# How to find the sum of non-missing values in an R data frame column?

To find the sum of non-missing values in an R data frame column, we can simply use sum function and set the na.rm to TRUE. For example, if we have a data frame called df that contains a column say x which has some missing values then the sum of the non-missing values can be found by using the command sum(df$x,na.rm=TRUE). ## Example1 Consider the below data frame − Live Demo x1<-sample(c(NA,2,3),20,replace=TRUE) x2<-sample(c(NA,5),20,replace=TRUE) df1<-data.frame(x1,x2) df1 ## Output  x1 x2 1 3 5 2 2 NA 3 3 5 4 NA 5 5 NA NA 6 3 NA 7 3 5 8 3 NA 9 NA 5 10 3 NA 11 3 NA 12 2 NA 13 2 5 14 2 5 15 3 NA 16 2 NA 17 3 5 18 NA 5 19 3 5 20 3 5 Finding the sum of non-missing values in columns x1 and x2 − sum(df1$x1,na.rm=TRUE)

[1] 43

sum(df1$x2,na.rm=TRUE) [1] 55 ## Example2 Live Demo y1<-sample(c(NA,rpois(1,2)),20,replace=TRUE) y2<-sample(c(NA,rpois(2,8)),20,replace=TRUE) df2<-data.frame(y1,y2) df2 ## Output  y1 y2 1 NA NA 2 3 NA 3 3 4 4 3 4 5 NA 6 6 3 NA 7 3 4 8 3 4 9 3 NA 10 3 4 11 NA 6 12 3 6 13 NA 6 14 NA NA 15 3 NA 16 NA 4 17 3 6 18 3 6 19 NA NA 20 3 6 Finding the sum of non-missing values in columns y1 and y2 − sum(df2$y1,na.rm=TRUE)

[1] 39

sum(df2\$y2,na.rm=TRUE)

[1] 66

Updated on: 06-Mar-2021

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