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.
- π The project was developed locally in VSCode, within a newly created virtual environment.
- π I cloned the PhonePe Pulse repository from the GitHub link provided by the GUVI team to extract and download the required dataset.
- π οΈ A new database named
phonepe_pulse.dbwas created, and the extracted data was structured into appropriate tables and inserted using custom scripts. - π 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.
- π Select Page dropdown:
DashboardorQuery Data - π Radio Buttons:
TransactionsandUsers - ποΈ Select Year dropdown
- π Select Quarter dropdown
- πΊοΈ Interactive 2D India map
- Hovering over any state shows:
- State name
- Total Transaction Amount
- Total Transaction Count
- π Transactions Table:
- Total Transactions (Count)
- Total Payment Value (Amount)
- Average Transaction Value
- π Categories Table:
- Merchant payments
- Peer-to-peer payments
- Recharge & bill payments
- Financial Services
- Others
- π Top 10 insights:
States,Districts,Postal Codes
- πΊοΈ Map showing:
- State name
- User Count
- User Percentage
- π Users Table:
- Registered PhonePe Users
- PhonePe App Opens
- π Top 10 insights:
States,Districts,Postal Codes
Provides analytical insights derived from SQL queries on the underlying database.
- π§ Includes 10 predefined analytical questions
- π§Ύ SQL queries display insights based on user selection
- β GitHub data extraction
- β Data cleaning with Pandas
- β SQL database integration
- β Streamlit + Plotly dashboard creation
- β Geo-visualization with maps
- β 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
- Clone the repository
- Install dependencies
pip install -r requirements.txt
- Launch the app
streamlit run phonepe_app.py