Creating 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}')

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}')

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.

Tarea

Swipe to show code editor

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

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¿Todo estuvo claro?

¡Gracias por tus comentarios!

Sección 1. Capítulo 3

Creating 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}')

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}')

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.

Tarea

Swipe to show code editor

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

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones

¿Todo estuvo claro?

¡Gracias por tus comentarios!

Sección 1. Capítulo 3

Cambia al escritorio para practicar en el mundo realContinúe desde donde se encuentra utilizando una de las siguientes opciones