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.
array : Input array to work on axis : [int, optional]Along a specified axis like 0 or 1
Array of indices into the array with same shape as array.shape. with the dimension along axis removed.
Code 1 :
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
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]
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 email@example.com. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
- Important differences between Python 2.x and Python 3.x with examples
- Python | Sort Python Dictionaries by Key or Value
- Python | Set 4 (Dictionary, Keywords in Python)
- Python | a += b is not always a = a + b
- max() and min() in Python
- Python Set | pop()
- SHA in Python
- pow() in Python
- SQL using Python | Set 1
- Use of min() and max() in Python
- zip() in Python
- bin() in Python
- set add() in python
- chr() in Python
- try and except in Python