Python 2D Arrays

By: Rajesh P.S.

A 2D array, also known as a two-dimensional array or a matrix, is a data structure that represents a collection of elements arranged in a grid of rows and columns. It is essentially an array of arrays, where each element of the outer array is itself an array of elements. Each element in a 2D array is identified by two indices: the row index and the column index.

2D arrays are commonly used in computer programming to represent tables of data, such as spreadsheets or game boards. For example, a chess board can be represented as an 8x8 matrix, where each element in the matrix represents a square on the board. Similarly, an image can be represented as a 2D array of pixels, where each pixel is represented by a set of values that determine its color and brightness.

The size of a 2D array is determined by the number of rows and columns it contains. For example, a 3x4 matrix contains 3 rows and 4 columns, for a total of 12 elements. The elements in a 2D array can be of any data type, such as integers, floating-point numbers, or strings.

Python 2D Array | Examples

In Python, a 2D array, also known as a matrix, is a collection of data arranged in a grid of rows and columns. A 2D array can be represented as a list of lists, where each list represents a row of the matrix. Each element in the matrix is accessed using its row and column indices.

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Following is an example of creating a 2D array in Python:

matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

In the above example, the matrix is a 3x3 grid with integers from 1 to 9. Each row of the matrix is represented as a list.

How to create a 2D array in Python?

Following is an example of how to create a 2D array in Python:

# create a 2D array of size 3x4 rows = 3 cols = 4 matrix = [[0 for j in range(cols)] for i in range(rows)] # fill the matrix with values for i in range(rows): for j in range(cols): matrix[i][j] = i + j # print the matrix for i in range(rows): for j in range(cols): print(matrix[i][j], end=' ') print()

In the above example, first create a 2D array of size 3x4 with all elements initialized to 0. Use a list comprehension to create the outer list of rows, and another list comprehension to create each inner list of columns. Next, fill the matrix with values using a nested for loop. For each row i and column j, set the value of matrix[i][j] to the sum of i and j. Finally, print the matrix using another nested for loop. Print each element of the matrix followed by a space, and then print a newline character after each row.

#Output: 0 1 2 3 1 2 3 4 2 3 4 5

This is a 3x4 matrix where each element is the sum of its row and column indices.

How to access elements in a 2D array in Python

In Python, you can access elements in a 2D array using their row and column indices. Following is an example of how to access elements in a 2D array:

Access a Single Element in 2d array

# create a 2D array of size 3x3 matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # access the element in the second row and third column print(matrix[1][2]) # output: 6

Access an Inner Array in 2d array

In a 2D array, accessing an inner array can be done by specifying the index of the outer array to get the inner array, and then specifying the index of the inner array to get the element you want.

For example, suppose you have the following 2D array. To access the inner array at index 1 (which contains [4, 5, 6]), you would use the following code:

matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] inner_arr = matrix[1] Now inner_arr contains [4, 5, 6]. matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] inner_arr = matrix[1] print(inner_arr) #Output: [4, 5, 6]

How to update elements in a 2D array in Python

In Python, you can update elements in a 2D array using their row and column indices. Following is an example of how to update elements in a 2D array:

Updating a Single Element in 2d array

# create a 2D array of size 3x3 matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # update the element in the second row and third column matrix[1][2] = 10 # print the updated matrix for row in matrix: print(row)

#Output: [1, 2, 3] [4, 5, 10] [7, 8, 9]

Updating an Inner Array in 2d array

To update an inner array in a 2D array in Python, you can use the indexing notation with the row index of the inner array and assign a new list to it.

# create a 2D array of size 3x3 matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # update the inner array at row 1 matrix[1] = [10, 11, 12] # print the updated array for row in matrix: print(row)

#Output: [1, 2, 3] [10, 11, 12] [7, 8, 9]

How to delete elements from a 2D array in Python

In Python, you can delete elements from a 2D array by using the del keyword to remove the entire row or column containing the element you want to delete. Following is an example of how to delete elements from a 2D array:

Deleting an Inner Array in 2d array

# create a 2D array of size 3x3 matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # delete the second row del matrix[1] # print the updated matrix for row in matrix: print(row)

#Output: [1, 2, 3] [7, 8, 9]

Deleting a Single Element in 2d array

To delete a single element in a 2D array in Python, you can use the del statement with the indexing notation with the row and column indices of the element you want to delete.

