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bookCreating Higher Dimensional Arrays

2D Arrays

Let's now create a higher dimensional array, namely a 2D array:


              
1234

            
import numpy as np
# Creating a 2D array
array_2d = np.array([[1, 2, 3], [4, 5, 6]])
print(f'2-dimensional array: \n{array_2d}')
copy

Basically, creating a higher-dimensional NumPy array involves passing a higher-dimensional list as the argument of the array() function.

Note

Any NumPy array object is called an ndarray.

Here is a visualization of our 2D array:

We can think of it as a 2x3 matrix.

3D Array

Creating 3D arrays is nearly identical to creating 2D arrays. The only difference is that we now need to pass a 3D list as an argument:


              
12345678

            
import numpy as np
# Creating a 3D array
array_3d = np.array([
    [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
    [[10, 11, 12], [13, 14, 15], [16, 17, 18]],
    [[19, 20, 21], [22, 23, 24], [25, 26, 27]]
])
print(f'3-dimensional array: \n{array_3d}')
copy

However, visualizing a 3D array is a bit more complex, but it can still be done:

The array is 3x3x3, which is why we have a cube with each side equal to 3.

In practice, the approach to handling 3D and higher-dimensional arrays is no different from handling 2D arrays.

Tarefa

Swipe to start coding

Create a 2D array using lists. This array can have any number of rows and columns, with arbitrary values.

Solução

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bookCreating Higher Dimensional Arrays

2D Arrays

Let's now create a higher dimensional array, namely a 2D array:


              
1234

            
import numpy as np
# Creating a 2D array
array_2d = np.array([[1, 2, 3], [4, 5, 6]])
print(f'2-dimensional array: \n{array_2d}')
copy

Basically, creating a higher-dimensional NumPy array involves passing a higher-dimensional list as the argument of the array() function.

Note

Any NumPy array object is called an ndarray.

Here is a visualization of our 2D array:

We can think of it as a 2x3 matrix.

3D Array

Creating 3D arrays is nearly identical to creating 2D arrays. The only difference is that we now need to pass a 3D list as an argument:


              
12345678

            
import numpy as np
# Creating a 3D array
array_3d = np.array([
    [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
    [[10, 11, 12], [13, 14, 15], [16, 17, 18]],
    [[19, 20, 21], [22, 23, 24], [25, 26, 27]]
])
print(f'3-dimensional array: \n{array_3d}')
copy

However, visualizing a 3D array is a bit more complex, but it can still be done:

The array is 3x3x3, which is why we have a cube with each side equal to 3.

In practice, the approach to handling 3D and higher-dimensional arrays is no different from handling 2D arrays.

Tarefa

Swipe to start coding

Create a 2D array using lists. This array can have any number of rows and columns, with arbitrary values.

Solução

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 1. Capítulo 3
single

single

close

Awesome!

Completion rate improved to 3.7

bookCreating Higher Dimensional Arrays

Deslize para mostrar o menu

2D Arrays

Let's now create a higher dimensional array, namely a 2D array:


              
1234

            
import numpy as np
# Creating a 2D array
array_2d = np.array([[1, 2, 3], [4, 5, 6]])
print(f'2-dimensional array: \n{array_2d}')
copy

Basically, creating a higher-dimensional NumPy array involves passing a higher-dimensional list as the argument of the array() function.

Note

Any NumPy array object is called an ndarray.

Here is a visualization of our 2D array:

We can think of it as a 2x3 matrix.

3D Array

Creating 3D arrays is nearly identical to creating 2D arrays. The only difference is that we now need to pass a 3D list as an argument:


              
12345678

            
import numpy as np
# Creating a 3D array
array_3d = np.array([
    [[1, 2, 3], [4, 5, 6], [7, 8, 9]],
    [[10, 11, 12], [13, 14, 15], [16, 17, 18]],
    [[19, 20, 21], [22, 23, 24], [25, 26, 27]]
])
print(f'3-dimensional array: \n{array_3d}')
copy

However, visualizing a 3D array is a bit more complex, but it can still be done:

The array is 3x3x3, which is why we have a cube with each side equal to 3.

In practice, the approach to handling 3D and higher-dimensional arrays is no different from handling 2D arrays.

Tarefa

Swipe to start coding

Create a 2D array using lists. This array can have any number of rows and columns, with arbitrary values.

Solução

Switch to desktopMude para o desktop para praticar no mundo realContinue de onde você está usando uma das opções abaixo
Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

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