DVD Rental Analytics — Streamlit Dashboard

A polished, local-first Streamlit dashboard for exploring the DVD Rental CSV dataset. Load your CSVs from a folder (e.g. ./data) and the app will register them into an in-memory DuckDB and provide 25 built-in analytics queries, interactive Plotly visualizations, a saved-queries panel, and an Advanced SQL explorer.

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🚀 Live Demo (Streamlit Cloud)

You can try the live deployed version here:

👉 https://customer-behavior.streamlit.app/

This deployment contains the full dashboard, all features, and supports uploading a dataset folder directly inside the app.

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Key features

• Auto-load all CSVs from a folder and register them in DuckDB.
• 7 interactive tabs: Overview, Customers, Rentals & Stores, Categories & Films, Revenue, Actors, Advanced SQL.
• 25 converted DuckDB saved queries (one-click buttons).
• Interactive Plotly charts: area, stacked bar, heatmap, treemap, sunburst, violin, scatter, Pareto, rolling averages.
• Compact dashboard header with metric cards and quick actions.
• Advanced SQL Explorer: run custom DuckDB SQL + visualize the results.
• CSV export of all registered tables.
• Single-file Streamlit app — fast, local, no external compute.

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Quick start

1. Clone your repo:

   git clone https://github.com/RobinMillford/Customer-Behavior-in-DVD-Rentals.git
   cd Customer-Behavior-in-DVD-Rentals

2. Create a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate        # macOS / Linux
   venv\Scripts\activate           # Windows PowerShell
   
   pip install -r requirements.txt

3. Place all CSV files in a folder such as ./data.

4. Run the dashboard:

   streamlit run dashboard.py

5. In the app sidebar:

   • Enter dataset folder path
   • Load CSVs
   • Explore visualizations
   • Run saved queries
   • Run your own SQL

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Saved Queries

All 25 queries from the original analysis are included in the Saved Queries area.

Examples include:

• Top 3 Spenders
• Monthly Rentals per Store
• Revenue, Cost & ROI by Category
• Family Movie Rental Counts
• Customer Lifetime Value
• Loyalty Tiers
• Late Returns Impact
• Most Profitable Actors
• Film Availability & Demand
• …and much more

Click a button → query runs instantly → results appear below → optional visualization.

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Visualizations & Interaction

• Interactive Plotly charts (zoom, hover, export).
• Auto-generated charts for saved queries and custom SQL.
• Multiple visualization types: scatter, bar, box, treemap, pie, histogram.
• Export all DuckDB tables back to CSV.

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Troubleshooting & Tips

• No CSVs found? Check the folder path.

• Table mismatch? Ensure file names loosely match (customer.csv, film_category.csv, etc.).

• Datetime issues? Disable Auto-Coerce Dates in the sidebar.

• DuckDB casting errors? Use:

  CAST(payment_date AS TIMESTAMP)

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Development Notes

• Uses in-memory DuckDB for fast SQL execution.
• All queries stored in SAVED_QUERIES.
• Clean CSS-based dark theme (full dark mode).
• Lightweight and easy to extend.

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Contributing

1. Fork the repo
2. Create a feature branch
3. Run locally and test
4. Submit PR 🚀

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Acknowledgements

Built with ❤️ using:

• Streamlit
• Pandas
• DuckDB
• Plotly

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