Create conditional variable in multiple data.tables (or data.frames) - r

Question

I want to execute the same action in multiple data.tables (or data.frames). For example, I want to create the same variable conditional on the same rule in all data.tables.
A simple example can be (df1=df2=df3, without loss of generality here)
df1 <- data.frame(var1 = c(1, 2, 2, 2, 1), var2 =c(20, 10, 10, 10, 20), var3 = c(10, 8, 15, 7, 9))
df2 <- data.frame(var1 = c(1, 2, 2, 2, 1), var2 =c(20, 10, 10, 10, 20), var3 = c(10, 8, 15, 7, 9))
df3 <- data.frame(var1 = c(1, 2, 2, 2, 1), var2 =c(20, 10, 10, 10, 20), var3 = c(10, 8, 15, 7, 9))
My approach was: (i) to create a list of the data frames (list.df), (ii) to loop on this list trying to create the variable:
list.df
list.df<-vector('list',3)
for(j in 1:3){
name <- paste('df',j,sep='')
list.df[j] <- name
}
My (bad) tentative:
for(i in 1:3){
a<-get(paste(list.df[[i]], "$var1", sep=""))
b<-get(paste(list.df[[i]], "$var2", sep=""))
name<-paste(list.df[[i]], "$var.new", sep="")
assign(name, ifelse(a==2 & b==10, 1, 0))
}
Clearly r cannot create this new variable the way I am doing as I get a error message "object not found".
Any clues on how to fix my bad code? I have a feeling that dplyr could help me but I don't know how.

Answer 1

We can use mget after creating the strings of object names with paste so that we get the values ie. data.frames in a list. We loop through the list (lapply(...,) and transform each dataset by creating the variable ('varNew') which is a binary variable. We can either use ifelse on the logical statement or just wrap with + to coerce the TRUE/FALSE to 1/0.
lst <- lapply(mget(paste0('df', 1:3)), transform,
varNew = +(var1==2 & var2==10))
If we need to update the original objects, we can use list2env.
list2env(lst, envir = .GlobalEnv)
df1
df2