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"Numpy Fundamentals Array"

Question 1

What does the dtype attribute of a numpy array represent?

The data type of the array.

The dimensions of the array.

The shape of the array.

The size of the array.

Question 2

What function is used to create a numpy array from a regular python list?

np.array()

np.ndarray()

np.arr()

np.fromlist()

Question 3

What is the primary data structure used in numpy?

List

Array

Dictionary

Tuple

Question 4

Which of the following statements is true about numpy arrays?

They can only store one data type.

They can store multiple data types.

They are limited to 1-dimensional data.

They are mutable.

Question 5

What is the result of multiplying two numpy arrays with the * operator?

Matrix multiplication.

Element-wise multiplication.

Scalar multiplication.

Dot product

Question 6

How can you find the maximum value in numpy array?

np.max()

np.maximum()

array.max()

All of the above

Question 7

Which of the following is a valid way to create a numpy array with all elements initialized to zero?

np.zeros(5, 5)

np.zeros(5)

np.zeros((5, 5))

np.zeros()

Question 8

How can you access elements in a 2-dimensional numpy array?

Using only one index.

Using two indices separated by a comma.

Using square brackets.

Using parentheses.

Question 9

What is the purpose of numpy's reshape() function?

To change the number of dimensions of an array.

To modify the data type of an array.

To add elements to an array.

To remove elements from an array.

Question 10

Which function is used to perform element-wise addition of two numpy arrays?

np.add()

np.plus()

np.sum()

np.concatenate()

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