Learn Java by Example: Java Program to Find Transpose of a Matrix

Java Program to Find Transpose of a Matrix

In this program, you’ll learn to find and print the transpose of a given matrix in Java.


Transpose of a matrix is the process of swapping the rows to columns. For 2x3 matrix,

a11    a12    a13
a21    a22    a23

Transposed Matrix
a11    a21
a12    a22
a13    a23

Example: Program to Find Transpose of a Matrix

public class Transpose{

    public static void main(String[] args){
        int row = 2, column = 3;
        int[][] matrix = { {2, 3, 4}, {5, 6, 4} };

        // Display current matrix

        // Transpose the matrix
        int[][] transpose = new int[column][row];
        for(int i = 0; i < row; i++) {
            for (int j = 0; j < column; j++) {
                transpose[j][i] = matrix[i][j];

        // Display transposed matrix

    public static void display(int[][] matrix){
        System.out.println("The matrix is: ");
        for(int[] row : matrix) {
            for (int column : row) {
                System.out.print(column + "    ");


The matrix is:
2    3    4    
5    6    4    
The matrix is:
2    5    
3    6    
4    4    

In the above program, display() function is only used to print the contents of a matrix to the screen.

Here, the given matrix is of form 2x3, i.e. row = 2 and column = 3.

For the transposed matrix, we change the order of transposed to 3x2, i.e. row = 3 and column = 2. So, we have transpose = int[column][row]

The transpose of the matrix is calculated by simply swapping columns to rows:

transpose[j][i] = matrix[i][j];




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.