Under construction

This package is a collection of data and tools that allows for the easy production of charts.

# install.packages("devtools")
devtools::install_github("ksreyes/gdiviz")

The key function of this package is gdiplot(), which generates a ggplot chart from a list of chart templates. It requires two arguments: code, which determines the variable and chart type to be created, and country, which is the 3-letter ISO code of the country to chart.

library(gdiviz)
gdiplot(code = "stocks", country = "DEU")

gdiplot(code = "popmap", country = "DEU")

gdiplot(code = "idp", country = "DEU")

To see the list of available charts and their respective codes, run gdiplots. Charts can be exported as SVG or PNG files with the export argument. See ?gdiplot for more information on this and other arguments.

The underlying data are bundled with this package and are available to users. Run gdidata to see the list. To check data availability for a country, run check_data(iso), where iso is the 3-letter ISO code.

Datasets are indexed by ISO codes. For the user’s convenience, countryname() can be used to look up the corresponding country name. For example, countryname("DEU") returns “Germany”. The reverse is also possible, with countryname("Germany", from = "name", to = "iso3c") returning “DEU”. Alternatively, run countrynames to see the full list of countries.

The function apply_theme() can be used to apply IOM theming to any ggplot chart. For example:

library(ggplot2)
library(gdiviz)

iris |>
  dplyr::summarise(Sepal.Length = mean(Sepal.Length), .by = Species) |>
  ggplot(aes(x = Species, y = Sepal.Length)) +
  geom_bar(stat = "identity", fill = pal("blues")) +
  ggtitle("The iris dataset") +
  apply_theme("bar-vertical")

Default sizes are optimized for export as an image with width 12 cm at 300 dpi. IOM color palettes are also available using pal(). See function documentation for details.

I wrote this package to make my job easier. Nothing here has the official endorsement of my employer.