midNumPy
What is the difference between view and copy in NumPy?
Updated May 17, 2026
Short answer
A view shares memory; a copy duplicates data.
Deep explanation
Views reflect changes in original arrays because they share memory. Copies are independent and safe from side effects but cost more memory.
Real-world example
Avoiding unintended modifications in data pipelines.
Common mistakes
- Assuming slicing always creates a copy.
Follow-up questions
- How to check if array is view?
- When should you use copy?