# Create a sub-folder into which we create files.
dir.create("temp_dir")
setwd("temp_dir")

# Create some files in temp_dir.
sapply(1:10, FUN = function(i) {
  xy <- data.frame(a = rnorm(10), b = rnorm(10), c = rnorm(10))
  write.table(xy, file = sprintf("filename_%s.txt", i), row.names = FALSE, col.names = TRUE)
})

# Find relevant files, you can use pattern to match if folder doesn't contain only
# files in question.
all.files <- list.files(pattern = "filename_")

# Read in all files. do not simplify the result because we'll need it "raw". The
# result is a list.
all.dfs <- sapply(all.files, FUN = read.table, header = TRUE, simplify = FALSE)

# Calculate grand mean of the data.frame.
all.means <- lapply(all.dfs, FUN = function(x) mean(sapply(x, mean)))

# Corce from a list to a vector.
one.mean <- as.numeric(all.means)

# Calculate mean for each column.
mean(one.mean)

# Clean up this example.
setwd("../")
unlink("temp_dir")