## code to prepare `vehicule_immatricule` dataset goes here
library(conflicted)
library(data.table)
library(purrr)
library(dplyr)
library(tidyr)
library(stringr)
vehicule_immatricule <- list.files("./data-raw/raw", pattern = "^vehicules-immatricules-baac", full.names = TRUE) %>%
map(fread, colClasses = "character", encoding = "UTF-8", na.strings = c("", "NA")) %>%
bind_rows() %>%
as_tibble() %>%
set_names(
c(
"id_accident", "code_alpha", "an", "territoire", "type_accident_old",
"cnit", "categorie_vehicule", "age_vehicule", "type_accident_new"
)
) %>%
mutate(
across(everything(), \(x) na_if(x, "N/A")),
an = as.numeric(an),
id_accident = str_replace_all(string = id_accident, pattern = "\\D", replacement = ""),
across(c(id_accident, age_vehicule), as.numeric)
) %>%
unite(
col = "type_accident", type_accident_old, type_accident_new,
sep = "", remove = TRUE, na.rm = TRUE
)
usethis::use_data(vehicule_immatricule, overwrite = TRUE, compress = "bzip2", ascii = FALSE)
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