16: Aunt Sue

library(mistlecode)

ticker <- 
  fread("ticker.txt", sep = ":") |>
  `colnames<-`(c("item", "qty")) |>
  deframe()
sue <-
  readLines("input.txt") |>
  map(\(x) {
    x |>
      str_split_1("[:, ]+") |>
      t() |>
      data.frame()
  }) |>
  bind_rows() |>
  select(-X1) |>
  `colnames<-`(
    c("sue", "item_1", "qty_1", "item_2", "qty_2", "item_3", "qty_3")
  ) |>
  mutate(across(c(sue, starts_with("qty_")), as.integer)) |>
  pivot_longer(
    cols = c(starts_with("item_"), starts_with("qty_")), 
    names_pattern = "(item|qty)_(.+)",
    names_to = c(".value", "sue_item")
  ) |>
  mutate(ticker_qty = ticker[item])

Hmmm. Just need to get the data in longer format then I can group by sue and filter as needed.

Part 1

Only tricky bit was remembering how to pivot longer with multiple columns.

sue |>
  filter(qty == ticker_qty) |>
  filter(n() == 3, .by = sue) |>
  pull(sue) |>
  unique()

[1] 373

Part 2

Not too bad. Just a gross filter and we’re good to go. Oh and don’t forget to put your ! in the right spot :).

sue |>
  filter(
    (item %in% c("cats", "trees") & qty > ticker_qty) |
      (item %in% c("pomeranians", "goldfish") & qty < ticker_qty) |
      (
        (!item %in% c("cats", "trees", "pomeranians", "goldfish") & 
            qty == ticker_qty)
      )
  ) |>
  filter(n() == 3, .by = sue) |>
  pull(sue) |>
  unique()

[1] 260