Test: Arrays - 2 - Software Development MCQ

In Python, arrays can be created using the array module. This module provides a class called array that allows creating arrays of a specific data type.

Accessing an element by index in an array has a time complexity of O(1) since it directly accesses the memory location based on the index.

Arrays can be created using different modules in Python, including numpy, array, and collections.

One advantage of using arrays in Python is that they can have a dynamic size, meaning elements can be added or removed easily.

In Python, arrays are zero-indexed, which means the first element of an array has an index of 0.

The code my_array[2] accesses the element at index 2 in the array my_array, which is 3.

The code my_array[1][2] accesses the element at index (1, 2) in the 2D array my_array, which is 6.

The code my_array[3] accesses the element at index 3 in the numpy array my_array, which is 4.

The code my_array[2][1] accesses the element at index (2, 1) in the 2D numpy array my_array, which is 8.

The code my_array[2] = 10 modifies the element at index 2 in the array new_array, not affecting the original array my_array. Therefore, the value of my_array[2] remains 3.

To access all the elements of the first row in a 2D array matrix, we can use a loop and iterate over the indices of the row, printing each element.

The numpy library provides multiple methods to find the maximum element in a 2D array, including matrix.max(), np.amax(matrix), and np.max(matrix).

The numpy library provides multiple methods to obtain the transpose of a matrix, including np.transpose(matrix), matrix.transpose(), and matrix.T.

The np.vstack() function in numpy can be used to concatenate two arrays vertically.

To pass an array arr as an argument to a function my_function in Python, we can directly pass the array name arr as an argument. No special syntax is required.