numpy.nanargmax() in Python

Last Updated : 23 Oct, 2020

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]Along a specified axis like 0 or 1

Return :

Array of indices into the array with same shape as array.shape
 with the dimension along axis removed.

Code 1 :

# Python Program illustrating 
# working of nanargmax() 
  
import numpy as geek  
  
# Working on 1D array 
array = [geek.nan, 4, 2, 3, 1] 
print("INPUT ARRAY 1 : \n", array) 
  
array2 = geek.array([[geek.nan, 4], [1, 3]]) 
  
# returning Indices of the max element 
# as per the indices ingnoring NaN 
print("\nIndices of max in array1 : ", geek.nanargmax(array)) 
  
# Working on 2D array 
print("\nINPUT ARRAY 2 : \n", array2) 
print("\nIndices of max in array2 : ", geek.nanargmax(array2)) 
  
print("\nIndices at axis 1 of array2 : ", geek.nanargmax(array2, axis = 1)) 

Output :

INPUT ARRAY 1 : 
 [nan, 4, 2, 3, 1]

Indices of max in array1 :  1

INPUT ARRAY 2 : 
 [[ nan   4.]
 [  1.   3.]]

Indices of max in array2 :  1

Indices at axis 1 of array2 :  [1 1]

Code 2 : Comparing working of argmax and nanargmax

# Python Program illustarting 
# working of nanargmax() 
  
import numpy as geek  
  
# Working on 2D array 
array = ( [[ 8, 13, 5, 0], 
           [ 16, geek.nan, 5, 3], 
           [geek.nan, 7, 15, 15], 
           [3, 11, 4, 12]]) 
print("INPUT ARRAY : \n", array) 
  
# returning Indices of the max element 
# as per the indices  
  
'''    
   [[ 8 13  5  0] 
   [ 16  2  5  3] 
   [10  7 15 15] 
   [ 3 11  4 12]] 
     ^  ^  ^  ^ 
       
'''
  
print("\nIndices of max using argmax : ", geek.argmax(array, axis = 0)) 
print("\nIndices of max using nanargmax :  : ", geek.nanargmax(array, axis = 0)) 

Output :

INPUT ARRAY : 
 [[8, 13, 5, 0], [16, nan, 5, 3], [nan, 7, 15, 15], [3, 11, 4, 12]]

Indices of max using argmax :  [2 1 2 2]

Indices of max using nanargmax :  :  [1 0 2 2]

References :
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.nanargmax.html#numpy.nanargmax

Note :
These codes won’t run on online-ID. Please run them on your systems to explore the working.

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