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In R, NaN (not a number) values can be handled by using the is.nan() function to check if a value is NaN, and the na.omit() function to remove any rows containing NaN from a data frame. Additionally, the na.rm argument can be used to remove any NA values from an operation or calculation. These tools can be used together to help you manage NaN values in your R projects.
In R, NaN stands for Not a Number.
Typically NaN values occur when you attempt to perform some calculation that results in an invalid result.
For example, dividing by zero or calculating the log of a negative number both produce NaN values:
#attempt to divide by zero 0 / 0 [1] NaN #attempt to calculate log of negative value log(-12) [1] NaN
Note that NaN values are different from NA values, which simply represent missing values.
You can use the following methods to handle NaN values in R:
#identify positions in vector with NaN values which(is.nan(x)) #count total NaN values in vector sum(is.nan(x)) #remove NaN values in vector x_new <- x[!is.nan(x)] #replace NaN values in vector x[is.nan(x)] <- 0
The following examples show how to use each of these methods in practice.
Example 1: Identify Positions in Vector with NaN Values
The following code shows how to identify the positions in a vector that contain NaN values:
#create vector with some NaN values
x <- c(1, NaN, 12, NaN, 50, 30)
#identify positions with NaN values
which(is.nan(x))
[1] 2 4
From the output we can see that the elements in positions 2 and 4 in the vector are NaN values.
Example 2: Count Total NaN Values in Vector
The following code shows how to count the total number of NaN values in a vector in R:
#create vector with some NaN values
x <- c(1, NaN, 12, NaN, 50, 30)
#identify positions with NaN values
sum(is.nan(x))
[1] 2
From the output we can see that there are 2 total NaN values in the vector.
Example 3: Remove NaN Values in Vector
#create vector with some NaN values
x <- c(1, NaN, 12, NaN, 50, 30)
#define new vector with NaN values removed
x_new <- x[!is.nan(x)]
#view new vector
x_new
[1] 1 12 50 30
Notice that both NaN values have been removed from the vector.
Example 4: Replace NaN Values in Vector
The following code shows how to replace NaN values in a vector with zeros:
#create vector with some NaN values
x <- c(1, NaN, 12, NaN, 50, 30)
#replace NaN values with zero
x[is.nan(x)] <- 0
#view updated vector
x
[1] 1 0 12 0 50 30
Notice that both NaN values have been replaced by zeros in the vector.
The following tutorials explain how to perform other common tasks in R: