What does print(np.sort(a, axis=1).tolist()) print? NumPy Sorting, Searching and unique

Block 7, Sorting, Searching and unique, question 17 of the NumPy sample

import numpy as np
a = np.array([[3, 1], [2, 4]])
print(np.sort(a, axis=1).tolist())

What does this print?

A. [[1, 3], [2, 4]]
B. [[2, 1], [3, 4]]
C. [[3, 1], [4, 2]]
D. [[1, 2], [3, 4]]

Show the answer and why each option is right or wrong

Answer, A. [[1, 3], [2, 4]]

A. [[1, 3], [2, 4]]: Correct. axis=1 sorts each row independently across its columns, so 3, 1 becomes 1, 3 and 2, 4 stays 2, 4.
B. [[2, 1], [3, 4]]: Sorts along the columns instead of the rows, the result axis=0 would actually give.
C. [[3, 1], [4, 2]]: Sorts each row in descending order instead of the default ascending order.
D. [[1, 2], [3, 4]]: Assumes the whole array gets flattened, sorted, and reshaped back, ignoring the axis argument entirely.

axis=1 on a 2D array sorts independently within each row, rearranging only the values that share a row. The default axis for np.sort on a multi dimensional array is the last one, which for a 2D array is exactly this row wise behavior.

The answer above is what NumPy 2.4.4 printed when the snippet was run, not what someone expected it to do.

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