Using group_by to summarize the data while looping - r

Question

For example, here is my df:
GP_A <- c(rep("a",3),rep("b",2),rep("c",2))
GP_B <- c(rep("d",2),rep("e",4),rep("f",1))
GENDER <- c(rep("M",4),rep("F",3))
LOC <- c(rep("HK",2),rep("UK",3),rep("JP",2))
SCORE <- c(50,70,80,20,30,80,90)
df <- data.frame(GP_A,GP_B,GENDER,LOC,SCORE)
> df
GP_A GP_B GENDER LOC SCORE
1 a d M HK 50
2 a d M HK 70
3 a e M UK 80
4 b e M UK 20
5 b e F UK 30
6 c e F JP 80
7 c f F JP 90
What I want is:
result[[GP_A]] <- df %>% group_by(GP_A,GENDER,LOC) %>% summarize(SCORE=mean(SCORE))
result[[GP_B]] <- df %>% group_by(GP_B,GENDER,LOC) %>% summarize(SCORE=mean(SCORE))
...
I have tried:
result <- list()
for (i in c("GP_A","GP_B")){
result[[i]] <- df %>% group_by(i,GENDER,LOC) %>% summarize(SCORE=mean(SCORE))
}
Here is the error:
Error: Column I is unknown
I also have tried to use setNames, i.e.
... %>% group_by(setNames(nm=i),GENDER,LOC) %>% ...
But it also doesn't work...

Answer 1

The group_by_at() function allows you to group by string inputs and is probably the best use here.
GP_A <- c(rep("a",3),rep("b",2),rep("c",2))
GP_B <- c(rep("d",2),rep("e",4),rep("f",1))
GENDER <- c(rep("M",4),rep("F",3))
LOC <- c(rep("HK",2),rep("UK",3),rep("JP",2))
SCORE <- c(50,70,80,20,30,80,90)
df <- data.frame(GP_A,GP_B,GENDER,LOC,SCORE)
result <- list()
for(i in c("GP_A","GP_B"))
{
result[[i]] <-
df %>%
group_by_at(c(i,"GENDER", "LOC")) %>%
summarise(SCORE = mean(SCORE)) %>%
ungroup()
}
Remember that it's always best practice to ungroup() your variables once you finish. This is so that in future you don't have unwanted grouping levels.