shprplotfun: R functions for SHPR annual report

#' Sweden map data set, compressed version
#'
#' A dataset used to create elegant figures of Sweden with ggplot2.
#'
#' @format A data frame with 6564 rows and 5 variables. This is a filtered
#'   version of swe_allpoints where all points with piece equal to "6" or larger
#'   are removed (small islands) and only every thirtieth point being used (see
#'   examples).
#'
#'   \describe{ \item{long}{longitude, numeric} \item{lat}{latitude, numeric}
#'   \item{order}{specifies the order for each point, integer} \item{piece}{"1"
#'   if point belongs to mainland,
#'
#'   "2" if point belongs to Gotland (largest island in Sweden),
#'
#'   "3" if point belongs to Öland,
#'
#'   "4" if point belongs to Orust or Tjörn,
#'
#'   "5" if point belongs to Fårö} \item{group}{Each region in the map is a
#'   polygon where
#'
#'   "1.1" if point belongs to mainland,
#'
#'   "1.2" if point belongs to Gotland (largest island in Sweden),
#'
#'   "1.3" if point belongs to Öland,
#'
#'   "1.4" if point belongs to Orust or Tjörn,
#'
#'   "1.5" if point belongs to Fårö} }
#'
#' @examples
#' # How the data set was created
#'
#' swe_example <- dplyr::filter(swe_allpoints,
#' piece %in% c("1", "2", "3", "4", "5")) %>%
#'   dplyr::filter(order %% 30 == 1) %>%
#'   droplevels()
#'
#' # Example on how to make map of Sweden using ggplot2.
#' # Note that coord_map() is essential for the map to be in actual scale.
#'
#' ggplot2::ggplot(data = swe, ggplot2::aes(x=long, y=lat, group = group)) +
#'   ggplot2::geom_polygon(color = "transparent", fill = "blue")  +
#'   ggplot2::coord_map() +
#'   ggplot2::theme_minimal()
"swe"