An attempt on creating an interactive plot

This week’s Tidy Tuesday challenge (2024-11-12) provided an excellent opportunity to explore country datasets through the lens of ISO Alpha-3 and numeric codes. Using the countries dataset from the repository, I created a clean and interactive world map visualization that showcases the geographic and numeric diversity of nations. Below, I walk you through the process and the insights gained.

Dataset Overview

The dataset includes three main components:

Countries: Information on modern countries, including ISO codes (Alpha-2, Alpha-3, and numeric), names, and additional metadata.
Country Subdivisions: Details about smaller administrative regions within countries.
Former Countries: Historical countries that no longer exist, offering a fascinating look at geopolitical changes.

For this visualization, I focused on the countries dataset to build an interactive map.

The Visualization

The goal was to highlight how ISO Alpha-3 codes and numeric codes can help represent countries visually. Using the plotly library, I created an interactive choropleth map. Each country is shaded based on its numeric ISO code, with hoverable tooltips providing details such as the country name.

Key features of the map include:

ISO Alpha-3 Codes: These codes are used to pinpoint countries on the map.
Color-Free Design: To keep the map simple and focused, I disabled the color legend, ensuring the visualization remains clean and distraction-free.
Custom Layout: The map uses an equirectangular projection with clean coastlines and unobtrusive white borders for better readability.

Code

library(tidyverse)
library(tidytuesdayR)
library(countries)
library(ggtext)
library(showtext)
library(glue)
library(plotly)

# Loading the data from TT repo

tuesdata <- tt_load("2024-11-12")

countries <- tuesdata$countries
country_subdiv <- tuesdata$country_subdivisions
former_countries <- tuesdata$former_countries


title <- "Global Interactive Visualization of Countries Using ISO Alpha-3 Codes and Numeric Codes"


map <- plot_ly(
  type = 'choropleth',
  locations = countries$alpha_3,  
  z = countries$numeric,          
  text = countries$name,        
  colorscale = '', 
  showscale = FALSE,
  marker = list(line = list(color = 'white', width = 0.5))
)

# Layout adjustments
map <- map %>%
  layout(
    title = "Global Interactive Visualization of Countries Using 
    ISO Alpha-3 Codes and Numeric Codes",
    geo = list(
      projection = list(type = 'equirectangular'),
      showcoastlines = TRUE,
      coastlinecolor = "black",
      showframe = FALSE
    )
  )


map