In NumPy, when you create a new array from an existing one, it can be created as either a view or a copy.


What is a View?

A view is a new array object that shares the same data (memory) as the original array.

  •  No new memory is created
  •  Changes in the view affect the original array
  •  Faster and memory-efficient

Example :

Python 
import numpy as np arr = np.array([10, 20, 30, 40, 50]) view_arr = arr[1:4] view_arr[0] = 999 print(arr) #output [ 10 999 30 40 50 ]


Check if an Array is a View :

Python 
import numpy as np arr = np.array([10, 20, 30, 40, 50]) view_arr = arr[1:4] view_arr[0] = 999 print(view_arr.base is arr) #output True


What is a Copy?

A copy creates a new array with its own memory.

  •  Independent data
  •  Changes do NOT affect original array
  •  Uses more memory

Example :

Python 
import numpy as np arr = np.array([10, 20, 30, 40, 50]) copy_arr = arr.copy() copy_arr[0] = 111 print(arr) print(copy_arr) #output [ 10 999 30 40 50 ] [111 999 30 40 50 ]

Creating a Copy explicitly using copy( )?
Python 
new_arr = arr.copy() #or new_arr = np.array(arr, copy=True)