Guided Notes

Indexing & Slicing

Accessing elements, negative indexes, 2-D indexing, slices with steps, and selecting rows and columns.

Indexing 1-D arrays

Slide 1 / 5

Access an element by its index in square brackets. Like Python lists, NumPy counts from 0:

arr = np.array([10, 20, 30, 40]) arr[0] β†’ 10 arr[2] + arr[3] β†’ 70

Negative indexes count from the end: arr[-1] is 40, the last element.

Indexes past the end raise an IndexError β€” an array of 4 elements has valid indexes 0–3 (or βˆ’1 to βˆ’4).

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