column merge and split

library(pipeR)
library(plyr)
library(dplyr)
library(tidyr)

# data generation (csv_files就是你的ldf)
num_csv <- 3e3
num_xlvls <- 30
num_ylvls <- 30
timePoints <- expand.grid(paste0("a", 1:num_xlvls),
                          paste0("b", 1:num_ylvls),
                          stringsAsFactors = FALSE)
csv_files <- lapply(1:num_csv, function(i){
  dat <- sample(1:nrow(timePoints), sample(400:600, 1)) %>>%
    rep(each = 5) %>>% (timePoints[., ]) %>>%
    modifyList(setNames(lapply(1:3, function(j){
      sample(1:100, nrow(.), TRUE)
    }), paste0("Var", 3:5))) %>>% tbl_df
})

# 整併 + 分開
st <- proc.time()
outRes1 <- lapply(csv_files, function(subdf){
  nest(subdf, -Var1, -Var2) %>>%
    mutate(data = lapply(data, function(x){
      as.matrix(x) %>>% t %>>% as.vector %>>% paste(collapse = ";")
    })) %>>% unnest(data) %>>% separate(data, paste0("V", 1:15)) %>>%
    mutate_each(funs(as.integer(.)), -Var1, -Var2)
}) %>>% bind_rows
proc.time() - st
#   user  system elapsed
# 263.93    0.02  265.86

st <- proc.time()
outRes2 <- lapply(csv_files, function(subdf){
  subdf %>>% gather(vars, values, -Var1, -Var2) %>>%
    group_by(Var1, Var2) %>>%
    summarise(tmp = paste(values, collapse = ";")) %>>% ungroup %>>%
    separate(tmp, paste0("V", 1:15)) %>>%
    mutate_each(funs(as.integer(.)), -Var1, -Var2)
}) %>>% bind_rows
proc.time() - st
#  user  system elapsed
# 70.01    0.00   70.25

library(data.table)
st <- proc.time()
outRes3 <- lapply(csv_files, function(subdf){
  subdf %>>% data.table %>>% melt(c("Var1", "Var2")) %>>%
    `[`( , list(tmp = paste(value, collapse = ";")), by = c("Var1", "Var2")) %>>%
    `[`( , `:=`(paste0("V", 1:15), tstrsplit(tmp, ";"))) %>>%
    `[`( , tmp := NULL) %>>%
    `[`( , `:=`(paste0("V", 1:15), lapply(.SD, as.integer)), .SDcols = V1:V15)
}) %>>% rbindlist
proc.time() - st
#  user  system elapsed
# 37.35    1.30   38.16