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styling-annotations

styling-annotations

Customize Chartify labels, legends, axes, callouts, palettes, style settings, options, and trusted YAML configuration.

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Documentación de la Skill

GitHub

name: styling-annotations description: "Customize Chartify labels, legends, axes, callouts, palettes, style settings, options, and trusted YAML configuration." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Styling and Annotations

Use this sub-skill when a task asks to polish or configure a Chartify chart: titles, subtitles, source labels, legend placement, axis labels/ranges/ticks, categorical factor order, callout lines/boxes/text, color palettes, accent colors, style settings, or Chartify YAML configuration.

Route data reshaping, plot-method selection, chart-type selection, second-axis plotting, radar plotting, and save/show basics to sibling basic-charting. Use the root skill for installation/import checks and cross-cutting browser export caveats.

Read/Run These Files

  • Read references/api-reference.md when you need verified method signatures for labels, legends, axes, callouts, palettes, options, colors, or style settings.
  • Read references/workflows.md for copyable patterns that customize labels, axes, legends, callouts, and palettes on a chart object.
  • Read references/configuration.md before creating or loading Chartify option, style, color, or palette YAML files.
  • Read references/troubleshooting.md when a palette name is invalid, a config directory is ignored, axis labels/ticks do not appear as expected, callouts land in the wrong place, or style settings do not apply.
  • Run scripts/check_chartify_style_config.py to inspect a Chartify install, print option keys, verify palette lookups, or write a small trusted sample config directory.

Quick Route Map

TaskStart here
Set title, subtitle, source label, or legend locationreferences/workflows.md
Set numeric/date ranges, tick values, tick formats, or factor orderreferences/workflows.md
Add vertical/horizontal reference lines, segments, shaded boxes, or text labelsreferences/workflows.md
Select categorical/sequential/diverging/accent palettesreferences/workflows.md
Create custom colors or palettesreferences/api-reference.md
Persist defaults through CHARTIFY_CONFIG_DIRreferences/configuration.md
Diagnose style/config issuesreferences/troubleshooting.md and scripts/check_chartify_style_config.py

Core Workflow

  1. Build or receive a chartify.Chart/chartify.RadarChart object from basic-charting.
  2. Apply labels first (set_title, set_subtitle, set_source_label) so the chart communicates the takeaway before visual polish.
  3. Choose axis controls that match the chart orientation and axis type. Categorical charts use factor order methods; numeric and datetime charts use range/tick methods.
  4. Choose the palette type before plotting when color assignment should affect glyph creation. Use accent palettes when a few categories should stand out and all other categories should use a default color.
  5. Add callouts after plotting so coordinates are meaningful in the rendered chart. For datetime axes, pass pandas timestamps or parseable datetime strings.
  6. Validate by checking ch.figure properties, ch.data, or a safe HTML save; avoid relying on notebook display as the only proof.

Decision Points

  • Use style.set_color_palette('categorical', ...) for unordered groups; use sequential or diverging only when values have meaningful order.
  • Use accent palettes with accent_values when one or more groups should be highlighted and the rest should fall back to style.color_palette_accent_default_color.
  • Use set_xaxis_factors/set_yaxis_factors for categorical axis ordering; use set_xaxis_range/set_yaxis_range for numeric or datetime axes.
  • Use list tick orientations only for grouped categorical axes; each level can have a different orientation.
  • Treat Chartify YAML config as trusted local configuration. Do not load YAML from untrusted users because some config paths use unsafe YAML loading.

Expected Outputs

A successful styling/annotation task usually returns code that mutates and returns a Chartify chart object, plus a validation note such as the updated figure title, axis range/factors, selected palette behavior, or an HTML save result. When a task asks for reusable defaults, provide a config-directory recipe from references/configuration.md and call out the trusted-file requirement.

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