CIA Factbook

library(tidyverse) # ggplot, lubridate, dplyr, stringr, readr...
library(maps)
library(praise)

The Data

This week we’re exploring the CIA World Factbook! The dataset this week comes from the CIA Factbook, Country Comparisons, 2014, via the {openintro} R package, via the {usdatasets} R package, via this post on LinkedIn.

The World Factbook provides basic intelligence on the history, people, government, economy, energy, geography, environment, communications, transportation, military, terrorism, and transnational issues for 265 world entities.

cia <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-10-22/cia_factbook.csv') |> 
  mutate(iso_a3 = countrycode::countrycode(
      country,
      origin = "country.name",
      destination = "iso3c"
    )) |> 
  drop_na(iso_a3)

World Map

world_data <- map_data("world") |>   # ggplot2
  mutate(iso_a3 = countrycode::countrycode(
      region,
      origin = "country.name",
      destination = "iso3c"
    )) |> 
  drop_na(iso_a3)

data4map <- world_data |> 
  left_join(cia, by = "iso_a3")

data4map |> 
  ggplot(aes(x = long, y = lat, group = group)) + 
  geom_polygon(aes(fill = death_rate), color = "black", size = 0.15) + 
  theme_void() + 
  scale_fill_gradient(trans = "log")

world map colored by the death rate (number of deaths per 1,000 people) in 2014.

  #scale_fill_gradient(low = "blue", high = "purple")

Shiny App

I also created a Shiny App which allows the user to change the variable that colors each country. However, I don’t have an obvious place to host the Shiny App. The source code for the Shiny App is in app.R which is located at https://github.com/hardin47/TidyTuesday/tree/gh-pages/2024-10-22/CIAFactbook .

praise()

[1] "You are groovy!"