Interactive data visualization in Python transforms static charts into dynamic tools for exploration. Using Matplotlib with ipympl in JupyterLab allows zooming, panning, and real-time updates.

Abstract: Our paper presents a centralized platform that streamlines participation and improves data-driven insights in response to the many obstacles university students encounter while accessing ...

Python’s visualization ecosystem in 2026 combines mature libraries like Matplotlib 3.10, Seaborn, and Plotly 6 with AI-driven platforms that produce visuals from data or text. Services such as Canva ...

We survey nearly 6,000 senior business executives at US, UK, German, and Australian firms to develop new evidence on AI adoption and its effects on jobs, productivity, and output. Specifically, we ask ...