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You have a large NumPy array data and want to modify a slice without affecting the original array. Which approach is best to ensure safety and memory efficiency?

hard📝 Application Q15 of 15
NumPy - Indexing and Slicing
You have a large NumPy array data and want to modify a slice without affecting the original array. Which approach is best to ensure safety and memory efficiency?
AUse <code>slice = data[100:200]</code> and modify <code>slice</code> directly.
BModify <code>data</code> directly without slicing.
CUse <code>slice = data[100:200].view()</code> and modify <code>slice</code>.
DUse <code>slice = data[100:200].copy()</code> to modify safely without changing <code>data</code>.
Step-by-Step Solution
Solution:
  1. Step 1: Understand views vs copies for safety

    Modifying a view changes the original array. To avoid this, a copy is needed.
  2. Step 2: Consider memory efficiency

    Copying only the needed slice with .copy() uses less memory than copying the whole array and ensures safe modification.
  3. Step 3: Evaluate other options

    Using slice = data[100:200] and modifying slice directly modifies the original data unintentionally. Using slice = data[100:200].view() and modifying slice creates a view, which is not safe. Modifying data directly without slicing affects the entire array, not just the slice.
  4. Final Answer:

    Use slice = data[100:200].copy() to modify safely without changing data. -> Option D
  5. Quick Check:

    Copy slice for safe, efficient modification [OK]
Quick Trick: Copy slice to avoid changing original large array [OK]
Common Mistakes:
  • Modifying views thinking they are copies
  • Copying entire array unnecessarily
  • Ignoring memory use in large arrays

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