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Kara Woo
@karawoo.com
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software engineer |
#rstats
| PDX | she/her
![Screenshot of the following code:
library("dplyr")
library("igraph")
dat <- read.table("input08.txt", sep = ",", col.names = c("x", "y", "z"))
dm <- as.matrix(dist(dat, method = "euclidean"))
xy <- t(combn(rownames(dat), 2))
dm_df <- data.frame(xy, dist = dm[xy]) |>
arrange(dist)
g <- make_empty_graph(n = nrow(dat), directed = FALSE)
## part 1
n <- 1000
for (i in seq_len(n)) {
g <- add_edges(g, c(dm_df[i, "X1"], dm_df[i, "X2"]))
}
prod(head(sort(components(g)$csize, decreasing = TRUE), 3))
## part 2
i <- n # continue where we left off on the loop above
while (!is_connected(g)) {
i <- i + 1
g <- add_edges(g, c(dm_df[i, "X1"], dm_df[i, "X2"]))
}
prod(dat[c(dm_df[i, "X1"], dm_df[i, "X2"]), "x"])](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreihquvl2ftgcfheveeknpwrpndb7bndsmz4bimkynzfegl7fgurlgq)
![Screenshot of the following code:
library("readr")
options(scipen = 9999)
file <- "input07.txt"
dat <- read_fwf(
file,
col_positions = fwf_widths(rep(1, nchar(readLines(file)[1])))
) |>
as.matrix()
count <- 0
tl <- vector(mode = "numeric", length = ncol(dat))
tl[which(dat == "S", arr.ind = TRUE)[, "col"]] <- 1
for (row in seq_len(nrow(dat))) {
for (col in seq_along(dat[row, ])) {
if (dat[row, col] == "^") {
if (tl[col] > 0) {
count <- count + 1
tl[col - 1] <- tl[col - 1] + tl[col]
tl[col + 1] <- tl[col + 1] + tl[col]
tl[col] <- 0
}
}
}
}
## part 1
count
## part 2
sum(tl)](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreicgkh56ikumyer4eupznzx73nfqewy6n5vunrg2q5mdddb36tq7we)
![Screenshot of the following code:
library("readr")
library("purrr")
library("dplyr")
options(scipen = 9999)
file <- "input06.txt"
orig <- readLines(file)
ncol <- length(strsplit(orig[[1]], "\\s+")[[1]])
## part 1
dat1 <- read_fwf(file, n_max = length(orig) - 1) |>
mutate(across(everything(), as.numeric))
ops <- tail(orig, 1) |>
strsplit("\\s+")
ops <- ops[[1]]
math <- function(x, op) {
init <- ifelse(op == "*", 1, 0)
Reduce(function(x, y) do.call(op, as.list(c(x, y))), x = x, init = init)
}
sum(mapply(math, dat1, ops))
## part 2
# read the data in one character per column
dat2 <- read_fwf(file, col_positions = fwf_widths(rep(1, max(nchar(orig)))))
dat2 <- dat2[-nrow(dat2), ]
# split into groups based on where there's a column of all NAs
seps <- map_dbl(dat2, ~ all(is.na(.x)))
splits <- cumsum(c(1, diff(seps) != 0))
split_problems <- split.default(dat2, splits) |>
keep(~ !all(is.na(.x)))
ceph_math <- function(x, op) {
vals <- as.list(x) |>
map(~ paste0(na.omit(.x), collapse = "")) |>
map_dbl(as.numeric)
math(vals, op)
}
sum(mapply(ceph_math, split_problems, ops))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreie3tl2styhiwyx6mxaseod37ttmugl7dt2zsqgtkbmsg5fffj3gle)
![Screenshot of the following code:
dat <- readLines("input05.txt")
ranges <- dat[1:(which(dat == "") - 1)] |>
strsplit("-") |>
lapply(as.numeric)
ingredients <- as.numeric(dat[(which(dat == "") + 1):length(dat)])
## part 1
count <- 0
for (i in ingredients) {
for (j in ranges) {
if (i >= j[1] && i <= j[2]) {
