🇪🇹 Ethiopia's Development Trajectory: Data Analysis

Overview

This project presents an exploratory data analysis (EDA) of Ethiopia's socio-economic development indicators using Python. The notebook analyzes historical development trends through data visualization and statistical exploration to better understand Ethiopia's development trajectory over time.

The project is implemented in Google Colab using Python and open-source data science libraries.

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Objectives

• Explore Ethiopia's historical development indicators.
• Clean and preprocess the dataset.
• Transform data into analysis-ready format.
• Visualize long-term development trends.
• Generate insights from socio-economic indicators.

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Dataset

The dataset contains historical development indicators for Ethiopia, including variables such as:

• GDP Growth (Annual %)
• Economic Indicators
• Development Metrics
• Year-wise observations

Note: The dataset is used for educational and analytical purposes.

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Technologies Used

• Python 3
• Google Colab
• Pandas
• NumPy
• Matplotlib
• Jupyter Notebook

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Project Structure

Ethiopia-s-Development-Trajectory-Data-Analysis/
│
├── Ethiopia's_Development_Trajectory.ipynb
├── README.md
├── requirements.txt

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Analysis Workflow

1. Import required libraries
2. Load dataset
3. Data cleaning
4. Handle missing values
5. Data transformation
6. Exploratory Data Analysis (EDA)
7. Visualization of development indicators
8. Interpretation of findings

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Example Visualizations

The notebook includes visualizations such as:

• GDP Growth over Time
• Indicator Trend Analysis
• Line Charts
• Comparative Development Trends

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Installation

Clone the repository

git clone https://github.com/Habtamariam/Ethiopia-s-Development-Trajectory-Data-Analysis-.git

Move into the project

cd Ethiopia-s-Development-Trajectory-Data-Analysis-

Install dependencies

pip install -r requirements.txt

Launch Jupyter Notebook

jupyter notebook

Open

Ethiopia's_Development_Trajectory.ipynb

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Results

The notebook demonstrates:

• Data preprocessing techniques
• Time-series visualization
• Development trend analysis
• Economic indicator exploration

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Future Improvements

• Interactive dashboards using Plotly
• Machine Learning forecasting
• Predictive economic analysis
• Additional development indicators

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Author

Habtamu Molla

• MSc in Information Technology
• Ethiopian Public Service University
• Ethiopia

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License

This project is released under the MIT License.

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Acknowledgements

• World Development Indicators (WDI)
• Google Colab
• Python Open Source Community