Generate a country map for a single variable.

This general purpose function can be used to generate a country map for a single variable. It has few defaults but the data supplied must contain a region_code variable for linking to mapping data. This function requires the installation of the rnaturalearth package.

country_map(
  data = NULL,
  country = NULL,
  variable = NULL,
  variable_label = NULL,
  trans = "identity",
  fill_labels = NULL,
  scale_fill = NULL,
  ...
)

Arguments

data	Dataframe containing variables to be mapped. Must contain a region_code variable.
country	Character string indicating the name of the country to be mapped.
variable	A character string indicating the variable to map data for. This must be supplied.
variable_label	A character string indicating the variable label to use. If not supplied then the underlying variable name is used.
trans	A character string specifying the transform to use on the specified metric. Defaults to no transform ("identity"). Other options include log scaling ("log") and log base 10 scaling ("log10"). For a complete list of options see ggplot2::continous_scale.
fill_labels	A function to use to allocate legend labels. An example (used below) is scales::percent, which can be used for percentage data.
scale_fill	Function to use for scaling the fill. Defaults to a custom ggplot2::scale_fill_manual
...	Additional arguments passed to the scale_fill function

Value

A ggplot2 object containing a country map.

Examples

country_map
#> function (data = NULL, country = NULL, variable = NULL, variable_label = NULL, 
#>     trans = "identity", fill_labels = NULL, scale_fill = NULL, 
#>     ...) 
#> {
#>     if (is.null(variable_label)) {
#>         variable_label <- variable
#>     }
#>     country <- rnaturalearth::ne_countries(scale = "large", country = country, 
#>         returnclass = "sf")
#>     regions <- rnaturalearth::ne_states(country, returnclass = "sf")
#>     data <- data.table::as.data.table(date)[, `:=`(provnum_ne, 
#>         region_code)]
#>     regions_with_data <- merge(regions, data, by = c("provnum_ne"), 
#>         all.x = TRUE)
#>     if (is.null(fill_labels)) {
#>         fill_labels <- ggplot2::waiver()
#>     }
#>     map <- ggplot(regions_with_data) + ggplot2::geom_sf(aes(fill = .data[[variable]]), 
#>         col = "white", alpha = 0.8, size = 0.2) + ggplot2::geom_sf(data = country, 
#>         col = "darkgrey", fill = NA, alpha = 1, size = 0.4)
#>     map <- EpiNow::theme_map(map, continuous = is.numeric(regions_with_data[[variable]]), 
#>         variable_label = variable_label, trans = trans, fill_labels = fill_labels, 
#>         scale_fill = NULL, breaks = levels(regions_with_data[[variable]]), 
#>         ...)
#>     return(map)
#> }
#> <bytecode: 0x10f1682b8>
#> <environment: namespace:EpiNow>