HoloViz and Panel Workshop

6 hours of instruction

Builds techniques for web-based data exploration and interactive-app development in Python using open-source Holoviz libraries (that is, HoloViews, HvPlot, Datashader, and Panel). These tools enable constructing rich high-performance, scalable, flexible, and deployable visualizations easily.

PREREQUISITES

Participants should have a decent working knowledge of the Python language and standard Python tools for data exploration & analysis (notably NumPy, Pandas, Jupyter). No prior experience using other Python data visualization frameworks (e.g., Seaborn, Altair, etc.) is expected but known some visualization concepts underlying Matplotlib will be useful. Prior exposure to Dask and Xarray will also be useful but neither is mandatory.

LEARNING OBJECTIVES

1. Identify and explain core capabilities HoloViz components (e.g., Panel, HoloViews, Datashader, etc.).
2. Deploy simple Panel apps combining plots and elementary interactive widgets.
3. Customize content in Panel apps by modifying layout and interlinking reactive components with callbacks.
4. Build plots with both the hvPlot and generic HoloViews constructors.
5. Combine and customize HoloViews elements with standard idioms
6. Construct interactive Panel apps deploying sophisticated data pipelines and HoloViews elements.
7. Apply Datashader to avoid memory overflow when rendering dynamic plots with very large amounts of data.
8. Build an advanced dashboard combining, e.g., hvPlot, HoloViews, Panel, and Datashader for interactive exploratory data analysis (EDA).