Reputation: 3
I'm new to R and are trying to combine a couple of datasets into one. I have the following structure of my data:
opt <- data.frame( name=c("opt1", "opt2","opt3"), week=c(1,1,1,2,2,3), price=c(0))
price <- data.frame( week=c(1,2,3), opt1=c(3, 4,3.15), opt2=c(4.2, 3.5, 5), opt3=c(3,2,6))
I now want to extract the the numbers in "data.frame price" if the entries in row opt$name
matches the column names in "data.frame price" and opt$week==price$week
.
The next step is to add the selected number to the opt$price
column.
To create a new data.frame that looks like this:
optcomp <- data.frame( name=c("opt1", "opt2","opt3"), week=c(1,1,1,2,2,3), price=c(3.00,4.2,3,4.00,3.5,6))
I have tried to construct some loops but my skills in R is to limited.
Any help would be greatly appreciated!
Donald
Upvotes: 0
Views: 3659
Reputation: 42629
Initial merge, to match the week
column:
x <- merge(opt,price)
x
## week name price opt1 opt2 opt3
## 1 1 opt1 0 3.00 4.2 3
## 2 1 opt2 0 3.00 4.2 3
## 3 1 opt3 0 3.00 4.2 3
## 4 2 opt1 0 4.00 3.5 2
## 5 2 opt2 0 4.00 3.5 2
## 6 3 opt3 0 3.15 5.0 6
The values that you want:
sapply(seq(nrow(x)), function(i) x[i,as.character(x$name[i])])
[1] 3.0 4.2 3.0 4.0 3.5 6.0
Specifying the row names of x
as character
allows matrix indexing by name (and returns character
)
rownames(x) <- as.character(rownames(x))
x.ind <- matrix(c(rownames(x), as.character(x$name)),,2)
x[x.ind]
## [1] "3.00" "4.2" "3" "4.00" "3.5" "6"
Upvotes: 1