numpy.argmax() in Python Last Updated : 08 Mar, 2024 Summarize Comments Improve Suggest changes Share Like Article Like Report The numpy.argmax() function returns indices of the max element of the array in a particular axis. Syntax : numpy.argmax(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 argmax() import numpy as geek # Working on 2D array array = geek.arange(12).reshape(3, 4) print("INPUT ARRAY : \n", array) # No axis mentioned, so works on entire array print("\nMax element : ", geek.argmax(array)) # returning Indices of the max element # as per the indices print("\nIndices of Max element : ", geek.argmax(array, axis=0)) print("\nIndices of Max element : ", geek.argmax(array, axis=1)) Output : INPUT ARRAY : [[ 0 1 2 3] [ 4 5 6 7] [ 8 9 10 11]] Max element : 11 Indices of Max element : [2 2 2 2] Indices of Max element : [3 3 3] Code 2 : Python # Python Program illustrating # working of argmax() import numpy as geek # Working on 2D array array = geek.random.randint(16, size=(4, 4)) print("INPUT ARRAY : \n", array) # No axis mentioned, so works on entire array print("\nMax element : ", geek.argmax(array)) # returning Indices of the max element # as per the indices ''' [[ 0 3 8 13] [12 11 2 11] [ 5 13 8 3] [12 15 3 4]] ^ ^ ^ ^ 12 15 8 13 - element 1 3 0 0 - indices ''' print("\nIndices of Max element : ", geek.argmax(array, axis = 0)) ''' ELEMENT INDEX ->[[ 0 3 8 13] 13 3 ->[12 11 2 11] 12 0 ->[ 5 13 8 3] 13 1 ->[12 15 3 4]] 15 1 ''' print("\nIndices of Max element : ", geek.argmax(array, axis = 1)) Output : INPUT ARRAY : [[ 0 3 8 13] [12 11 2 11] [ 5 13 8 3] [12 15 3 4]] Max element : 15 Indices of Max element : [1 3 0 0] Indices of Max element : [3 0 1 1] Code 3 : Python # Python Program illustrating # working of argmax() import numpy as geek # Working on 2D array array = geek.arange(10).reshape(2, 5) print("array : \n", array) array[0][1] = 6 print("\narray : \n", array) # Returns max element print("\narray : ", geek.argmax(array)) # First occurrence of an max element is given print("\nMAX ELEMENT INDICES : ", geek.argmax(array, axis = 0)) Output : array : [[0 1 2 3 4] [5 6 7 8 9]] array : [[0 6 2 3 4] [5 6 7 8 9]] array : 9 MAX ELEMENT INDICES : [1 0 1 1 1] Note : These codes won’t run on online IDE’s. Please run them on your systems to explore the working. Comment More infoAdvertise with us Next Article numpy.amin() in Python M Mohit Gupta Improve Article Tags : Python Python-numpy Python numpy-Sorting Searching Practice Tags : python Similar Reads numpy.amax() in Python The numpy.amax() method returns the maximum of an array or maximum along the axis(if mentioned). Syntax: numpy.amax(arr, axis = None, out = None, keepdims = <class numpy._globals._NoValue>) Parameters - arr : [array_like] input dataaxis : [int or tuples of int] axis along which we want the ma 2 min read numpy.argmin() in Python 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 inser 2 min read numpy.fmax() in Python numpy.fmax() function is used to compute element-wise maximum of array elements. This function compare two arrays and returns a new array containing the element-wise maxima. If one of the elements being compared is a NaN, then the non-nan element is returned. If both elements are NaNs then the first 2 min read numpy.amin() in Python The numpy.amin() function returns minimum of an array or minimum along axis(if mentioned). Syntax : numpy.amin(arr, axis = None, out = None, keepdims = <class numpy._globals._NoValue>) Parameters : arr : [array_like]input dataaxis : [int or tuples of int]axis along which we want the min value. 2 min read numpy.nanargmax() in Python The numpy.nanargmax() function returns indices of the max element of the array in a particular axis ignoring NaNs. The results cannot be trusted if a slice contains only NaNs and Infs. Syntax: numpy.nanargmax(array, axis = None) Parameters : array : Input array to work on axis : [int, optional]Al 2 min read numpy.nanargmin() in Python The numpy.nanargmin() function returns indices of the min element of the array in a particular axis ignoring NaNs. The results cannot be trusted if a slice contains only NaNs and Infs. Syntax:  numpy.nanargmin(array, axis = None) Parameters : array : Input array to work on axis : [int, optional]A 2 min read Like