I would like to fuse 3 data frames (AA, AB and BB) which contain exactly the same dimensions and will never contain a number in the same coordinate (if one contain a number the others will contain a NA. Can also be true that a specific coordinate contain NA for all data frames). This is my input:
AA <- 'pr_id sample1 sample2 sample3
AX-1 NA 120 130
AX-2 NA NA NA
AX-3 NA NA NA'
AA <- read.table(text=AA, header=T)
AB <- 'pr_id sample1 sample2 sample3
AX-1 100 NA NA
AX-2 NA 180 NA
AX-3 NA 120 NA'
AB <- read.table(text=AB, header=T)
BB <- 'pr_id sample1 sample2 sample3
AX-1 NA NA NA
AX-2 150 NA NA
AX-3 160 NA NA'
BB <- read.table(text=BB, header=T)
My expected output:
Fus <- 'pr_id sample1 sample2 sample3
AX-1 100 120 130
AX-2 150 180 NA
AX-3 160 120 NA'
Fus <- read.table(text=Fus, header=T)
Some idea to perform this fusion?
Here is a possible solution giving you a matrix
L <- lapply(list(AA, AB, BB), function(x) { row.names(x) <- x[[1]]; as.matrix(x[-1])})
Reduce(function(x, y) ifelse(is.na(x), y, x), L)
If you want a dataframe:
L <- lapply(list(AA, AB, BB), function(x) { row.names(x) <- x[[1]]; as.matrix(x[-1])})
X <- Reduce(function(x, y) ifelse(is.na(x), y, x), L)
as.data.frame(X) # Fus <- as.data.frame(X)
You can do it also in a loop:
L <- lapply(list(AA, AB, BB), function(x) { row.names(x) <- x[[1]]; as.matrix(x[-1])})
X <- L[[1]]
for (i in 2:length(L)) X <- ifelse(is.na(X), L[[i]], X)
X
or
L <- lapply(list(AA, AB, BB), function(x) { row.names(x) <- x[[1]]; as.matrix(x[-1])})
X <- L[[1]]
for (i in 2:length(L)) X[is.na(X)] <- L[[i]][is.na(X)]
X