count <- count + 1
break
}
}
}
count
## part 2
sorted_ranges <- ranges[order(sapply(ranges, `[[`, 1))]
highest <- 0
count <- 0
for (i in sorted_ranges) {
if (i[2] <= highest) {
next
} else if (i[1] > highest) {
count <- count + (i[2] - i[1]) + 1
} else {
count <- count + (i[2] - (highest))
}
if (i[2] > highest) {
highest <- i[2]
}
}
count](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreid2r4332uq6xihy3qxgcbnwtutiwlk5vrmkfocnpc2462vuf37hmu)
![Screenshot of the following code:
library("tidyverse")
file <- "input04.txt"
dat <- read_fwf(
file,
col_positions = fwf_widths(rep(1, nchar(readLines(file, n = 1))))
) |>
as.matrix()
oob <- function(x, dat) {
x == 0 | x > max(dim(dat)) # assumes square matrix
}
get_neighbors <- function(row, col, dat) {
x <- row
y <- col
possible <- list(
tl = c(row - 1, col - 1),
t = c(row - 1, col),
tr = c(row - 1, col + 1),
l = c(row, col - 1),
r = c(row, col + 1),
bl = c(row + 1, col - 1),
b = c(row + 1, col),
br = c(row + 1, col + 1)
)
neighbors <- do.call(rbind, possible)
colnames(neighbors) <- c("row", "col")
neighbors[!oob(neighbors[1, ], dat) && !oob(neighbors[2, ], dat), ]
}
is_movable <- function(neighbors, dat) {
sum(dat[as.matrix(neighbors)] == "@") < 4
}
rolls <- which(dat == "@")
rolls_xy <- arrayInd(rolls, dim(dat))
neighbors <- apply(rolls_xy, 1, function(x) get_neighbors(x[1], x[2], dat))
## part 1
neighbors |>
map_lgl(is_movable, dat) |>
sum()
## part 2
clear <- function(rolls, neighbors, dat) {
moved <- neighbors |>
map_lgl(is_movable, dat)
dat[rolls[moved]] <- "."
if (any(moved)) {
clear(rolls[!moved], neighbors[!moved], dat)
} else {
return(dat)
}
}
sum(dat == "@") - sum(clear(rolls, neighbors, dat) == "@")](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreidou7gwksiajgzsmjoxaucz4p3edsnabtzbh742kkdvzqlgol4yim)
![Screenshot of the following code:
library("purrr")
options(scipen = 9999)
dat <- readLines("input03.txt") |>
strsplit("")
joltage <- function(bank, n) {
if (n > 0) {
candidates <- head(bank, length(bank) - n + 1)
i <- which.max(candidates)
paste0(bank[i], joltage(bank[(i + 1):length(bank)], n = n - 1))
}
}
## part 1
map_dbl(dat, ~ as.numeric(joltage(.x, n = 2))) |>
sum()
## part 2
map_dbl(dat, ~ as.numeric(joltage(.x, n = 12))) |>
sum()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreicienemuhrysulljy777fs7iscbrc2kh3fdhxwq7kza2km2bspmpm)
![Screenshot of the following code:
library("stringr")
library("purrr")
dat <- readLines("input02.txt")
# discard any that have more than length/2 unique digits
candidate <- function(val) {
val_str <- str_split(val, "")[[1]]
length(unique(val_str)) <= (length(val_str) / 2)
}
to_check <- str_split(dat, ",")[[1]] |>
str_split("-") |>
map(~ seq(.x[1], .x[2])) |>
unlist() |>
keep(candidate)
## part 1
invalid1 <- function(x) {
x <- str_split(x, "")[[1]]
if (identical(head(x, length(x) / 2), tail(x, length(x) / 2))) {
as.numeric(paste0(x, collapse = ""))
} else {
0
}
}
map_dbl(to_check, invalid1) |>
sum()
## part 2
## divide up string into pieces of length n
split_group_size <- function(string, n) {
x <- str_split(string, "")[[1]]
groups <- ceiling(seq_along(x) / n)
split(x, groups) |>
map(paste0, collapse = "")
