Advent of Code 2020 Day 6

— Day 6: Custom Customs —

Customs forms are being handed out on the flight and you need to work out who answers yes to how many questions.

For each group, count the number of questions to which anyone answered “yes”. What is the sum of those counts?

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.6
✔ forcats   1.0.1     ✔ stringr   1.6.0
✔ ggplot2   4.0.1     ✔ tibble    3.3.0
✔ lubridate 1.9.4     ✔ tidyr     1.3.1
✔ purrr     1.2.0     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

# read all at once
answers <- read_file("data-2020-06.txt")

Unique letters, by group

# split into elements with double end line
answer_groups <- str_split(answers, "\r\n\r\n")
# names
names(answer_groups) <- c("ans")
# combo each piece
answer_join <- str_remove_all(answer_groups$ans, "\r\n")

# count letters
counters <- function(lett) {
  sum(str_count(lett, letters) > 0)
}


# apply
count_answers <- map(answer_join, counters)
# reduce
Reduce(`+`, count_answers)

[1] 6504

— Part Two —

We don’t have to work out any person answered yes, we have to count all who answered yes.

For each group, count the number of questions to which everyone answered “yes”. What is the sum of those counts?

count_groups <- function(lett, num) {
  sum(str_count(lett, letters) == num)
}

# part two
answer_split <- str_split(answer_groups$ans, "\r\n")

ans_tbl_rev <- tibble(
                      long_str = answer_join, 
                      ans_piece = answer_split
                     ) %>% 
              mutate(grp_len = lengths(ans_piece), 
                     grp_cnt = map2_dbl(long_str, grp_len, count_groups))
  
Reduce(`+`, ans_tbl_rev$grp_cnt)

[1] 3351

Tibble calculations

ans_tbl <- tibble(ans = answer_split) %>% 
  mutate(grp = row_number()) %>% 
  unnest_longer(ans) %>% 
  mutate(cnt = map(ans, str_count, letters)) %>% 
  nest(data = c("ans", "cnt"))

ans_tbl$num <- 0

for (n in seq_len(nrow(ans_tbl))) {
  tt = ans_tbl$data[[n]]$cnt
  x = tt[[1]]
  if (length(tt) > 1) {
    for (m in seq(2, length(tt))) {
      y = tt[[m]]
      x = bitwAnd(x, y)
    }  
  }
  ans_tbl$num[[n]] = sum(x)
}

# part two answer
sum(ans_tbl$num)

[1] 3351

Another strategy for part two

# part two type 2
split_ans <- function(aa) {
  ans_collect = NULL
  for (i in seq_len(length(aa))) {
    ans_each = str_split(aa[[i]], pattern = "")
    # print(ans_each[[1]])
    if (i == 1) {
      ans_collect = ans_each[[1]]
    } else {
      ans_collect = intersect(ans_collect, ans_each[[1]])
    }
  }
  
  return(glue::glue_collapse(ans_collect))
}

ans_tbl <- tibble(ans = answer_split) %>% 
  mutate(ans_v = map(ans, split_ans), 
         cnt = map(ans_v, counters))


Reduce(`+`, ans_tbl$cnt)

[1] 3351