how can I replace the NaN value in an array, zero if an operation is performed such that as a result instead of the NaN value is zero operations as
0 / 0 = NaN can be replaced by 0
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.
In NumPy, to replace missing values NaN ( np. nan ) in ndarray with other numbers, use np. nan_to_num() or np. isnan() .
To replace NA with 0 in an R data frame, use is.na() function and then select all those values with NA and assign them to 0.
In Python, NumPy NAN stands for not a number and is defined as a substitute for declaring value which are numerical values that are missing values in an array as NumPy is used to deal with arrays in Python and this can be initialized using numpy.
If you have Python 2.6 you have the math.isnan()
function to find NaN
values.
With this we can use a list comprehension to replace the NaN
values in a list as follows:
import math
mylist = [0 if math.isnan(x) else x for x in mylist]
If you have Python 2.5 we can use the NaN != NaN
trick from this question so you do this:
mylist = [0 if x != x else x for x in mylist]
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