}
invalid2 <- function(x) {
for (i in seq_len(nchar(x)) / 2) {
pieces <- split_group_size(x, i)
if (length(unique(unlist(pieces))) == 1) {
return(sum(as.numeric(x)))
}
}
0
}
## it's slowww
map_dbl(to_check, invalid2) |>
sum()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreib26fxkc2w5gh6ovxftt57onr67ozbvnlinvhghgwi5k5bjn6q2ea)
![Screenshot of the following text in green and yellow on a dark background:
[2024] 23*
[2023] 21*
[2022] 15*
[2021] 15*
[2020]
[2019]
[2018]
[2017]
[2016]
[2015]](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreih5caipuc3trzkjhgetx6gdvazge7c4urdseg3y234oz5lchrcqh4)
![Screenshot of the following R code:
library("purrr")
dat <- readLines("input11.txt") |>
strsplit(" ")
dat <- as.numeric(dat[[1]])
change <- function(stone) {
char <- as.character(stone)
if (stone == 0) {
return(1)
} else if (nchar(char) %% 2 == 0) {
return(
c(
as.numeric(substr(char, 1, nchar(char) / 2)),
as.numeric(substr(char, nchar(char) / 2 + 1, nchar(char)))
)
)
} else {
return(stone * 2024)
}
}
blink <- function(dat, times) {
x <- table(dat)
for (i in seq_len(times)) {
tmp <- imap(x, function(x, idx) {
new <- change(as.numeric(idx))
setNames(rep(x, length(new)), new)
}) |>
unname() |>
unlist()
x <- tapply(tmp, names(tmp), sum)
}
x
}
## part 1
sum(blink(dat, 25))
## part 2
sum(blink(dat, 75))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreicon6cjs5qzl76fjplixfprxrqeo226ouuekghw44crojkmvlld5e)
![screenshot of the following R code:
library("readr")
library("tidyverse")
library("igraph")
dat <- read_fwf(
"input10.txt",
col_positions = fwf_widths(rep(1, nchar(readLines("input10.txt", n = 1))))
) |>
as.matrix()
## Create graph where each node is connected to adjacent squares in the matrix
## that have a value of n+1
long_dat <- as.data.frame.table(dat) |>
rename(row = Var1, col = Var2, value = Freq) |>
mutate(id = paste0(row, ",", col))
dat_adj <- expand_grid(x = long_dat$id, y = long_dat$id) |>
left_join(long_dat, by = join_by(x == id)) |>
left_join(long_dat, by = join_by(y == id)) |>
mutate(across(matches("^(row|col)"), as.numeric)) |>
filter(
abs(col.y - col.x) == 1 & row.y == row.x |
abs(row.y - row.x) == 1 & col.y == col.x
) |>
filter(value.y - value.x == 1)
g <- graph_from_data_frame(
dat_adj[, c("x", "y")],
vertices = unique(long_dat[, c("id", "value")])
)
starts <- which(vertex_attr(g, "value") == 0)
## part 1
count_9s <- function(start, g) {
sum(vertex_attr(g, "value", subcomponent(g, start, "out")) == 9)
}
map_dbl(starts, count_9s, g) |>
sum()
## part 2
count_paths <- function(start, g) {
sub <- subcomponent(g, start, "out")
ends <- sub[which(sub$value == 9)]
paths <- 0
if (length(ends) > 0) {
for (i in seq_along(ends)) {
paths <- paths + length(all_simple_paths(g, start, ends[i]))
}
}
paths
}
map_dbl(starts, count_paths, g) |>
sum()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreihb7oztipeu7kvu6gkmkrnudkw4rpcter2nw5tnjjs3zyuintgcyu)
![Screenshot of the following R code:
library("stringr")
library("purrr")
library("gtools")
library("parallel")
library("parallelly")
dat <- readLines("input07.txt") |>
str_split(":?\\s") |>
map(as.numeric)
results <- map(dat, `[[`, 1)
