I need a medium-scope solution that lets me explore and compare economic data trends side-by-side without manual effort. What I’m after • A Python script (pandas, NumPy, requests, or similar) that automatically pulls multiple public-source economic series, cleans them, and stores the results locally. • The script should push the refreshed data into an Excel workbook (openpyxl / xlwings) that already contains a polished dashboard with slicers, dynamic charts, and clear labels. • Charts must focus on comparative analysis—think GDP vs. inflation, yield curves against equity indices, or any other pairs I can configure in a simple settings file. Workflow I imagine 1. I run a single command (or a scheduled task). 2. Data is fetched, transformed, and written to Excel sheets dedicated to raw, clean, and pivoted data. 3. The dashboard tab updates automatically, showing the latest visuals ready for quick interpretation. Deliverables • Python code, clearly commented and modular. • Excel file containing the interactive dashboard, formulas, and linked live charts. • A short README detailing how to add or swap data series and how to rerun the pipeline. Acceptance criteria – Data refresh completes in under 5 minutes on a typical laptop. – No hard-coded API keys or file paths; use a config file or environment variables. – Dashboard loads with no missing references or broken visuals. If you have experience with Plotly or Power Query integrations inside Excel, feel free to suggest them—I’m open to enhancements that stay within this functional scope.