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I've got a following list:

> list(c(3, 4, 5, 8), c(2, 6, 9, 10), c(1, 7))

[[1]]

[1] 3 4 5 8



[[2]]

[1]  2  6  9 10



[[3]]

[1] 1 7

So we can say that 3 belongs to group 1, 6 belongs to group 2, 7 belongs to group 3 and so on. I need a reverse mapping, i.e. to every number I want to have a group id that it belongs to (see expected output):

> list(3, 2, 1, 1, 1, 2, 3, 1, 2, 2)

[[1]]

[1] 3



[[2]]

[1] 2



[[3]]

[1] 1



[[4]]

[1] 1



[[5]]

[1] 1



[[6]]

[1] 2



[[7]]

[1] 3



[[8]]

[1] 1



[[9]]

[1] 2



[[10]]

[1] 2

I thought purrr::transpose should do the job but it doesn't exactly do what I intend, is it? How can it be done?

PS. Ultimately, I need just a vector of a form: 3 2 1 1 1 2 3 1 2 2, but having above I think unlist() is enough to convert.

Here is a base solution ...

list <- list(c(3, 4, 5, 8), c(2, 6, 9, 10), c(1, 7))



rep(1:length(list), sapply(list, length))[order(unlist(list))]

Can I suggest an old-fashioned loop:

# your list

x <- list(c(3, 4, 5, 8), c(2, 6, 9, 10), c(1, 7))

# the data in the list as vector

num <- unlist( x )

# the variable that will be the position vector

pos <- NULL



# loop through the possible position, see which number it contains

# find which "group it belongs to, and add that finding to the position vector

for( i in 1:length( num ) )

    for( j in  1:length( x ) )

        if( i %in% x[[j]] ) pos <- c( pos, j )



pos

[1] 3 2 1 1 1 2 3 1 2 2

Also in base, something like this

L <- as.list(setNames( rep(1:length(lengths(l)), lengths(l)), unlist(l)))

# if wanted, sort it with

L[as.character(sort(as.integer(names(L))))]

# if wanted, unname with

unname(L)

with l <- list(c(3, 4, 5, 8), c(2, 6, 9, 10), c(1, 7)).

Or wrapped in a function

list_inside_out <- function (l, unName = TRUE) { 

  l2 <- lengths(l)

  out <- as.list(setNames(rep(1:length(l2), l2), unlist(l)))

  out <- out[as.character(sort(as.integer(names(out))))] 

  if (unName) return(unname(out))

  out

}

list_inside_out(l)

# [[1]]

# [1] 3

# 

# [[2]]

# [1] 2

# 

# [[3]]

# [1] 1

# ...

Check this solution:

library(tidyverse)

library(magrittr)

library(wrapr)



list(c(3, 4, 5, 8), c(2, 6, 9, 10), c(1, 7)) %.>%

  tibble(x = .) %>%

  mutate(rn = row_number()) %>%

  unnest() %>%

  arrange(x) %$%

  set_names(rn, x) %>%

  as.list()

x <- list(c(3, 4, 5, 8), c(2, 6, 9, 10), c(1, 7))

Following 3 forms will get the same outputs:

library(tidyverse)



# (1)

x %>% set_names(1:3) %>% stack %>% arrange(values) %>% select(ind)



# (2)

x %>% enframe %>% unnest %>% arrange(value) %>% select(name)



# (3)

x %>% (reshape2::melt) %>% arrange(value) %>% select(L1)

A solution using purrr. dat2 is the final output, an integer vector.

dat <- list(c(3, 4, 5, 8), c(2, 6, 9, 10), c(1, 7))



library(purrr)



dat2 <- dat %>%

  imap(~set_names(.x, rep(.y, length(.x)))) %>%

  unlist() %>%

  sort() %>%

  names() %>%

  as.integer()

dat2

# [1] 3 2 1 1 1 2 3 1 2 2