Skip to content

Farhaknight/PhonePe-Transactions

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

10 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

🚀 PhonePe Transaction Insights Dashboard

Welcome to PhonePe Transaction Insights, an interactive and data-rich web dashboard that explores India's evolving digital payments using real data from PhonePe Pulse.

Built using Python, SQL and Streamlit, this project helps decode where, how, and how much India transacts digitally — uncovering growth areas, user behavior, and regional insights.


📁 Project Structure

📦 PhonePe-Transaction

├── sql_queries/ → SQL scripts for business use cases

├── colab_notebooks/ → Google Colab notebooks for EDA

├── streamlit_app/ → Streamlit files (app.py, home.py, db_config.py)

├── datasets/ → Raw & processed PhonePe data

└── README.md → This file


🛠️ Tools & Tech Stack

Tool Purpose
SQL Querying & transforming raw data
Pandas Data cleaning & manipulation
Plotly Interactive charts & maps
Streamlit Web dashboard development
Colab Exploratory data analysis
Git & GitHub Version control & collaboration

🧠 Problem Statement

With India’s digital payments skyrocketing post-2018, it’s crucial to understand how different regions use PhonePe — helping businesses target users better, boost financial inclusion, and optimize services.

This project explores PhonePe data by transaction type, geography, insurance coverage, and user patterns.


🔍 Business Use Cases Covered

  1. Transaction Dynamics 📈
    Analyze how transaction types vary over time and region.

  2. User & Device Engagement 📱
    Identify high-usage states/districts for expansion or offers.

  3. Insurance Growth & Penetration 🛡️
    Understand how and where users buy digital insurance.

  4. Year-on-Year Comparative Analysis 📊
    Track how behavior changed between 2018–2023.


💡 Dashboard Features (Streamlit)

Sidebar Filters

  • Transaction Type
  • Year
  • Quarter
  • View: States | Districts | Postal Codes

🖼️ Visual Elements

  • 📊 Bar charts (top 10 performers)
  • 📈 Scatter plots (growth vs penetration)

🔄 Real-time querying via SQL → pandas → Plotly


📈 Key Insights Gained

Andhra Pradesh, Maharashtra, Karnataka lead in volume & value 💰

Insurance still has low penetration in eastern & NE states

🎯 Business Recommendations

✅ Focus on Emerging Districts: Target areas like NTR District, Vizianagaram with offers.

✅ Boost Insurance Awareness: Use data to guide outreach in low-penetration states.


🤝 Contributing Want to make this project better? Found a bug or have an idea? Fork it, star it, and open a PR! 🚀


🙌 Thank You! This project was made to showcase practical SQL + Python + Visualization integration with real Indian financial data. If you find this useful, feel free to ⭐️ the repo and share your feedback.

📬 Let the data talk. Let insights drive decisions.

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors