Now, let's dive into **sorting** arrays. Sorting an array involves arranging its elements in a specific order, whether it's ascending, descending, or some other sequence.

 Let's try to sort the array:

import numpy as np

array = np.array([3, -4, 6, 0, 12, 499, -123])

print('unsorted array', array)
print('sorted array', np.sort(array))

 >Note
>
>The `sort()` function returns a **copy** of the array, while the original array remains unchanged.

import numpy as np

array = np.array([[-2, 4, -12, -434, 62], [1, 4, 7, 93, 75]])
print('Unsorted array', array)
print('Sorted array', np.sort(array))

NumPy is one of the basic packages for scientific computing in Python. The 'NumPy in a Nutshell' course will introduce you to such a powerful tool as NumPy, which is convenient for working with arrays of different sizes. After completing this course, you will be able to easily work with matrices, using various functions. In addition, during the course, you will learn basic methods for working with arrays that simplify code writing.

In this section we will get acquainted with what the NumPy library is, as well as learn how to create an array.

In this section we will get acquainted with arrays of different dimensions, and understand the difference between them.

In this section we should recall what slices are and learn how to make them for arrays of different dimensions. We shall also learn to refer to elements in an array using their indexes.

In this section we will learn how to reshape arrays and also how to concatenate an array. Moreover we will learn how to sort an array. Also we will learn about such an interesting method that is often used for arrays, namely: copy().

NumPy in a Nutshell

Sorting Arrays

Tarea

NumPy in a Nutshell

Sorting Arrays

Tarea