JAVA Syllabus

Explain Jagged array in Java with an example?

In Java, a jagged array is a multi-dimensional array where each row can have a different number of columns. This means that a jagged array is an array of arrays, where each sub-array can have a different length.

To create a jagged array in Java, you can use the following syntax:

dataType[][] arrayName = new dataType[numRows][];
arrayName[0] = new dataType[numColumns1];
arrayName[1] = new dataType[numColumns2];
// ...
arrayName[numRows-1] = new dataType[numColumnsN];

Here, dataType can be any valid Java data type, such as int, double, String, etc. arrayName is the name of the array, numRows specifies the number of rows, and numColumns1 to numColumnsN specify the number of columns in each row.

For example, to create a jagged array of integers with 3 rows and different number of columns, you can use the following code:

int[][] myArray = new int[3][];
myArray[0] = new int[] {1, 2, 3};
myArray[1] = new int[] {4, 5};
myArray[2] = new int[] {6, 7, 8, 9};

This creates a jagged array with 3 rows, where the first row has 3 columns, the second row has 2 columns, and the third row has 4 columns.

To access an element in a jagged array, you can use the index of the row and column. For example, to access the element in the second row and first column of myArray, you can use the following code:

int element = myArray[1][0];

This will retrieve the value of the element in the second row and first column, which is the element at index [1][0] of the array.

You can also loop through a jagged array using nested loops. For example, to print all the elements of myArray, you can use the following code:

for (int i = 0; i < myArray.length; i++) {
    for (int j = 0; j < myArray[i].length; j++) {
        System.out.print(myArray[i][j] + " ");

This will print each element of the array, separated by a space, with each row on a new line.

Overall, jagged arrays in Java are a useful way to represent data structures where the number of columns varies between rows, and they are commonly used in applications such as data analysis, machine learning, and natural language processing.

25/03/2023, 6:01 am Read : 124 times