https://github.com/aymen016/uber-analytics-dashboard
The Uber Analytics Dashboard is an interactive data visualization tool built with Streamlit. It helps analyze ride bookings, cancellations, revenue, and customer behavior with filters, KPIs, and charts. This dashboard enables businesses to gain actionable insights into ride demand and performance trends.
https://github.com/aymen016/uber-analytics-dashboard
matplotlib-pyplot pandas plotly python seaborn streamlit
Last synced: about 2 months ago
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The Uber Analytics Dashboard is an interactive data visualization tool built with Streamlit. It helps analyze ride bookings, cancellations, revenue, and customer behavior with filters, KPIs, and charts. This dashboard enables businesses to gain actionable insights into ride demand and performance trends.
- Host: GitHub
- URL: https://github.com/aymen016/uber-analytics-dashboard
- Owner: Aymen016
- License: mit
- Created: 2025-08-22T10:38:13.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-08-29T10:24:44.000Z (10 months ago)
- Last Synced: 2025-09-12T22:32:14.708Z (9 months ago)
- Topics: matplotlib-pyplot, pandas, plotly, python, seaborn, streamlit
- Language: Python
- Homepage: https://uber-anlytics-dashboard-itv3kjahgtjdnghgc8bnf5.streamlit.app/
- Size: 6.71 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🚗 Uber Ride Analytics Dashboard (2024)
An interactive **Streamlit dashboard** for analyzing Uber ride data — providing insights into **bookings, cancellations, revenue trends, customer behavior, and ride patterns**.
This dashboard helps analysts, managers, and business users understand **performance metrics, demand fluctuations, cancellations, and satisfaction trends** with **appealing visualizations** powered by Plotly, Seaborn, and Matplotlib.
---
## ✨ Features
- **Filters** for Vehicle Type and Payment Method
- **Key Performance Indicators (KPIs)**: Total Bookings, Completed Rides, Total Revenue
- **Visualizations**:
- Booking Status Distribution (Pie Chart)
- Revenue Contribution by Vehicle Type (Bar Chart)
- Correlation Heatmap of numeric variables
- Analytics Overview Section:
- Rides by Hour (Line Chart)
- Cancellations by Vehicle Type (Bar Chart)
- Ratings Comparison (Driver vs Customer)
- Revenue Trends Over Time (Area Chart)
---
## 🛠️ Tech Stack
- [Python 3.8+](https://www.python.org/)
- [Streamlit](https://streamlit.io/)
- [Pandas](https://pandas.pydata.org/)
- [Plotly Express](https://plotly.com/python/plotly-express/)
- [Seaborn](https://seaborn.pydata.org/)
- [Matplotlib](https://matplotlib.org/)
---
## 📂 Project Structure
uber-analytics-dashboard/
│── app.py # Main Streamlit app
│── ncr_ride_bookings.csv # Dataset (sample)
│── README.md # Project documentation
│── requirements.txt # Dependencies
---
## 🚀 Installation & Usage
### 1. Clone the repo
```bash
git clone https://github.com/your-username/uber-analytics-dashboard.git
cd uber-analytics-dashboard
```
### 2. Install dependencies
```bash
pip install -r requirements.txt
```
### 3. Run the App
```bash
streamlit run app.py
```
---
### 5. Open in browser
Go to 👉 ([dashbaord](https://uber-anlytics-dashboard-itv3kjahgtjdnghgc8bnf5.streamlit.app/))
---
## 📊 Sample Dashboard Preview
Interactive charts and filters let you explore ride demand, cancellations, and revenue over time.
---
## 📌 Future Enhancements
- Add Geo-visualization (maps) of pickup/drop locations
- Implement Predictive Analytics for demand forecasting
- Export reports in PDF/Excel format
---
## 👨💻 Author
**Aymen Baig**