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Create Row Sum and Row Product Columns in R Data Frame
To create a row sum and a row product column in an R data frame, we can use rowSums function and the star sign (*) for the product of column values inside the transform function. For example, if we have a data frame df that contains x, y, z then the column of row sums and row product can be created as:
transform(df,RowSums=rowSums(df),RowProducts=x*y*z)
Example
Consider the below data frame:
> set.seed(3251) > x1<-rpois(20,2) > y1<-rpois(20,5) > z1<-rpois(20,6) > a1<-rpois(20,8) > b1<-rpois(20,7) > df1<-data.frame(x1,y1,z1,a1,b1) > df1
Output
x1 y1 z1 a1 b1 1 2 4 10 10 5 2 0 9 5 5 8 3 4 7 6 12 9 4 2 3 3 11 2 5 2 5 11 8 6 6 2 4 9 9 12 7 1 8 3 7 6 8 2 7 7 6 3 9 3 9 10 13 8 10 1 8 7 12 5 11 0 3 9 7 7 12 2 4 9 10 5 13 3 5 5 8 7 14 3 6 4 4 10 15 1 5 11 11 4 16 0 6 7 6 6 17 3 2 10 10 5 18 2 5 4 7 14 19 4 6 3 4 7 20 1 7 6 13 6
Creating row sums and row products column in df1:
Example
> transform(df1,RowSums=rowSums(df1),RowProducts=x1*y1*z1*a1*b1)
Output
x1 y1 z1 a1 b1 RowSums RowProducts 1 2 4 10 10 5 31 4000 2 0 9 5 5 8 27 0 3 4 7 6 12 9 38 18144 4 2 3 3 11 2 21 396 5 2 5 11 8 6 32 5280 6 2 4 9 9 12 36 7776 7 1 8 3 7 6 25 1008 8 2 7 7 6 3 25 1764 9 3 9 10 13 8 43 28080 10 1 8 7 12 5 33 3360 11 0 3 9 7 7 26 0 12 2 4 9 10 5 30 3600 13 3 5 5 8 7 28 4200 14 3 6 4 4 10 27 2880 15 1 5 11 11 4 32 2420 16 0 6 7 6 6 25 0 17 3 2 10 10 5 30 3000 18 2 5 4 7 14 32 3920 19 4 6 3 4 7 24 2016 20 1 7 6 13 6 33 3276
Let’s have a look at another example:
Example
> x2<-sample(0:9,20,replace=TRUE) > y2<-sample(0:9,20,replace=TRUE) > z2<-sample(0:9,20,replace=TRUE) > a2<-sample(0:9,20,replace=TRUE) > b2<-sample(0:9,20,replace=TRUE) > df2<-data.frame(x2,y2,z2,a2,b2) > df2
Output
x2 y2 z2 a2 b2 1 3 2 9 5 9 2 9 9 3 3 8 3 7 7 9 0 3 4 8 0 2 1 8 5 7 5 3 0 8 6 4 5 3 8 2 7 2 2 0 7 0 8 7 7 9 5 9 9 2 9 3 0 2 10 4 4 5 8 6 11 3 1 0 6 7 12 6 1 5 1 9 13 0 3 1 6 3 14 3 3 3 2 4 15 6 7 8 3 1 16 7 1 7 4 4 17 3 3 8 4 5 18 2 6 1 8 1 19 0 2 1 7 6 20 8 6 2 8 6
Creating row sums and row products column in df2:
Example
> transform(df2,RowSums=rowSums(df2),RowProducts=x2*y2*z2*a2*b2)
Output
x2 y2 z2 a2 b2 RowSums RowProducts 1 3 2 9 5 9 28 2430 2 9 9 3 3 8 32 5832 3 7 7 9 0 3 26 0 4 8 0 2 1 8 19 0 5 7 5 3 0 8 23 0 6 4 5 3 8 2 22 960 7 2 2 0 7 0 11 0 8 7 7 9 5 9 37 19845 9 2 9 3 0 2 16 0 10 4 4 5 8 6 27 3840 11 3 1 0 6 7 17 0 12 6 1 5 1 9 22 270 13 0 3 1 6 3 13 0 14 3 3 3 2 4 15 216 15 6 7 8 3 1 25 1008 16 7 1 7 4 4 23 784 17 3 3 8 4 5 23 1440 18 2 6 1 8 1 18 96 19 0 2 1 7 6 16 0 20 8 6 2 8 6 30 4608
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