expand a series, then fill remaining columns

Question

I am trying to expand a series contained in part of a dataframe and repeat the values in the remaining columns to fill in the new rows. I have a grouping variable that I need to use, and then recombine to have a single dataframe again. Here's an example of what I mean, and how I'd do it piece-wise:

df <- data.frame("group" = c(rep("A",3),rep("B",3)), val=rep(c(1,3,5),2))
values <- data.frame(val=seq(1:5))

df2.a <- df[df$group=="A",]
df3.a <- right_join(df2.a, values, "val")
df3.a$group <- "A"

df2.b <- df[df$group=="B",]
df3.b <- right_join(df2.b, values, "val")
df3.b$group <- "B"

df4 <- rbind(df3.a, df3.b)

Here, df4 is my desired output.

But I'm sure I can be way more efficient using dplyr or some other split-apply-combine approach, though I'm clearly missing something.

Conceptually, this makes sense to me:

df.interp <- df %>%
  group_by(group) %>%
  full_join(x=., y=values, by="val") %>%
  fill(group)

Though I can't complete the last line here because I can't edit the grouping variable. But if I ungroup, then I'm no longer operating on one group at a time, and I fill the new rows (which there aren't enough of) with the wrong value.

I'm sure I'm missing something simple here...what is it?

Answer 1

library(dplyr)
library(tidyr)

df %>% 
  group_by(group) %>% 
  complete(val = min(val):max(val))

# # A tibble: 10 x 2
# # Groups:   group [2]
#    group   val
#    <fct> <dbl>
# 1  A         1
# 2  A         2
# 3  A         3
# 4  A         4
# 5  A         5
# 6  B         1
# 7  B         2
# 8  B         3
# 9  B         4
# 10 B         5

Answer 2

Adding a data.table option.

Define a helper function

f <- function(x) {
  tmp <- range(x)
  tmp[1]:tmp[2]
}

Apply f by group

library(data.table)
out <- setDT(df)[, .(val = f(val)), by=group]
out
#    group val
# 1:     A   1
# 2:     A   2
# 3:     A   3
# 4:     A   4
# 5:     A   5
# 6:     B   1
# 7:     B   2
# 8:     B   3
# 9:     B   4
#10:     B   5