https://github.com/dineshdhamodharan24/phonepe-pulse-data-visualization-and-exploration
PhonePe Pulse: Data Visualization and Exploration a User-Friendly Tool using MySQL, Streamlit, and Plotly.
https://github.com/dineshdhamodharan24/phonepe-pulse-data-visualization-and-exploration
cloning guvi-projects json mysql os pandas plotly python3 streamlit-dashboard
Last synced: about 2 months ago
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PhonePe Pulse: Data Visualization and Exploration a User-Friendly Tool using MySQL, Streamlit, and Plotly.
- Host: GitHub
- URL: https://github.com/dineshdhamodharan24/phonepe-pulse-data-visualization-and-exploration
- Owner: DineshDhamodharan24
- Created: 2023-11-15T15:02:58.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-11-18T14:49:07.000Z (over 1 year ago)
- Last Synced: 2025-04-23T05:17:50.751Z (about 2 months ago)
- Topics: cloning, guvi-projects, json, mysql, os, pandas, plotly, python3, streamlit-dashboard
- Language: Jupyter Notebook
- Homepage: https://www.linkedin.com/in/dinesh-dhamodharan-2bbb9722b/
- Size: 955 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Phonepe-Pulse-Data-Visualization-and-Exploration
**To check website in My Project**
Link: [phonepe-plus-project.onrender.com](https://phonepe-plus-project.onrender.com/)
**Problem Statement**
Retrieve data from the Phonepe Pulse GitHub repository, perform data transformation and cleansing,insert it into a MySQL database, and develop a live geo-visualization dashboard using Streamlit and Plotly in Python.The dashboard will present the data interactively and aesthetically, featuring a minimum of 10 diverse dropdown optionsfor users to select various facts and figures. The solution aims to be secure, efficient, and user-friendly, offering valuable insights and information about the data within the Phonepe Pulse GitHub repository.
**Technology Stack Used:**
1. Python
2. MySQL
3. Streamlit
4. colab
5. Github Cloning
6. Geo Visualisation
**Installation:**
pip install pandas
pip install numpy
pip install os
pip install mysql.connector
pip install git_clone
pip install stramlit
**Import Libraries:**
import pandas as pd
import numpy as np
import os
import json
import mysql.connector
import streamlit as st
import plotly.express as px
**Approach:**
1. Data Extraction: The data is obtained from the PhonePe Pulse GitHub repository using scripting techniques and cloned for further processing [(link)](https://github.com/PhonePe/pulse.git).
2. Data Transformation: Process the cloned data using Python algorithms to transform it into DataFrame format, ensuring it is clean and ready for analysis.
3. Database Integration: The transformed data is inserted into a MySQL database, providing efficient storage and retrieval capabilities.
4. Live Geo Visualization Dashboard: Utilizing Python's Streamlit and Plotly libraries, create an interactive and visually appealing dashboard. This real-time dashboard enables users to explore insights effectively.
5. Database Integration with the Dashboard: Fetch relevant data from the MySQL database and seamlessly integrate it into the dashboard, ensuring that the displayed information is up-to-date and accurate.
6. Visualization: Finally, create a dashboard using Streamlit, incorporating selection and dropdown options. Showcase the output through Geo visualization, bar charts, and a DataFrame table.
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