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How to convert NaN to NA in an R data frame?
To convert NaN to NA in an R data frame, we can set the NaN values to NA values by using single square brackets. Firstly, we would need to access the column that contains NaN values then NaN values will be accessed using is.nan then we can set those values to NA as shown in the below examples.
Consider the below data frame −
Example
x1<-sample(c(1,2,5,NaN),20,replace=TRUE) x2<-rpois(20,2) df1<-data.frame(x1,x2) df1
Output
x1 x2 1 5 1 2 1 2 3 5 3 4 NaN 2 5 5 1 6 5 2 7 NaN 1 8 5 4 9 5 2 10 2 0 11 NaN 0 12 1 0 13 NaN 4 14 1 2 15 5 1 16 1 2 17 2 2 18 5 0 19 2 1 20 5 1
Replacing NaN with NA in column x1 of df1 −
Example
df1$x1[is.nan(df1$x1)]<-NA df1
Output
x1 x2 1 5 1 2 1 2 3 5 3 4 NA 2 5 5 1 6 5 2 7 NA 1 8 5 4 9 5 2 10 2 0 11 NA 0 12 1 0 13 NA 4 14 1 2 15 5 1 16 1 2 17 2 2 18 5 0 19 2 1 20 5 1
Example
y1<-sample(c(rnorm(2),NaN),20,replace=TRUE) y2<-rnorm(20) y3<-rnorm(20) df2<-data.frame(y1,y2,y3) df2
Output
y1 y2 y3 1 -0.0867355 -1.28729227 -0.20581922 2 NaN 1.11408057 0.56750161 3 NaN 0.47302790 -0.72410253 4 NaN -0.34217866 0.33855658 5 NaN -2.52516598 0.78809964 6 -0.0867355 -0.65268724 -0.04150251 7 -0.0867355 0.42845639 -0.12955272 8 -0.0867355 0.71995182 0.24011099 9 -0.0867355 0.07829339 3.10334568 10 -0.9135175 0.07250105 -0.41307585 11 -0.0867355 1.58477752 0.96751855 12 NaN -1.84389126 -0.42843257 13 -0.0867355 -0.10860452 -0.32978319 14 -0.9135175 -1.25311587 -1.07537515 15 -0.0867355 0.58514141 2.05516953 16 NaN 2.02405825 0.18098639 17 -0.9135175 0.90327161 -0.22561346 18 -0.9135175 0.81260538 -1.98065156 19 NaN -1.60608848 -1.39970818 20 NaN -0.82239927 -1.45993348
Replacing NaN with NA in column y1 of df2 −
Example
df2$y1[is.nan(df2$y1)]<-NA df2
Output
y1 y2 y3 1 -0.0867355 -1.28729227 -0.20581922 2 NA 1.11408057 0.56750161 3 NA 0.47302790 -0.72410253 4 NA -0.34217866 0.33855658 5 NA -2.52516598 0.78809964 6 -0.0867355 -0.65268724 -0.04150251 7 -0.0867355 0.42845639 -0.12955272 8 -0.0867355 0.71995182 0.24011099 9 -0.0867355 0.07829339 3.10334568 10 -0.9135175 0.07250105 -0.41307585 11 -0.0867355 1.58477752 0.96751855 12 NA -1.84389126 -0.42843257 13 -0.0867355 -0.10860452 -0.32978319 14 -0.9135175 -1.25311587 -1.07537515 15 -0.0867355 0.58514141 2.05516953 16 NA 2.02405825 0.18098639 17 -0.9135175 0.90327161 -0.22561346 18 -0.9135175 0.81260538 -1.98065156 19 NA -1.60608848 -1.39970818 20 NA -0.82239927 -1.45993348
Updated on: 10-Feb-2021
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