numpy
  1. numpy-numpysort
PreviousNext

numpy.sort()

The numpy.sort() function is a built-in NumPy function that returns a sorted copy of an input NumPy array. The sorted array is created by sorting elements of the input array along a specified axis.

Syntax

The basic syntax for using numpy.sort() function is as follows:

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

Here, a is the input array that needs to be sorted. axis is the 0-based index of the axis along which the input array needs to be sorted. kind is the sorting algorithm that needs to be used, and order is the field to order the data by.

Example

Consider the following example that demonstrates the use of the numpy.sort() function to sort an input NumPy array:

import numpy as np

arr = np.array([3, 1, 4, 2, 8, 5])
sorted_arr = np.sort(arr)

print(sorted_arr)

Output:

[1 2 3 4 5 8]

In this example, the numpy.sort() function is used to sort the arr array in ascending order. The sorted array is stored in sorted_arr, which is then printed to the console.

Explanation

The numpy.sort() function is used to sort elements of an input NumPy array along a specified axis. By default, the input array is sorted along its last axis. If you want to sort the input array along a different axis, you need to specify the axis as a second parameter.

The kind parameter of the function specifies the sorting algorithm that needs to be used. By default, the kind parameter is set to None, which means that numpy.sort() function uses quicksort algorithm.

The order parameter of the function is used to sort the data elements by a specific field. This parameter is useful when the input array is an array of structured or record type. More specifically, it is useful in cases where you have an array of custom data types, and you need to sort the elements based on a specific field of that custom data type.

Use

The numpy.sort() function is useful in cases where you need to sort the elements of a NumPy array along a specified axis. It is widely used in data analysis and scientific computing when dealing with large arrays of data.

Important Points

  • The numpy.sort() function returns a sorted copy of the input array but does not modify the original input array.
  • The numpy.sort() function supports different sorting algorithms such as quicksort, mergesort, and heapsort.
  • You can use the numpy.argsort() function to get the indices that would sort the input array instead of the sorted values.

Summary

The numpy.sort() function is a built-in NumPy function that sorts the elements of a NumPy array along a specified axis. You can use this function to sort arrays in ascending or descending order using a variety of sorting algorithms such as quicksort, mergesort, or heapsort. You can also use the numpy.argsort() function to get the indices that would sort the input array instead of the sorted values.

numpy.histogram()numpy.average()
Published on: