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")))))
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 )
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)
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