arsema16/ethiopia-fi-forecast

# Ethiopia Financial Inclusion Forecast ## Project Overview This project forecasts financial inclusion in Ethiopia using time series methods, focusing on Access (Account Ownership) and Usage (Digital Payment Adoption) dimensions. ## 📂 Repository Structure ``` ethiopia-fi-forecast/ ├── data/ │ ├── raw/ # Starter and enriched datasets │ │ ├── ethiopia_fi_unified_data.csv │ │ └── reference_codes.csv │ └── processed/ # Analysis-ready data ├── notebooks/ │ ├── task1_data_exploration_and_enrichment.ipynb │ └── task2_exploratory_data_analysis.ipynb ├── src/ # Source code ├── dashboard/ # Streamlit dashboard ├── tests/ # Unit tests ├── reports/ │ ├── data_enrichment_log.md # Documentation of data additions │ └── figures/ # Generated visualizations └── requirements.txt # Python dependencies ``` ## 🚀 Quick Start ### Prerequisites - Python 3.8+ - Jupyter Notebook/Lab - Git ### Installation ``` # Clone the repository git clone github.com cd ethiopia-fi-forecast ``` ``` # Install dependencies pip install -r requirements.txt ``` # Launch Jupyter jupyter notebook # Running the Notebooks Task 1: notebooks/task1_data_exploration_and_enrichment.ipynb # Explores the schema and enriches the dataset Task 2: notebooks/task2_exploratory_data_analysis.ipynb Comprehensive EDA with visualizations and insights # 📊 Key Findings (Interim Submission) ### 1. Access Trends Account ownership: 14% (2011) → 49% (2024) Growth deceleration: 11pp (2017-2021) → 3pp (2021-2024) ### 2. Usage Trends Digital payment adoption: ~35% (2024) Mobile money accounts: 9.45% (2024) ### 3. Key Insights Event impacts show lagged effects (6-12 months) # Infrastructure correlates positively with adoption Data gaps in gender and regional disaggregation # 📈 Visualizations Generated visualizations are available in reports/figures/: Dataset overview Temporal coverage heatmap Access trajectory Usage trajectory Event timeline Correlation matrix …