https://github.com/praveendecode/phonepe_pulse

Phonepe Pulse Data Visualization and Exploration: A User-Friendly Tool Using Streamlit and Plotly
https://github.com/praveendecode/phonepe_pulse

data-visualization dataanalysis financial-analysis mongodb postgres python sql streamlit-dashboard

Last synced: 30 days ago
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Phonepe Pulse Data Visualization and Exploration: A User-Friendly Tool Using Streamlit and Plotly

• Host: GitHub
• URL: https://github.com/praveendecode/phonepe_pulse
• Owner: praveendecode
• Created: 2023-08-07T10:17:26.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-12-21T12:22:32.000Z (over 1 year ago)
• Last Synced: 2025-02-09T13:35:01.790Z (3 months ago)
• Topics: data-visualization, dataanalysis, financial-analysis, mongodb, postgres, python, sql, streamlit-dashboard
• Language: Jupyter Notebook
• Homepage:
• Size: 6.76 MB
• Stars: 0
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Phonepe Revenue Analysis 

  ![image](https://github.com/praveendecode/phonepe_pulse/assets/95226524/24048113-5ef7-449c-9c7d-6f6cd78c98bd)

 

# 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.