data-raw/locations.R

In aftonsteps/rdew: rdew

## Loads Locations data

locations <-
  readr::read_csv("data-raw/files/Locations.csv") %>%
  make_cols_snake_case() %>%
  dplyr::mutate(spring_foraging =
                  convert_to_na(x = spring_foraging, value = -1),
                summer_foraging =
                  convert_to_na(x = summer_foraging, value = -1),
                fall_foraging =
                  convert_to_na(x = fall_foraging, value = -1),
                winter_foraging =
                  convert_to_na(x = winter_foraging, value = -1),
                spring_fishing =
                  convert_to_na(x = spring_fishing, value = -1),
                summer_fishing =
                  convert_to_na(x = summer_fishing, value = -1),
                fall_fishing =
                  convert_to_na(x = fall_fishing, value = -1),
                winter_fishing =
                  convert_to_na(x = winter_fishing, value = -1),
                artifact_data =
                  convert_to_na(x = artifact_data, value = -1)) %>%
  tidyr::pivot_longer(cols = spring_foraging:artifact_data,
                      names_to = "split_name",
                      values_to = "split_value") %>%
  dplyr::mutate(unnest_me =
                  purrr::map(
                    .x = split_value,
                    .f = column_splitter,
                    column_names = c("object_id", "probability")
                  )) %>%
  tidyr::unnest(unnest_me) %>%
  tidyr::separate(col = split_name,
                  into = c("season", "type"),
                  sep = "_") %>%
  dplyr::relocate(object_id,
                  probability,
                  .after = type) %>%
  dplyr::select(-split_value) %>%
  ## There are NA objects from the pivot, remove them
  tidyr::drop_na(object_id) %>%
  dplyr::mutate(
    dplyr::across(
      c(object_id, probability),
      as.numeric))

usethis::use_data(locations, overwrite = TRUE)