[Solved] If you have a 2D array arr with shape (3, 4), what does np.sum(arr, axis=0) compute? — Ans: Sum of each column, resulting in an array of length 4. | NumPy

NumPy - Aggregation Functions

If you have a 2D array arr with shape (3, 4), what does np.sum(arr, axis=0) compute?

ASum of each row, resulting in an array of length 3.

BSum of each column, resulting in an array of length 4.

CSum of all elements, resulting in a scalar.

DSum of diagonal elements only.

Step-by-Step Solution

Solution:

Step 1: Identify axis=0 meaning
Axis 0 means summing down the rows, so we sum elements column-wise.
Step 2: Result shape
Since there are 4 columns, the result is an array of length 4 with sums of each column.
Final Answer:
Sum of each column, resulting in an array of length 4. -> Option B
Quick Check:
axis=0 sums columns = array length 4 [OK]

Quick Trick: axis=0 sums down rows (columns summed) [OK]

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If you have a 2D array arr with shape (3, 4), what does np.sum(arr, axis=0) compute?