grouped operations that result in length not equal to 1 or length of group in dplyr

Question

I'm not sure which function to use to do the following:

library(data.table)
dt = data.table(a = 1:4, b = 1:2)

dt[, rep(a[1], 3), by = b]
#   b V1
#1: 1  1
#2: 1  1
#3: 1  1
#4: 2  2
#5: 2  2
#6: 2  2

Both summarise and mutate are unhappy with this length:

library(dplyr)
df = data.frame(a = 1:4, b = 1:2)

df %.% group_by(b) %.% summarise(rep(a[1], 3))
#Error: expecting a single value

df %.% group_by(b) %.% mutate(rep(a[1], 3))
#Error: incompatible size (3), expecting 2 (the group size) or 1

Answer 1

In dplyr version 0.2 you could do this using the do operator:

> df %>% group_by(b) %>% do(data.frame(a = rep(.$a[1], 3)))
#Source: local data frame [6 x 2]
#Groups: b
#
#  b a
#1 1 1
#2 1 1
#3 1 1
#4 2 2
#5 2 2
#6 2 2

Answer 2

While @beginneR's answer does work, it doesn't seem to be a real substitute to the data.table behavior. Consider:

df <- data.frame(a = 1, b = rep(1:1e4, 2))
dt <- data.table(df)
microbenchmark(times=5,
  dt[, rep(a[1], 3), by = b],
  df %>% group_by(b) %>% do(data.frame(a = rep(.$a[1], 3)))
)

has the dplyr implementation >200x slower.

Unit: milliseconds
                                                      expr        min         lq     median         uq
                                dt[, rep(a[1], 3), by = b]   13.14318   13.70248   14.60524   15.26676
 df %>% group_by(b) %>% do(data.frame(a = rep(.$a[1], 3))) 3269.40731 3359.11614 3583.19430 3736.67162

Maybe there is a better way to do this with do that doesn't require calling data.frame each do? Also, the syntax is a bit involved for what is something very simple in data.table.

Otherwise, as per Hadley's issue link, it seems this is expected to be implemented in dplyr in 3.1, which looks to be the next release.