Replacing missing value in R with mean
I have a dataframe with data columns with a missing value and I would like to replace the missing value by taking the average using the values of the cells above and below.
df1<-c(2,2,NA,10, 20, NA,3)
if(df1[i]== NA){
df1[i]= mean(df1[i+1],df1[i-1])
}
However I am getting this error
Error in if (df1[i] == NA) { : missing value where TRUE/FALSE needed
In addition: Warning message:
In if (df1[i] == NA) { :
the condition has length > 1 and only the first element will be used
Any advice would be appreciated to resolve this issue.
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If you are sure that you have no consecutive NA values, and the first and last elements are never NA, then you can do
df1<-c(2,2,NA,10, 20, NA,3)
idx<-which(is.na(df1))
df1[idx] <- (df1[idx-1] + df1[idx+1])/2
df1
# [1] 2.0 2.0 6.0 10.0 20.0 11.5 3.0
It should be more efficient than a loop.
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You can use na.approx()
from package zoo
to replace NA
with interpolated values:
library(zoo)
> na.approx(df1)
# [1] 2.0 2.0 6.0 10.0 20.0 11.5 3.0
As @ G. Grothendieck mentioned, this will fill NA
in if there are multiple in the line NA
. Also, if there may be at the ends NA
, then adding an argument will na.rm = FALSE
keep them, or adding rule = 2
will replace them with the first or last not NA
.
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to check what NA is used is.na()
, create a loop and give a mean()
vector as an argument, otherwise it will only see the first value. This should work if you don't have consecutive NA's and the first and last entries are not NA:
df1<-c(2,2,NA,10, 20, NA,3)
for(i in 2:(length(df1)-1)){
if(is.na(df1[i])){
df1[i]= mean(c(df1[i+1],df1[i-1]))
}
}
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