You have a 4x4 numpy array arr filled with numbers 1 to 16 in row-major order. Which code correctly changes the element in the last row and second column to 100?

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NumPy - Indexing and Slicing

You have a 4x4 numpy array arr filled with numbers 1 to 16 in row-major order. Which code correctly changes the element in the last row and second column to 100?

Aarr[3, -2] = 100

Barr[4, 2] = 100

Carr[-1, 2] = 100

Darr[3, 1] = 100

Step-by-Step Solution

Solution:

Step 1: Identify last row and second column indexes
For a 4x4 array, rows and columns are indexed 0 to 3. Last row is index 3, second column is index 1.
Step 2: Check each option
arr[3, 1] = 100 uses arr[3, 1] which is correct. arr[4, 2] = 100 uses invalid index 4. arr[-1, 2] = 100 uses column index 2 (third column), not second. arr[3, -2] = 100 uses negative index -2 for column which is the third column, not second.
Final Answer:
arr[3, 1] = 100 -> Option D
Quick Check:
Last row = 3, second column = 1 [OK]

Quick Trick: Use zero-based indexes: last row is size-1, second column is 1 [OK]

Common Mistakes:

Using out-of-range indexes like 4
Confusing negative indexes for columns
Mixing row and column positions

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You have a 4x4 numpy array arr filled with numbers 1 to 16 in row-major order. Which code correctly changes the element in the last row and second column to 100?

Step 1: Identify last row and second column indexes

Step 2: Check each option

Final Answer:

Quick Check:

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