eqs <- map(dat, \(x) x[2:length(x)])
calculate <- function(x, y, fun = c("sum", "prod", "paste0")) {
as.numeric(do.call(fun, list(x, y)))
}
find_true_eq <- function(input, result, operators) {
perms <- permutations(
length(operators),
length(input) - 1,
operators,
repeats.allowed = TRUE
)
for (i in seq_len(nrow(perms))) {
output <- reduce2(input, perms[i, ], calculate)
if (isTRUE(output == result)) {
return(result)
}
}
}
## part 1
p1 <- mapply(
find_true_eq,
eqs,
results,
MoreArgs = list(operators = c("sum", "prod"))
)
sum(unlist(p1))
## part 2
p2 <- mcmapply(
find_true_eq,
eqs,
results,
MoreArgs = list(operators = c("sum", "prod", "paste0")),
mc.cores = availableCores()
)
sum(unlist(p2))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreigvndxagqffcmvraldh6hne2m3c6eenbj5tj2hwdgjwrryzx4qbbq)
![Screenshot of the following R code:
dat <- readLines("input05.txt")
rules <- dat[1:which(dat == "") - 1] |>
strsplit("\\|") |>
lapply(as.numeric)
updates <- dat[(which(dat == "") + 1):length(dat)] |>
strsplit(",") |>
lapply(as.numeric)
is_ok <- function(u, rules) {
for (rule in rules) {
if (isTRUE(which(u == rule[1]) > which(u == rule[2]))) {
return(FALSE)
}
}
TRUE
}
## part 1
sapply(updates, \(x) ifelse(is_ok(x, rules), x[ceiling(length(x) / 2)], 0)) |>
sum()
## part 2
bad <- updates[sapply(updates, \(x) !is_ok(x, rules))]
sum <- 0
for (update in bad) {
for (i in seq_len(length(update) - 1)) {
for (j in 2:length(update)) {
if (!is_ok(update[(j-1):j], rules)) {
update[(j-1):j] <- rev(update[(j-1):j])
}
}
}
sum <- sum + update[ceiling(length(update) / 2)]
}
sum](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreibspp3w4n6di2zfde32r2d5aol4ecgurhmhmnup3hljhoweilyryq)
![Screenshot of the following R code:
library("stringr")
library("readr")
library("purrr")
dat <- read_fwf("input04.txt", col_positions = fwf_widths(rep(1, 140)))|>
as.matrix()
## part 1
## get horizontal, vertical, and diagonal lines in the matrix
h <- apply(dat, 1, paste, collapse = "")
v <- apply(dat, 2, paste, collapse = "")
d1 <- row(dat) - col(dat)
d2 <- row(dat) + col(dat)
diag1 <- split(dat, d1) |> map_chr(paste, collapse = "")
diag2 <- split(dat, d2) |> map_chr(paste, collapse = "")
all_ways <- c(h, v, diag1, diag2)
sum(str_count(all_ways, "XMAS"), str_count(all_ways, "SAMX"))
## part 2
## find the indices of the letter A when it's not in the outer rows & columns
a <- which(dat == "A", arr.ind = TRUE)
a_interior <- a[apply(a, 1, \(x) !any(x %in% c(1, 140))), ]
## get the diagonals crossing each A
get_diagonals <- function(idx, dat) {
rows <- seq(idx["row"] - 1, idx["row"] + 1)
cols <- seq(idx["col"] - 1, idx["col"] + 1)
diags <- list(
mapply(\(x, y) dat[x, y], rows, cols),
mapply(\(x, y) dat[x, y], rows, rev(cols))
)
map_chr(diags, paste, collapse = "")
}
diags <- apply(a_interior, 1, get_diagonals, dat = dat, simplify = FALSE)
sum(map_lgl(diags, \(x) all(x %in% c("MAS", "SAM"))))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreifrh65ionrzfb5egfux3mwalzauunp6f4rra7wg3h5cj5edzgl4bm)
![Screenshot of the following R code:
library("stringr")
library("purrr")
dat <- readLines("input03.txt")
run_program <- function(data) {
str_extract_all(data, "(?<=mul\\()\\d{1,3},\\d{1,3}(?=\\))") |>
