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This is way more than what you asked for, but I wrote a function called <a href="https://gist.github.com/mrdwab/6424112" rel="nofollow"><code>stratified</code></a> that lets you take random samples from a <code>data.frame</code> by one or more group variables. You can load it and use it like this: <pre><code>library(devtools) source_gist("https://gist.github.com/mrdwab/6424112") # [1] "https://raw.github.com/gist/6424112" # SHA-1 hash of file is 0006d8548785ec8a5651c3dd599648cc88d153a4 ## One row stratified(mydf, "v2", 1) # v1 v2 # 10 E 1 # 8 C 2 ## Two rows stratified(mydf, "v2", 2) # v1 v2 # 2 B 1 # 6 B 1 # 3 C 2 # 5 B 2 </code></pre> <hr> I'll add official documentation to the function at some point, but here's a summary to help you get the best use out of it: The arguments to <code>stratified</code> are: <ul> <li><code>df</code>: The input <code>data.frame</code></li> <li><code>group</code>: A character vector of the column or columns that make up the "strata".</li> <li><code>size</code>: The desired sample size. <ul> <li>If <code>size</code> is a value less than 1, a proportionate sample is taken from each stratum.</li> <li>If <code>size</code> is a single integer of 1 or more, that number of samples is taken from each stratum.</li> <li>If <code>size</code> is a vector of integers, the specified number of samples is taken for each stratum. It is recommended that you use a named vector. For example, if you have two strata, "A" and "B", and you wanted 5 samples from "A" and 10 from "B", you would enter <code>size = c(A = 5, B = 10)</code>.</li> </ul></li> <li><code>select</code>: This allows you to subset the groups in the sampling process. This is a <code>list</code>. For instance, if your <code>group</code> variable was "Group", and it contained three strata, "A", "B", and "C", but you only wanted to sample from "A" and "C", you can use <code>select = list(Group = c("A", "C"))</code>.</li> <li><code>replace</code>: For sampling with replacement.</li> </ul>
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