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Pyecharts Viz Examples

skill-pyecharts-skills-pyecharts-viz-examples · by pyecharts

生成 pyecharts 可视化示例代码。当用户需要创建 pyecharts 图表、查看图表示例、了解图表用法或生成数据可视化代码时使用此技能。支持 49 种图表类型:基础图表 (Bar、Line、Pie、Scatter、Map 等 31 种)、复合图表 (Grid、Page、Tab、Timeline)、3D 图表 (Bar3D、Line3D、Scatter3D 等 8 种) 和 Echarts 6 新图表 (Violin、Stage 等 6 种)。

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Install

$ agentstack add skill-pyecharts-skills-pyecharts-viz-examples

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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Reliability & compatibility

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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

pyecharts 可视化示例生成

快速开始

生成 pyecharts 图表示例的基本步骤:

  1. 确定图表类型 - 根据用户需求选择合适的图表类型
  2. 查找示例 - 从 references/chart_types.md 查找对应示例代码
  3. 修改数据 - 根据用户数据替换示例中的测试数据
  4. 渲染输出 - 调用 .render() 生成 HTML 文件或 .render_notebook() 在 Notebook 中使用

图表类型概览

详细图表类型和示例代码见 references/chart_types.md

| 类别 | 图表数量 | 主要类型 | |------|---------|---------| | 基础图表 | 31 种 | Bar、Line、Pie、Scatter、Map、Geo、Graph、HeatMap 等 | | 复合图表 | 4 种 | Grid、Page、Tab、Timeline | | 3D 图表 | 8 种 | Bar3D、Line3D、Scatter3D、Surface3D、Map3D、MapGlobe 等 | | Echarts 6 新图表 | 6 种 | Violin、Stage、SegmentedDoughnut、Contour、BarRange、LineRange |

总计支持 49 种图表类型

核心能力

  1. 生成示例代码 - 提供任何图表类型的完整可运行示例
  2. 使用 Faker 测试数据 - 快速生成测试数据进行验证
  3. 图表组合 - 使用 Grid、Page、Tab、Timeline 组合多个图表
  4. 地图集成 - 支持中国地图、世界地图,以及百度/高德/Google/Leaflet 地图
  5. 输出配置 - HTML 文件、图片 (需 snapshot_selenium)、Notebook

标准图表结构

from pyecharts import options as opts
from pyecharts.charts import [图表类型]

chart = (
    [ChartType]()
    .add_xaxis([...])  # XY 轴图表需要
    .add_yaxis("系列名", [...])
    .set_global_opts(
        title_opts=opts.TitleOpts(title="图表标题"),
        xaxis_opts=opts.AxisOpts(),
        yaxis_opts=opts.AxisOpts(),
    )
)
chart.render("output.html")

常用配置项速查

全局配置 (setglobalopts)

  • title_opts - 标题配置
  • legend_opts - 图例配置
  • tooltip_opts - 提示框配置
  • xaxis_opts / yaxis_opts - 坐标轴配置
  • visualmap_opts - 视觉映射配置
  • datazoom_opts - 区域缩放配置

系列配置

  • label_opts - 标签样式
  • itemstyle_opts - 图形样式
  • linestyle_opts - 线样式
  • markpoint_opts / markline_opts - 标记点/线

输出配置

渲染为 HTML 文件

chart.render("chart.html")

渲染为图片(需要额外依赖)

from snapshot_selenium import snapshot as driver
from pyecharts.render import make_snapshot

make_snapshot(driver, chart.render(), "chart.png")

Notebook 环境

chart.render_notebook()

参考资料

  • 详细图表类型和示例: references/chart_types.md
  • pyecharts 官方文档: https://pyecharts.org
  • 示例画廊: https://gallery.pyecharts.org

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.