Time-series forecasting and event impact analysis of financial inclusion indicators in Ethiopia. Uses historical data, policy events, and machine learning to model trends, assess policy effects, and generate evidence-based insights for decision-making.
# Ethiopia Financial Inclusion Forecasting
Project for forecasting financial inclusion in Ethiopia using comprehensive data exploration, analysis, modeling, and interactive visualization.
## Project Structure
```
├── .github/workflows/
│ └── unittests.yml # CI/CD workflow for unit tests
├── data/
│ ├── raw/ # Starter dataset
│ │ ├── ethiopia_fi_unified_data.xlsx
│ │ └── reference_codes.xlsx
│ └── processed/ # Analysis-ready data
├── notebooks/
│ ├── 01_data_exploration.ipynb # Task 1: Data exploration
│ ├── 02_data_enrichment.ipynb # Task 1: Data enrichment
│ ├── 03_eda.ipynb # Task 2: Exploratory Data Analysis
│ ├── 04_impact_modeling.ipynb # Task 3: Event Impact Modeling
│ └── 05_forecasting.ipynb # Task 4: Forecasting Access and Usage
├── src/
│ ├── __init__.py
│ ├── task1_data_exploration.py # Task 1: OOP data exploration & enrichment
│ ├── task2_eda.py # Task 2: OOP exploratory data analysis
│ ├── task3_impact_modeling.py # Task 3: OOP event impact modeling
│ ├── task4_forecasting.py # Task 4: OOP forecasting module
│ └── dashboard_components.py # Task 5: Dashboard components
├── dashboard/
│ └── app.py # Streamlit dashboard application
├── tests/
│ └── __init__.py
├── models/ # Trained models
├── reports/
│ └── figures/ # Generated visualizations
├── requirements.txt
├── README.md
└── .gitignore
```
## Setup
1. Create a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
2. Install dependencies:
```bash
pip install -r requirements.txt
```
## Usage
### Task 5: Dashboard Development (Main Interface)
Interactive Streamlit dashboard for exploring data, understanding event impacts, and viewing forecasts.
#### Quick Start
```bash
# Install dependencies (if not already installed)
pip …