---

name: function-interface description: "Use seaborn's classic plotting functions for relational, distribution, categorical, regression, and matrix statistical graphics." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

Function Interface

Use this sub-skill when the task asks for sns.scatterplot, lineplot, histplot, catplot, regplot, heatmap, clustermap, or another classic seaborn plotting function.

Route Here For

• Relational plots: scatterplot, lineplot, and figure-level relplot.
• Distribution plots: histplot, kdeplot, ecdfplot, rugplot, and figure-level displot.
• Categorical plots: stripplot, swarmplot, boxplot, violinplot, boxenplot, pointplot, barplot, countplot, and figure-level catplot.
• Regression plots: regplot, residplot, and figure-level lmplot.
• Matrix plots: heatmap and clustermap.
• Choosing axes-level versus figure-level APIs and translating user intent into seaborn function parameters.

Use Another Sub-skill For

• Declarative seaborn.objects composition: ../objects-interface/SKILL.md.
• Direct FacetGrid, PairGrid, or JointGrid programming and layout/legend access: ../figure-grids/SKILL.md.
• Themes, contexts, palettes, colormaps, and color utilities: ../themes-palettes/SKILL.md.
• Data-shape checks, load_dataset, or cache/network issues: ../data-utilities/SKILL.md.

Start With

1. Identify the statistical relationship: relation, distribution, category summary, regression, or matrix.
2. Decide axes-level versus figure-level. Use axes-level functions when the caller has axes or needs subplot composition; use figure-level functions for faceting and automatic figure management.
3. Confirm data semantics: long-form data=df, x="col", y="col"; wide-form data=wide_df without x/y; vector arrays for small scripts.
4. Add semantic variables (hue, size, style, row, col) only when the data columns exist and the legend/facet behavior is useful.
5. Check optional dependencies before claiming clustermap, cumulative KDE, lowess, logistic, or robust regression support.

References

• Function signatures and parameter groups: references/api-reference.md.
• No-network recipes and examples: references/workflows.md.
• Failure recovery for plot functions: references/troubleshooting.md.
• Shared package API map: ../../references/api-summary.md.
• Shared data contracts: ../../references/data-semantics.md.

Quick Smoke Check

python sub-skills/function-interface/scripts/function_plot_smoke.py --output-dir /tmp/seaborn-function-smoke

The helper creates synthetic data, uses the Agg backend, renders representative axes-level plots, and conditionally checks SciPy/statsmodels-backed features when available.