#' Sweden map data set with county included, compressed version
#'
#' @format A data frame with 7,791 rows and 19 variables. This is a filtered
#' version of swe_landsting_allpoints where all points with piece equal to "3"
#' or larger are removed (small details) and only every thirtieth point being
#' used (see examples). Also some example variables are included for example
#' purposes, calculated for 2016 annual report.
#'
#' \describe{
#' \item{NAME_1 }{name of county, character}
#' \item{id }{id of county, character}
#' \item{long }{longitude, numeric}
#' \item{lat }{latitude, numeric}
#' \item{order }{specifies the order for each point, integer}
#' \item{piece }{"1" for the most essential, "2" and more for
#' detailed points (Öland, Orust, and Tjörn included
#' in "2"), factor}
#' \item{group }{Each region or island in the map is a polygon where
#' each level in this variable is a polygon, factor}
#' \item{VARNAME_1 }{alternative name of county, character}
#' \item{cat_eq5d }{Preoperative EQ5D*}
#' \item{cat_eqvas }{Preoperative EQ VAS*}
#' \item{cat_pain }{Preoperative Pain VAS*}
#' \item{cat_eq5d_post }{Postoperative EQ5D*}
#' \item{cat_eqvas_post}{Postoperative EQ VAS*}
#' \item{cat_pain_post }{Postoperative Pain VAS*}
#' \item{cat_sati_post }{Postoperative Satisfaction VAS*}
#' \item{cat_eq5d_dev }{Postoperative adjusted EQ5D*}
#' \item{cat_eqvas_dev }{Postoperative adjusted EQ VAS*}
#' \item{cat_pain_dev }{Postoperative adjusted Pain VAS*}
#' \item{cat_sati_dev }{Postoperative adjusted Satisfaction VAS*}
#' }
#'
#' * Factor variable with 3 levels for counties compared to the interval
#' \eqn{(\mu - \sigma, \mu + \sigma} where \eqn{\mu} and \eqn{\sigma} are the
#' mean and standard deviation for whole Sweden:
#' bad (below the interval), average (within) and good (above).
#'
#' @examples
#' # How swe_landsting_allpoints was filtered
#'
#' swe_example <-
#' dplyr::filter(swe_landsting_allpoints,
#' piece %in% c("1", "2")) %>%
#' 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_landsting,
#' ggplot2::aes(x=long, y=lat, group = group)
#' ) +
#' ggplot2::geom_polygon(color = "transparent", fill = "blue") +
#' ggplot2::coord_map() +
#' ggplot2::theme_minimal()
#'
#' # Example on how to make a nice Sweden map with text guides.
#'
#' ggplot2::ggplot(
#' data = swe_landsting,
#' ggplot2::aes(x=long, y=lat, group = group)
#' ) +
#' ggplot2::geom_polygon(color = "white", size = 0, fill = "grey") +
#' ggplot2::geom_point(
#' data = cnames1,
#' ggplot2::aes(x = long, y = lat, group = NAME_1, shape = NAME_1),
#' size = 6 * 0.352777778,
#' color = "black"
#' ) +
#' ggplot2::scale_shape_manual(
#' values = as.character(1:9),
#' guide = ggplot2::guide_legend(ncol = 1)
#' ) +
#' ggplot2::geom_text(
#' data = cnames2,
#' ggplot2::aes(x = long, y = lat, group = NAME_1, label = as.character(NAME_1)),
#' size = 6 * 0.352777778,
#' color = "black",
#' hjust = 0.5
#' ) +
#' ggplot2::coord_map() +
#' ggplot2::theme_minimal() +
#' ggplot2::xlab("") +
#' ggplot2::ylab("") +
#' ggplot2::theme(
#' plot.title = ggplot2::element_blank(),
#' axis.text = ggplot2::element_blank(),
#' axis.title.x = ggplot2::element_text(size = 8, color = "black"),
#' axis.title.y = ggplot2::element_text(size = 8, color = "black"),
#' panel.grid = ggplot2::element_blank(),
#' panel.background = ggplot2::element_blank(),
#' axis.ticks = ggplot2::element_blank(),
#' legend.text = ggplot2::element_text(size = 6),
#' legend.title = ggplot2::element_blank(),
#' legend.key.height = ggplot2::unit(6, "pt"),
#' legend.key.width = ggplot2::unit(6, "pt"),
#' legend.position = c(-0.13,1),
#' legend.justification = c(0,1),
#' plot.margin = ggplot2::margin(0,0,0,0, unit = "cm")
#' )
"swe_landsting"
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