Replicate a procedure: generate m dataframes, each one with a variable that includes random values, and append them, in R

Question

Which is the most efficient way to generate m dataframes, where each one has a variable that includes random values, and append them?

Here's an example:

df <- data.frame(id = 1:10, var = sample(1:500), 10, replace=TRUE)


id var

1  65
2  123
3  42
4  16
5  463
6  129
7  367
8  99
9  489
10 63

If m = 2, two dataframes should be generated and appended, having:

Ronak Shah · Accepted Answer · 2024-05-10 11:35:15Z

2

Put the dataframe to be generated in a function

fun <- function() {
  df <- data.frame(id = 1:10, var = sample(1:500, 10, replace=TRUE))  
  df
}

Then there are multiple ways to call this function m times and bind.

Base R using replicate

m <- 2
do.call(rbind, replicate(m, fun(), simplify = FALSE))

Base R using lapply

do.call(rbind, lapply(seq_len(m),\(x) fun()))

purrr::map_df

purrr::map_df(seq_len(m), ~fun())

answered May 10, 2024 at 11:35

Ronak Shah

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Comments

jblood94 · Accepted Answer · 2024-05-10 12:51:56Z

0

The most efficient way to create a data.frame with those characteristics for an arbitrary m is to avoid appending by creating a single data.frame to begin with:

df <- data.frame(id = 1:10, var = sample(500, 10*m, 1))

answered May 10, 2024 at 12:51

jblood94

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