Organizing the files under the group name - r

Question

The data I have look like in a list:
G085_1.csv, G085_2.csv, G085_3.csv, .. G100_1.csv, G100_2.csv, .. G173_1, csv., G173_2, csv., G173_3.csv
where G stands for the group followed by the identification of each group member (1, 2, or 3). Notably, some groups do not have all three members.
What I'm trying to do is to create a loop for running the following code (an example for 1 group) for the entire groups.
i1 <- fread("sample/G085_1.csv")
i2 <- fread("sample/G085_2.csv")
i3 <- fread("sample/G085_3.csv")
What I have been doing is:
Groups <- c()
for(g in 85:173){
Groups[g] <- ifelse(g<100,
paste0("G0", g),
paste0("G", g))
}
Members <- c("i1", "i2", "i3")
for(g in 1:length(Groups)){
for(m in 1:3) {
filename<- paste0("i",m)
wd <- paste0("sample/", Groups[g],"_",
m, ".csv")
ifelse(file.exists(wd),assign(filename,fread(wd)),
function(){})
}
assign(Groups[g],...
)
}
The place that I'm stuck in is the last part (assign(Groups[g]...). I'm not sure what would allow for calling in all the i1, i2, i3 dataframes for each group under the group. Is there a better way than using assign function here?

Answer 1

This code is not exactly assign to i1, i2, i3 but will gave you a list for your work with the Group names assgined to the list items. Each group item is a list contain three data.frame read from the files. In case the file not exists the item will be NULL.
Using foreach approach
library(foreach)
list_data <- foreach(g = Groups, .final = function(x) { setNames(x, Groups) }) %do% {
current_group <- foreach(m = 1:3) %do% {
filename<- paste0("i",m)
wd <- paste0("sample/", Groups[g],"_",
m, ".csv")
data <- ifelse(file.exists(wd) , fread(wd), NULL)
return(data)
}
return(current_group)
}
Using purrr map
library(purrr)
item_index <- c(1:3)
all_group_data <- map(.x = Groups, .f = function(g) {
list_files <- paste0("sample/", g,"_", item_index, ".csv")
group_data <- map(.x = list_files, .f = function(file) {
if (file.exists(file)) {
data <- fread(file)
} else {
data <- NULL
}
data
})
group_data
})
names(all_group_data) <- Groups