Data Pipeline · Visualisation · NLP

Gender Equality Tracker

An end-to-end Python project that pulls public data from the World Bank and OECD, scrapes live news, and turns it into a single composite score measuring gender equality across 209 countries.

Countries scored
209
across 12 indicators
Avg equality score
69.6
out of 100
Top country
Virgin Islands (U.S.)
score 95.1
Avg OECD wage gap
12.7%
395 headlines analysed

🌍 Composite Gender Equality Score

Weighted average of 6 sub-indicators (labor participation, women in parliament, literacy, wage workers, unemployment gap, school enrolment parity). Higher = more equal.

Source: World Bank Indicators API · methodology in config.py

💼 Gender Wage Gap by Country

Difference between male and female median earnings, latest OECD figure for each country.

Source: OECD SDMX — Gender Wage Gap dataset

📰 News Sentiment Mix

VADER-classified tone of all gender-equality headlines collected this run.

Source: Google News RSS · VADER sentiment

📈 Labor Force Participation Over Time

Female (left) vs male (right) labor participation for a diverse basket of 8 economies. Each colour is one country across both panels.

Source: World Bank · indicators SL.TLF.CACT.FE.ZS / SL.TLF.CACT.MA.ZS

🎓 Education Drives Workforce Participation

Each bubble is a country. Larger bubbles = more women in parliament. Colour reflects the composite Equality Score.

Source: World Bank — latest available value per country

🗞️ Headline Volume & Sentiment

Daily news activity (bars) and average sentiment (line) for gender-equality headlines pulled from Google News.

Source: Google News RSS · VADER compound score