numpy.argmin() in Python
Last Updated :
08 Mar, 2024
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The numpy.argmin() method returns indices of the min element of the array in a particular axis.
Syntax :
numpy.argmin(array, axis = None, out = None)
Parameters :
array : Input array to work on
axis : [int, optional]Along a specified axis like 0 or 1
out : [array optional]Provides a feature to insert output to the out
array and it should be of appropriate shape and dtype
Return :
Array of indices into the array with same shape as array.shape with the dimension along axis removed.
Code 1 :
Python
# Python Program illustrating # working of argmin() import numpy as geek # Working on 1D array array = geek.arange(8) print("INPUT ARRAY : \n", array) # returning Indices of the min element # as per the indices print("\nIndices of min element : ", geek.argmin(array, axis=0)) |
Output :
INPUT ARRAY : [0 1 2 3 4 5 6 7] Indices of min element : 0
Code 2 :
Python
# Python Program illustrating # working of argmin() import numpy as geek # Working on 2D array array = geek.random.randint(16, size=(4, 4)) print("INPUT ARRAY : \n", array) # returning Indices of the min element # as per the indices ''' [[ 8 13 5 0] [ 0 2 5 3] [10 7 15 15] [ 3 11 4 12]] ^ ^ ^ ^ 0 2 4 0 - element 1 1 3 0 - indices '''print("\nIndices of min element : ", geek.argmin(array, axis = 0)) |
Output :
INPUT ARRAY : [[ 8 13 5 0] [ 0 2 5 3] [10 7 15 15] [ 3 11 4 12]] Indices of min element : [1 1 3 0]
Code 3 :
Python
# Python Program illustrating # working of argmin() import numpy as geek # Working on 2D array array = geek.arange(10).reshape(2, 5) print("array : \n", array) array[0][0] = 10array[1][1] = 1array[0][1] = 1print("\narray : \n", array) # Returns min element print("\narray : ", geek.argmin(array)) # First occurrence of an min element is given print("\nmin ELEMENT INDICES : ", geek.argmin(array, axis = 0)) |
Output :
array : [[0 1 2 3 4] [5 6 7 8 9]] array : [[10 1 2 3 4] [ 5 1 7 8 9]] array : 1 min ELEMENT INDICES : [1 0 0 0 0]
