#' Load the relevant occurrence data
#' @param min_occurrences The minimum number of occurrences per species.
#' @param min_species The minimum number of species recorded at the combination
#' of location and year.
#' @export
#' @importFrom assertthat assert_that is.count
#' @importFrom dplyr filter group_by inner_join n transmute ungroup
#' @importFrom git2rdata read_vc
#' @importFrom tidyr pivot_wider
load_relevant <- function(min_occurrences = 1000, min_species = 3) {
assert_that(is.count(min_occurrences), is.count(min_species))
read_vc("occurrence", system.file(package = "ladybird")) %>%
group_by(.data$taxon_key) %>%
filter(n() >= min_occurrences) %>%
group_by(.data$location, .data$year) %>%
filter(n() >= min_species) %>%
group_by(.data$taxon_key) %>%
filter(n() >= min_occurrences) %>%
group_by(.data$location, .data$year) %>%
filter(n() >= min_species) %>%
ungroup() %>%
inner_join(
read_vc("species", system.file(package = "ladybird")),
by = "taxon_key"
) %>%
transmute(
.data$year, .data$location, species = .data$code, observed = 1L
) %>%
pivot_wider(
names_from = .data$species, values_from = .data$observed, values_fill = 0L
)
}
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