What is the best way to filter a data.frame to only get groups of say size 5?
So my data looks as follows:
require(dplyr)
n <- 1e5
x <- rnorm(n
Here's another dplyr approach you can try
semi_join(dat, count(dat, cat) %>% filter(n == 5), by = "cat")
--
Here's another approach based on OP's original approach with a little modification:
n <- 1e5
x <- rnorm(n)
# Category size ranging each from 1 to 5
cat <- rep(seq_len(n/3), sample(1:5, n/3, replace = TRUE))[1:n]
dat <- data.frame(x = x, cat = cat)
# second data set for the dt approch
dat2 <- data.frame(x = x, cat = cat)
sol_floo0 <- function(dat){
dat <- group_by(dat, cat)
all_ind <- rep(seq_len(n_groups(dat)), group_size(dat))
take_only <- which(group_size(dat) == 5L)
dat[all_ind %in% take_only, ]
}
sol_floo0_v2 <- function(dat){
g <- group_by(dat, cat) %>% group_size()
ind <- rep(g == 5, g)
dat[ind, ]
}
microbenchmark::microbenchmark(times = 10,
sol_floo0(dat),
sol_floo0_v2(dat2))
#Unit: milliseconds
# expr min lq mean median uq max neval cld
# sol_floo0(dat) 43.72903 44.89957 45.71121 45.10773 46.59019 48.64595 10 b
# sol_floo0_v2(dat2) 29.83724 30.56719 32.92777 31.97169 34.10451 38.31037 10 a
all.equal(sol_floo0(dat), sol_floo0_v2(dat2))
#[1] TRUE