Phonepe-Pulse-Data-Visualization-And-Exploration

Domain: Fintech

Introduction

PhonePe Pulse Data Visualization and Exploration project is designed to transform and visualize data from the PhonePe Pulse GitHub repository in an engaging and intuitive way.It provides insights into various metrics and statistics related to PhonePe's transactions,insurance and user data.

Technologies Used
Installation
Import Libraries from Modules
Usage
Features

Technologies Used:

Python
Pandas
MySQL
Streamlit
Plotly
GitHub

Installation

pip install pandas
pip install mysql-connector-python
pip install stramlit
pip install plotly

Import Libraries from Modules

import streamlit as st
from streamlit_option_menu import option_menu
import os
import json
import pandas as pd
import mysql.connector
import requests
import plotly.express as px
from PIL import Image
from streamlit_lottie import st_lottie
import base64

Usage

Steps to be followed for effectively using the application:

Access the Streamlit App in the web browser
Select the Analysis method from the Navigation Menu such as Aggregated Analysis,Map Analysis, Insurance Analysis, Data Analysis.
After selecting the Analysis method and apply filters such as year,quarter and state.
Now the Streamlit will display the details using visualizations.
Use the input box provided to select from a variety of queries for data analysis.
By selecting the Query, streamlit will process the request and display the answers.

Features

Data Extraction: Data is fetched from the PhonePe Pulse GitHub respository and cloned into the local environment.
Data Transformation: Clean and Structure the data using Python and Pandas.
Database Insertion: Storing the cleaned and structured data in MySQL Database.
Dashboard Creation: Create an interactive dashboard using Streamlit and Plotly
Data Retrieval: Retrieve data from the MySQL database to ensure the dashboard updates dynamically.

Geeth-Priya/Phonepe-Pulse-Data-Visualization-And-Exploration