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README.md

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----
-title: Book Sales Analytics App
-emoji: 📚
-colorFrom: indigo
-colorTo: purple
-sdk: gradio
-sdk_version: 5.22.0
-app_file: app.py
-pinned: false
----
-
-# Book Sales Analytics App
-
-This Space converts the logic from the uploaded Jupyter notebook into a single `app.py` file and runs it on:
-
-- `synthetic_book_reviews.csv`
-- `synthetic_sales_data.csv`
-
-## What the app does
-
-1. Loads the two CSV datasets.
-2. Recreates the notebook analysis in Python functions.
-3. Generates:
-   - static figures
-   - KPI summaries
-   - dashboard tables
-   - pricing decisions
-   - ARIMA forecast visualizations
-4. Displays the outputs in a Gradio dashboard.
-
-## Files included
-
-- `app.py` — main Hugging Face Space app
-- `requirements.txt` — pinned Python dependencies
-- `style.css` — lightweight UI styling
-- `synthetic_book_reviews.csv` — input dataset
-- `synthetic_sales_data.csv` — input dataset
-
-## Deploy on Hugging Face Spaces
-
-1. Create a new **Gradio** Space.
-2. Upload all files from this folder.
-3. Wait for the Space to build.
-4. Open the app and click **Run Full Pipeline**.
-5. Then open **Dashboard** and click **Refresh Dashboard**.
-
-## Notes
-
-- The original notebook created synthetic review text before sentiment analysis. Because your attached reviews CSV does not contain a `review_text` column, the app recreates that step programmatically.
-- The app uses a fixed random seed for reproducible results.
-- No background images are required.