EpiNow2 (version 1.1.0)

global_map: Generate a global map for a single variable.

Description

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

Usage

global_map(
  data = 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 country variable.

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, which expects the possible values to be "Increasing", "Likely increasing", "Likely decreasing", "Decreasing" or "Unsure".

...

Additional arguments passed to the scale_fill function

Value

A ggplot2 object containing a global map.

Examples

# NOT RUN {
if(requireNamespace("rnaturalearth") & requireNamespace("scales")){
# Example 1 - categorical data
# If values are "Increasing", "Likely increasing" etc (see ?EpiNow2::theme_map), 
# then the default fill scale works
eg_data <- data.table::data.table(variable = c("Increasing", 
                                               "Decreasing", 
                                               "Unsure", 
                                               "Likely decreasing",
                                               "Likely increasing"),
                                  country = c("France", 
                                              "Germany", 
                                              "United Kingdom", 
                                              "Spain",
                                              "Australia") )
# Make variable a factor so the ordering is sensible in the legend
eg_data$variable <- factor(eg_data$variable, levels = c("Decreasing", "Likely decreasing",
                                                        "Unsure", "Likely increasing",
                                                        "Increasing"))
global_map(eg_data, variable = "variable", variable_label = "Direction\nof change")


# Example 2 - numeric data
# numeric data requires scale_fill and a global viridis_palette specified
eg_data$second_variable <- runif(nrow(eg_data))
viridis_palette <- "A"
global_map(eg_data, variable = "second_variable", scale_fill = scale_fill_viridis_c)
}
# }