🇸🇳 Senegal Macroeconomic Analysis

The goal is to build a structured and reproducible macroeconomic analysis pipeline that retrieves, cleans, transforms, visualizes, and interprets economic data from the World Bank API.

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Indicators

The current analysis focuses on GDP, with inflation planned as the next macroeconomic indicator.

• GDP — NY.GDP.MKTP.CD
• Inflation — FP.CPI.TOTL.ZG (planned)

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Data Source

All data is retrieved from the World Bank Open Data API.

• Country: Senegal (SN)
• Period: 1990 – 2024

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Project Structure

senegal-macro-analysis/
│
├── data/
│   ├── raw/
│   └── processed/
│
├── notebooks/
│   └── senegal_macroeconomic_analysis.ipynb
│
├── src/
│   ├── __init__.py
│   ├── data.py
│   ├── cleaning.py
│   ├── indicators.py
│   ├── time_series.py
│   └── visualization.py
│
├── README.md
└── requirements.txt

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Methodology

The analysis follows a structured pipeline:

1. Data collection from the World Bank API
2. Data cleaning and preprocessing
3. Macroeconomic indicator computation
   • GDP growth rate
   • CAGR / TCAM
   • Moving average
   • Volatility
   • Rolling volatility
4. Data visualization and economic interpretation

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Utility Modules

Reusable functions are implemented in the src/ directory and organized by responsibility.

src/data.py includes:

• get_data → retrieve and structure data from the World Bank API

src/cleaning.py includes:

• clean_data → clean datasets and detect/remove outliers

src/visualization.py includes:

• line_plt → time series visualization
• hist_plt → distribution analysis
• scat_plt → relationship between variables
• box_plt → outlier visualization

src/indicators.py includes:

• compute_growth_rate → compute annual percentage growth
• compute_cagr → compute compound annual growth rate over a selected period
• compute_moving_average → smooth time-series indicators using a rolling average
• compute_volatility → measure the instability of an indicator using standard deviation
• compute_rolling_volatility → measure how volatility evolves over time using a rolling window

src/time_series.py includes:

• test_stationarity → test whether a time series is stationary using the Augmented Dickey-Fuller test

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🎯 Future Improvements

Roadmap

• Build a clean data pipeline using the World Bank API
• Add data cleaning and outlier detection functions
• Add reusable visualization functions
• Refactor source code into dedicated modules
• Add GDP growth rate indicator
• Add CAGR / TCAM indicator
• Add GDP growth moving average indicator
• Add GDP growth volatility indicator
• Add GDP growth rolling volatility indicator
• Add stationarity tests for time-series analysis
• Add inflation analysis
• Analyze the relationship between GDP growth and inflation
• Add forecasting models such as ARIMA and VAR
• Build an interactive dashboard for country-level macroeconomic analysis

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How to Use

Clone the repository:

git clone https://github.com/MalickThaKidd/senegal-macro-analysis.git
cd senegal-macro-analysis