Copying Arrays
It's worth noting that NumPy offers various methods for duplicating arrays. In this section, we'll explore one of these methods, namely: .copy().
Note
The
.copy()method creates a new array with the data from the original one.
Using the .copy() method:
123456789import numpy as np arr = np.array([7, 43, 56, 123, 10, 3]) x = arr.copy() arr[0] = 42 print(arr) print(x)
Swipe to start coding
You have the following array: [12, 56, 78, 65, 1, 5].
You have to obtain the following arrays using the correct method:
arr_1 = [11, 56, 78, 0, 1, 5]
arr_2 = [12, 56, 78, 65, 1, 5]
Replace element 12 with 11, and element 65 with 0.
Oplossing
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It's worth noting that NumPy offers various methods for duplicating arrays. In this section, we'll explore one of these methods, namely: .copy().
Note
The
.copy()method creates a new array with the data from the original one.
Using the .copy() method:
123456789import numpy as np arr = np.array([7, 43, 56, 123, 10, 3]) x = arr.copy() arr[0] = 42 print(arr) print(x)
Swipe to start coding
You have the following array: [12, 56, 78, 65, 1, 5].
You have to obtain the following arrays using the correct method:
arr_1 = [11, 56, 78, 0, 1, 5]
arr_2 = [12, 56, 78, 65, 1, 5]
Replace element 12 with 11, and element 65 with 0.
Oplossing
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Completion rate improved to 4.76single
