Function array()

In fact, there are various functions in NumPy for creating arrays. Now, we'll explore one of the most commonly used ones, namely np.array(). Below, you'll find an example of how to use this function:


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# Importing NumPy
import numpy as np

# Creating array
arr = np.array([1, 3, 5, 7, 9, 11, 13])

# Displaying array
print(arr)

Let's now determine the type of object that this function creates. We can do this using the well-known function type().

Note

The type() function takes an object of any type and returns its type. The argument can indeed be of any type: number, string, list, dictionary, tuple, function, class, module, etc.


              12345678
            
import numpy as np
arr = np.array([1, 3, 5, 7, 9, 11, 13])

# Displaying array
print(arr)

# Displaying the type of created array
print(type(arr))

We can see the type of the created array is ndarray. But what does that mean? ndarray - This object is a multidimensional homogeneous array with a predetermined number of elements.

Now it's time to practice!

Tarea

Swipe to show code editor

You have to create two NumPy arrays. The first one should look like this: [65, 2, 89, 5, 0, 1] and the second one should look like this: [1, 2, 3].
Display these arrays on the screen.
Display the type of these arrays on the screen.

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 2

Function array()


              12345678
            
# Importing NumPy
import numpy as np

# Creating array
arr = np.array([1, 3, 5, 7, 9, 11, 13])

# Displaying array
print(arr)

Let's now determine the type of object that this function creates. We can do this using the well-known function type().

Note

The type() function takes an object of any type and returns its type. The argument can indeed be of any type: number, string, list, dictionary, tuple, function, class, module, etc.


              12345678
            
import numpy as np
arr = np.array([1, 3, 5, 7, 9, 11, 13])

# Displaying array
print(arr)

# Displaying the type of created array
print(type(arr))

We can see the type of the created array is ndarray. But what does that mean? ndarray - This object is a multidimensional homogeneous array with a predetermined number of elements.

Now it's time to practice!

Tarea

Swipe to show code editor

You have to create two NumPy arrays. The first one should look like this: [65, 2, 89, 5, 0, 1] and the second one should look like this: [1, 2, 3].
Display these arrays on the screen.
Display the type of these arrays on the screen.

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 2

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