Controlling copy behavior in NumPy - Cheat Sheet & Quick Revision

Recall & Review

beginner

What does it mean when a NumPy operation returns a view instead of a copy?

A view means the new array shares the same data in memory as the original array. Changes to the view affect the original array and vice versa.

beginner

How can you create a true copy of a NumPy array?

Use the copy() method on the array, like arr.copy(). This creates a new array with its own data in memory.

intermediate

What is the difference between shallow copy and deep copy in NumPy?

A shallow copy creates a new array object but shares the data buffer (like a view). A deep copy duplicates both the array object and the data buffer (like copy()).

beginner

Why might slicing a NumPy array not create a copy?

Slicing usually creates a view to save memory and time. It does not copy data but references the original array's data.

intermediate

How can you check if a NumPy array owns its data or is a view?

Check the base attribute. If arr.base is None, the array owns its data. Otherwise, it is a view referencing another array.

What does arr.copy() do in NumPy?

A Creates a new array with its own data

B Creates a view sharing the same data

C Deletes the original array

D Modifies the original array in place

arr.copy() creates a new array with a separate copy of the data, so changes to the copy do not affect the original.

If you slice a NumPy array like arr[1:4], what is usually returned?

A A view referencing the original data

B A deep copy of the slice

C A Python list

D An error

Slicing usually returns a view that shares data with the original array to save memory.

How can you tell if a NumPy array is a view or owns its data?

A Check if <code>arr.size</code> is zero

B Check if <code>arr.shape</code> is empty

C Check if <code>arr.base</code> is <code>None</code>

D Check if <code>arr.dtype</code> is <code>object</code>

If arr.base is None, the array owns its data; otherwise, it is a view.

What happens if you modify a view of a NumPy array?

A Only the view changes

B Both the view and original array change

C Only the original array changes

D An error is raised

Since a view shares data with the original array, changes to the view affect the original array as well.

Which method creates a deep copy of a NumPy array?

A <code>arr.flatten()</code>

B <code>arr.view()</code>

C <code>arr.slice()</code>

D <code>arr.copy()</code>

arr.copy() creates a deep copy with its own data buffer.

Explain the difference between a view and a copy in NumPy arrays.

Think about memory sharing and data changes.

Describe how to check if a NumPy array owns its data or is a view.

Look at the array's base attribute.