numpy.argmin() in Python - GeeksforGeeks

09 Mar, 2022
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 arrayarray = geek.arange(8)print("INPUT ARRAY : \n", array)    # returning Indices of the min element# as per the indicesprint("\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 arrayarray =  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 arrayarray =  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 elementprint("\narray : ", geek.argmin(array))  # First occurrence of an min element is givenprint("\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]
References : https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.argmin.html#numpy.argminNote : These codes won’t run on online IDE’s. Please run them on your systems to explore the working . This article is contributed by Mohit Gupta_OMG . If you like GeeksforGeeks and would like to contribute, you can also write an article using write.geeksforgeeks.org or mail your article to review-team@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
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