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Why does NumPy return views instead of copies when slicing arrays?

hard📝 Conceptual Q10 of 15
NumPy - Indexing and Slicing
Why does NumPy return views instead of copies when slicing arrays?
ABecause copies are not supported
BTo save memory and improve performance
CTo prevent any changes to the original array
DBecause views are easier to program
Step-by-Step Solution
Solution:

  1. Step 1: Understand the design goal of NumPy slicing

    Returning views avoids copying data, saving memory.

  2. Step 2: Recognize performance benefits

    Views allow fast operations without duplicating data.

  3. Final Answer:

    To save memory and improve performance -> Option B

  4. Quick Check:

    Views save memory and speed up code = B [OK]
Quick Trick: Views save memory and speed up array operations [OK]
Common Mistakes:
  • Thinking copies are not supported
  • Believing views prevent changes
  • Assuming views are simpler to program

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