.sort()

In NumPy, the .sort() function sorts the elements of an array or matrix along a specified axis. It returns a new array with elements sorted in ascending order, leaving the original array unchanged. Sorting can be performed along different axes (such as rows or columns in a 2D array), with the default being along the last axis (axis=-1).

Syntax

numpy.sort(a, axis=-1, kind=None, order=None)

• a: The array of elements to be sorted.
• axis: The axis along which to sort. If set to None, the array is flattened before sorting. The default is -1, which sorts along the last axis.
• kind: The sorting algorithm to use. The options are:
  • 'quicksort': Default algorithm, a fast, comparison-based algorithm.
  • 'mergesort': Stable sort using a divide-and-conquer algorithm.
  • 'heapsort': A comparison-based sort using a heap.
  • 'stable': A stable sorting algorithm, typically mergesort.
• order: If a is a structured array, this specifies the field(s) to sort by. If not provided, sorting will be done based on the order of the fields in a.

Example

The following example demonstrates how to use the .sort() function with various parameters:

import numpy as np

arr = np.array([[3, 1, 2], [6, 4, 5]])

print(np.sort(arr))
print(np.sort(arr, axis=0))
print(np.sort(arr, axis=None))

This example results in the following output:

[[1 2 3]
 [4 5 6]]
[[3 1 2]
 [6 4 5]]
[1 2 3 4 5 6]

Codebyte Example

Run the following codebyte example to better understand the .sort() function:

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