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August 29, 2015 14:23
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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)) | |
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