In NumPy, array slicing uses the format [start:stop:step]. To select the last two rows, the slice is [-2:], which starts from the second-to-last element and goes to the end. Similarly, to select the last two columns, the slice is [-2:]. Combining these for a 2D array results in the syntax array[-2:, -2:], which correctly subsets the desired rows and columns.

A. array[-2:, :] selects the last two rows but includes all columns, not just the last two.

B. array[-1:, -1:] selects only the very last row and the very last column, not the last two of each.

D. array[:, -2:] selects all rows and only the last two columns, failing to subset the rows.

1. NumPy v1.26 Manual, "Indexing on ndarrays," Section: "Slicing and striding." The documentation explains that negative indices count from the end of the array and that a slice i:j includes elements from i up to (but not including) j. A blank j implies the rest of the array. (Source: Official Vendor Documentation)

2. VanderPlas, J. (2016). Python Data Science Handbook. O'Reilly Media. Chapter 2, Section: "The Basics of NumPy Arrays," Sub-section: "Array Slicing: Accessing Subarrays." This section details how to use comma-separated slices to access subarrays, e.g., x[rowslice, colslice]. (Source: Peer-reviewed academic publication)