Forecasting Ethiopia's financial inclusion using time series analysis, event modeling, and interactive dashboards.
# Ethiopia Financial Inclusion Forecast
Week 11 — Financial Inclusion Forecasting Challenge.
## Project Overview
This project forecasts financial inclusion indicators for Ethiopia. It provides a
reproducible pipeline for ingesting the raw data, engineering features, training
time-series and machine-learning forecasting models, evaluating their performance,
and presenting the results through an interactive dashboard.
The goal is to support data-driven decision making by producing reliable forecasts
of key financial inclusion metrics and communicating them clearly to stakeholders.
## Folder Structure
```
ethiopia-financial-inclusion-forecast/
├── data/
│ ├── raw/ # Original, immutable source data
│ ├── processed/ # Cleaned and transformed data ready for modeling
│ └── external/ # Third-party / reference datasets
├── notebooks/ # Exploratory and reporting notebooks
├── src/ # Source code (importable package)
│ ├── data/ # Data loading and preprocessing
│ ├── features/ # Feature engineering
│ ├── models/ # Model training and forecasting
│ └── visualization/ # Plotting and reporting helpers
├── dashboard/ # Streamlit dashboard application
├── models/ # Serialized / trained model artifacts
├── reports/
│ └── figures/ # Generated charts and figures
├── tests/ # Unit tests (pytest)
├── requirements.txt # Python dependencies
├── .gitignore
└── README.md
```
## Installation Instructions
1. Clone the repository:
```bash
git clone
cd ethiopia-financial-inclusion-forecast
```
2. Create and activate a virtual environment:
On Windows (PowerShell):
```powershell
python -m venv venv
.\venv\Scripts\Activate.ps1
```
On macOS / Linux:
```bash
python -m venv venv
source venv/bin/activate
```
3. Install the dependencies:
```bash
pip install -r requirements.txt
```
## How to Run
Run the test suite:
```bash
pytest
```
Launch the interactive …