colMeans(df) is same map_dbl(df,mean) ?

[Rsky]

I'm learning purrr.
I now know that furrr executes functions on multiple cores(because fast).
I don't understand what Benefits of purrr.

For example, if I had this data,

df <- tibble(
  a = rnorm(100000000),
  b = rnorm(100000000),
  c = rnorm(100000000),
  d = rnorm(100000000)
)

They all have the same execution time.

library(tictoc)
library(robustbase)

output <- vector("double", length(df))
for (i in seq_along(df)) {
  output[[i]] <- median(df[[i]])
}

colMedians(as.matrix(df))

map_dbl(df, median)

Can you tell me the geeky differences inside these calculators?

I've heard that map is implemented in C and is a bit faster, but can't you feel this level of speed?
The other possible advantage is that the code is easier to read once you get used to it?

thank you

[martin.R]

colMeans() is written in C, you can check the code.

There is essentially no difference between using colMeans(df) and purrr::map_dbl(df, mean) except that the latter has a tiny bit of additional overhead.

[Rsky]

@martin.R

Thank you !