Reputation: 2651
I think this will have a simple answer, but I can't work it out! Here is an example using the iris
dataset:
a <- table(iris[,2])
b <- table(iris[,3])
How do I add these two tables together? For example, the variable 3 would have a value of 27 (26+1) and variable 3.3 a value of 8 (6+2) in the new output table.
Any help much appreciated.
Upvotes: 11
Views: 16636
Reputation: 630
The merge function of the data.table package may be what you want: https://rpubs.com/ronasta/join_data_tables
Upvotes: 1
Reputation: 995
Here's a slightly tortured one-liner version of the merge()
solution:
do.call(function(Var1, Freq.x, Freq.y) data.frame(Var1=Var1, Freq=rowSums(cbind(Freq.x, Freq.y))), merge(a, b, by="Var1"))
Here's the one if you want to use all variables:
do.call(function(Var1, Freq.x, Freq.y) data.frame(Var1=Var1, Freq=rowSums(cbind(Freq.x, Freq.y), na.rm=TRUE)), merge(a, b, by="Var1", all=TRUE))
Unlike the transform()
one-liner, it doesn't accumulate .x and .y so it can be used iteratively.
Upvotes: 2
Reputation: 81733
This will work if you want to use the variables which are present in both a
and b
:
n <- intersect(names(a), names(b))
a[n] + b[n]
# 3 3.3 3.5 3.6 3.7 3.8 3.9 4 4.1 4.2 4.4
# 27 8 8 5 4 7 5 6 4 5 5
If you want to use all variables:
n <- intersect(names(a), names(b))
res <- c(a[!(names(a) %in% n)], b[!(names(b) %in% n)], a[n] + b[n])
res[order(names(res))] # sort the results
Upvotes: 9
Reputation: 14453
Here is another one:
transform(merge(a,b, by="Var1"), sum=Freq.x + Freq.y)
Var1 Freq.x Freq.y sum
1 3 26 1 27
2 3.3 6 2 8
3 3.5 6 2 8
4 3.6 4 1 5
5 3.7 3 1 4
6 3.8 6 1 7
7 3.9 2 3 5
8 4 1 5 6
9 4.1 1 3 4
10 4.2 1 4 5
11 4.4 1 4 5
Upvotes: 3
Reputation: 18323
temp<-merge(a,b,by='Var1')
temp$sum<-temp$Freq.x + temp$Freq.y
Var1 Freq.x Freq.y sum
1 3 26 1 27
2 3.3 6 2 8
3 3.5 6 2 8
4 3.6 4 1 5
5 3.7 3 1 4
6 3.8 6 1 7
7 3.9 2 3 5
8 4 1 5 6
9 4.1 1 3 4
10 4.2 1 4 5
11 4.4 1 4 5
Upvotes: 3