https://github.com/nitheshgoutham/phonepe-pulse-data
Phonepe Pulse Data Visualization and Exploration: A User-Friendly Tool Using Streamlit and Plotly
https://github.com/nitheshgoutham/phonepe-pulse-data
data-science data-visualization plotly python sql streamlit
Last synced: about 2 months 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/nitheshgoutham/phonepe-pulse-data
- Owner: NitheshGoutham
- Created: 2024-06-12T07:54:50.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-06-12T08:03:31.000Z (11 months ago)
- Last Synced: 2025-01-26T11:08:14.417Z (4 months ago)
- Topics: data-science, data-visualization, plotly, python, sql, streamlit
- Language: Python
- Homepage:
- Size: 28.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Phonepe Pulse Data Visualization and Exploration: A User-Friendly Tool Using Streamlit and Plotly
## 📘 Introduction
* This project involves cloning the PhonePe Pulse dataset using Git
* then transforming the data into dataframe by using Pandas.
* Transformed data is subsequently stored in a SQL database with help of SQL conncetor and SQL-Alchemy engine.
* Additionally, an interactive dashboard is developed with Streamlit and Plotly, featuring geoplots and other visualization elements for enhanced data exploration and insights.
### Domain : 💰*Fintech*
### 🎨 Skills Takeaway
Github Cloning, Python Scripting , MySQL Database,mysql-connector-python, Streamlit, and Plotly.
### 🛠 Technology and Tools
* Python
* MYSQL
* Streamlit
* Plotly
### 📚 Packages and Libraries
* import os
* import json
* import git
* import pandas as pd
* import plotly.express as px
* import streamlit as st
* from streamlit_option_menu import option_menu
* import time
* import mysql.connector
* from sqlalchemy import create_engine
### 📂 Data Source
The data utilized in this project predominantly consists of openly available datasets sourced from PhonePe.[click here to view](https://github.com/PhonePe/pulse/tree/master/data/aggregated/transaction/country/india/state)
### 📘 Overview
#### ✂️ Data Extraction:
* the data is extracted from the PhonePe Pulse GitHub repository and cloned to the local environment, ensuring access to the latest dataset for analysis.
#### 🔁 Data Transformation:
* The raw data undergoes transformation, including cleaning, formatting, and structuring in dataframe format using pandas
#### 🗃️ Database Integration:
* Mysql connector used for connection between Python and MySQL database with XAMPP, enabling data transfer. SQLAlchemy's engine facilitates efficient data insertion and querying, simplifying database interactions for Python.
#### 📊 Data Visualization And Analysis:
* With the assistance of Streamlit and Plotly, a dashboard and charts are created, offering geospatial visualizations and top insights. This setup empowers users to explore and reveal trends within the dataset, facilitating insightful analysis.
### 📘 Features
#### 🌐 GEO visualization:
* The geo visualization showcases transaction amounts and counts across Indian states, plotted on a map. Additionally, it incorporates registered user counts, providing a state-wise overview on the map
#### 🔝 TOP Insights:
* Top insights encompass various key findings derived from the data, visualized through charts showcasing the most significant trends.
#### ⏯️ Filter Insight:
* Filter insights enable users to customize analysis by selecting specific criteria like state, year, and quarter. This generates top insights in charts based on the chosen parameters, offering tailored visualizations for deeper analysis.
### 👨🏫 Reference
* [Python Documentation](https://docs.python.org/3/)
* [Mysql Documentation](https://dev.mysql.com/doc/)
* [Streamlit Documentation](https://docs.streamlit.io/)
* [Plotly Documentation](https://plotly.com/python/)
### 📞 Contact
LINKEDIN: https://www.linkedin.com/in/nithesh-goutham-m-0b0514205/
WEBSITE : https://digital-cv-using-streamlit.onrender.com/
EMAIL : [email protected]