You have a 3D numpy array arr = np.array([[[1,2],[3,4]], [[5,6],[7,8]]]). What is the shape of the result when you run np.sum(arr, axis=1)?

hard📝 Application Q15 of 15

NumPy - Aggregation Functions

You have a 3D numpy array arr = np.array([[[1,2],[3,4]], [[5,6],[7,8]]]). What is the shape of the result when you run np.sum(arr, axis=1)?

A(1, 2)

B(3, 2)

C(2, 4)

D(2, 2)

Step-by-Step Solution

Solution:

Step 1: Understand the shape of arr
arr has shape (2, 2, 2): 2 blocks, each with 2 rows and 2 columns.
Step 2: Summing along axis=1
axis=1 sums over the second dimension (rows), reducing it from 2 to 1, so shape changes from (2, 2, 2) to (2, 2).
Final Answer:
(2, 2) -> Option D
Quick Check:
Sum axis=1 reduces dimension 2 to 1 [OK]

Quick Trick: Sum along axis removes that dimension [OK]

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