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[ Phonepe Pulse Data Visualization dependence on given specifications. ] | ( Disclaimer: Transaction and user analysis of Phonepe app in INDIA 2018 - 2022 only ) | Clone | Python | Pandas | Numpy | MySQL | Streamlit | Plotly | Geo visualization |

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Gopinathalpha7/Phonepe_Pulse_Data_Visualization

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Phonepe Pulse Data Visualization

Introduction

  • 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 "

Intro GUI

Developer Guide

1. Tools install

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

2. Requirement Libraries to Install

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

3. Import Libraries

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

4. E T L Process

a) Extract data

b) Process and Transform the data

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

c) Load data

  • 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()})

5. E D A Process and Frame work

a) Access MySQL DB

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

b) Filter the data

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

c) Visualization

  • 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

User Guide

Step 1.

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

Step 2.

  • Select any one option fron Transaction or User.

Step 3.

  • Select any Year, Quarter and additional required option.

Step 4.

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

Video link

  • Click the below Image

Intro GUI

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[ Phonepe Pulse Data Visualization dependence on given specifications. ] | ( Disclaimer: Transaction and user analysis of Phonepe app in INDIA 2018 - 2022 only ) | Clone | Python | Pandas | Numpy | MySQL | Streamlit | Plotly | Geo visualization |

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