  # numpy.ndarray.copy () in Python

NumPy | Python Methods and Functions

`numpy.ndarray.copy() ` returns a copy of the array.

Syntax: numpy.ndarray .copy (order = `C`)

Parameters:
order: Controls the memory layout of the copy. `C` means C-order, `F` means F-order, `A` means `F` if a is Fortran contiguous, `C` otherwise. `K` means match the layout of a as closely as possible.

Code # 1:

 ` # Python program explaining ` ` # numpy.ndarray.copy () function ` ` `  ` import ` ` numpy as geek `     ` x ` ` = ` ` geek.array ([[` ` 0 ` `, ` ` 1 ` `, ` ` 2 ` `, ` ` 3 ` `], [` ` 4 ` `, ` ` 5 ` `, ` ` 6 ` `, ` ` 7 ` `]], ` ` order ` ` = ` `` F` ` `) ` ` print ` ` (` ` "x is:" ` `, x) ``   # copy x to y y = x.copy () print ( "y is:" , y) print ( "x is copied to y " ) `

Output:

` xi s: [[0 1 2 3] [4 5 6 7]] y is: [[0 1 2 3] [4 5 6 7]] x is copied to y `

Code no. 2:

 ` # Python program explaining ` ` # numpy.ndarray. copy () function `   ` import ` ` numpy as geek `     ` x ` ` = ` ` geek.array ([[ ` ` 0 ` `, ` ` 1 ` `,], [` ` 2 ` `, ` ` 3 ` `]]) ` ` print ` ` (` `" x is: "` `, x) ` ` `  ` # copy x to y ` ` y ` ` = x.copy () ``   # filling x 1 x.fill ( 1 ) print ( " Now x is: " , x)    print ( "y is:" , y) `

Exit:

` x is: [[0 1] [2 3]] Now x is: [[1 1] [1 1]] y is: [[0 1] [2 3]] `