{"id":22376718,"url":"https://github.com/hemanthkumarsunkari27/pmay_analysis_project","last_synced_at":"2025-03-26T18:17:40.390Z","repository":{"id":264627311,"uuid":"892989781","full_name":"Hemanthkumarsunkari27/pmay_analysis_project","owner":"Hemanthkumarsunkari27","description":"Built for the 1st AI for Good Hackathon by Snowflake, this project uses data analytics and AI to explore housing and sanitation trends in India under PMAY. 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Using data from Snowflake and interactive visualizations with Streamlit, the application enables users to explore PMAY beneficiaries and sanitation progress across different states. The project identifies key insights and gaps in housing and sanitation infrastructure, helping inform policy decisions.\n\n## Features\n\n1.Data Ingestion: Loads PMAY and sanitation data from Snowflake.\n2.Data Transformation**: Processes and transforms the data for analysis.\n3.Data Analysis: Computes insights such as beneficiary percentages and sanitation coverage trends.\n4.Interactive Visualizations: Users can explore data by state, district, and year with an interactive Streamlit app.\n4.Downloadable Data: Processed data is available for download for further analysis.\n\n## Technology Stack\n\n- **Snowflake**: Centralized data storage and processing.\n- **Python**: Data manipulation, analysis, and visualization.\n- **Streamlit**: Builds the interactive user interface for data exploration.\n- **Pandas**: Data processing and manipulation.\n- **Seaborn \u0026 Matplotlib**: Data visualization libraries.\n\n## Project Structure\n\n├── app.py # Main Streamlit app file ├── snowflake_connection.py # Snowflake connection setup ├── data_processing.py # Data retrieval functions ├── analysis.py # Data analysis functions ├── requirements.txt # Dependencies └── README.md # Project documentation\n\n\n## Setup Instructions\n\n### Prerequisites\n\n- Python 3.7 or later\n- Snowflake account (for database access)\n- Streamlit installed for running the app\n\n### Installation\n\n2.Set up a virtual environment (optional but recommended):\npython -m venv venv\nsource venv/bin/activate  # On Windows: venv\\Scripts\\activate\n\n3.Install the required dependencies:\npip install -r requirements.txt\n\n4.Configure your Snowflake connection in snowflake_connection.py by updating the following placeholders with your credentials:\nuser='\u003cUSERNAME\u003e'\npassword='\u003cPASSWORD\u003e'\naccount='\u003cACCOUNT\u003e'\nwarehouse='\u003cWAREHOUSE\u003e'\ndatabase='\u003cDATABASE\u003e'\nschema='\u003cSCHEMA\u003e'\n\n\n#### Running the application\n\n1.Start the Streamlit app:\nstreamlit run app.py\n\n2.Open the link provided (e.g., http://localhost:8501) in your web browser.\n\n\n##### Usage\nPMAY Beneficiaries Analysis: Explore the percentage of PMAY beneficiaries across states.\nSanitation Coverage Analysis: View sanitation progress for each state over time.\nData Download: Use the download buttons to export data for further analysis.\n\n\n###### Error Handling and Logging\nErrors during data ingestion, transformation, or visualization are logged in error_log.log. Check this file if issues arise.\nThe application validates data completeness and logs any discrepancies for troubleshooting.\n\n\n###### Deployment(Optional)\nTo deploy this app on Streamlit Cloud:\n1.Push your project to a GitHub repository.\n2.Go to Streamlit Cloud and connect to your GitHub account.\n3.Select your project repository and configure environment variables for Snowflake credentials if required.\n4.Deploy the app for online access.\n\n\n###### License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhemanthkumarsunkari27%2Fpmay_analysis_project","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhemanthkumarsunkari27%2Fpmay_analysis_project","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhemanthkumarsunkari27%2Fpmay_analysis_project/lists"}