r - Sample n random rows per group in a dataframe

From these questions - Random sample of rows from subset of an R dataframe & Sample random rows in dataframe I can easily see how to randomly sample (select) 'n' rows from a df, or 'n' rows that originate from a specific level of a factor within a df.

Here are some sample data:

df <- data.frame(matrix(rnorm(80), nrow=40))
df$color <-  rep(c("blue", "red", "yellow", "pink"), each=10)

df[sample(nrow(df), 3), ] #samples 3 random rows from df, without replacement.

To e.g. just sample 3 random rows from 'pink' color - using library(kimisc):

library(kimisc)
sample.rows(subset(df, color == "pink"), 3)

or writing custom function:

sample.df <- function(df, n) df[sample(nrow(df), n), , drop = FALSE]
sample.df(subset(df, color == "pink"), 3)

However, I want to sample 3 (or n) random rows from each level of the factor. I.e. the new df would have 12 rows (3 from blue, 3 from red, 3 from yellow, 3 from pink). It's obviously possible to run this several times, create newdfs for each color, and then bind them together, but I am looking for a simpler solution.

Answer

You can assign a random ID to each element that has a particular factor level using ave. Then you can select all random IDs in a certain range.

rndid <- with(df, ave(X1, color, FUN=function(x) {sample.int(length(x))}))
df[rndid<=3,]

This has the advantage of preserving the original row order and row names if that's something you are interested in. Plus you can re-use the rndid vector to create subset of different lengths fairly easily.