Given a numpy array arr = np.array([10, 15, 20, 25]), how can you create a boolean mask selecting elements greater than 12 and less than 24?

hard📝 Application Q8 of 15

NumPy - Array Operations

Given a numpy array arr = np.array([10, 15, 20, 25]), how can you create a boolean mask selecting elements greater than 12 and less than 24?

A(arr > 12) && (arr < 24)

Barr > 12 and arr < 24

C(arr > 12) & (arr < 24)

Dlogical_and(arr > 12, arr < 24)

Step-by-Step Solution

Solution:

Step 1: Understand element-wise logical operations
In numpy, '&' is used for element-wise AND, while 'and' or '&&' cause errors.
Step 2: Apply correct syntax
(arr > 12) & (arr < 24) uses '(arr > 12) & (arr < 24)', which is correct for boolean masking.
Final Answer:
(arr > 12) & (arr < 24) -> Option C
Quick Check:
Use '&' for element-wise AND in numpy [OK]

Quick Trick: Use '&' for element-wise AND, not 'and' or '&&' [OK]

Common Mistakes:

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