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: \n", x) # copying x to y y = x.copy() print("y is :\n", y) print("\nx is copied to y") |
Output:
x is: [[0 1 2 3] [4 5 6 7]] y is : [[0 1 2 3] [4 5 6 7]] x is copied to y
Code #2:
# Python program explaining # numpy.ndarray.copy() function import numpy as geek x = geek.array([[0, 1, ], [2, 3]]) print("x is:\n", x) # copying x to y y = x.copy() # filling x with 1's x.fill(1) print("\n Now x is : \n", x) print("\n y is: \n", y) |
Output:
x is: [[0 1] [2 3]] Now x is : [[1 1] [1 1]] y is: [[0 1] [2 3]]
