📊 PhonePe Pulse Data Visualization and Exploration

This project aims to extract, process, and visualize large-scale data related to digital transactions and user statistics from the PhonePe Pulse GitHub repository. The data is transformed and presented through an interactive and user-friendly web dashboard built using Streamlit and Plotly.

• 📁 The project was developed locally in VSCode, within a newly created virtual environment.
• 🔗 I cloned the PhonePe Pulse repository from the GitHub link provided by the GUVI team to extract and download the required dataset.
• 🛠️ A new database named phonepe_pulse.db was created, and the extracted data was structured into appropriate tables and inserted using custom scripts.
• 📊 A two-page Streamlit dashboard was designed and developed based on the core requirements of the project.

The app consists of two main pages:

Provides an intuitive interface for exploring digital transaction and user data across India.

• 📄 Select Page dropdown: Dashboard or Query Data
• 🔘 Radio Buttons: Transactions and Users
• 🗓️ Select Year dropdown
• 📆 Select Quarter dropdown

• 🗺️ Interactive 2D India map
• Hovering over any state shows:
  • State name
  • Total Transaction Amount
  • Total Transaction Count
• 📉 Transactions Table:
  • Total Transactions (Count)
  • Total Payment Value (Amount)
  • Average Transaction Value
• 📊 Categories Table:
  • Merchant payments
  • Peer-to-peer payments
  • Recharge & bill payments
  • Financial Services
  • Others
• 🔘 Top 10 insights: States, Districts, Postal Codes

• 🗺️ Map showing:
  • State name
  • User Count
  • User Percentage
• 📉 Users Table:
  • Registered PhonePe Users
  • PhonePe App Opens
• 🔘 Top 10 insights: States, Districts, Postal Codes

Provides analytical insights derived from SQL queries on the underlying database.

• 🧠 Includes 10 predefined analytical questions
• 🧾 SQL queries display insights based on user selection

• ✅ GitHub data extraction
• ✅ Data cleaning with Pandas
• ✅ SQL database integration
• ✅ Streamlit + Plotly dashboard creation
• ✅ Geo-visualization with maps
• ✅ Writing and integrating SQL queries

• Python
• Pandas
• Streamlit
• Plotly
• MySQL / SQLite
• mysql-connector-python
• Git / GitHub

• Source: PhonePe Pulse GitHub Repository
• Type: Digital Payments & User Statistics
• Inspired by: PhonePe Pulse

1. Clone the repository
2. Install dependencies

   pip install -r requirements.txt

3. Launch the app

   streamlit run phonepe_app.py