Data Science with Python Certification Data Science with Python NumPy Array Manipulation 2

Question 1

What does `np.broadcast_to(a, shape)` do?

Accepted Answer

Returns a read-only view of the array broadcast to the given shape

Answer

`np.broadcast_to` returns a read-only view of the array stretched to the target shape without copying data.

Question 2

Which function stacks 1-D arrays as rows into a 2-D array?

Accepted Answer

np.vstack

Answer

`np.vstack` stacks arrays vertically (row-wise), converting 1-D arrays into rows of a 2-D array.

Question 3

What is the result of `np.arange(10).reshape(2,5)[1, ::2]`?

Accepted Answer

array([5, 7, 9])

Answer

Row index 1 gives [5,6,7,8,9], and step-2 slicing starting at 0 yields elements at positions 0,2,4 → [5,7,9].

Question 4

Which attribute gives the total number of elements in a NumPy array?

Accepted Answer

array.size

Answer

`array.size` returns the total count of elements (product of all shape dimensions).

Question 5

What does `np.squeeze(a)` do?

Accepted Answer

Removes axes of length one from the array's shape

Answer

`np.squeeze` removes dimensions of size 1, reducing unnecessary singleton axes from the shape.

Data Science with Python Certification Practice Test