This project presents a fully interactive data dashboard that visualizes PhonePe Pulse transaction data across India using Streamlit, Plotly, and MySQL. It also includes a professional Power BI report for high-level business insights.
PhonePe is one of India's most popular digital payment platforms. This dashboard helps visualize key patterns and behaviors across different states, districts, quarters, and years.
- 📈 Track transaction volume and value trends
- 👤 Analyze user registrations and engagement across devices
- 🛡 Evaluate insurance penetration across regions
- 📍 Explore district-wise and pincode-level insights
- ✅ Real-time visualizations using Plotly and GeoJSON maps
- ✅ Year and Quarter filters for dynamic exploration
- ✅ Business Case Studies across 6 dimensions:
- Decoding Transaction Dynamics
- Device Dominance & User Engagement
- Insurance Growth Analysis
- Market Expansion via Transactions
- User Engagement Trends
- Insurance Engagement by District
- ✅ Power BI Dashboard Report (
/PowerBIfolder) - ✅ Clean and branded UI with Streamlit
| Tool | Purpose |
|---|---|
| Python | Backend Data Processing |
| MySQL | Database for structured data |
| Streamlit | Interactive Web App |
| Plotly | Visualizations and Charts |
| Power BI | Professional Report Insights |
| GitHub | Version Control & Deployment |
├── phonepay.py # Streamlit App Source Code
├── datafetch_notebook.ipynb # Jupyter Notebook for Data Extraction
├── /PowerBI # Reports and Power BI visuals
│ ├── PhonePe_Insights_Report.docx
│ └── Dashboard_Visuals.pbix
├── /data # Raw JSON Files from PhonePe Pulse
└── README.md # This file
- Clone the repository:
git clone https://github.com/YourUsername/Phonepe_Transaction_Insights.git
cd Phonepe_Transaction_Insights- Install required packages:
pip install -r requirements.txt- Run the Streamlit App:
streamlit run phonepe.py