Phonepe Revenue Analysis

Overview

• This project aims to create an interactive data visualization tool for the Phonepe Pulse data available on GitHub. The tool provides user-friendly access to various metrics and statistics.

Features

• Data Extraction: Automates the process of fetching data from the Phonepe Pulse GitHub repository

• Data Transformation: Cleans and processes the data using Python and Pandas.

• Database Integration: Stores the cleaned data in a PostgreSQL database for efficient retrieval.

• Interactive Dashboard: Presents data using Streamlit and Plotly, offering dynamic visualizations.

• Data Retrieval: Connects to the PostgreSQL database to display data on the dashboard.

• Customization: Offers more interactive options for users to select different data visualizations.

Getting Started

• Clone the GitHub repository.

• Use Python, Pandas, and pymongo for data processing.

• Set up the PostgreSQL database for data storage.

• Create the interactive dashboard using Streamlit and Plotly.

• Fetch data from the database for dashboard updates.

Technical Steps to Execute the Project

Step 1: Install Required Libraries

• Before running the project, make sure to install the necessary libraries mentioned in the Dashboard.py file.

Step 2: Execute ETL Process

• Use the ETL.py file to perform the Extract, Transform, Load (ETL) process on the Phonepe Pulse data.

Step 3: Run the Dashboard

• Fork the Dashboard folder and run it in your local integrated development environment (IDE).

Step 4: Utilize the Phonepe_pulse Class

• In this project, a Phonepe_pulse class has been created to manage the methods and processes.

Methods:

• Dashboard : This method contains the code for the interactive dashboard, where data visualizations are presented.

• Note: Streamlit is used in this project to make our code visually appealing and to provide an eye-catching data presentation.

Tools Covered

• Python (Scripting)

• ETL (Extract, Transform, Load)

• MongoDB

• SQL (Structured Query Language)

• Data Management using PostgreSQL

• User Interface: Streamlit

• Data Visualization: Plotly-express

• IDE: PyCharm Community Version

Results

• This project delivers a user-friendly geo-visualization dashboard for exploring Phonepe Pulse data. Users can access and interact with various data visualizations through a web browser, gaining valuable insights from the Phonepe Pulse GitHub repository.