learn-python/contrib/numpy/sorting-array.md

Sorting NumPy Arrays

• Sorting arrays is a common operation in data manipulation and analysis.
• NumPy provides various functions to sort arrays efficiently.
• The primary methods are numpy.sort,numpy.argsort, and numpy.lexsort

1. numpy.sort()

The numpy.sort function returns a sorted copy of an array.

Syntax :

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

• arr : Array to be sorted.
• axis : Axis along which to sort. (By Default is -1)
• kind : Sorting algorithm. Options are 'quicksort', 'mergesort', 'heapsort', and 'stable'. (By Default 'quicksort')
• order : When arr is an array with fields defined, this argument specifies which fields to compare first.

Example :

import numpy as np

arr = np.array([1,7,0,4,6])
sarr = np.sort(arr)
print(sarr)

Output :

[0 1 4 6 7]

2. numpy.argsort()

The numpy.argsort function returns the indices that would sort an array. Using those indices you can sort the array.

Syntax :

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

• arr : Array to be sorted.
• axis : Axis along which to sort. (By Default is -1)
• kind : Sorting algorithm. Options are 'quicksort', 'mergesort', 'heapsort', and 'stable'. (By Default 'quicksort')
• order : When arr is an array with fields defined, this argument specifies which fields to compare first.

Example :

import numpy as np

arr = np.array([2.1,7,4.2,4.3,6])
indices = np.argsort(arr)
print(indices)
s_arr = arr[indices]
print(s_arr)

Output :

[0 2 3 4 1]
[2.1 4.2 4.3 6. 7. ]

3. np.lexsort()

The np.lexsort function performs an indirect stable sort using a sequence of keys.

Syntax :

numpy.lexsort(keys, axis=-1)

• keys: Sequence of arrays to sort by. The last key is the primary sort key.
• axis: Axis to be indirectly sorted.(By Default -1)

Example :

import numpy as np

a = np.array([5,4,3,2])
b = np.array(['a','d','c','b'])
indices = np.lexsort((a,b))
print(indices)

s_arr = a[indices]
print(s_arr)

s_arr = b[indices]
print(s_arr)

Output :

[0 3 2 1]
[2 3 4 5]
['a' 'b' 'c' 'd']

NumPy provides powerful and flexible functions for sorting arrays, including np.sort, np.argsort, and np.lexsort. These functions support sorting along different axes, using various algorithms, and sorting by multiple keys, making them suitable for a wide range of data manipulation tasks.