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https://github.com/moha-cm/phonepe-pulse-with-streamlit
Phonepe Pulse Data Visualization and Exploration: A User-Friendly Tool Using Streamlit and Plotly
https://github.com/moha-cm/phonepe-pulse-with-streamlit
github-cloning mysql-connector-python mysql-database plotly python python-script sqlalchemy streamlit
Last synced: 7 days 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/moha-cm/phonepe-pulse-with-streamlit
- Owner: Moha-cm
- Created: 2023-11-05T03:45:31.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2023-12-02T14:34:04.000Z (12 months ago)
- Last Synced: 2024-01-29T10:12:18.264Z (10 months ago)
- Topics: github-cloning, mysql-connector-python, mysql-database, plotly, python, python-script, sqlalchemy, streamlit
- Language: Python
- Homepage:
- Size: 63.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Project Title :Phonepe-Pulse-with-streamlit
Phonepe Pulse Data Visualization and Exploration: A User-Friendly Tool Using Streamlit and Plotly
## **Overview**
The Phonepe pulse Github repository contains a large amount of data information related to Tarnsaction and Users in the states of India. ...
## Approach
1. **Data Extraction:**
- Employ scripting to clone the Phonepe pulse Github repository, extracting data related to transactions and user activities.
2. **Data Transformation:**
- Using **Python** libraries such as Pandas, to manipulate and preprocess the extracted data. This step involves cleaning, handling missing values, and transforming the data into a format conducive to analysis.
3. **Database Insertion:**
- Utilize the "mysql-connector-python" library in Python to establish a connection with a MySQL database. Execute SQL commands to seamlessly insert the transformed data, ensuring efficient storage and retrieval.
4. **Dashboard Creation:**
- Harness the capabilities of **Streamlit** and **Plotly** in Python to craft an interactive and visually captivating dashboard. This platform will serve as the gateway for users to explore and understand the insights derived from the data.
5. **Data Retrieval:**
- Employ the "mysql-connector-python" library to connect to the MySQL database. Retrieve the data into a Pandas dataframe, enabling dynamic updates to the dashboard and ensuring users always have access to the latest information.
6. **Data Analysis**
- Develop a comprehensive dashboard that facilitates an effective and insightful analysis of the data.
## Pyhton packages
```
pip install pandas
pip install streamlit
Pip install sqlalchemy
pip install PyMySQL
pip isstall git
pip install plotly
```
Dowload the source files from repo and use the bellow commandas to run
## Script Execution
## Data Extraction and Transformation
Run the following commands to extract and transform data related to users:
```
python .\Transaction_database.py
python .\users_datase.py
```
This script employs scripting to clone the Phonepe Pulse GitHub repository, then extracts users and transaction data and store in database.
## Run the application using the following command
```
streamlit run ./home.py
```
This will launch the Streamlit application.