So, I have a function:
complete <- function(directory,id = 1:332 ) {
directory <- list.files(path="......a")
g <- list()
for(i in 1:length(directory)) {
g[[i]] <- read.csv(directory[i],header=TRUE)
}
rbg <- do.call(rbind,g)
rbgr <- na.omit(rbg) #reads files and omits NA's
complete_subset <- subset(rbgr,rbgr$ID %in% id,select = ID)
table.rbgr <- sapply(complete_subset,table)
table.rbd <- data.frame(table.rbgr)
id.table <- c(id)
findla.tb <- cbind (id.table,table.rbd)
names(findla.tb) <- c("id","nob")
print(findla.tb) #creates table with number of observations
}
Basically when you call the specific numberic id (say 4), you are suppose to get this output
id nobs
15 328
So, I just need the nobs data to be fed into another function which measures the correlation between two columns if the nobs value is greater than another arbitrarily determined value(T). Since nobs is determined by the value of id, I am uncertain how to create a function that takes into account the output of the other function?
I have tried something like this:
corr <- function (directory, t) {
directory <- list.files(path=".......")
g <- list()
for(i in 1:length(directory)) {
g[[i]] <- read.csv(directory[i],header=TRUE)
}
rbg <- do.call(rbind,g)
g.all <- na.omit(rbg) #reads files and removes observations
source(".....complete.R") #sourcing the complete function above
complete("spec",id)
g.allse <- subset(g.all,g.all$ID %in% id,scol )
g.allnit <- subset(g.all,g.all$ID %in% id,nit )
for(g.all$ID %in% id) {
if(id > t) {
cor(g.allse,g.allnit) #calcualte correlation of these two columns if they have similar id
}
}
#basically for each id that matches the ID in g.all function, if the id > t variable, calculate the correlation between columns
}
complete("spec", 3)
cr <- corr("spec", 150)
head(cr)
I have also tried to make the complete function a data.frame but it does not work and it gives me the following error: error in data.frame(... check.names = false) arguments imply differing number of rows. So, I am not sure how to proceed....