Python Financial Data Visualization

I have a sizeable set of raw financial figures—prices, volumes, and a few macro-economic indicators—already sitting in CSV files. The data is clean enough for exploration, but I need compelling visual stories and concise written insights that decision-makers can absorb quickly.

Here’s what I’d like from you: use your Python toolkit—pandas for manipulation, plus matplotlib, seaborn or Plotly (whichever you feel suits each graphic)—to craft a series of clear line charts, heatmaps, and comparative bar plots that highlight trends, anomalies, and correlations. A short, well-structured report (Markdown or Jupyter Notebook is fine) should accompany the visuals, explaining what each chart reveals and flagging any noteworthy patterns you notice.

Deliverables
• Python script or notebook that reproduces every figure end-to-end from the raw CSVs
• High-resolution images or an interactive HTML dashboard for the charts, ready to drop into presentations
• A brief written narrative (½–1 page per topic) summarising key takeaways and suggested next questions

Acceptance is simple: if I can run the notebook, get identical visuals, and the commentary reads clearly to a non-technical finance stakeholder, we’re done. Let me know your preferred libraries or any clarifications you need, and we’ll get started.