Zero-based indexing, negative indexing, and multi-dimensional matrix coordinate selection.
NumPy arrays use zero-based indexing. Multi-dimensional elements are accessed with clean comma-separated coordinates `arr[row, col]`.
Think of 2D indexing `arr[row, col]` like battleship coordinates: first pick the horizontal row tier, then pinpoint the vertical column slot.
NumPy uses `matrix[row, col]` instead of standard Python nested brackets `matrix[row][col]`. Comma syntax is faster and cleaner.
val = matrix[0, 1]val = matrix[1][2] # Slower Python double lookupval = matrix[1, 2]Using `matrix[row, col]` accesses C-level memory in a single pointer jump.
Solve the objective below using NumPy vectorized syntax
Given `arr = np.array([[5, 10], [15, 20]])`, access the element at row 1, column 0 (value 15) and print it.
15