unlist() |>
str_split(",") |>
map_dbl(\(x) prod(as.numeric(x))) |>
sum()
}
## part 1
run_program(dat)
## part 2
str_split(paste(dat, collapse = ""), "do\\(\\)")[[1]] |>
str_split_i("(don't\\(\\)|$)", 1) |>
run_program()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreigxgdpb5f7vfvadryg5gxgvafbuadsl22bpblp6shxkbxwc2vjhve)
![Screenshot of the following R code:
library("purrr")
library("stringr")
dat <- readLines("input02.txt") %>%
str_extract_all("\\d+") %>%
map(as.numeric)
safe <- function(x, dampener = FALSE) {
d <- diff(x)
if (length(unique(sign(d))) > 1 || max(abs(d)) > 3 || min(abs(d)) < 1) {
if (dampener) {
return(any(map_lgl(seq_along(x), \(i) safe(x[-i]))))
} else {
return(FALSE)
}
}
TRUE
}
## part 1
sum(map_lgl(dat, safe))
## part 2
sum(map_lgl(dat, safe, dampener = TRUE))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreiepjoeo577pcovmmmk34cwr22l2mmml54ttvc3x7vcllzc4yxamxi)
![Screenshot of the following R code
library("readr")
library("stringr")
dat <- read_lines("input09.txt") %>%
str_split(" ") %>%
lapply(as.numeric)
get_next_val <- function(dat, dir = "forward") {
i <- 1
diffs <- list(dat)
while (!all(diffs[[i]] == 0)) {
i <- i + 1
diffs[[i]] <- diff(diffs[[i - 1]])
}
diffs <- rev(diffs)
for (i in 2:length(diffs)) {
if (dir == "forward") {
diffs[[i]] <- c(diffs[[i]], diffs[[i]][length(diffs[[i]])] + tail(diffs[[i - 1]], 1))
} else {
diffs[[i]] <- c(diffs[[i]][1] - head(diffs[[i - 1]], 1), diffs[[i]])
}
}
if (dir == "forward") {
return(tail(diffs[[length(diffs)]], 1))
} else {
return(head(diffs[[length(diffs)]], 1))
}
}
sum(vapply(dat, get_next_val, numeric(1), dir = "forward"))
sum(vapply(dat, get_next_val, numeric(1), dir = "backward"))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreihjpnqtikho2idqtfqhb3uqtqud4atd5k6gcz3zgtphalfcgl4knu)
![Screenshot of the following R code:
library("readr")
library("stringr")
dat <- read_lines("input06.txt") %>%
str_extract_all("\\d+") %>%
lapply(as.numeric) %>%
setNames(c("time", "duration"))
race_result <- function(duration) {
hold_time <- 0:duration
move_time <- duration - hold_time
hold_time * move_time
}
get_winning_times <- function(poss_results, record) {
sum(poss_results > record)
}
get_answer <- function(dat) {
poss_results <- lapply(dat[["time"]], race_result)
prod(mapply(get_winning_times, poss_results, dat[["duration"]]))
}
## Part 1
get_answer(dat)
## Part 2
dat <- lapply(dat, function(x) as.numeric(paste0(x, collapse = "")))
get_answer(dat)](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreifag3dirzsn7k7nveoep6hhqy4atielr6azt47tzin4nfhpfnt3ym)
![Screenshot of the following R code:
library("readr")
library("stringr")
dat <- read_lines("input06.txt") %>%
str_extract_all("\\d+") %>%
lapply(as.numeric) %>%
setNames(c("time", "duration"))
race_result <- function(hold_time, duration) {
move_time <- duration - hold_time
hold_time * move_time
}
get_possible_results <- function(duration) {
vapply(0:duration, race_result, numeric(1), duration = duration)
}
get_winning_times <- function(poss_results, record) {
sum(poss_results > record)
}
## Part 1
poss_results <- lapply(dat[["time"]], get_possible_results)
