numpy.nanargmax() in Python (original) (raw)
Last Updated : 19 Sep, 2023
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 `
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 `
Python Program illustrating
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]
Note :
These codes won't run on online IDE's. So please, run them on your systems to explore the working.