R alternative to "for loops"?

August 19, 2022

I am working in big data frames with a lot of information and I need to get specific information from on to merge it into my main data frame. I made a small example here with smaller samples:

ID <- c(12,44,56,16,18,29)
people <- data.frame(ID)

  ID
1 12
2 44
3 56
4 16
5 18
6 29

sex<-c("f","f","m","f","m","m")
age <- c(12,34,55,23,43,32)
ID2 <- c(44,12,16,18,56,29)
info <- data.frame(ID2,age,sex)

  ID2 age sex
1  44  12   f
2  12  34   f
3  16  55   m
4  18  23   f
5  56  43   m
6  29  32   m

My goal here is to merge the information of "info" into "people" while considering the ID. For this, I used a for loop like this:

for (i in 1:nrow(people)) {
  for (j in 1:nrow(info)){
    if(people$ID[i] == info$ID2[j]){
      people$age[i] <- info$age[j]
      people$sex[i] <- info$sex[j]
    }
  }
}

My code works fine but it seems like when I apply it in a bigger sample, the calculation time is very high. Is there an alternative to this loop?

>Solution :

You could use base merge? Should do what you need.

ID <- c(12,44,56,16,18,29)
people <- data.frame(ID)

sex<-c("f","f","m","f","m","m")
age <- c(12,34,55,23,43,32)
ID2 <- c(44,12,16,18,56,29)
info <- data.frame(ID2,age,sex)

merge(people, 
      info, 
      by.x = "ID", 
      by.y = "ID2")
#>   ID age sex
#> 1 12  34   f
#> 2 16  55   m
#> 3 18  23   f
#> 4 29  32   m
#> 5 44  12   f
#> 6 56  43   m