🌍 Life Expectancy Data Analysis & Visualization

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🧭 Overview

This project delivers a comprehensive data-driven exploration of global life expectancy trends, using data from the World Bank and other trusted international sources.
It demonstrates a complete data analytics pipeline, from data collection and cleaning to exploratory data analysis (EDA), feature engineering, and interactive visualization.

By combining statistical reasoning, data storytelling, and human-centered analysis, this work turns global socio-economic data into clear, interpretable insights — a hallmark of professional data science practice.

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🔍 Project Highlights

1. Data Collection & Preprocessing

• Sourced datasets from the World Bank Open Data platform.
• Performed data wrangling, normalization, and missing value handling using pandas and numpy.
• Applied feature engineering to create meaningful indicators such as GDP per capita and health expenditure ratios.

2. Exploratory Data Analysis (EDA)

• Conducted statistical summaries, correlation analysis, and trend exploration.
• Compared regional patterns of life expectancy with economic and healthcare variables.
• Combined explorative and explanatory approaches to identify and communicate key insights.

3. Data Visualization & Storytelling

• Developed interactive and static visualizations using matplotlib, seaborn, and plotly.
• Focused on clarity, accessibility, and data-driven storytelling for both technical and non-technical audiences.
• Designed visuals that highlight socio-economic contrasts and long-term global health trends.

4. Insights & Interpretation

• Showcases global inequalities in life expectancy and their relationships to economic and social factors.
• Demonstrates the power of data visualization for communicating complex insights effectively.
• Emphasizes evidence-based reasoning and interpretability.

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🧠 Tools & Technologies

Category	Tools & Techniques
Programming & Data Processing	Python, Pandas, NumPy
Visualization & Storytelling	Matplotlib, Seaborn, Plotly
Statistical & Exploratory Analysis	Correlation, Regression, Feature Engineering
Data Sources	World Bank Open Data, Global Development Indicators
Soft Skills	Analytical Thinking, Data Storytelling, Insight Communication

🚀 Live Demo

🔗 Explore the full analysis and interactive visualizations:
Life Expectancy Analysis

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🧩 Future Directions

• Integrating predictive modeling (e.g., regression or clustering) to estimate life expectancy trends.
• Expanding the dataset to include climate, education, and urbanization factors.
• Building a Streamlit or Dash dashboard for a fully interactive analytical experience.

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👩‍💻 Authors

- Davide Venuto
- Jakob Boëtius Andersen
- Huayuan Song

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© 2025 — Licensed under the MIT License