相关疑难解决方法(0)

采取以下行动的惯用方式是什么data.table？

library(dplyr)
df %>% 
  group_by(b) %>% 
  slice(1:10)

我可以

library(data.table)
df[, .SD[1:10]
   , by = b]

但这似乎要慢得多。有没有更好的办法？

set.seed(0)
df <- rep(1:500, sample(500:1000, 500, T)) %>% 
        data.table(a = runif(length(.))
                  ,b = .)

f1 <- function(df){
  df %>% 
    group_by(b) %>% 
    slice(1:10)
}
f2 <- function(df){
  df[, .SD[1:10]
     , by = b]
}

library(microbenchmark)
microbenchmark(f1(df), f2(df))
#Unit: milliseconds
#   expr      min       lq      mean   median        uq      max neval
# f1(df) 17.67435 19.50381  22.06026 20.50166  21.42668  78.3318   100
# f2(df) 69.69554 79.43387 119.67845 88.25585 …