You can create a choropleth of Countries with the function country_choropleth:

library(choroplethr)

?df_pop_country
data(df_pop_country)

?country_choropleth
country_choropleth(df_pop_country)

As demonstrated above, the only required parameter to country_choropleth is a data.frame. You can see the optional parameters by typing ?country_choropleth.

This map demonstrates another feature of choroplethr: regions for which no value is provided (what is the population of Antarctica?) appear, by default, as black.

Data Requirements

The data.frame that you provide to country_choropleth must have one column named “region” and one column named “value”. Your entries for “region” must exactly match how regions are named in the map which choroplethr uses. These names are defined in the object country.regions:

library(choroplethrMaps)

?country.regions
data(country.regions)
head(country.regions)

       region iso2c
1 afghanistan    AF
2      angola    AO
3  azerbaijan    AZ
4     moldova    MD
5  madagascar    MG
6      mexico    MX

In order to use choroplethr, you must use the naming convention in the “region” column of country.regions. That is, you must use full names in all lowercase letters.

Exploring Data

The country_choropleth function provides two parameters to facilitate exploring data: num_colors and zoom. num_colors defaults to 7, which means that there are 7 colors on the map. An equal number of regions is assigned to each color; a value of 1 uses a continuous scale. zoom defaults to NULL, which means that all states are shown. You can set it to be a vector of valid regions.

As an example, here is how you can use choroplethr to show the population of the US, Canada and Mexico.

country_choropleth(df_pop_country,
                   title = "2012 Population Estimates",
                   legend = "Population",
                   num_colors = 1,
                   zoom = c("united states of america", "mexico", "canada"))

Advanced Options

Any customization outside the optional parameters presented above will require you to create a CountryChoropleth object. choroplethr uses R6 to take advantage of object-oriented programming. Here is an example of using the ggplot2_scale on the base Choropleth object to customize the palette used.

library(ggplot2)

choro = CountryChoropleth$new(df_pop_country)
choro$title = "2012 Population Estimates"
choro$ggplot_scale = scale_fill_brewer(name="Population", palette=2)
choro$render()