# create a 2D array of size 3x3 matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # delete an element at row 1 and column 2 del matrix[1][2] # print the updated array for row in matrix: print(row)

#Output: [1, 2, 3] [4, 5] [7, 8, 9]

How to iterate over a 2D array in Python

In Python, you can iterate over a 2D array using nested for loops. Following is an example of how to iterate over a 2D array:

# create a 2D array of size 3x3 matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # iterate over the matrix and print each element for row in matrix: for elem in row: print(elem)

#Output: 1 2 3 4 5 6 7 8 9

How to find the length of a 2D array in Python

You can find the length of a 2D array by using the len() function. The length of a 2D array is the number of rows in the array.

# create a 2D array of size 3x3 matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # find the length of the matrix length = len(matrix) # print the length of the matrix print("The length of the matrix is:", length)

#Output: The length of the matrix is: 3

How to transpose a 2D array in Python

You can transpose a 2D array using the built-in zip() function. The zip() function takes one or more sequences as input and returns an iterator of tuples where the first element in each tuple comes from the first sequence, the second element comes from the second sequence, and so on.

# create a 2D array of size 3x4 matrix = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]] # transpose the matrix using the zip function transposed_matrix = list(zip(*matrix)) # print the original and transposed matrices print("Original matrix:") for row in matrix: print(row) print("Transposed matrix:") for row in transposed_matrix: print(row)

#Output: Original matrix: [1, 2, 3, 4] [5, 6, 7, 8] [9, 10, 11, 12] Transposed matrix: (1, 5, 9) (2, 6, 10) (3, 7, 11) (4, 8, 12)

How to convert a 2D array into a 1D array in Python

You can convert a 2D array into a 1D array using the numpy library. The numpy library provides a flatten() function that can be used to convert a 2D array into a 1D array.

import numpy as np # create a 2D array of size 3x3 matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # convert the matrix to a 1D array using numpy arr = np.array(matrix).flatten() # print the original and flattened arrays print("Original array:") for row in matrix: print(row) print("Flattened array:") print(arr)

#Output: Original array: [1, 2, 3] [4, 5, 6] [7, 8, 9] Flattened array: [1 2 3 4 5 6 7 8 9]

How to concatenate two 2D arrays in Python

You can concatenate two 2D arrays using the numpy library's concatenate() function. This function allows us to concatenate two arrays along a specified axis.

Following is an example of how to concatenate two 2D arrays using the numpy library:

import numpy as np # create two 2D arrays of size 3x3 matrix1 = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] matrix2 = [[10, 11, 12], [13, 14, 15], [16, 17, 18]] # concatenate the matrices along the rows concatenated_matrix = np.concatenate((matrix1, matrix2), axis=0) # print the original and concatenated matrices print("Matrix 1:") for row in matrix1: print(row) print("Matrix 2:") for row in matrix2: print(row) print("Concatenated matrix:") for row in concatenated_matrix: print(row)

#Output: Matrix 1: [1, 2, 3] [4, 5, 6] [7, 8, 9] Matrix 2: [10, 11, 12] [13, 14, 15] [16, 17, 18] Concatenated matrix: [1 2 3] [4 5 6] [7 8 9] [10 11 12] [13 14 15] [16 17 18]

How to sort a 2D array in Python

You can sort a 2D array using the numpy library's sort() function. This function allows us to sort the elements of an array along a specified axis.

import numpy as np # create a 2D array of size 3x3 matrix = [[9, 8, 7], [6, 5, 4], [3, 2, 1]] # sort the matrix along the rows sorted_matrix = np.sort(matrix, axis=0) # print the original and sorted matrices print("Original matrix:") for row in matrix: print(row) print("Sorted matrix:") for row in sorted_matrix: print(row)

#Output: Original matrix: [9, 8, 7] [6, 5, 4] [3, 2, 1] Sorted matrix: [3 2 1] [6 5 4] [9 8 7]

This shows that you can sort a 2D array in Python using the numpy library's sort() function. Note that you need to specify the axis along which to sort the array. In this example, sorted the matrix along the rows, so the resulting matrix has the smallest elements in the first row and the largest elements in the last row.

How to search for an element in a 2D array in Python

To search for an element in a 2D array in Python, you can use a nested loop to iterate over each element in the array and check if the element matches the target value.

