How to apply same operation to multiple data frames in dplyr-R?

Question

I would like to apply the same operation to multiple data frames in 'R' but cannot get how to deal with this matter.

This is an example of pipe operation in dplyr:

library(dplyr)

    iris %>% mutate(Sepal=rowSums(select(.,starts_with("Sepal"))),
                    Length=rowSums(select(.,ends_with("Length"))),
                    Width=rowSums(select(.,ends_with("Width"))))
iris2 <- iris
iris3 <- iris

Could you suggest how to apply the same pipe function to iris, iris2 and isis3? I need to use dplyr piping operation.

I suppose map function may help but as I have not fully understand its concept, I got errors to apply it.

Sample script:

library(purrr)

iris.set <- c(iris,iris2,iris3)
map(iris.set, ~ . %>% mutate(Sepal=rowSums(select(.,starts_with("Sepal"))),
                Length=rowSums(select(.,ends_with("Length"))),
                Width=rowSums(select(.,ends_with("Width")))))

Answer 1

If you turn your operation into a function:

library(dplyr)
my_fun <- function(x) { 
      x %>%       
          mutate(Sepal=rowSums(select(.,starts_with("Sepal"))),
          Length=rowSums(select(.,ends_with("Length"))),
          Width=rowSums(select(.,ends_with("Width"))))
}

You can pipe a list of data frames to it easily:

result <- list( iris, iris2, iris3 ) %>%
    lapply( my_fun )

Answer 2

is it good for you ?

    library(dplyr)

    #matrices replication 
    iris1=iris
    iris2=iris
    iris3=iris

    #list of combinations: apply is tricky for array input
    irises=matrix(c("iris1","iris2","iris3"), ncol=1)

    #function design
    Funct<-function(df_name){

      df=get(df_name)
      df %>% mutate(Sepal=rowSums(select(.,starts_with("Sepal"))),
                    Length=rowSums(select(.,ends_with("Length"))),
                    Width=rowSums(select(.,ends_with("Width"))))
    }

    apply(irises,MARGIN=2, Funct)