Oman Economic Data Analysis

A comprehensive economic analysis of Oman using World Bank data, with comparisons to other GCC countries. This project demonstrates Python data analysis skills with real-world economic data.

Overview

This project analyzes Oman's economic performance across multiple dimensions:

• GDP and economic growth trends
• Trade and export patterns
• Employment and labor market
• Inflation and price stability
• Regional comparison with GCC countries

Why This Matters for GCC

Understanding Oman's economic position is crucial for:

• Business investment decisions
• Policy analysis
• Regional economic planning
• Career opportunities in data analytics

Project Structure

oman-economic-analysis/
├── README.md
├── requirements.txt
├── LICENSE
├── data/
│   ├── raw/              # Downloaded World Bank data
│   └── processed/        # Cleaned and transformed data
├── notebooks/
│   ├── 01_data_collection.ipynb    # Data fetching from World Bank API
│   ├── 02_gdp_analysis.ipynb       # GDP and growth analysis
│   ├── 03_trade_analysis.ipynb     # Trade and exports
│   └── 04_gcc_comparison.ipynb     # Regional comparison
├── src/
│   ├── __init__.py
│   ├── data_collector.py    # World Bank API wrapper
│   ├── data_processor.py    # Data cleaning utilities
│   └── visualizations.py    # Chart generation
├── outputs/
│   └── charts/              # Generated visualizations
└── reports/
    └── key_findings.md      # Analysis summary

Quick Start

1. Clone the repository

git clone https://github.com/yourusername/oman-economic-analysis.git
cd oman-economic-analysis

2. Install dependencies

pip install -r requirements.txt

3. Run the analysis

# Start with data collection
jupyter notebook notebooks/01_data_collection.ipynb

Or run the data collector directly:

python -m src.data_collector

Key Findings

Oman's Economic Profile

Metric	Value	GCC Rank
GDP	~$85B	6th
GDP per Capita	~$19,000	4th-5th
GDP Growth (avg)	3-4%	Variable
Oil Dependency	25-40% of GDP	Moderate

Notable Insights

1. Oil Dependency: Oman's economy remains significantly tied to oil prices, though diversification efforts are ongoing through Vision 2040.

2. GCC Position: While Oman has the smallest economy in the GCC, it maintains competitive GDP per capita above Bahrain.

3. Growth Volatility: GDP growth shows strong correlation with global oil prices, with notable contractions in 2015-2016 and 2020.

4. Diversification Progress: Non-oil sectors including tourism, logistics, and manufacturing are growing.

Data Sources

This project uses the World Bank Open Data API, which provides free access to:

• GDP and growth indicators
• Trade statistics
• Employment data
• Inflation metrics
• Population statistics

API Documentation: https://datahelpdesk.worldbank.org/knowledgebase/articles/889392

Countries Analyzed

Country	Code	Region
Oman	OMN	GCC
Saudi Arabia	SAU	GCC
United Arab Emirates	ARE	GCC
Qatar	QAT	GCC
Kuwait	KWT	GCC
Bahrain	BHR	GCC

Economic Indicators

The analysis covers 20+ World Bank indicators:

GDP & Growth

• NY.GDP.MKTP.CD - GDP (current US$)
• NY.GDP.MKTP.KD.ZG - GDP growth (annual %)
• NY.GDP.PCAP.CD - GDP per capita

Trade

• NE.EXP.GNFS.ZS - Exports (% of GDP)
• NE.IMP.GNFS.ZS - Imports (% of GDP)
• BN.CAB.XOKA.CD - Current account balance

Employment

• SL.UEM.TOTL.ZS - Unemployment rate
• SL.TLF.TOTL.IN - Labor force

Other

• FP.CPI.TOTL.ZG - Inflation rate
• NY.GDP.PETR.RT.ZS - Oil rents (% of GDP)

Sample Visualizations

The project generates various charts including:

• GDP trend analysis
• GCC comparison bar charts
• Trade balance over time
• Oil dependency trends
• Inflation heatmaps

Technologies Used

• Python 3.10+
• pandas - Data manipulation
• numpy - Numerical operations
• matplotlib - Static visualizations
• seaborn - Statistical plots
• requests - API calls
• jupyter - Interactive notebooks

Usage Examples

Fetch Oman Data

from src.data_collector import OmanDataCollector

collector = OmanDataCollector()
df = collector.fetch_oman_data(start_year=2000, end_year=2023)
print(df.head())

Create Visualizations

from src.visualizations import EconomicVisualizer

viz = EconomicVisualizer()
viz.plot_time_series(gdp_data, title='Oman GDP Trend', ylabel='Billion USD')

Process Data

from src.data_processor import DataProcessor

processor = DataProcessor()
df = processor.load_data('gcc_economic_data.csv')
latest = processor.get_latest_values(df, 'OMN')

Future Enhancements

• Add interactive Plotly dashboards
• Include more GCC-specific data sources
• Add forecasting models
• Create Streamlit web app
• Add sector-specific analysis (tourism, logistics)

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Author

Created as part of a Data Analytics portfolio project focused on GCC economic analysis.

Acknowledgments

• World Bank for providing open access to economic data
• Oman Vision 2040 documentation for strategic context
• GCC statistical agencies for regional data

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Star this repository if you find it useful for understanding GCC economics!