Use rle to group by runs when using dplyr

Question

In R, I want to summarize my data after grouping it based on the runs of a variable x (aka each group of the data corresponds to a subset of the data where cons

Answer 1

One option seems to be the use of {} as in:

dat %>%
    group_by(yy = {yy = rle(x); rep(seq_along(yy$lengths), yy$lengths)}) %>%
    summarize(mean(y))
#Source: local data frame [4 x 2]
#
#     yy mean(y)
#  (int)   (dbl)
#1     1     2.0
#2     2     4.5
#3     3     6.0
#4     4     7.0

It would be nice if future dplyr versions also had an equivalent of data.table's rleid function.

---

I noticed that this problem occurs when using a data.frame or tbl_df input but not, when using a tbl_dt or data.table input:

dat %>% 
    tbl_df %>% 
    group_by(yy = with(rle(x), rep(seq_along(lengths), lengths))) %>%
    summarize(mean(y))
Error: cannot coerce type 'closure' to vector of type 'integer'

dat %>% 
    tbl_dt %>% 
    group_by(yy = with(rle(x), rep(seq_along(lengths), lengths))) %>%
    summarize(mean(y))
Source: local data table [4 x 2]

     yy mean(y)
  (int)   (dbl)
1     1     2.0
2     2     4.5
3     3     6.0
4     4     7.0

I reported this as an issue on dplyr's github page.

Answer 2

If you explicitly create a grouping variable g it more or less works:

> dat %>% transform(g=with(rle(dat$x),{ rep(seq_along(lengths), lengths)}))%>%                                   
 group_by(g) %>% summarize(mean(y))
Source: local data frame [4 x 2]

      g mean(y)
  (int)   (dbl)
1     1     2.0
2     2     4.5
3     3     6.0
4     4     7.0

I used transform here because mutate throws an error.