputs. The speed will depend a lot on the amount of data too. As per the comparison between all the sorting algorithms, Quicksort is the fastest because of its average case inputs.