I’m sharpening my data-science skills and want focused, hands-on guidance with Pandas. The sessions should walk me through three core areas—data manipulation, data cleaning, and data visualization—using realistic datasets in Jupyter Notebook. Along the way, we’ll weave in complementary concepts such as running a basic linear-regression model and building a small data cube so I understand how Pandas fits into a wider analytics workflow. Here’s how I picture our work together: • Interactive calls or screen-sharing where you demonstrate techniques, then watch me replicate them. • Short, well-commented notebooks I can keep as reference, covering the specific topics above. • Practical homework exercises so I can test my understanding between meetings. When you reply, please include a sample of past work—a GitHub link, notebook, or brief case study—that highlights your teaching style or a project where you used Pandas extensively. That will help me gauge fit quickly. I’m open to scheduling details and pacing that suits us both; consistency and clear explanations are the priority.