Given a 2D NumPy array a with shape (5, 3) and a 1D array b = np.array([4, 5, 6]), which code correctly adds b to each row of a?

easy📝 Syntax Q3 of 15

NumPy - Broadcasting

Given a 2D NumPy array a with shape (5, 3) and a 1D array b = np.array([4, 5, 6]), which code correctly adds b to each row of a?

Aresult = a + b.T

Bresult = a + b.reshape(3, 1)

Cresult = a + b

Dresult = a + b.reshape(1, 5)

Step-by-Step Solution

Solution:

Step 1: Check shapes
a has shape (5, 3), and b has shape (3,). Adding them directly triggers broadcasting along rows.
Step 2: Understand broadcasting rules
Since b matches the second dimension of a, it broadcasts across rows automatically.
Step 3: Evaluate options
result = a + b adds b directly, which is correct. result = a + b.reshape(3, 1) reshapes b incorrectly. result = a + b.T uses transpose on 1D array (no effect). result = a + b.reshape(1, 5) reshapes b to (1,5), incompatible with a.
Final Answer:
result = a + b -> Option C
Quick Check:
1D array shape matches columns; direct addition works. [OK]

Quick Trick: Add 1D array matching columns directly to 2D array. [OK]

Common Mistakes:

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