[Solved] Why does boolean indexing in numpy return a 1D array even when applied to a 2D array? — Ans: Because boolean indexing flattens the array and returns matching elements in 1D | NumPy

NumPy - Indexing and Slicing

Why does boolean indexing in numpy return a 1D array even when applied to a 2D array?

ABecause boolean indexing flattens the array and returns matching elements in 1D

BBecause numpy does not support boolean indexing on 2D arrays

CBecause the original array is converted to a list first

DBecause the condition must be 1D for boolean indexing

Step-by-Step Solution

Solution:

Step 1: Understand boolean indexing behavior on multi-dimensional arrays
Boolean indexing selects elements matching condition and returns them flattened.
Step 2: Check options for correct explanation
Because boolean indexing flattens the array and returns matching elements in 1D correctly states that boolean indexing flattens and returns matching elements as 1D.
Final Answer:
Because boolean indexing flattens the array and returns matching elements in 1D -> Option A
Quick Check:
Boolean indexing flattens multi-dimensional arrays [OK]

Quick Trick: Boolean indexing flattens arrays to 1D output [OK]

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Why does boolean indexing in numpy return a 1D array even when applied to a 2D array?