Create long data format based on strings of sequences defined by colons and concatenated vectors

Question

I have data where the IDs of each observation are numbers stored as sequences usually in the form of X:Y, but sometimes concatenated lists. I would like to tidy the data so each observation has its own row so that I can then use a join function to add more descriptive IDs. Normally I'd use the gather() function from tidyr to do this but I'm having trouble unpacking the IDs as they are characters.

The data looks like this:

example <- data_frame(x = LETTERS[1:3], y = c("Condition 1", "Condition 2", "Condition 3"), z = c("1:3", "4:6", "c(7,9,10)"))

example
# A tibble: 3 × 3
      x           y         z
  <chr>       <chr>     <chr>
1     A Condition 1       1:3
2     B Condition 2       4:6
3     C Condition 3 c(7,9,10)

However these do not work and all produce NA:

as.numeric("1:3")
as.integer("1:3")
as.numeric("c(7,9,10)")
as.integer("c(7,9,10)")

There must be a simple way to do this but I thought one long way might be to extract the numbers and store them as a list first. For the X:Y IDs I could do this by spliting the string at ":" and then creating a sequence from one number to the other like so:

example[1:2,] %>% 
+   separate(z, c("a", "b"), sep = ":") %>% 
+   mutate(a = as.numeric(a), b = as.numeric(b), new = list(seq(a, b)))
Error in eval(expr, envir, enclos) : 'from' must be of length 1

However this did not work.

What I'm aiming for looks like this:

# A tibble: 9 × 3
      x           y     z
  <chr>       <chr> <dbl>
1     A Condition 1     1
2     A Condition 1     2
3     A Condition 1     3
4     B Condition 2     4
5     B Condition 2     5
6     B Condition 2     6
7     C Condition 3     7
8     C Condition 3     9
9     C Condition 3    10

What is the simplest way of achieving it?

Answer 1

We can use tidyverse

library(tidyverse)
example %>%
    group_by(x) %>%
    mutate(z = list(eval(parse(text=z)))) %>%
    unnest
#      x           y     z
#   <chr>       <chr> <dbl>
#1     A Condition 1     1
#2     A Condition 1     2
#3     A Condition 1     3
#4     B Condition 2     4
#5     B Condition 2     5
#6     B Condition 2     6
#7     C Condition 3     7
#8     C Condition 3     9
#9     C Condition 3    10