You have a 3D array arr with shape (2, 3, 4). How would you sum all elements along the second axis (axis=1) and what will be the shape of the result?

hard📝 Application Q8 of 15

NumPy - Aggregation Functions

You have a 3D array arr with shape (2, 3, 4). How would you sum all elements along the second axis (axis=1) and what will be the shape of the result?

AUse <code>np.sum(arr, axis=1)</code>, result shape will be (3, 4).

BUse <code>np.sum(arr, axis=1)</code>, result shape will be (2, 4).

CUse <code>np.sum(arr, axis=2)</code>, result shape will be (2, 3).

DUse <code>np.sum(arr, axis=0)</code>, result shape will be (3, 4).

Step-by-Step Solution

Solution:

Step 1: Understand axis=1 in 3D array
Axis 1 corresponds to the second dimension (size 3).
Step 2: Sum along axis=1
Summing along axis=1 collapses that dimension, resulting in shape (2, 4).
Final Answer:
Use np.sum(arr, axis=1), result shape will be (2, 4). -> Option B
Quick Check:
Sum axis=1 removes second dimension [OK]

Quick Trick: Sum axis removes that dimension from shape [OK]

Common Mistakes:

Confusing axis numbers
Expecting original shape
Using wrong axis for sum

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You have a 3D array arr with shape (2, 3, 4). How would you sum all elements along the second axis (axis=1) and what will be the shape of the result?

Step 1: Understand axis=1 in 3D array

Step 2: Sum along axis=1

Final Answer:

Quick Check:

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