PhonePe has become one of the most popular digital payment platforms in India, with millions of users relying on it for their day-to-day transactions. The app is known for its simplicity, user-friendly interface, and fast and secure payment processing. It has also won several awards and accolades for its innovative features and contributions to the digital payments industry.

We create a web app to analyse the Phonepe transaction and users depending on various Years, Quarters, States, and Types of transaction and give a Geographical and Geo visualization output based on given requirements.

" Disclaimer:-This data between 2018 to 2022 in INDIA only "

virtual code. Jupyter notebook. Python 3.11.0 or higher. MySQL Git

pip install pandas numpy os json requests subprocess mysql.connector sqlalchemy pymysql streamlit plotly.express

clone libraries

import requests import subprocess pandas, numpy and file handling libraries

import pandas as pd import numpy as np import os import json SQL libraries

import mysql.connector import sqlalchemy from sqlalchemy import create_engine import pymysql Dashboard libraries

import streamlit as st import plotly.express as px

Initially, we Clone the data from the Phonepe GitHub repository by using Python libraries. https://github.com/PhonePe/pulse.git

Process the clone data by using Python algorithms and transform the processed data into DataFrame formate.

Finally, create a connection to the MySQL server and create a Database and stored the Transformed data in the MySQL server by using the given method. df.to_sql('table_name', connection, if_exists = 'replace', index = False, dtype={'Col_name':sqlalchemy.types.datatype()})

Create a connection to the MySQL server and access the specified MySQL DataBase by using pymysql library

Filter and process the collected data depending on the given requirements by using SQL queries

Finally, create a Dashboard by using Streamlit and applying selection and dropdown options on the Dashboard and show the output are Geo visualization, bar chart, and Dataframe Table

Select any one option fron All India or State wise or Top Ten categories.

Select any one option fron Transaction or User.

Select any Year, Quarter and additional required option.

Finally, You get the Geo Visualization Analysis or Bar chart Analysis and Table format Analysis