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设计与创意 · SKILL.md

visualization-and-charts

visualization-and-charts

【设计与创意】Use geemap charting, colormap, legend, cartoee static map, Plotly, pydeck, kepler.gl, and MapLibre visualization workflows.

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技能说明

GitHub

name: visualization-and-charts description: "Use geemap charting, colormap, legend, cartoee static map, Plotly, pydeck, kepler.gl, and MapLibre visualization workflows." disable-model-invocation: true metadata: disco-role: operating license: MIT

geemap visualization and charts

Use this sub-skill when a task needs geemap visual outputs: bqplot charts from local or Earth Engine data, matplotlib colorbars and palettes, built-in dataset legends, publication-style static cartopy/cartoee maps, or optional Plotly, pydeck, kepler.gl, and MapLibre visualization backends.

For package setup and Earth Engine authentication, use the root setup reference: installation and auth. For cross-cutting package failures, use root troubleshooting first, then this sub-skill's visualization troubleshooting.

Route boundaries

Use this sub-skill for:

  • geemap.chart: DataTable, Chart, array_values, feature charts, image/region charts, histograms, and time series charts.
  • geemap.colormaps, top-level geemap.create_colorbar, and geemap.legends: palettes, colorbars, built-in legends, and legend table conversion.
  • geemap.cartoee: cartopy-based static maps with Earth Engine layers, colorbars, gridlines, north arrows, scale bars, legends, and savefig.
  • geemap.plot and geemap.plotlymap: Plotly Express charts, Plotly map tiles, heatmaps, GeoDataFrames, and static Plotly export.
  • geemap.deck, geemap.kepler, and geemap.maplibregl: optional visualization backends and style/layer validation.

Route elsewhere when the primary task is:

  • Interactive ipyleaflet or folium map construction, base map controls, drawing widgets, inspectors, and layer managers: interactive Earth Engine maps.
  • Data conversion, local file ingestion, Earth Engine export/download tasks, COG/STAC tile URL generation as a data I/O problem, or OSM acquisition: conversion and I/O.
  • Timelapse animations, GIF/MP4 production, and app publication workflows: timelapse and apps.

Operating checklist

  1. Choose the output target before selecting an API:
    • notebook chart: geemap.chart.Chart or geemap.chart.* wrappers;
    • local tabular chart: geemap.plot.* for Plotly Express;
    • publication static map: geemap.cartoee;
    • web/notebook map backend: plotlymap, deck, kepler, or maplibregl.
  2. Check optional backend availability and missing-extra recovery with backend options.
  3. Validate visual parameters before creating the object: color strings, palette length, min/max scalar values, opacity range, colorbar orientation, legend label/color lengths, and chart reducer/scale/region requirements.
  4. For Earth Engine chart or cartoee workflows, make authentication and network needs explicit. Do not treat a local import as proof that remote EE reductions or thumbnail requests will succeed.
  5. For a quick no-credentials smoke check, run the bundled script in scripts/visualization_smoke.py.

Reference bundle

  • Workflows: practical recipes for charts, colorbars, static maps, Plotly maps, pydeck, kepler.gl, and MapLibre.
  • API reference: verified signatures and argument contracts.
  • Backend options: dependency, credential, renderer, and fallback matrix.
  • Troubleshooting: chart, colorbar, cartoee, optional backend, and token/style failures.
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