Merging and summarizing two dataframes - r

Question

I have the following data:
a <- data.frame(ID=c("A","B","Z","H"), a=c(0,1,2,45), b=c(3,4,5,22), c=c(6,7,8,3))
> a
ID a b c
1 A 0 3 6
2 B 1 4 7
3 Z 2 5 8
4 H 45 22 3
b <- data.frame(ID=c("A","B","E","W","Z","H"), a=c(9,10,11,39,5,0), b=c(4,2,7,54,12,34), c=c(12,0,34,23,13,14))
> b
ID a b c
1: A 9 4 12
2: B 10 2 0
3: E 11 7 34
4: W 39 54 23
5: Z 5 12 13
6: H 0 34 14
I want to merge both dataframes, keeping only rows of data.frame a and summarize the same columns, so at the end I get:
> z
ID a b c
1 A 9 7 18
2 B 11 6 7
3 Z 7 17 21
4 H 45 56 17
So far I have tried the following:
merge(a,b,by="ID",all.x=T,all.y=F)
> merge(a,b,by="ID",all.x=T,all.y=F)
ID a.x b.x c.x a.y b.y c.y
1 A 0 3 6 9 4 12
2 B 1 4 7 10 2 0
3 H 45 22 3 0 34 14
4 Z 2 5 8 5 12 13
> join(a,b,type="left",by="ID")
ID a b c a b c
1 A 0 3 6 9 4 12
2 B 1 4 7 10 2 0
3 Z 2 5 8 5 12 13
4 H 45 22 3 0 34 14
I cannot manage to summarize the columns.
My dataframe is pretty big so if the solution can speed up things that would even be better.

Answer 1

If your data.frame is very big, then you may consider this option:
library(data.table)
## convert data.frame to data.table
setDT(a)
## convert data.frame to data.table
setDT(b)
## merge the two data.tables
c <- merge(a,b,by='ID')
## extract names of all columns except the first one i.e. ID
col_names <- colnames(a)[-1]
## query building
col_1 <- paste0(col_names,'.x')
col_2 <- paste0(col_names,'.y')
cols <- paste(col_1,col_2,sep=',')
cols_2 <- paste0(col_names," = sum(",cols,")")
cols_3 <- paste(cols_2,collapse=',')
query <- paste0("z <- c[,.(",cols_3,"),by=ID]")
## query execution
eval(parse(text = query))

Answer 2

This works at least for your example:
a <- data.frame(ID=c("A","B","Z","H"), a=c(0,1,2,45), b=c(3,4,5,22), c=c(6,7,8,3))
b <- data.frame(ID=c("A","B","E","W","Z","H"), a=c(9,10,11,39,5,0), b=c(4,2,7,54,12,34), c=c(12,0,34,23,13,14))
match_a <- na.omit(match(b$ID, a$ID))
match_b <- na.omit(match(a$ID, b$ID))
df <- cbind(ID = a$ID[match_a], a[match_a, -1] + b[match_b, -1])
First, get matching rows from a in b and vice versa, so we can be sure that we only have those rows that appear in both data frames (and we now know their row-indices in both data frames). Then, simply use vectorized additions for those matching rows, but omit ID, as factor cannot be summed up; add ID back manually.

Answer 3

You cannot directly add both data frame is because both the data frames are of unequal size. To make them of equal size you can check for IDs in a which are present in b and then add them element wise.
new <- b[b$ID %in% a$ID, ]
cbind(ID = a$ID, a[-1] + new[-1])
# ID a b c
#1 A 9 7 18
#2 B 11 6 7
#3 Z 7 17 21
#4 H 45 56 17