R/ppendemic_data.R

In ppendemic: A Glimpse at the Diversity of Peru's Endemic Plants

#' ppendemic_tab14: Endemic Plant Database of Peru
#'
#' The ppendemic_tab14 dataset is a tibble (data frame) that provides easy access
#' to a comprehensive database of Peru's endemic plant species. It contains a total
#' of 7,898 records with essential botanical information, including the accepted
#' name, accepted family, genus, species, infraspecific information, taxon authors,
#' primary author, place of publication, volume and page, publication years, and
#' version details.
#'
#' @format A tibble (data frame) with 7,898 rows and 18 columns:
#'   \describe{
#'     \item{taxon_name}{Character vector. The accepted name of the endemic
#'     plant species.}
#'     \item{taxon_status}{Character vector. The taxonomic status of the species
#'     (e.g., "Accepted").}
#'     \item{family}{Character vector. The family of the accepted name
#'     of the endemic plant species.}
#'     \item{genus}{Character vector. The genus of the endemic plant species.}
#'     \item{species}{Character vector. The specific epithet of the endemic
#'     plant species.}
#'     \item{infraspecific_rank}{Character vector. The infraspecific rank
#'     (e.g., "subsp.", "var.") when applicable.}
#'     \item{infraspecies}{Character vector. The infraspecific epithet when
#'     applicable.}
#'     \item{taxon_authors}{Character vector. The author(s) of the accepted
#'     name of the endemic plant species.}
#'     \item{primary_author}{Character vector. The primary author(s) of the
#'     publication containing the endemic plant species information.}
#'     \item{place_of_publication}{Character vector. The place of publication of
#'     the endemic plant species information.}
#'     \item{volume_and_page}{Character vector. The volume and page number of the
#'     publication containing the endemic plant species information.}
#'     \item{first_published}{Character vector. The first published year of the
#'     publication containing the endemic plant species information.}
#'     \item{year_actual}{Numeric vector. The actual year of publication extracted
#'     from first_published.}
#'     \item{year_nominal}{Numeric vector. The nominal year of publication extracted
#'     from first_published.}
#'     \item{both_years}{Character vector. Both actual and nominal years when
#'     different, extracted from first_published.}
#'     \item{has_different_years}{Logical vector. Indicates whether the actual
#'     and nominal publication years differ (TRUE when both_years contains the
#'     pattern "YYYY|YYYY").}
#'     \item{version}{Character vector. The version identifier "V-14" of the
#'     ppendemic database.}
#'     \item{version_date}{Character vector. The version date "28-05-2025"
#'     indicating when this version was created.}
#'   }
#'
#' @details The dataset provides a curated and up-to-date collection of Peru's
#' endemic plant species, gathered from reputable botanical sources and publications.
#' The data for this database was extracted and compiled from the World Checklist
#' of Vascular Plants (WCVP) database, which is a comprehensive and reliable
#' repository of botanical information.
#'
#' This version (ppendemic_tab14) includes enhanced temporal information with
#' separate numeric fields for actual and nominal publication years. This allows for more
#' precise bibliographic tracking and citation accuracy. The dataset also includes
#' improved infraspecific taxonomy handling with dedicated fields for ranks and
#' epithets.
#'
#' The year extraction process uses sophisticated pattern matching to distinguish
#' between actual publication years and nominal years, with the has_different_years
#' field automatically flagging records where these differ. This is particularly
#' important for historical botanical publications where publication delays were
#' common.
#'
#'
#' @source The dataset has been carefully compiled and updated to offer the latest
#' insights into Peru's endemic plant species. The data is sourced from the World
#' Checklist of Vascular Plants (WCVP) database, an international collaborative
#' programme initiated in 1988 by Rafaël Govaerts that provides high-quality
#' expert-reviewed taxonomic data on all vascular plants.
#'
#' For detailed methodology, see Govaerts et al. (2021) "The World Checklist of
#' Vascular Plants, a continuously updated resource for exploring global plant
#' diversity" in Nature Scientific Data.
#'
#'
#' @examples
#'
#' # Load the package
#' library(ppendemic)
#'
#' # Access the dataset
#' data("ppendemic_tab14")
#'
#' # View the structure of the dataset
#' str(ppendemic_tab14)
#'
#' # View first few rows
#' head(ppendemic_tab14)
#'
#' # Check for species with different actual and nominal years
#' different_years <- subset(ppendemic_tab14, has_different_years == TRUE)
#' nrow(different_years)
#'
#' # View records with both years information
#' head(ppendemic_tab14$both_years[ppendemic_tab14$has_different_years])
#'
#'
#' @keywords dataset
#'
"ppendemic_tab14"