[Solved] What is the output of the following code?import numpy as np arr = np.array([[3, 7, 2], [5, 1, 9]]) print(np.min(arr, axis=0)) | NumPy

NumPy - Aggregation Functions

What is the output of the following code?

import numpy as np
arr = np.array([[3, 7, 2], [5, 1, 9]])
print(np.min(arr, axis=0))

A[3 1 2]

B[3 7 2]

C[5 1 9]

D[1 2 3]

Step-by-Step Solution

Solution:

Step 1: Understand axis=0 in np.min()
Using axis=0 means finding the minimum value down each column.
Step 2: Calculate minimum per column
Column 1: min(3,5) = 3
Column 2: min(7,1) = 1
Column 3: min(2,9) = 2
Final Answer:
[3 1 2] -> Option A
Quick Check:
np.min(arr, axis=0) = [3 1 2] [OK]

Quick Trick: axis=0 finds min down columns, axis=1 across rows [OK]

Common Mistakes:

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