🌍 Economic Freedom and Global Well-Being

Exploratory Data Analysis • PCA • Clustering • Data Visualization

This project started with a simple question: how does freedom shape the way people live? I explored global datasets from the Heritage Foundation, Human Freedom Index, and World Happiness Report to uncover how economic and personal freedoms relate to life satisfaction around the world.

🧩 Merging the Puzzle Pieces

I brought together diverse global indicators, standardized scoring systems, and handled missing data carefully. After cleaning and preprocessing, I had a unified dataset of over 150 countries, including measures of rights, liberties, and well-being.

📈 Finding Meaningful Patterns

I engineered new features to capture themes like political voice, property rights, and institutional trust. Using heatmaps and correlation matrices, I found clear patterns: countries with higher levels of freedom consistently had higher well-being scores.

🧠 Simplifying with PCA

With so many overlapping metrics, I used Principal Component Analysis to cut through the noise. Three components emerged—economic freedom, civil liberties, and governance strength—explaining over 80% of the total variance.

🌐 Who’s Similar to Whom?

I applied clustering algorithms to group countries based on their freedom profiles. Visualizing these clusters on a world map revealed fascinating global trends, showing how countries align in values and policies—even when separated by geography.

💡 Key Takeaways

• 📊 Economic freedom closely correlates with life satisfaction
• ⚖️ Civil rights like judicial independence and free speech are strong predictors of well-being
• 🌎 Different regions exhibit unique freedom “signatures” tied to culture and policy

🛠 Tools & Technologies

Python • pandas • matplotlib • seaborn • scikit-learn • geopandas • PCA • k-means clustering • Plotly

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