  # numpy.nanargmax () in Python

NumPy | Python Methods and Functions

numpy.nanargmax (array, axis = None): returns the indices of the max array element on a specific axis, ignoring NaN.
Results cannot be trusted if the slice contains only NaN 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:            ` # Python program illustrating `  ` # nanargmax () work `      ` import ` ` numpy as geek `    ` # Working with 1D array `   ` array ` ` = ` ` [geek.nan, ` ` 4 ` `, ` ` 2 ` `, ` ` 3 ` `, ` ` 1 ` `] `  ` print ` ` (` ` "INPUT ARRAY 1:" ` `, array) `     ` array2 ` ` = ` ` geek.array ([[geek.nan, ` ` 4 ` `], [` ` 1 ` `, ` ` 3 ` `]]) `     ` # returns the max element indices `  ` # by indicators that take NaN into account `   ` print ` ` (` ` "Indices of max in array1:" ` `, geek.nanargm ax (array)) `    ` # Working with 2D array `   ` print ` ` (` ` "INPUT ARRAY 2:"  , array2) ``   print   (  "Indices of max in array2:"  , geek.nanargmax (array2))       print   (  "Indices 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 a t axis 1 of array2: [1 1]    Code 2: Comparison of argmax and nanargmax operation            ` # Python program illustrating `  ` # nanargmax () work `      ` import ` ` numpy as geek `  ` `  ` # Working with 2D array `   ` array ` ` = ` ` ([[` ` 8 ` `, ` ` 13 ` `, ` ` 5 ` `, ` ` 0 ` `], `   ` [` ` 16  , geek.nan,   5  ,   3  ], ``     [ geek.nan,   7  ,   15  ,   15  ],     [  3  ,   11  ,   4  ,   12  ]])    print   (  "INPUT ARRAY:"  , array)  ``    # returns the indices of the max element    # by indicators `     ` "" "`    ` [[8 13 5 0] `    ` [16 2 5 3] `    ` [10 7 15 15] `    ` [3 11 4 12 ]] `    ` ^ ^ ^ ^ `     ` "" "`   `  ``   print   (  "Indices of max using argmax:"  , geek.argmax (array, axis   =   0  ))    prin t   (  "Indices 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]    Links:    https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.nanargmax.html#numpy. nanargmax     Notes:   These codes will not work for online IDs. Please run them on your systems to see how they work.   This article is courtesy of  Mohit Gupta_OMG