A comprehensive data analysis project examining global GDP per capita trends using World Bank data from 1990 to 2023. This portfolio project showcases advanced data analysis, visualization, and economic insights for professional presentation.
- Comprehensive EDA (Exploratory Data Analysis)
- Time series analysis and trend examination
- Geographic visualizations (Interactive world maps)
- Economic crisis impact analysis (2008 Financial Crisis, COVID-19)
- Interactive dashboards and animated charts
- Advanced feature engineering and statistical analysis
- Python - Primary programming language
- Pandas & NumPy - Data manipulation and analysis
- Plotly - Interactive visualizations and dashboards
- Seaborn & Matplotlib - Statistical graphics
- Folium - Geographic mapping
- Jupyter Notebook - Development and analysis environment
├── data/ # Dataset files
│ └── gdp-per-capita-worldbank.csv
├── notebooks/ # Jupyter notebooks
│ ├── 01_data_exploration.ipynb # Data discovery and cleaning
│ ├── 02_eda_analysis.ipynb # Comprehensive EDA
│ └── 03_feature_engineering.ipynb # Advanced feature creation
├── src/ # Python modules
│ ├── data_processing.py # Data processing functions
│ ├── visualization.py # Visualization utilities
│ └── utils.py # Helper functions
├── outputs/ # Output files
│ ├── plots/ # Charts and visualizations (17 files)
│ │ ├── 01_gdp_distribution.png
│ │ ├── 04_world_gdp_trend.html # Interactive plots
│ │ ├── 10_summary_dashboard.png # Project overview
│ │ └── ... (see plots/README.md)
│ └── gdp_with_features.csv # Enhanced dataset
├── requirements.txt # Required packages
└── README.md # Project documentation
- Clone the repository:
git clone https://github.com/[username]/Global-GDP-Analysis.git
cd Global-GDP-Analysis- Install required packages:
pip install -r requirements.txt- Run Jupyter Notebooks:
jupyter notebook- Generate all visualizations:
python generate_plots.py- Global Growth: World average GDP per capita increased 42.1% from 2000-2023
- Continental Disparities: Europe leads in wealth, Asia shows fastest growth
- Crisis Impact: COVID-19 had more severe economic impact than 2008 financial crisis
- Wealth Inequality: 160x gap between richest (Luxembourg) and poorest (Burundi) countries
- Economic Resilience: China maintained positive growth during both major crises
- Interactive World Map - Color-coded GDP levels with modern styling
- Animated Time Series - Dynamic GDP evolution over decades
- Continental Comparison Dashboard - Multi-panel interactive analysis
- Crisis Impact Analysis - Before/after economic shock comparisons
- Wealth Inequality Trends - Long-term disparity analysis
- 26 Engineered Features - Growth rates, volatility, economic cycles
- Crisis Detection Algorithm - Automated recession identification
- Risk-Adjusted Performance Metrics - Advanced economic indicators
- Interactive Dashboards - Professional-grade visualizations
This analysis provides insights for:
- Economic Policy - Understanding global growth patterns
- Investment Decisions - Risk-return country profiles
- Development Planning - Benchmarking economic performance
- Academic Research - Economic trend analysis framework
Portfolio Project for Global Economic Analysis
- 📧 Contact: xcanozden@gmail.com
- 💼 LinkedIn: (https://www.linkedin.com/in/xcanozden/)
- 🔗 GitHub: https://github.com/xcan16
This project is licensed under the MIT License - see the LICENSE file for details.
Last Updated: September 2025 | Data Source: World Bank | Analysis Period: 1990-2023 ⭐ If you liked this project, don’t forget to give it a star!