How to get the indices of the sorted array using NumPy in Python?
We can get the indices of the sorted elements of a given array with the help of argsort() method. This function is used to perform an indirect sort along the given axis using the algorithm specified by the kind keyword. It returns an array of indices of the same shape as arr that that would sort the array.
Syntax:
numpy.argsort(arr, axis=-1, kind=’quicksort’, order=None)
Example 1:
Python3
import numpy as np # Original array array = np.array([10, 52, 62, 16, 16, 54, 453]) print(array) # Indices of the sorted elements of a # given array indices = np.argsort(array) print(indices) |
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Output:
[ 10 52 62 16 16 54 453] [0 3 4 1 5 2 6]
Example 2:
Python3
import numpy as np # Original array array = np.array([1, 2, 3, 4, 5]) print(array) # Indices of the sorted elements of # a given array indices = np.argsort(array) print(indices) |
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Output:
[1 2 3 4 5] [0 1 2 3 4]
Example 3:
Python3
import numpy as np # input 2d array in_arr = np.array([[ 2, 0, 1], [ 5, 4, 3]]) print ("Input array :\n", in_arr) # output sorted array indices out_arr1 = np.argsort(in_arr, kind ='mergesort', axis = 0) print ("\nOutput sorteded array indices along axis 0:\n", out_arr1) out_arr2 = np.argsort(in_arr, kind ='heapsort', axis = 1) print ("\nOutput sorteded array indices along axis 1:\n", out_arr2) |
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Output:
Input array : [[2 0 1] [5 4 3]] Output sorteded array indices along axis 0: [[0 0 0] [1 1 1]] Output sorteded array indices along axis 1: [[1 2 0] [2 1 0]]
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