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Copying Arrays | Important Functions
NumPy in a Nutshell
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NumPy in a Nutshell

NumPy in a Nutshell

1. Getting Started with NumPy
2. Dimensions in Arrays
3. Indexing and Slicing
4. Important Functions

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:

123456789
import numpy as np arr = np.array([7, 43, 56, 123, 10, 3]) x = arr.copy() arr[0] = 42 print(arr) print(x)
copy

Tarefa

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.

Tarefa

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.

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Tudo estava claro?

Seção 4. Capítulo 5
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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:

123456789
import numpy as np arr = np.array([7, 43, 56, 123, 10, 3]) x = arr.copy() arr[0] = 42 print(arr) print(x)
copy

Tarefa

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.

Tarefa

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

Seção 4. Capítulo 5
toggle bottom row

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:

123456789
import numpy as np arr = np.array([7, 43, 56, 123, 10, 3]) x = arr.copy() arr[0] = 42 print(arr) print(x)
copy

Tarefa

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.

Tarefa

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo

Tudo estava claro?

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:

123456789
import numpy as np arr = np.array([7, 43, 56, 123, 10, 3]) x = arr.copy() arr[0] = 42 print(arr) print(x)
copy

Tarefa

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.

Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Seção 4. Capítulo 5
Mude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
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