Variations in different Sorting techniques in Python

Introduction

1. sort() – In-Place Sorting

import numpy as np
a = np.array([9, 3, 1, 7, 4, 3, 6])
print("Original array:", a)
a.sort()
print("Sorted array:", a)

Original array: [9 3 1 7 4 3 6]
Sorted array: [1 3 3 4 6 7 9]

• Sorts the array in-place.
• Does not return a new array; returns None.
• Modifies the original array.
• Faster than sorted() for NumPy arrays.

2. argsort() – Indirect Sorting

import numpy as np
a = np.array([9, 3, 1, 7, 4, 3, 6])
indices = np.argsort(a)
print("Sorted indices:", indices)
sorted_array = a[indices]
print("Sorted array:", sorted_array)

Sorted indices: [2 1 5 4 6 3 0]
Sorted array: [1 3 3 4 6 7 9]

• Returns the indices that would sort the array.
• Useful for sorting arrays based on the order of elements in another array.
• Does not modify the original array.

3. lexsort() – Lexicographical Sorting

import numpy as np
a = np.array([9, 3, 1, 3, 4, 3, 6])
b = np.array([4, 6, 9, 2, 1, 8, 7])
indices = np.lexsort((b, a))
sorted_array = np.column_stack((a[indices], b[indices]))
print("Sorted array by a then b:", sorted_array)

Sorted array by a then b:
[[3 2]
 [3 6]
 [3 8]
 [1 9]
 [4 1]
 [6 7]
 [9 4]]

• Performs lexicographical sorting using multiple keys.
• The last key in the tuple is the primary sort key.
• Useful for sorting structured data based on multiple criteria.
• Returns the indices that sort the keys along the specified axis.

Choosing the Right Sorting Function

• Use sort() when you need to sort the array in-place and do not require the original order.
• Use argsort() when you need the indices that would sort the array, especially when sorting based on another array.
• Use lexsort() when you need to perform lexicographical sorting using multiple keys.