# create a 2D array of size 3x3 matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]] # define the target value target = 5 # search for the target value in the matrix found = False for i in range(len(matrix)): for j in range(len(matrix[i])): if matrix[i][j] == target: found = True break # print the result of the search if found: print("The target value", target, "was found in the matrix.") else: print("The target value", target, "was not found in the matrix.")

#Output: The target value 5 was found in the matrix.

How to compare two 2D arrays in Python

To compare two 2D arrays in Python, you can iterate over each element in both arrays and compare them.

# create two 2D arrays of size 2x2 array1 = [[1, 2], [3, 4]] array2 = [[1, 2], [3, 5]] # compare the two arrays equal = True for i in range(len(array1)): for j in range(len(array1[i])): if array1[i][j] != array2[i][j]: equal = False break # print the result of the comparison if equal: print("The two arrays are equal.") else: print("The two arrays are not equal.")

#Output: The two arrays are not equal.

How to perform arithmetic operations on two 2D arrays

Performing arithmetic operations on two 2D arrays in Python involves performing the operation on corresponding elements of both arrays. Following are some examples:

Add the two 2D arrays

# create two 2D arrays of size 2x2 array1 = [[1, 2], [3, 4]] array2 = [[5, 6], [7, 8]] # add the two arrays result = [[0, 0], [0, 0]] for i in range(len(array1)): for j in range(len(array1[i])): result[i][j] = array1[i][j] + array2[i][j] # print the result of the addition print("The result of the addition is:") for row in result: print(row)

#Output: The result of the addition is: [6, 8] [10, 12]

Subtract the two 2D arrays

# create two 2D arrays of size 2x2 array1 = [[1, 2], [3, 4]] array2 = [[5, 6], [7, 8]] # subtract the two arrays result = [[0, 0], [0, 0]] for i in range(len(array1)): for j in range(len(array1[i])): result[i][j] = array1[i][j] - array2[i][j] # print the result of the subtraction print("The result of the subtraction is:") for row in result: print(row)

#Output: The result of the subtraction is: [-4, -4] [-4, -4]

Multiply the two arrays

# create two 2D arrays of size 2x2 array1 = [[1, 2], [3, 4]] array2 = [[5, 6], [7, 8]] # multiply the two 2D arrays result = [[0, 0], [0, 0]] for i in range(len(array1)): for j in range(len(array1[i])): result[i][j] = array1[i][j] * array2[i][j] # print the result of the multiplication print("The result of the multiplication is:") for row in result: print(row)

#Output: The result of the multiplication is: [5, 12] [21, 32]

Divide the two 2D arrays

# create two 2D arrays of size 2x2 array1 = [[1, 2], [3, 4]] array2 = [[5, 6], [7, 8]] result = [[0, 0], [0, 0]] for i in range(len(array1)): for j in range(len(array1[i])): result[i][j] = array1[i][j] / array2[i][j] # print the result of the division print("The result of the division is:") for row in result: print(row)

#Output: The result of the division is: [0.2, 0.3333333333333333] [0.42857142857142855, 0.5]

Above examples show how you can perform subtraction, multiplication, and division on two 2D arrays in Python. The approach is similar to that used for addition: we use nested loops to iterate over each element in both arrays and perform the appropriate operation.

How to initialize a 2D array with default values in Python

To initialize a 2D array with default values in Python, you can use nested loops to create a new array and assign the default value to each element.

# initialize a 2D array with default value 0 rows = 3 cols = 4 my_array = [[0 for j in range(cols)] for i in range(rows)] # print the initialized array for row in my_array: print(row)

In the above example, create a 2D array with 3 rows and 4 columns and initialize each element to the default value 0 using nested loops. Then print the initialized array using another loop.

#Output: [0, 0, 0, 0] [0, 0, 0, 0] [0, 0, 0, 0]

Above example shows that you can initialize a 2D array with default values in Python by using nested loops to create a new array and assign the default value to each element.

You can replace the default value of 0 with any other value you want to initialize the array with.

Conclusion

A 2D array is a data structure that organizes elements in a grid-like fashion, with rows and columns forming a matrix. It is implemented using nested lists or arrays, providing a convenient way to store and manipulate data in a tabular format, facilitating various applications such as image processing, board games, and numerical computations.

Next > Linked Lists in Python

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