How to lookup and sum multiple columns in R - r

Question

Suppose I have 2 dataframes structured as such:
GROUPS:
P1 P2 P3 P4
123 213 312 231
345 123 213 567
INDIVIDUAL_RESULTS:
ID SCORE
123 23
213 12
312 11
213 19
345 10
567 22
I want to add a column to the GROUPS which is a sum of each of their individual results:
P1 P2 P3 P4 SCORE
123 213 312 231 65
I've tried using various merge techniques, but have really just created a mess. I feel like there's a simple solution I just don't know about, would really appreciate some guidance!

Answer 1

d1=read.table(text="
P1 P2 P3 P4
123 213 312 231
345 123 213 567",h=T)
d2=read.table(text="
ID SCORE
123 23
213 12
312 11
231 19
345 10
567 22",h=T)
I will be using the apply and match functions. Apply will apply the match function to each row of d1, match will find the matching values from the row of d1 and d2$ID (their indices) and then take the values in d2$SCORE at those indices. In the end we sum them up.
d1$SCORE=apply(d1,1,function(x){
sum(d2$SCORE[match(x,d2$ID)])
})
and the result
P1 P2 P3 P4 SCORE
1 123 213 312 231 65
2 345 123 213 567 67

Answer 2

I would try a slow but could be an intuitive way for new users. I think the difficulty was created by the format of your data d1. If you do a little bit of tidy up:
library(tidyverse)
d1<-data.frame(t(d1))
colnames(d1) <-c("group1", "group2")
d1$P = row.names(d1)
d1<-d1 %>%
pivot_longer(
cols = group1:group2,
names_to = "Group",
values_to = "ID"
)
df <-left_join(d1, d2, by ="ID")
df
# A tibble: 8 x 4
P Group ID SCORE
<chr> <chr> <int> <int>
1 P1 group1 123 23
2 P1 group2 345 10
3 P2 group1 213 12
4 P2 group2 123 23
5 P3 group1 312 11
6 P3 group2 213 12
7 P4 group1 231 19
8 P4 group2 567 22
Once you get the data to this more "conventional" format, we can easily work out a tidyverse solution.
df %>%
group_by(Group) %>%
summarize(SCORE = sum(SCORE))
# A tibble: 2 x 2
Group SCORE
<chr> <int>
1 group1 65
2 group2 67

Answer 3

Another possibility is to reformat the first data.frame to contain the group and subgroup Information:
groups <- tidyr::gather(d1,name,number,P1:P4)
These information could be added to the second data.frame and could be further used for different analyses. Such as aggregrations.
d2_groups <- merge(groups, d2, by.x = "number",by.y = "ID")
aggregate(d2_groups$SCORE, by=list(groups = d2_groups$name), FUN=sum)