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How to calculate row means by excluding NA values in an R data frame?
To find the row means we can use rowMeans function but if we have some missing values in the data frame then na.rm=TRUE argument can be used in the same way as it is used while calculating the means for columns. For example, if we have a data frame df that contains two columns x and y each having some missing values then the row means can be calculated as rowMeans(df,na.rm=TRUE).
Example
Consider the below data frame −
set.seed(1515) x1<-sample(c(NA,1,25,31),20,replace=TRUE) x2<-sample(c(NA,5,12,27),20,replace=TRUE) x3<-sample(c(NA,15),20,replace=TRUE) x4<-sample(c(NA,15,9),20,replace=TRUE) df1<-data.frame(x1,x2,x3,x4) df1
Output
x1 x2 x3 x4 1 25 NA NA NA 2 25 12 15 NA 3 25 NA 15 NA 4 31 5 NA NA 5 31 27 15 15 6 NA 5 NA 9 7 25 12 15 NA 8 31 5 15 NA 9 1 5 15 15 10 1 27 NA NA 11 25 NA 15 NA 12 25 12 15 15 13 25 NA 15 9 14 31 NA 15 15 15 31 27 15 9 16 1 12 NA 15 17 1 NA NA 9 18 25 27 15 NA 19 31 5 15 9 20 NA 5 15 NA
Finding the row means of df1 −
rowMeans(df1,na.rm=TRUE)
Output
[1] 25.000000 17.333333 20.000000 18.000000 22.000000 7.000000 17.333333 [8] 17.000000 9.000000 14.000000 20.000000 16.750000 16.333333 20.333333 [15] 20.500000 9.333333 5.000000 22.333333 15.000000 10.000000
Let’s have a look at another example −
Example
y1<-sample(c(NA,rnorm(5,1,0.003)),20,replace=TRUE) y2<-sample(c(NA,rnorm(10,50,2.47)),20,replace=TRUE) y3<-sample(c(NA,runif(5,1,4)),20,replace=TRUE) y4<-sample(c(NA,runif(5,2,10)),20,replace=TRUE) y5<-sample(c(NA,rexp(5,3.5)),20,replace=TRUE) df2<-data.frame(y1,y2,y3,y4,y5) df2
Output
y1 y2 y3 y4 y5 1 0.9965744 48.73434 2.097240 9.657755 0.32815971 2 1.0003618 44.83392 2.877004 9.735341 0.27053003 3 0.9974534 NA 2.097240 9.657755 0.64288668 4 0.9999057 54.12249 2.097240 NA 0.06486254 5 1.0003618 54.12249 2.877004 5.945301 NA 6 0.9965744 NA NA NA 0.27053003 7 1.0003618 54.12249 NA 5.945301 0.06486254 8 1.0022832 44.83392 1.065712 5.945301 0.64288668 9 1.0003618 54.34290 NA 9.735341 0.64288668 10 1.0003618 NA 2.323069 3.774950 NA 11 0.9999057 54.12249 1.834897 3.774950 0.64288668 12 0.9999057 53.84937 1.834897 NA 0.44797666 13 0.9974534 47.75855 1.065712 9.735341 0.44797666 14 1.0022832 NA 1.065712 3.774950 0.32815971 15 1.0003618 54.12249 2.877004 5.945301 0.27053003 16 0.9974534 54.34290 2.323069 9.657755 0.64288668 17 NA 44.83392 1.065712 3.774950 0.32815971 18 0.9965744 54.34290 NA NA 0.06486254 19 1.0022832 49.89409 2.323069 3.774950 0.06486254 20 1.0003618 49.89409 1.065712 4.078849 0.32815971
Finding the row means of df2 −
Example
rowMeans(df2,na.rm=TRUE)
Output
[1] 12.3628143 11.7434319 3.3488338 14.3211253 15.9862898 0.6335522 [7] 15.2832544 10.6980210 16.4303723 2.3661269 12.2750266 14.2830369 [13] 12.0010071 1.5427764 12.8431379 13.5928126 12.5006862 18.4681122 [19] 11.4118515 11.2734351
Updated on: 17-Oct-2020
2K+ Views
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