RESEARCH USE
Where HoloViews fits
HoloViews lets a Python or Jupyter workflow describe the dimensions and semantics of data before selecting a rendering backend such as Bokeh, Matplotlib, or Plotly. Views can be composed, linked, and parameterized for exploration. Record the transformations, backend, extension configuration, and package versions used for a final figure or application.
Research tasks
- Generate composable views from labelled data
- Build linked interactive displays for exploration
- Organize reproducible visualization work in Jupyter
What to evaluate before use
- Appearance and interaction depend on the selected plotting backend, and equivalent objects may not render identically across backends.
- A declarative interface reduces plotting code but does not determine an appropriate statistical graphic, scale, or representation of uncertainty.
Verification note
This entry summarizes the tool's role without assessing scientific accuracy or endorsing its outputs. Features and terms can change; consult the official source before adopting it for consequential work.
Pythondeclarative visualization
Last verified: 2026-09-06
Source: official documentation ↗