r - how to fill in values on stepped data hierarchy - r

Question

Is there an elegant/tidy way to fill in the data if there are non-null values to the right? I have a wonky work-around but wanted to know if there was a nice dplyr way to do this.
actual <-
tibble(
a = c("A", NA, NA, NA, NA, NA, NA, "B", NA, NA, NA),
b = c(NA, "A", NA, NA, NA, "C", NA, NA, "E", NA, NA),
c = c(NA, NA, "B", NA, NA, NA, "D", NA, NA, "F", "G"),
d = c(NA, NA, NA, "C", "D", NA, NA, NA, NA, NA, NA)
)
desired <-
tibble(
w = c("A", "A", "A", "A", "A", "A", "A", "B", "B", "B", "B"),
x = c(NA, "A", "A", "A", "A", "C", "C", NA, "E", "E", "E"),
y = c(NA, NA, "B", "B", "B", NA, "D", NA, NA, "F", "G"),
z = c(NA, NA, NA, "C", "D", NA, NA, NA, NA, NA, NA)
)

Answer 1

We can use fill from tidyr together with dplyr like the following.
library(dplyr)
library(tidyr)
dat <- actual %>%
fill(a) %>%
group_by(a) %>%
fill(b) %>%
group_by(b) %>%
fill(c) %>%
group_by(c) %>%
fill(d) %>%
ungroup()
print(dat)
# # A tibble: 11 x 4
# a b c d
# <chr> <chr> <chr> <chr>
# 1 A NA NA NA
# 2 A A NA NA
# 3 A A B NA
# 4 A A B C
# 5 A A B D
# 6 A C NA NA
# 7 A C D NA
# 8 B NA NA NA
# 9 B E NA NA
# 10 B E F NA
# 11 B E G NA