Ride-Analysis

🚗 Ride Analysis

A data analytics project focused on understanding trends, patterns, and insights from ride-sharing datasets. This project leverages Python-based data science tools to process, analyze, and visualize ride data to assist in business decision-making and operational efficiency.

Open this Link for live demo: ride-analysis-pclcv5djzd7hxmbhdtnyzo.streamlit.app/

📊 Project Overview

The goal of this project is to analyze ride data (e.g., ride times, durations, and patterns) using:

• Data Cleaning & Preprocessing
• Exploratory Data Analysis (EDA)
• Time-based Feature Engineering
• Interactive Visualizations with Matplotlib & Seaborn
• Deployment via Streamlit Dashboard

🧰 Tech Stack

• Python 3.10+
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Streamlit
• Jupyter Notebooks

📁 Project Structure

Ride-Analysis/
│
├── data/                   # Raw and processed datasets
├── chat.txt/                # Dataset
├── Ride Analysis.ipynb     # Jupyter notebook with full analysis
├── Ride_Analysis.py        # Converted .py file for Streamlit app
├── requirements.txt        # Dependencies
└── README.md               # Project documentation

🚀 Getting Started

1. Clone the repo

git clone https://github.com/wassupjay/Ride-Analysis.git
cd Ride-Analysis

2. Create virtual environment (optional but recommended)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Run Streamlit app

streamlit run Ride_Analysis.py

📌 Key Features

• Extracts hour and time slot features from timestamps
• Identifies peak ride hours and frequency
• Highlights anomalies and trends through visual exploration
• Deployable as a lightweight Streamlit dashboard

📷 Sample Visualizations

Add images to show line plots, bar graphs, or time heatmaps

💡 Future Enhancements

• Integrate with real-time APIs for live data monitoring
• Add predictive analytics (e.g., ride demand forecasting)
• Deploy as a web app with authentication

🤝 Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss your ideas.

🧾 License

MIT License. See LICENSE for details.