Python | Numpy ndarray.__array__()

Python | Numpy ndarray.copy()

Last Updated : 29 Mar, 2019

With the help of Numpy ndarray.__copy__() method, we can make a copy of all the data elements that is present in numpy array. If you change any data element in the copy, it will not affect the original numpy array.

Syntax : numpy.__copy__() Return : Copy of all the data elements

Example #1 : In this example we can see that with the help of numpy.__copy__() method we are making the copy of an elements.

Python3 1==

# import the important module in python
import numpy as np
      
# make an array with numpy
gfg = np.array([1, 2, 3, 4, 5])
      
# applying ndarray.__copy__() method
geeks = gfg.__copy__()

print(geeks)

Output:

[1 2 3 4 5]

Example #2 :

Python3 1==

# import the important module in python
import numpy as np
      
# make an array with numpy
gfg = np.array([[1, 2, 3, 4, 5],
                [6, 5, 4, 3, 2]])
      
# applying ndarray.__copy__() method
geeks = gfg.__copy__()

# Change the data element
geeks[0][2] = 10

print(gfg, end ='\n\n')
print(geeks)

Output:

[[1 2 3 4 5]
 [6 5 4 3 2]]

[[ 1  2 10  4  5]
 [ 6  5  4  3  2]]

Python | Numpy ndarray.__array__()

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