This is my Phonepe pulse data visualization from 2018-2022 project

Importing required libraries

import streamlit as st
from PIL import Image
import os
import json
from streamlit_option_menu import option_menu
import pandas as pd
import sqlite3
import plotly.express as px

if the module shows any error or module not found it can be overcome by using below command

pip install<module name>

In order to get the data clone the github

• Inorder to clone the github data into to working environment use below command

import requests
response = requests.get(url)
repo = response.json()
clone_url = repo['clone_url']
repo_name = "pulse"
clone_dir = os.path.join(os.getcwd(), repo_name)

Creating csv file

• after cloning the data from github the dat in the form of json file
• In order to convert json file into data frame we use below code

clm={'State':[], 'Year':[],'Quater':[],'Transaction_type':[], 'Transaction_count':[], 'Transaction_amount':[]}
for i in Agg_state_list:
    p_i=path+i+"/"
    Agg_yr=os.listdir(p_i)
    for j in Agg_yr:
        p_j=p_i+j+"/"
        Agg_yr_list=os.listdir(p_j)
        for k in Agg_yr_list:
            p_k=p_j+k
            Data=open(p_k,'r')
            D=json.load(Data)
            for z in D['data']['transactionData']:
              Name=z['name']
              count=z['paymentInstruments'][0]['count']
              amount=z['paymentInstruments'][0]['amount']
              clm['Transaction_type'].append(Name)
              clm['Transaction_count'].append(count)
              clm['Transaction_amount'].append(amount)
              clm['State'].append(i)
              clm['Year'].append(j)
              clm['Quater'].append(int(k.strip('.json')))

# Successfully created a dataframe
df_aggregated_transaction=pd.DataFrame(clm)

• After creating dataframe insert the dataframe into sql server by using sqlite3
• To Establish the connection with sql server

connection = sqlite3.connect("phonepe pulse.db")
cursor = connection.cursor()

• Create sql queries to fetch the data as per the user requirement

SELECT * FROM "Table"
WHERE "Condition"
GROUP BY "Columns"
ORDER BY "Data"

• create the streamlit app with basic tabs Reference
• visualizing the data with plotly and streamlit

I hope this project helps you to the understand more about phonepe