File:Countries by Military expenditures (% of GDP) in 2014 v2.svg

library(magrittr)

selectedYear <- 2014

getWorldBankData <- function(indicatorCode, indicatorName) {
    baseName <- paste('API', indicatorCode, 'DS2_en_csv_v2', sep='_')
    ## Download zipfile if necessary
    zipfile <- paste(baseName, 'zip', sep='.')
    if (!file.exists(zipfile)) {
        zipurl <- paste(paste('http://api.worldbank.org/v2/en/indicator',
                              indicatorCode, sep='/'),
                        'downloadformat=csv', sep='?')
        download.file(zipurl, zipfile)
    }
    csvfile <- paste(baseName, 'csv', sep='.')
    ## This produces a warning because of the trailing commas. Safe to ignore.
    readr::read_csv(unz(zipfile, csvfile), skip=4,
                    col_types = list(`Indicator Name` = readr::col_character(),
                                     `Indicator Code` = readr::col_character(),
                                     `Country Name` = readr::col_character(),
                                     `Country Code` = readr::col_character(),
                                     .default = readr::col_double())) %>%
        dplyr::select(-c(`Indicator Name`, `Indicator Code`, `Country Name`))
}

## Obtain and merge World Bank data
worldBankData <- getWorldBankData('MS.MIL.XPND.GD.ZS') %>%
    tidyr::gather(-`Country Code`, convert=TRUE,
                  key='Year', value=`Military expenditure (% of GDP)`,
                  na.rm = TRUE) %>%
    dplyr::filter(Year == selectedYear) %>%
    dplyr::mutate(Year = NULL)

## Plotting: Obtain Geographic data
mapData <- tibble::as.tibble(ggplot2::map_data("world")) %>%
    dplyr::mutate(`Country Code` =
                      countrycode::countrycode(region, "country.name", "iso3c"),
                  ## This produces a warning but I do not see how we could do better
                  ## since we started with fuzzy names.
                  region = NULL, subregion = NULL)

combinedData <- dplyr::left_join(mapData, worldBankData)

ggplot2::ggplot(data = combinedData, ggplot2::aes(long,lat)) +
    ggplot2::geom_polygon(ggplot2::aes(group = group,
                                       fill  = `Military expenditure (% of GDP)`),
                          color = '#606060', lwd=0.05) +
    ggplot2::scale_fill_gradientn(colours= rev(viridis::magma(256, alpha = 0.5)),
                                  name = "% GDP",
                                  breaks = 2*0:50,
                                  limits = c(0,14)) +
    ggplot2::coord_fixed() +
    ggplot2::theme_bw() +
    ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
          axis.title = ggplot2::element_blank(),
          axis.text = ggplot2::element_blank(),
          axis.ticks = ggplot2::element_blank(),
          panel.grid.major = ggplot2::element_blank(),
          panel.grid.minor = ggplot2::element_blank(),
          panel.border = ggplot2::element_blank(),
          panel.background = ggplot2::element_blank()) +
    ggplot2::labs(title = paste("Countries by military expenditures in",
                                selectedYear))

ggplot2::ggsave(paste(selectedYear, 'militrary_expenditures_relative.svg', sep='_'),
                height=100, units='mm')