Exploring Global Development with Gapminder and R

Author

Louise Izere

Published

September 22, 2026

In this post, I explore how life expectancy and GDP per capita differ across continents using the Gapminder dataset.

Data source: Gapminder

License: Creative Commons Attribution (CC BY)

Attribution: Based on free material from GAPMINDER.ORG, CC-BY LICENSE.

library(tidyverse)
library(gapminder)

First, I look at countries with the highest life expectancy in 2007.

filtered_gapminder <- filter(gapminder, year == 2007)
filtered_gapminder |>
  arrange(desc(lifeExp)) |>
  select(country, continent, lifeExp, gdpPercap) |>
  head(10)

# A tibble: 10 × 4
   country          continent lifeExp gdpPercap
   <fct>            <fct>       <dbl>     <dbl>
 1 Japan            Asia         82.6    31656.
 2 Hong Kong, China Asia         82.2    39725.
 3 Iceland          Europe       81.8    36181.
 4 Switzerland      Europe       81.7    37506.
 5 Australia        Oceania      81.2    34435.
 6 Spain            Europe       80.9    28821.
 7 Sweden           Europe       80.9    33860.
 8 Israel           Asia         80.7    25523.
 9 France           Europe       80.7    30470.
10 Canada           Americas     80.7    36319.

The countries with the highest life expectancy in 2007 were mostly in Asia and Europe.

Next, I calculate the average life expectancy and GDP per capita for each continent.

filtered_gapminder |>
  group_by(continent) |>
  summarise(
    life_exp = mean(lifeExp),
    gdp_per_capita = mean(gdpPercap)
  )

# A tibble: 5 × 3
  continent life_exp gdp_per_capita
  <fct>        <dbl>          <dbl>
1 Africa        54.8          3089.
2 Americas      73.6         11003.
3 Asia          70.7         12473.
4 Europe        77.6         25054.
5 Oceania       80.7         29810.

The results show considerable differences between continents in both economic conditions and life expectancy.

Finally, I visualize the relationship between GDP per capita and life expectancy.

filtered_gapminder |>
  ggplot(aes(
    x = gdpPercap,
    y = lifeExp,
    colour = continent
  )) +
  geom_point() +
  scale_x_log10() +
  labs(
    title = "GDP and Life Expectancy in 2007",
    x = "GDP per capita",
    y = "Life expectancy"
  ) +
  theme_minimal()

Figure 1: Relationship between GDP per capita and life expectancy across countries in 2007.

Countries with higher GDP per capita generally have higher life expectancy. However, the relationship becomes less pronounced among wealthier countries, suggesting that increases in income are not associated with equally large increases in life expectancy at all income levels.