R/country_colors.R

In gapminder: Data from Gapminder

#' Gapminder color schemes.
#'
#' Color schemes for the countries and continents in the Gapminder data.
#'
#' @aliases continent_colors
#' @format Named character vectors giving country and continent colors:
#' \describe{
#'   \item{country_colors}{colors for the 142 countries}
#'   \item{continent_colors}{colors for the 5 continents}
#'   }
#' @seealso [`gapminder`] for a description of the dataset
#' @examples
#' # ggplot2 examples are below these base graphics examples!
#'
#' # using country_colors with base graphics
#'
#' # for convenience, integrate the country colors into the data.frame
#' gap_with_colors <-
#'   data.frame(gapminder,
#'     cc = I(country_colors[match(
#'       gapminder$country,
#'       names(country_colors)
#'     )])
#'   )
#'
#' # bubble plot, focus just on Africa and Europe in 2007
#' keepers <- with(
#'   gap_with_colors,
#'   continent %in% c("Africa", "Europe") & year == 2007
#' )
#' plot(lifeExp ~ gdpPercap, gap_with_colors,
#'   subset = keepers, log = "x", pch = 21,
#'   cex = sqrt(gap_with_colors$pop[keepers] / pi) / 1500,
#'   bg = gap_with_colors$cc[keepers]
#' )
#'
#' if (require(ggplot2)) {
#'   # with ggplot2, just provide country_colors to scale_color_manual():
#'   # ... + scale_color_manual(values = country_colors) + ...
#'
#'   # simple line plot for 5 countries
#'   h_countries <- c("Egypt", "Haiti", "Romania", "Thailand", "Venezuela")
#'   h_dat <- droplevels(subset(gapminder, country %in% h_countries))
#'   h_dat$country <- with(h_dat, reorder(country, lifeExp, max))
#'   ggplot(h_dat, aes(x = year, y = lifeExp)) +
#'     geom_line(aes(color = country)) +
#'     scale_colour_manual(values = country_colors) +
#'     guides(color = guide_legend(reverse = TRUE))
#'
#'   # spaghetti plot for lots of countries
#'   ggplot(
#'     subset(gapminder, continent != "Oceania"),
#'     aes(x = year, y = lifeExp, group = country, color = country)
#'   ) +
#'     geom_line(lwd = 1, show_guide = FALSE) +
#'     facet_wrap(~continent) +
#'     scale_color_manual(values = country_colors) +
#'     theme_bw() +
#'     theme(strip.text = element_text(size = rel(1.1)))
#'
#'   # bubble plot for lots of countries
#'   gap_bit <- subset(gapminder, year == 2007 & continent != "Oceania")
#'   gap_bit <- gap_bit[with(gap_bit, order(continent, -1 * pop)), ]
#'   ggplot(gap_bit, aes(x = gdpPercap, y = lifeExp, size = pop)) +
#'     scale_x_log10(limits = c(150, 115000)) +
#'     ylim(c(16, 96)) +
#'     geom_point(pch = 21, color = "grey20", show_guide = FALSE) +
#'     scale_size_area(max_size = 40) +
#'     facet_wrap(~continent) +
#'     coord_fixed(ratio = 1 / 43) +
#'     aes(fill = country) +
#'     scale_fill_manual(values = country_colors) +
#'     theme_bw() +
#'     theme(strip.text = element_text(size = rel(1.1)))
#' }
#'
"country_colors"