Revamp Python Scraping Dashboard

I already have a localhost application that reliably scrapes the data I need. The next step is to layer in proper analytics and present the results through a cleaner, mobile–friendly frontend while leaving the core scraper intact.

Python scope
• Extend the existing code so the scraped dataset feeds directly into statistical analysis, mathematical modelling, and quick data-visualisation routines.
• Prefer familiar libraries such as Pandas, NumPy/SciPy, Matplotlib or Plotly, but I’m open to alternatives if they suit the task better.
• Keep the workflow end-to-end: once the scraper finishes, the calculations should run automatically and expose structured results ready for the UI.

Frontend scope
• Refresh the HTML/CSS (vanilla or lightweight framework) to give the dashboard a modern, responsive layout.
• Add form elements that let me tweak model parameters or filter data on the fly, with the back-end endpoints already in place.
• Apply intuitive styling so charts and tables render clearly on desktop and mobile alike.

Deliverables
1. Updated Python modules that perform the new calculations and return tidy, serialisable output.
2. A responsive HTML interface with integrated forms and real-time chart/table placeholders bound to that output.
3. Brief hand-off notes explaining file structure and how to run the entire stack locally.

Everything runs on localhost today, so no deployment work is needed—just clean, well-documented code that stitches the pieces together smoothly.