GDP per capita from Gapminder (1800-2022)
This dataset records country-level GDP per capita over time using public Gapminder data. In Sequenzo, it is prepared as a categorical sequence dataset so that countries can be compared by long-run economic-development trajectories rather than by one year at a time.
Income (GDP per capita)
GDP per capita is a country-level measure of average economic output per person. It is often used as a broad indicator of economic development, while recognizing that it does not directly measure inequality, well-being, or household income.
For sequence analysis, the numeric GDP-per-capita values are converted into ordered categorical states. This makes it possible to study questions such as:
- Which countries follow similar long-run development trajectories?
- Which countries move steadily upward, remain stable, or fluctuate across income categories?
- How do country trajectories compare across historical periods or regions?
Built-in Dataset
The package includes a built-in file named country_gdp_per_capita_quintiles.
from sequenzo import load_dataset
gdp = load_dataset("country_gdp_per_capita_quintiles")
print(gdp.head())The states represent quintile groups derived from the GDP-per-capita distribution. Use this dataset when you want a compact country-level example; use the CO₂ emissions dataset if you want the same style of workflow with environmental indicators.
Related Pages
See Also
- Datasets Overview helps choose a dataset by research question.
SequenceDatashows how to define sequences from a dataset.- Quickstart runs a complete analysis on a bundled dataset.
References
Gapminder. (2025). https://www.gapminder.org/data/documentation/.
Author: Yuqi Liang