Data sim and set.seed() - r

Question

I've been assigned to create a dataset of simulated patient data in R for an assignment. We've been provided variable names and thats it. I want to be able to get a random sample of 100, and use set.seed() to make it reproducible, but when I run the code, I originally got different sample variables each time I re-open the script, and now it I just get error messages and it won't run
This is what I have:
pulse_data <- data.frame(
group = c(rep("control", "treatment")),
age = sample(c(20:75)),
gender = c(rep("male", "female")),
resting_pulse = sample(c(40:120)),
height_cm = sample(c(140:220))
)
set.seed(30)
pulse_sim <- sample_n(pulse_data, 100, replace = FALSE)
am I missing something fundamental?!
(total beginner, speak to me like an idiot and I might understand :) )
I've tried to sample_n() straight from the dataframe, with the set.seed() and to put set.seed() inside the pulse_sim but to no avail... as for why I get errors now, I'm at my wits end

Answer 1

Realize that pulse_data is created using random data, so each time the script is called, you get random data. After you create it, you set the random seed, so you get the same rows you did the last time you opened the script, but ... the rows have different data. SOLUTION: set the random seed before you define pulse_data.
pulse_data <- data.frame(
group = rep(c("control", "treatment"), length.out=30),
age = sample(c(20:75), size=30),
gender = rep(c("male", "female"), length.out=30),
resting_pulse = sample(c(40:120), size=30),
height_cm = sample(c(140:220), size=30)
)
pulse_sim <- sample_n(pulse_data, 10, replace = FALSE)
I have put that code, plus a simple pulse_sim again (to print it) in a file 74408236.R. (Note that I added length.out and changed your sample size from 100 to 10, for the sake of this demonstration.) I can run this briefly with this shell command (not in R):
$ Rscript.exe 74408236.R
group age gender resting_pulse height_cm
1 treatment 28 female 76 210
2 treatment 24 female 118 140
3 control 44 male 57 141
4 control 70 male 96 184
5 treatment 22 female 87 177
6 control 30 male 50 168
7 control 39 male 56 145
8 treatment 37 female 120 182
9 treatment 20 female 79 181
10 treatment 75 female 98 186
When I run it a few times in a row, I get the same output. For brevity, I'll demonstrate same-ness by showing its MD5 checksum; while MD5 is not the most "secure" (cryptographically), I think this is an easy way to suggest that the output is unlikely to be different. (This is shell-scripting, still not in R.)
$ for rep in $(seq 1 5) ; do Rscript.exe 74408236.R | md5sum; done
0f06ecd84c1b65d6d5e4ee36dea76add -
0f06ecd84c1b65d6d5e4ee36dea76add -
0f06ecd84c1b65d6d5e4ee36dea76add -
0f06ecd84c1b65d6d5e4ee36dea76add -
0f06ecd84c1b65d6d5e4ee36dea76add -
In fact, if I repeat it 100 times, I still see no change. I'll pipe through uniq -c to replace repeated output with the count (first number) and the output (everything else, the checksum).
$ for rep in $(seq 1 100) ; do /mnt/c/R/R-4.1.2/bin/Rscript.exe 74408236.R | md5sum; done | uniq -c
100 0f06ecd84c1b65d6d5e4ee36dea76add -