Given a numpy array data = np.array([10, 15, 20, 25, 30]), how can you select elements greater than 12 and less than 28 using boolean indexing?

hard📝 Application Q15 of 15

NumPy - Indexing and Slicing

Given a numpy array data = np.array([10, 15, 20, 25, 30]), how can you select elements greater than 12 and less than 28 using boolean indexing?

Adata[data > 12 and data < 28]

Bdata[(data > 12) & (data < 28)]

Cdata[data > 12 | data < 28]

Ddata[(data > 12) or (data < 28)]

Step-by-Step Solution

Solution:

Step 1: Understand combining conditions with & and parentheses
In numpy, use & for element-wise AND and wrap each condition in parentheses.
Step 2: Check each option
data[(data > 12) & (data < 28)] correctly uses & (element-wise AND) with parentheses around each condition. Using Python keywords and/or cause errors because they don't work element-wise on arrays. Using | (bitwise OR) selects elements greater than 12 or less than 28, which is wrong here.
Final Answer:
data[(data > 12) & (data < 28)] -> Option B
Quick Check:
Use & with parentheses for AND conditions [OK]

Quick Trick: Use & with parentheses for multiple conditions [OK]

Common Mistakes:

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