Enhancement/panel holoviews follow up#141
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Pull request overview
Updates the Panel + HoloViews “Linked Selections / Cross-Filtering” skill documentation to cover categorical bar charts while preserving HoloViews data lineage for link_selections.
Changes:
- Added guidance + example for building categorical bar charts via a custom HoloViews
Operationto preserve lineage for cross-filtering. - Expanded “DON’T” guidance with additional failure cases for categorical dimensions and auto-detected
vdims. - Added
ipywidgets_bokeh,pyarrow,shapely, andsetuptoolsto thepydataoptional dependency group.
Reviewed changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.
| File | Description |
|---|---|
src/holoviz_mcp/config/resources/skills/panel-holoviews.md |
Documents a lineage-preserving approach for categorical bars under link_selections, plus expanded anti-patterns. |
pyproject.toml |
Extends the pydata extra with dependencies relevant to the documented cross-filtering behavior. |
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| dimension = param.String(doc="Categorical dimension to count") | ||
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| def _process(self, element, key=None): | ||
| vals = element.dimension_values(self.p.dimension, expanded=True) | ||
| unique, counts = np.unique(vals, return_counts=True) |
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The category_count example isn’t copy/paste runnable as written: param, np, hv, and histogram are used in this code block but not imported in the block (and won’t be in scope if someone runs just this snippet). Add the missing imports (or explicitly state that it relies on imports from a previous snippet) so the example executes without NameError.
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