在R中删除多个文件中的NA列

Question

I have a large dataset and I used splitting to make the data more approachable. I ended up with ~250 splits. As a result, each split has different number of columns that are empty. I want to remove the empty columns and write the updated files. I am able to do it manually, but as I mentioned, I have roughly 250 splits so I can't do it to all of them.

Below is a reproducible example:

df <- data.frame(Size= c(800, 850, 1100, 1200, 1000), 
                 Value= c(900, NA, 1300, 1100, NA),
                 Location= c(NA, 'midcity', 'uptown', NA, 'Lakeview'),
                 Num1 = c(2, NA, 3, 2, NA),
                 Num2 = c(2,3,3,1,2),
                 Rent= c('y', 'y', 'n', 'y', 'n'))

This is what I have so far.

Splitting:

index <- apply(is.na(df)*1, 1,paste, collapse = "")
s <- split(df, index)
split(df, index)
for (i in 1:length(s)) 
{write.csv(s[i], file = paste0("Splits/", i, "splits.csv"), row.names=FALSE, na = "")}

Removing empty columns:

split <- read.csv("Splits/3splits.csv")
updated_split <- split[,colSums(is.na(split))<nrow(split)]
write.csv(updated_split, file = "updated_3split.csv", row.names=FALSE)

split <- read.csv("Splits/2splits.csv")
updated_split <- split[,colSums(is.na(split))<nrow(split)]
write.csv(updated_split, file = "updated_2split.csv", row.names=FALSE)

split <- read.csv("Splits/1splits.csv")
updated_split <- split[,colSums(is.na(split))<nrow(split)]
write.csv(updated_split, file = "updated_1split.csv", row.names=FALSE)

Is there a way to automate the process above? What I mean by automate is to find a way to remove the empty columns in those three files without repeating the same three lines over and over again (doing it with 250 files isn't really an option).

Edit 1:

Like this?

for (i in 1:length(s))
{
lapply(s, function(x) x[,colSums(is.na(x))<nrow(x)])
write.csv(s[i], file = paste0("Splits/", i, "splits.csv"), row.names=FALSE, na = "")
}

Answer 1

Maybe this:

df <- data.frame(Size= c(800, 850, 1100, 1200, 1000), 
                 Value= c(900, NA, 1300, 1100, NA),
                 Location= c(NA, 'midcity', 'uptown', NA, 'Lakeview'),
                 Num1 = c(2, NA, 3, 2, NA),
                 Num2 = c(2,3,3,1,2),
                 Rent= c('y', 'y', 'n', 'y', 'n'))

index <- apply(is.na(df)*1, 1,paste, collapse = "")
s <- split(df, index)
split(df, index)
for (i in 1:length(s)) 
{
   write.csv(s[i], file = paste0("Splits/", i, "splits.csv"), row.names=FALSE, na = "")
   sdf <- data.frame(s[i])
   updated_split <- sdf[,colSums(is.na(sdf))<nrow(sdf)]
   write.csv(updated_split, file = paste0("updated", i, "split.csv"), row.names=FALSE)
}