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]]
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