# numpy.nanargmin() in Python

numpy.nanargmin(array, axis = None) : 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.
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 nanargmin() ` ` `  `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 min element ` `# as per the indices ingnoring NaN ` `print``(``"\nIndices of min in array1 : "``, geek.nanargmin(array)) ` ` `  `# Working on 2D array ` `print``(``"\nINPUT ARRAY 2 : \n"``, array2) ` `print``(``"\nIndices of min in array2 : "``, geek.nanargmin(array2)) ` ` `  `print``(``"\nIndices at axis 1 of array2 : "``, geek.nanargmin(array2, axis ``=` `1``)) `

Output :

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

Indices of min in array1 :  4

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

Indices of min in array2 :  2

Indices at axis 1 of array2 :  [1 0]
```

Code 2 : Comparing working of argmin and nanargmin

 `# Python Program illustarting ` `# working of nanargmin() ` ` `  `import` `numpy as geek  ` ` `  `# Working on 2D array ` `array ``=` `( [[ ``8``, ``13``, ``5``, ``0``], ` `           ``[ geek.nan, geek.nan, ``5``, ``3``], ` `           ``[``10``, ``7``, ``15``, ``15``], ` `           ``[``3``, ``11``, ``4``, ``12``]]) ` `print``(``"INPUT ARRAY : \n"``, array) ` ` `  `# returning Indices of the min element ` `# as per the indices  ` ` `  `'''    ` `   ``[[ 8 13  5  0] ` `   ``[ 0  2  5  3] ` `   ``[10  7 15 15] ` `   ``[ 3 11  4 12]] ` `     ``^  ^  ^  ^ ` `     ``0  2  4  0  - element ` `     ``1  1  3  0  - indices ` `'''` ` `  `print``(``"\nIndices of min using argmin : "``, geek.argmin(array, axis ``=` `0``)) ` `print``(``"\nIndices of min using nanargmin :  : "``, geek.nanargmin(array, axis ``=` `0``)) `

Output :

```INPUT ARRAY :
[[ 8 13  5  0]
[ 0  2  5  3]
[10  7 15 15]
[ 3 11  4 12]]

Indices of min element :  [1 1 3 0]
```

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