Calculate 95th percentile of values with grouping variable

Question

I'm trying to calculate the 95th percentile for multiple water quality values grouped by watershed, for example:

Watershed   WQ
50500101    62.370661
50500101    65.505046
50500101    58.741477
50500105    71.220034
50500105    57.917249

I reviewed this question posted - Percentile for Each Observation w/r/t Grouping Variable. It seems very close to what I want to do but it's for EACH observation. I need it for each grouping variable. so ideally,

Watershed   WQ - 95th
50500101    x
50500105    y

Answer 1

Use a combination of the tapply and quantile functions. For example, if your dataset looks like this:

DF <- data.frame('watershed'=sample(c('a','b','c','d'), 1000, replace=T), wq=rnorm(1000))

Use this:

with(DF, tapply(wq, watershed, quantile, probs=0.95))

Answer 2

I hope I understand your question correctly. Is this what you're looking for?

my.df <- data.frame(group = gl(3, 5), var = runif(15))
aggregate(my.df$var, by = list(my.df$group), FUN = function(x) quantile(x, probs = 0.95))

  Group.1         x
1       1 0.6913747
2       2 0.8067847
3       3 0.9643744

EDIT

Based on Vincent's answer,

aggregate(my.df$var, by = list(my.df$group), FUN = quantile, probs  = 0.95)

also works (you can skin a cat 1001 ways - I've been told). A side note, you can specify a vector of desired -iles, say c(0.1, 0.2, 0.3...) for deciles. Or you can try function summary for some predefined statistics.

aggregate(my.df$var, by = list(my.df$group), FUN = summary)