How to implement guide with generating random samples in r without replacement using `sample()`
I'm refactoring my project and I'm dealing with I'm trying to generate a set of random samples from a vector in R without replacement, but I'm running into unexpected behavior when the sample size exceeds the number of available unique elements... My code looks like this: ```r set.seed(123) my_vector <- c(1, 2, 3, 4, 5) sample_size <- 6 random_samples <- sample(my_vector, sample_size, replace = FALSE) ``` When I run this, I get the following behavior: `behavior in sample.int(n, size, replace, prob) : want to take a sample larger than the population when 'replace = FALSE'`. However, I expected it to return only the available unique elements. I’ve also tried setting `replace = TRUE`, but that gives me duplicates, which is not what I want. Is there a way to handle cases where the sample size exceeds the vector length but still return all unique elements? Ideally, I'd like a solution that either adjusts the sample size automatically or provides a clear message when the sample size exceeds the population. Any suggestions on best practices for this would be greatly appreciated! What's the best practice here? Is there a better approach? This is part of a larger web app I'm building. Is there a simpler solution I'm overlooking? Thanks for taking the time to read this!