Day 4 ⋆⋆

Puzzle

https://adventofcode.com/2023/day/4

Solution

Preprocessing

helper1_day4 <- function (vec, strs_to_drop) {
  vec %>% 
    stringr::str_split(" ") %>% 
    map(~.x %>% 
          setdiff(strs_to_drop) %>% 
          as.numeric() %>% 
          .[!is.na(.)]
    )
}
input_df = readr::read_delim(
  "input.txt", 
  delim = "|", 
  col_names = FALSE
)
my_counts <- input_df %>% 
  transmute(
    card = 1:n(),
    winning_numbers = helper1_day4(X1, strs_to_drop = c("Card", "")),
    my_numbers = helper1_day4(X2, strs_to_drop = "")
  ) %>% 
  rowwise() %>% 
  mutate(count = sum(my_numbers %in% winning_numbers)) %>% 
  ungroup()

Part One

answer1 <- sum(ifelse(my_counts$count > 0, 2^(my_counts$count - 1), 0))
answer1

[1] 21821

Part Two

I find tasks like this – “bespoke” rowwise data frame manipulation – to be easier with for loops. Not pretty, but it gets the job done:

tmp1_pt2 <- my_counts %>% 
  mutate(copies = 1)
for (card in 1:nrow(tmp1_pt2)) {
  this_count <- pull(tmp1_pt2[card,], count)
  if (this_count > 0) {
    tmp1_pt2$copies[(card + 1):(card + this_count)] %<>% 
      `+`(tmp1_pt2$copies[card]) ## Syntactic sugar to avoid repeating a long object name
  }
}
answer2 <- sum(tmp1_pt2$copies)
answer2

[1] 5539496