numpy.nanargmax() in Python

numpy.nanargmax(array, axis = None) : 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.
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 :

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# 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))

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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













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# 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)) 



















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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.


This article is contributed by Mohit Gupta_OMG 😀. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.


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