720 rows · 9 columns

World development indicators

A tidy panel of thirty countries over twenty-four years with GDP per capita, life expectancy, population, CO₂ and internet penetration — small enough to hold in your head, rich enough for real modelling.

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What is in it, and what is wrong with it

This is the dataset to reach for when you want to practise small-multiples, animated scatter plots, or fixed-effects regression. It contains a genuine Simpson's paradox: pooled across all countries, internet penetration correlates negatively with growth in life expectancy, while within every single country the relationship is positive.

Schema

Column	Type	Description
country	category	Country name (synthetic panel).
iso3	string	Three-letter code.
region	category	World region.
year	integer	Calendar year, 2000–2023.
population	integer	Mid-year population.
gdp_per_capita_usd	float	GDP per capita, constant dollars.
life_expectancy	float	Life expectancy at birth, years.
co2_tonnes_per_capita	float	CO₂ emissions per capita.
internet_pct	float	Share of population using the internet.

First twelve rows

country	iso3	region	year	population	gdp_per_capita_usd	life_expectancy	co2_tonnes_per_capita
Avalonia	AVA	Europe	2000	117306382	27439.4	76.01	5.261
Avalonia	AVA	Europe	2001	117552743	27843.3	76.14	2.851
Avalonia	AVA	Europe	2002	118132310	29135.4	76.31	5.288
Avalonia	AVA	Europe	2003	119000189	30758	76.61	2.975
Avalonia	AVA	Europe	2004	119842517	31360.1	76.64	3.949
Avalonia	AVA	Europe	2005	120410826	32350.5	77.12	3.278
Avalonia	AVA	Europe	2006	120743607	33402.8	76.92	4.245
Avalonia	AVA	Europe	2007	121564099	35607.6	76.86	5.658
Avalonia	AVA	Europe	2008	122016872	38708	76.94	5.951
Avalonia	AVA	Europe	2009	122851240	40687.2	77.18	5.506
Avalonia	AVA	Europe	2010	123329505	42277.5	77.12	4.398
Avalonia	AVA	Europe	2011	123592181	44916	77.34	5.512

Showing the first 8 of 9 columns. Open the full table in the Explorer.

Grain

One row per country per year.

Things to try

Rebuild the famous bubble chart: GDP per capita against life expectancy, sized by population.
Find the Simpson's paradox and explain it with a small-multiples panel.
Fit a country fixed-effects model and compare it with the pooled one.
Rank countries by CO₂ per capita and by CO₂ per dollar of GDP — the orders differ.

Load it

python

import pandas as pd

df = pd.read_csv(
  "https://datanemics.com/datasets/data/world-indicators.csv"
)

Licence

Public domain, CC0 1.0. Synthetic data — no attribution required.