gistfile1.txt

library(dplyr)
library(ggplot2)
library(microbenchmark)
x1 <- bind_rows(lapply(1:10, function(x)iris))
x2 <-data.frame();for(i in 1:10){x2<-rbind(x2,iris)}
all.equal(x1, x2)

f1 <- function(vector){
  bind_rows(lapply(vector, function(x)iris))
}
f2 <- function(vector){
  x2 <-data.frame();
  for(i in vector){
    x2<-rbind(x2,iris)
    }
}
f3 <- function(n){
  iris[rep(1:nrow(iris), n),]
}

microbenchmark(f1(1:20), f2(1:20), f3(20))

#It looks like copying a full dataframe is substantially faster than a complete subset of the dataframe

g1 <- function(vector){
 lapply(vector, function(x)iris)
}

g2 <- function(vector){
 lapply(vector, function(x)iris[1:150, ])
}

microbenchmark(g1(1:20), g2(1:20))