## code to prepare `tourism_monthly` dataset goes here
library(tidyverse)
library(tsibble)
tourism_raw <- read_csv("data-raw/tourism-monthly.csv", skip = 5)
tourism_meta <- tourism_raw %>%
slice(1:2) %>%
select(3:(ncol(tourism_raw) - 1)) %>%
t() %>%
as_tibble(.name_repair = ~ c("Region", "Purpose")) %>%
fill(Region, .direction = "down") %>%
mutate(region_purpose = paste(Region, Purpose, sep = "_"))
tourism_monthly <- tourism_raw %>%
fill(X1, .direction = "down") %>%
filter(X1 != "Total") %>%
slice(4:(n() - 1)) %>%
mutate(Month = yearmonth(paste(X1, `Summation Options`, sep = "-"))) %>%
select(-c(1:2, 311)) %>%
mutate(across(where(is.character), as.numeric)) %>%
rename_with(~ tourism_meta$region_purpose, where(is.numeric)) %>%
pivot_longer(
-c("Month"), names_sep = "_",
names_to = c("Region", "Purpose"), values_to = "Trips"
) %>%
left_join(tourism %>% distinct(State, Region), by = "Region") %>%
relocate(State, .after = Month) %>%
mutate(State = if_else(is.na(State), "Queensland", State)) %>%
as_tsibble(index = Month, key = c(State, Region, Purpose))
usethis::use_data(tourism_monthly, overwrite = TRUE)
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