How To Use numpy.sort() in Python

This tutorial help to understand usage with the example of numpy.sort() method. We’ll cover all the different ways to use into python application. This function returns a sorted copy of an array.

Python numpy.sort()

let’s create a simple python file and demonstrate numpy.sort() method.

Syntax:

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

The Parameters are:

arr : Array to be sorted.
axis : Axis along which we need an array to be started.
order : This argument specifies which fields to compare first.
kind : [‘quicksort’{default}, ‘mergesort’, ‘heapsort’]Sorting algorithm.

Sort an Single Dimensional array using numpy.sort()

Let’s sort a simple array using this method.

Importing libraries,

import numpy as np

Let’s take a NumPy array,

arr = np.array([3, 4, 5, 7, 9, 12, 14])

Let’s create a sorted array using global numpy.sort() function:

sortedArr = np.sort(arr)
print('Sorted Array : ', sortedArr)
print('Original Array : ', arr)

Output:

Sorted Array : [ 3 4 5 7 9 12 14]
Original Array : [ 3 4 5 7 9 12 14]

** Process exited - Return Code: 0 **
Press Enter to exit terminal

Sorting Two Dimentional array Using Numpy

let’s sort a two-dimensional array using axis parameter.

Importing libraries,

import numpy as np

Sorting using the first axis:

a = np.array([[6, 7], [8, 4]])
arr1 = np.sort(a, axis = 0)
print ("Result : \n", arr1)

Sorting using the last axis:

a = np.array([[6, 7], [8, 4]])
arr2 = np.sort(a, axis = -1)
print ("\nResult : \n", arr2)

Output:

Result : 
 [[6 4]
 [8 7]]

Result : 
 [[6 7]
 [4 8]]
** Process exited - Return Code: 0 **
Press Enter to exit terminal