[Solved] Which of the following numpy operations correctly uses broadcasting? — Ans: np.array([1, 2, 3]) + 5 | NumPy

NumPy - Broadcasting

Which of the following numpy operations correctly uses broadcasting?

A<code>np.array([1, 2, 3]) + np.array([4, 5])</code>

B<code>np.array([[1], [2], [3]]) + np.array([4, 5, 6])</code>

C<code>np.array([1, 2, 3]) + 5</code>

D<code>np.array([1, 2, 3]) + np.array([[4], [5]])</code>

Step-by-Step Solution

Solution:

Step 1: Check each operation for broadcasting rules
np.array([1, 2, 3]) + np.array([4, 5]) fails because shapes (3,) and (2,) are incompatible. np.array([[1], [2], [3]]) + np.array([4, 5, 6]) works because shapes (3,1) and (3,) broadcast to (3,3). np.array([1, 2, 3]) + 5 works because scalar 5 broadcasts to (3,). np.array([1, 2, 3]) + np.array([[4], [5]]) fails due to incompatible shapes (3,) and (2,1).
Step 2: Identify correct broadcasting usage
Both np.array([[1], [2], [3]]) + np.array([4, 5, 6]) and np.array([1, 2, 3]) + 5 are valid broadcasting operations, but since only one option can be correct, and np.array([[1], [2], [3]]) + np.array([4, 5, 6]) is valid, the question needs correction to avoid multiple correct answers.
Final Answer:
np.array([1, 2, 3]) + 5 -> Option C
Quick Check:
Scalar + array always broadcasts [OK]

Quick Trick: Adding scalar to array always broadcasts correctly [OK]

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