ExamAdept

What is the purpose of the NumPy function numpy.flipud(arr)?

A:

Flip array vertically.

B:

Flip array horizontally.

C:

Rotate array 90 degrees clockwise.

D:

Transpose the array.

Answer: A

The numpy.flipud() function flips the array vertically.

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How can you calculate the element-wise square root of a NumPy array arr?

A:

np.sqrt(arr)

B:

arr ** 0.5

C:

np.square_root(arr)

D:

np.power(arr, 0.5)

Answer: A

The np.sqrt() function calculates the element-wise square root of the array.

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What does the NumPy function numpy.arange(1, 10, 2) generate?

A:

[1, 3, 5, 7, 9]

B:

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

C:

[2, 4, 6, 8, 10]

D:

[1, 4, 7]

Answer: A

The numpy.arange() function generates an array with evenly spaced values.

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How can you concatenate two NumPy arrays arr1 and arr2 vertically?

A:

np.concatenate((arr1, arr2), axis=0)

B:

np.vstack((arr1, arr2))

C:

np.vertical_concatenate((arr1, arr2))

D:

arr1 + arr2

Answer: B

The np.vstack() function vertically stacks arrays.

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Given a NumPy array arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]), how can you extract the diagonal elements?

A:

arr.diagonal()

B:

arr[1:3, 1:3]

C:

np.diag(arr)

D:

arr[::2, ::2]

Answer: C

The np.diag() function extracts the diagonal elements of the array.

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Questions for: Arrays