If you have a 2D array arr with shape (3, 4), what will be the shape of the result after applying np.mean(arr, axis=1)?

easy📝 Conceptual Q2 of 15

NumPy - Aggregation Functions

If you have a 2D array arr with shape (3, 4), what will be the shape of the result after applying np.mean(arr, axis=1)?

A(3,)

B(4,)

C()

D(3, 4)

Step-by-Step Solution

Solution:

Step 1: Identify the shape of the original array
The array has 3 rows and 4 columns, shape (3, 4).
Step 2: Understand what axis=1 means for aggregation
Axis=1 means aggregation happens across columns for each row, so each row reduces to a single value.
Final Answer:
The result shape is (3,) because each of the 3 rows becomes one mean value -> Option A
Quick Check:
axis=1 reduces columns, output shape = (3,) [OK]

Quick Trick: axis=1 aggregates across columns, output shape matches rows [OK]

Common Mistakes:

Master "Aggregation Functions" in NumPy

9 interactive learning modes - each teaches the same concept differently

Want More Practice?

15+ quiz questions · All difficulty levels · Free

More NumPy Quizzes