Structured Data Visualization in Python

I have a collection of well-formatted CSV files and a live SQL database that I need to turn into clear, insightful visuals. The core of this engagement is data visualization—using Python to translate rows and columns into plots, dashboards, or interactive charts that quickly communicate trends and outliers to non-technical stakeholders.

You will have direct access to the structured data; most of it is already clean, so the emphasis is on choosing the right libraries (Pandas, Matplotlib, Seaborn, or Plotly—whatever suits the story best), crafting reusable code, and presenting the results in a concise, easy-to-update format. If you are comfortable adding light data-cleaning steps or basic statistical summaries along the way, that flexibility is welcome, but not required.

Deliverables
• Well-commented Python script or Jupyter notebook that pulls the data and generates the visuals
• Exported chart files (PNG, SVG, or interactive HTML) ready for reports
• A brief README explaining how to rerun or adapt the code for new datasets

I’m ready to share sample data and discuss the specific questions I’m hoping the visuals will answer.