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Design et création · SKILL.md

exploration-visualization

exploration-visualization

Routes Orange3 exploratory plots, distance matrices, projections, clustering, statistics, and unsupervised widgets.

Independent GitHub snapshot · Automated classification · Original documentation governs

Documentation de la Skill

GitHub

name: exploration-visualization description: "Routes Orange3 exploratory plots, distance matrices, projections, clustering, statistics, and unsupervised widgets." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

exploration-visualization

Use this sub-skill when an existing Orange table or distance matrix must be explored with Orange3 plots, projections, distances, clustering, statistics, or unsupervised widgets.

Route here for

  • Choosing and wiring Orange.widgets.visualize exploratory widgets such as Scatter Plot, Box Plot, Distributions, Violin Plot, Heat Map, Sieve/Mosaic, Silhouette Plot, FreeViz, Linear Projection, and Radviz.
  • Choosing and wiring Orange.widgets.unsupervised widgets such as Distances, Distance Matrix/Map, k-Means, DBSCAN, Louvain, Hierarchical Clustering, PCA, MDS, t-SNE, Manifold Learning, SOM, and Correspondence Analysis.
  • Programmatic use of Orange.distance, Orange.clustering, Orange.projection, and Orange.statistics for exploratory analysis.
  • Explaining Orange.misc.DistMatrix flow between distance, clustering, map, MDS, t-SNE, and silhouette widgets.
  • Diagnosing plot/projection/clustering failures caused by invalid coordinates, stale context, sparse inputs, distance matrix shape/symmetry, or clustering bounds.

Route elsewhere

  • Loading, saving, SQL, Table/Domain construction, file formats, and generic data preparation: use data-preparation.
  • Supervised learner/model construction, prediction, scoring, or evaluation: use supervised-modeling.
  • Building custom Orange widgets, Canvas workflow internals, widget catalog tooling, or GUI framework tests: use widget-development.
  • Trained-model visualization widgets such as tree viewers, nomograms, rule viewers, scoring-sheet viewers, or Pythagorean tree/forest unless the task is only to inspect an already-created model; create or evaluate the model elsewhere first.

Read first

  • Exploration reference for verified distance, clustering, projection, statistics, and DistMatrix API patterns.
  • Plot catalog for widget selection, inputs/outputs, and the APIs behind each plot or unsupervised widget family.
  • Troubleshooting for incompatible domains, missing coordinates, empty selections, invalid projections, clustering bounds, sparse/large-data caveats, and widget context staleness.

Typical workflow

  1. Start from an already-prepared Orange.data.Table or Orange.misc.DistMatrix; do not re-own file/SQL loading here.
  2. Decide whether the user needs a plot, a distance matrix, a clustering annotation, a low-dimensional projection, or a cluster-quality diagnostic.
  3. For code, use the verified APIs in references/exploration-reference.md; for GUI work, use the widget catalog and preserve each widget's input/output contract.
  4. Before trusting selections or downstream outputs, check whether the widget has valid coordinates/projections and whether the current context was restored from a compatible domain.

Bundled scripts

No helper script is bundled for this sub-skill. The selected repository evidence did not provide a small visualization helper that improves on the distilled references. For GUI smoke checks, instantiate native widgets or WidgetPreview from the active Orange environment rather than adding a copied build/release helper.

Evidence distilled

This sub-skill distills Orange3 3.41.0.dev exploratory behavior for Orange.distance, Orange.clustering, Orange.projection, Orange.statistics, Orange.widgets.visualize, and Orange.widgets.unsupervised. Runtime guidance is self-contained and relies on installed Orange APIs plus the bundled references here.

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