👤 Personal Motivation

I’ve always been curious about personal finance, macroeconomic trends, and how they affect people’s quality of life. As I started considering the idea of relocating to another country for better opportunities, I realized I needed a structured way to compare options - beyond gut feeling or headlines.

This project started as a personal exploration:

Where would I thrive economically and socially, based on real data?

It evolved into a complete data science pipeline - combining data collection, exploratory analysis, scoring models, and a predictive dashboard.

🔎 Problem Statement

How can we compare countries in a meaningful way for relocation decisions?

Key challenges:

• Country comparisons are often subjective and not tailored to individual priorities.
• Public data is fragmented, inconsistent, or incomplete.
• Predicting future trends requires reliable historical series.

🛠️ Tools Used

• Python (pandas, scikit-learn, matplotlib, seaborn)
• Streamlit for interactive dashboard
• World Bank API + UNDP HDI data
• Jupyter notebooks for EDA & modeling