This project involves extracting data from the PhonePe Pulse GitHub repository, transforming it, and visualizing it using a live geo dashboard built with Streamlit and Plotly. The solution provides valuable insights and information about various metrics and statistics from the PhonePe Pulse data.
Tools and Technologies GitHub Cloning: To fetch the data from the PhonePe Pulse GitHub repository. Python: For scripting and data processing. Pandas: For data manipulation and cleaning. MySQL: For efficient data storage and retrieval. mysql-connector-python: To connect Python with MySQL. Streamlit: For creating an interactive dashboard. Plotly: For data visualization. Steps to Solution
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Clone the GitHub Repository Clone the PhonePe Pulse GitHub repository to your local machine to access the raw data files.
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Data Extraction and Preprocessing Extract data from the cloned repository and process it using Python and Pandas:
Load the data from the files. Combine data from multiple files if necessary. Clean the data by handling missing values, ensuring data consistency, and transforming it into a suitable format for analysis.
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Insert Data into MySQL Database Set up a MySQL database and create a table structure that fits the data schema. Insert the cleaned and transformed data into the MySQL database for efficient storage and retrieval.
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Create Live Geo Visualization Dashboard Develop an interactive dashboard using Streamlit and Plotly:
Connect to the MySQL database to fetch the data. Provide a user-friendly interface for selecting different metrics and visualizations. Use Plotly to create interactive and visually appealing geo visualizations. 5. Fetch Data from MySQL for Dashboard Ensure the dashboard dynamically fetches data from the MySQL database to display up-to-date information. Implement caching where necessary to improve performance.
- Provide Dropdown Options Include at least 10 dropdown options on the dashboard for users to select different metrics and figures to display. Each option should trigger an update in the visualization to reflect the selected data.
Running the Project Clone the Repository:
Use Git to clone the PhonePe Pulse repository to your local machine. Set Up MySQL Database:
Install MySQL and set up a new database. Create the necessary tables to store the extracted data. Extract and Insert Data:
Use Python scripts to read data from the cloned repository. Clean and transform the data as needed. Insert the processed data into the MySQL database. Run the Streamlit Dashboard:
Develop the Streamlit application to create the dashboard. Ensure the application connects to the MySQL database to fetch and display data. Use Plotly to create interactive geo visualizations based on the data. Access the Dashboard:
Launch the Streamlit application to access the interactive dashboard. Use the dropdown options to explore different metrics and visualizations. Security, Efficiency, and User Experience Security: Ensure secure connections to the MySQL database. Implement proper authentication and authorization mechanisms. Efficiency: Optimize data fetching and processing to ensure the dashboard is responsive. Implement caching strategies to reduce load times. User Experience: Design the dashboard to be intuitive and easy to use. Provide clear instructions and tooltips to guide users through different functionalities.
Conclusion : This project provides a comprehensive solution for extracting, processing, and visualizing PhonePe Pulse data. The interactive dashboard created with Streamlit and Plotly offers a user-friendly interface for exploring various metrics and gaining valuable insights from the data.