ExamAdept

What is the purpose of the NumPy function numpy.concatenate((arr1, arr2), axis=0)?

A:

Joins the arrays along the columns.

B:

Joins the arrays along the rows.

C:

Creates a new array with the maximum values from both arrays.

D:

Computes the dot product of the arrays.

Answer: B

The numpy.concatenate() function joins the arrays along the specified axis, in this case, along the rows.

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Given a NumPy array arr = np.array([5, 2, 8, 1, 7]), what does np.argmax(arr) return?

A:

1

B:

2

C:

4

D:

0

Answer: B

The np.argmax() function returns the index of the maximum value in the array.

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What does the NumPy function numpy.diag([1, 2, 3]) do?

A:

Creates a 3x3 array with values 1, 2, and 3 on the main diagonal.

B:

Generates a diagonal matrix with values 1, 2, and 3.

C:

Reshapes an existing array to have dimensions 1x3.

D:

Computes the determinant of a 3x3 matrix.

Answer: B

The numpy.diag() function creates a diagonal matrix with the specified values on the main diagonal.

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How can you check if all elements in a NumPy array arr are non-zero?

A:

np.nonzero(arr)

B:

np.all(arr != 0)

C:

arr.all_nonzero()

D:

arr.is_nonzero()

Answer: B

The code np.all(arr != 0) checks if all elements in the array are non-zero.

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What does the NumPy function numpy.flip(arr, axis=1) do?

A:

Flips the array vertically.

B:

Flips the array horizontally.

C:

Flips the array along both axes.

D:

Flips the array along the specified axis.

Answer: B

The numpy.flip() function flips the array horizontally along the specified axis.

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Questions for: Arrays