athrafstos1234/ride-hailing_ds

Ride-hailing data science project (fare + demand prediction in Ghana) # 🚖 Ride-Hailing Data Science Project (Ghana Context) ## 📌 Project Overview This project analyzes ride-hailing data (similar to Bolt/Uber in Accra, Ghana) to: - Predict **fares (GHS)** based on distance. - Predict **demand levels** (Low, Medium, High). - Visualize insights with charts. It was built as a portfolio project for **Computer Science (Data Science focus)**. --- ## 📂 Features - **Dataset** – Small sample dataset of trips in Accra (Distance, Fare, Route, Demand). - **Visualization** – Demand distribution + Fare vs Distance (with regression line). - **Machine Learning Models** - Linear Regression → Predicts ride fares. - Random Forest Classifier → Predicts demand level. - **Predictions** – Example predictions for trips (e.g., 10 km fare, 12 km/34 GHS demand). --- ## 📊 Example Outputs **Fare Formula (learned from data):** ``` Fare = 2.05 \* Distance + 5.30 ```` - Predicted Fare (10 km): ~28 GHS - Predicted Demand (12 km, 34 GHS): Medium --- ## 🛠️ Tech Stack - Python 3.x - Pandas, NumPy - Matplotlib, Seaborn - scikit-learn --- ## 📸 Visualizations - `demand_distribution.png` → Shows demand levels (Low/Medium/High). - `fare_vs_distance_with_line.png` → Shows fare vs distance with regression line. --- ## 🚀 How to Run 1. Clone this repo: ```bash git clone github.com cd ride-hailing-ds ```` 2. Install dependencies: ```bash pip install pandas numpy matplotlib seaborn scikit-learn ``` 3. Run the script: ```bash python ride_hailing.py ``` --- ## 🎯 Why This Project? This project demonstrates **data analysis + machine learning** skills in a real-world Ghanaian context. It serves as a strong **portfolio piece** for academic and job applications in Data Science. --- ## 👨‍💻 Author **Nartey Emmanuel Kwame Athrafstos** Computer Science Student, Accra Technical University # ride-hailing_ds …