NumPy ndarray.copy() Method | Make Copy of a Array
Last Updated :
05 Feb, 2024
The ndarray.copy() method returns a copy of the array.
It is used to create a new array that is a copy of an existing array but does not share memory with it. This means that making any changes to the original array won’t affect the existing array.
Example
Python3
import numpy as geek
x = geek.array([[ 0 , 1 , 2 , 3 ], [ 4 , 5 , 6 , 7 ]],
order = 'F' )
print ( "x is: \n" , x)
y = x.copy()
print ( "y is :\n" , y)
print ( "\nx is copied to y" )
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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
Syntax
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
Returns: Copy of an Array
How to make a copy of a NumPy array
To make a copy of a NumPy array in Python, we use ndarray.copy method of the NumPy library
Let us understand it better with an example:
Example: Make a Copy of ndarray
Python3
import numpy as geek
x = geek.array([[ 0 , 1 , ], [ 2 , 3 ]])
print ( "x is:\n" , x)
y = x.copy()
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]]
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