Java Program to Implement Bubble Sort algorithm
In this example, we will learn to execute bubble sort algorithm in Java.
Example: Java Program to Implement Bubble Sort Algorithm
// import the Class
import java.util.Arrays;
import java.util.Scanner;
class Main{
// create an object of scanner
// to take input from the user
Scanner input = new Scanner(System.in);
// method to perform bubble sort
void bubbleSort(int array[]){
int size = array.length;
// for ascending or descending sort
System.out.println("Choose Sorting Order:");
System.out.println("1 for Ascending n2 for Descending");
int sortOrder = input.nextInt();
// run loops two times
// first loop access each element of the array
for (int i = 0; i < size - 1; i++)
// second loop performs the comparison in each iteration
for (int j = 0; j < size - i - 1; j++)
// sort the array in ascending order
if (sortOrder == 1) {
// compares the adjacent element
if (array[j] > array[j + 1]) {
// swap if left element is greater than right
int temp = array[j];
array[j] = array[j + 1];
array[j + 1] = temp;
}
}
// sort the array in descending order
else {
// compares the adjacent element
if (array[j] < array[j + 1]) {
// swap if left element is smaller than right
int temp = array[j];
array[j] = array[j + 1];
array[j + 1] = temp;
}
}
}
// driver code
public static void main(String args[]){
// create an array
int[] data = { -2, 45, 0, 11, -9 };
// create an object of Main class
Main bs = new Main();
// call the method bubbleSort using object bs
// pass the array as the method argument
bs.bubbleSort(data);
System.out.println("Sorted Array in Ascending Order:");
// call toString() of Arrays class
// to convert data into the string
System.out.println(Arrays.toString(data));
}
}
Output 1
Choose Sorting Order: 1 for Ascending 2 for Descending 1 Sorted Array: [-9, -2, 0, 11, 45]
In this case, we have entered 1 as input. Hence, the program sort the array in ascending order.
Output 2
Choose Sorting Order: 1 for Ascending 2 for Descending 2 Sorted Array: [45, 11, 0, -2, -9]
In this case, we have entered 2 as input. Hence, the program sort the array in descending order.
Python Example for Beginners
Two Machine Learning Fields
There are two sides to machine learning:
- Practical Machine Learning:This is about querying databases, cleaning data, writing scripts to transform data and gluing algorithm and libraries together and writing custom code to squeeze reliable answers from data to satisfy difficult and ill defined questions. It’s the mess of reality.
- Theoretical Machine Learning: This is about math and abstraction and idealized scenarios and limits and beauty and informing what is possible. It is a whole lot neater and cleaner and removed from the mess of reality.
Data Science Resources: Data Science Recipes and Applied Machine Learning Recipes
Introduction to Applied Machine Learning & Data Science for Beginners, Business Analysts, Students, Researchers and Freelancers with Python & R Codes @ Western Australian Center for Applied Machine Learning & Data Science (WACAMLDS) !!!
Latest end-to-end Learn by Coding Recipes in Project-Based Learning:
Applied Statistics with R for Beginners and Business Professionals
Data Science and Machine Learning Projects in Python: Tabular Data Analytics
Data Science and Machine Learning Projects in R: Tabular Data Analytics
Python Machine Learning & Data Science Recipes: Learn by Coding
R Machine Learning & Data Science Recipes: Learn by Coding
Comparing Different Machine Learning Algorithms in Python for Classification (FREE)
Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.