numpy.nan_to_num() function is used when we want to replace nan(Not A Number) with zero and inf with finite numbers in an array. It returns (positive) infinity with a very large number and negative infinity with a very small (or negative) number.
Syntax : numpy.nan_to_num(arr, copy=True)
arr : [array_like] Input data.
copy : [bool, optional] Whether to create a copy of arr (True) or to replace values in-place (False). The in-place operation only occurs if casting to an array does not require a copy. Default is True.
Return : [ndarray] New Array with the same shape as arr and dtype of the element in arr with the greatest precision. If arr is inexact, then NaN is replaced by zero, and infinity (-infinity) is replaced by the largest (smallest or most negative) floating point value that fits in the output dtype. If arr is not inexact, then a copy of arr is returned.
Code #1 : Working
Input number : nan output number : 0.0
Code #2 :
Input array : [[ 2. inf 2.] [ 2. 2. nan]] output array: [[ 2.00000000e+000 1.79769313e+308 2.00000000e+000] [ 2.00000000e+000 2.00000000e+000 0.00000000e+000]]
Code #3 :
Input array : Input array : [[2 2 2] [2 2 6]] Output array: [[2 2 2] [2 2 6]]
- 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 Set | pop()
- try and except in Python
- chr() in Python
- SHA in Python
- set add() in python
- SQL using Python | Set 1
- max() and min() in Python
- bin() in Python
- abs() in Python
- Any & All in Python
- zip() in Python
- gcd() in Python
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.