prod(mapply(get_winning_times, poss_results, dat[["duration"]]))
## Part 2
dat2 <- lapply(dat, function(x) as.numeric(paste0(x, collapse = "")))
poss_results2 <- get_possible_results(dat2[["time"]])
prod(get_winning_times(poss_results2, dat2[["duration"]]))](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreibsxsuuwsxrd3vhx542w2jv7tgbrzp6jcxg3pxaolvcenswy3hofe)
![library("readr")
library("stringr")
library("purrr")
dat_orig <- read_file("input05.txt") %>%
str_split("\\n+")
dat_orig <- dat_orig[[1]][!dat_orig[[1]] == ""]
split_data <- function(x) {
split_points <- which(c(1, diff(cumsum(str_detect(x, "map")))) == 1)
dat_list <- split(x, cumsum(seq_along(x) %in% split_points))
names(dat_list)[[1]] <- "seeds:"
dat_list[[1]] <- str_remove(dat_list[[1]], "seeds: ")
for (i in 2:length(dat_list)) {
names(dat_list)[[i]] <- dat_list[[i]][[1]]
dat_list[[i]] <- dat_list[[i]][-1]
}
dat_list
}
dat <- dat_orig %>%
split_data() %>%
map(str_split, " +") %>%
map_depth(.depth = 2, as.numeric)
map_input_to_dest <- function(input, map) {
result <- input
for (i in map) {
if (i[[2]] <= input && input <= i[[2]] + i[[3]]) {
result <- i[[1]] + (input - i[[2]])
break
}
}
result
}
results <- vector(mode = "list", length = length(dat))
results[[1]] <- dat[[1]][[1]]
for (i in 2:length(dat)) {
results[[i]] <- vappl](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreibf6iko3d7u7y37w6pzgwln5eszn7b36cy4nt2hmmwiyjxwxyeop4)
![Screenshot of the following R code
library("readr")
library("stringr")
dat <- read_lines("input04.txt")
nums <- str_remove_all(dat, "Card +\\d+: +") %>%
str_split(" \\| +") %>%
lapply(function(x) lapply(str_split(x, " +"), as.numeric))
winning <- lapply(nums, `[[`, 1)
cards <- lapply(nums, `[[`, 2)
## Part 1
score <- function(card, winning) {
any(card %in% winning) * 2^(sum(card %in% winning) - 1)
}
sum(mapply(score, cards, winning))
## Part 2
copies <- rep(1, length(cards))
score2 <- function(copies, i, cards, winning) {
n_copies <- copies[[i]]
n_new <- sum(cards[[i]] %in% winning[[i]])
if (n_new > 0) {
copies[(i+1):(i+n_new)] <- copies[(i+1):(i+n_new)] + n_copies
}
copies
}
for (i in seq_along(copies)) {
copies <- score2(copies, i, cards, winning)
}
sum(copies)](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreiexdhucgxs7ue3q5ooinomrj2t5yjm5cqsmk5aflfresc2pk6r42i)
![Screenshot of the following R code
library("readr")
library("stringr")
library("tidyverse")
dat <- read_lines("input01.txt")
## Part 1
str_extract_all(dat, "[[:digit:]]") %>%
vapply(
function(x) as.numeric(paste(x[1], x[length(x)], sep = "")),
double(1)
) %>%
sum()
## Part 2
char_to_num <- function(x) {
case_when(
x == "one" ~ "1",
x == "two" ~ "2",
x == "three" ~ "3",
x == "four" ~ "4",
x == "five" ~ "5",
x == "six" ~ "6",
x == "seven" ~ "7",
x == "eight" ~ "8",
x == "nine" ~ "9",
TRUE ~ x
)
}
str_match_all(
dat,
"(?=([[:digit:]]|one|two|three|four|five|six|seven|eight|nine))"
) %>%
lapply(function(x) x[, 2]) %>%
lapply(char_to_num) %>%
vapply(function(x) as.numeric(paste0(x[1], x[length(x)])), numeric(1)) %>%
sum()](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:o4tcgqoslmipb3j62vjhrq73/bafkreieqsfjkn7cptzfl25g4gtfi2qyhihevu3sbz7nz4fbeiurwupgdci)
