Echarts

This wraps Apache ECharts in Python via pyecharts to generate standalone HTML reports with interactive charts. It covers the essentials: bar, line, pie, heatmap, and scatter plots with real configuration examples for things like tooltips, themes, and label rotation. The most useful bit is the blunt reminder to always convert pandas and numpy data to lists before passing to the charts, since that's apparently where things go wrong in the browser. Good for generating self-contained visualization reports from data analysis without needing a web server or React setup. The formatting helpers for currency and the troubleshooting section suggest this was written after debugging actual rendering issues, which makes it more practical than most chart library docs.

skills.sh installs: 187
GitHub stars: 5
last updated: Jun 3, 2026

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Install

$ npx -y skills add eng0ai/eng0-template-skills --skill echarts --agent claude-code

Installs into .claude/skills of the current project.

Files

ECharts Skill

Technology Stack

pyecharts: Python wrapper for Apache ECharts
Apache ECharts: JavaScript charting library
Output: Self-contained HTML with embedded JS

Chart Types Reference

Bar Charts

from pyecharts.charts import Bar
from pyecharts import options as opts

chart = Bar()
chart.add_xaxis(labels)
chart.add_yaxis("Series Name", values)
chart.set_global_opts(
    title_opts=opts.TitleOpts(title="Chart Title"),
    tooltip_opts=opts.TooltipOpts(trigger="axis"),
    xaxis_opts=opts.AxisOpts(axislabel_opts=opts.LabelOpts(rotate=45)),
)

Line Charts

from pyecharts.charts import Line

chart = Line()
chart.add_xaxis(dates)
chart.add_yaxis("Actual", values, is_smooth=True)
chart.add_yaxis("7-Day MA", moving_avg_7, is_smooth=True, linestyle_opts=opts.LineStyleOpts(type_="dashed"))

Pie Charts

from pyecharts.charts import Pie

chart = Pie()
chart.add("", list(zip(labels, values)))
chart.set_global_opts(legend_opts=opts.LegendOpts(orient="vertical", pos_left="left"))