Expanding data frame using tidyverse

Question

Here's an example of what I'm trying to do:

df <- data.frame(
  id = letters[1:5],
  enum_start = c(1, 1, 1, 1, 1),
  enum_end = c(1, 5, 3, 7, 2)
)

df2 <- df %>%
  split(.$id) %>%
  lapply(function(x) cbind(x, hello = seq(x$enum_start, x$enum_end, by = 1L))) %>%
  bind_rows
df2
#     id enum_start enum_end hello
# 1   a          1        1  1
# 2   b          1        5  1
# 3   b          1        5  2
# 4   b          1        5  3
# 5   b          1        5  4
# 6   b          1        5  5
# 7   c          1        3  1
# 8   c          1        3  2
# 9   c          1        3  3
# 10  d          1        7  1
# 11  d          1        7  2
# 12  d          1        7  3
# 13  d          1        7  4
# 14  d          1        7  5
# 15  d          1        7  6
# 16  d          1        7  7
# 17  e          1        2  1
# 18  e          1        2  2

Note that the starting and ending values for hello depend on the data and hence the number of rows for each id is dynamic. I'm looking for a solution that involves maybe expand from tidyr but am struggling.

Answer 1

Here is a base R method that produces the desired output.

dfNew <- within(df[rep(seq_len(nrow(df)), df$enum_end), ],
                hello <- sequence(df$enum_end))

sequence will return the natural numbers and takes a vector that allows for repeated recounting. It is used to produce the "hello" variable. within reduces typing and returns a modified data.frame. I fed it an expanded version of df where rows are repeated using rep and [.

dfNew
    id enum_start enum_end hello
1    a          1        1     1
2    b          1        5     1
2.1  b          1        5     2
2.2  b          1        5     3
2.3  b          1        5     4
2.4  b          1        5     5
3    c          1        3     1
3.1  c          1        3     2
3.2  c          1        3     3
4    d          1        7     1
4.1  d          1        7     2
4.2  d          1        7     3
4.3  d          1        7     4
4.4  d          1        7     5
4.5  d          1        7     6
4.6  d          1        7     7
5    e          1        2     1
5.1  e          1        2     2

Answer 2

Here's a dplyr/tidyr approach

group_by(df, id) %>% 
  expand(enum_start, enum_end, hello = full_seq(enum_end:enum_start, 1))

Not sure if there's a tidyr-way without grouping the data (would be interesting to know)