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 This question already has an answer here: Calculate mean across rows with NA values in R 2 answers I've got a dataframe with 1000 observations. For each observation I got five variables. Now I'd like to create a new variable which is an aggregation from those 5 variables. I typed the following: df$aggr_variable <- (1/5)*(var1+var2+var3+var4+var5)  I then got the new aggregated variable, but also a problem. If let's say observation 839 got a missing value NA in var2, but still values for the other four variables, it gives me NA in the aggregated variable. How can I leave the NA's of the five variables out without having to leave out the whole observation when one variable contains an NA? YQ.Wang 2# YQ.Wang Reply to 2017-12-04 13:04:22Z  According to your aggregate equation, you are computing the average value of these five variables for each sample(row). #some reproduciable data df <- data.frame(var1=rnorm(20,10,5),var2=rnorm(20,5,1),var3=rnorm(20,30,1), var4=rnorm(20,0,1),var5=rnorm(20,3,3)) #generates some NAs: df[11,5] <- NA df[8,3] <- NA df[9,1] <- NA df[17,2] <- NA df[11,2] <- NA #aggregate by mean df$aggr_variable <- apply(df,1,function(x){mean(x,na.rm=T)})