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Why does negative indexing in numpy arrays start at -1 instead of 0?

hard📝 Conceptual Q10 of 15
NumPy - Indexing and Slicing
Why does negative indexing in numpy arrays start at -1 instead of 0?
ABecause -1 represents the last element, making counting from the end intuitive
BBecause numpy arrays do not support zero-based indexing
CBecause negative indexes count elements twice
DBecause -1 is the first element in the array
Step-by-Step Solution
Solution:

  1. Step 1: Understand negative indexing logic

    Negative indexing starts at -1 to represent the last element, making it easy to count backwards.

  2. Step 2: Evaluate options

    Only Because -1 represents the last element, making counting from the end intuitive correctly explains the intuitive reason for starting at -1.

  3. Final Answer:

    Because -1 represents the last element, making counting from the end intuitive -> Option A

  4. Quick Check:

    Negative index start = -1 for last element [OK]
Quick Trick: Negative index -1 always means last element [OK]
Common Mistakes:
  • Thinking negative indexes start at 0
  • Believing numpy lacks zero-based indexing
  • Misunderstanding negative index meaning

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