Given a numpy array data = np.array([5, 10, 15, 20, 25]), how can you use a boolean mask to select only values greater than 12 and less than 22?

hard📝 Application Q15 of 15

NumPy - Array Data Types

Given a numpy array data = np.array([5, 10, 15, 20, 25]), how can you use a boolean mask to select only values greater than 12 and less than 22?

Amask = (data > 12) & (data < 22); result = data[mask]

Bmask = data > 12 or data < 22; result = data[mask]

Cmask = data > 12 and data < 22; result = data[mask]

Dmask = (data > 12) | (data < 22); result = data[mask]

Step-by-Step Solution

Solution:

Step 1: Create correct boolean mask with logical AND
To select values greater than 12 and less than 22, use element-wise AND: (data > 12) & (data < 22).
Step 2: Apply mask to data array
Use the mask to index data: data[mask] returns values meeting both conditions.
Final Answer:
mask = (data > 12) & (data < 22); result = data[mask] -> Option A
Quick Check:
Use '&' for element-wise AND in numpy [OK]

Quick Trick: Use '&' for AND, '|' for OR in numpy boolean masks [OK]

Common Mistakes:

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