[Solved] Why does np.sum() with axis parameter return an array instead of a scalar? — Ans: Because summing along an axis collapses that axis but keeps others, resulting... | NumPy

NumPy - Aggregation Functions

Why does np.sum() with axis parameter return an array instead of a scalar?

ABecause axis parameter is ignored and output shape never changes.

BBecause np.sum always returns an array regardless of axis.

CBecause summing along an axis collapses that axis but keeps others, resulting in a lower-dimensional array.

DBecause np.sum cannot sum to a scalar.

Step-by-Step Solution

Solution:

Step 1: Understand axis summation effect
Summing along an axis removes that axis, but other axes remain.
Step 2: Result shape explanation
This results in an array with one less dimension, not a scalar unless all axes are summed.
Final Answer:
Because summing along an axis collapses that axis but keeps others, resulting in a lower-dimensional array. -> Option C
Quick Check:
Axis sum reduces dimension, returns array [OK]

Quick Trick: Sum along axis reduces dimension, returns array [OK]

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Why does np.sum() with axis parameter return an array instead of a scalar?