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echarts

echarts

github.com/rebyteai-templateData & databases17362 installsUpdated 19w ago
Repository

About echarts

echarts is a skill for creating data visualizations with pyecharts and Apache ECharts. It covers common chart types, presentation options, and producing self-contained HTML reports for people building Python-based visualizations.

Key features

  1. 01Create bar, line, pie, heatmap, and scatter charts
  2. 02Configure themes, labels, legends, and tooltips
  3. 03Export visualizations as self-contained HTML
  4. 04Prepare data as lists for browser rendering
  5. 05Troubleshoot chart layout and rendering

Use cases

  1. 01Build charts for data analysis reports
  2. 02Visualize time series and moving averages
  3. 03Highlight anomalies in scatter plots
  4. 04Generate HTML visualization reports

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/rebyteai-template/rebyte-skills --skill echarts

After installing, type/echartsin Claude Code to confirm it loaded.

Details

From the project README

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"))
Heatmaps
from pyecharts.charts import HeatMap

chart = HeatMap()
chart.add_xaxis(x_labels)
chart.add_yaxis("", y_labels, value=[[x, y, val], ...])
chart.set_global_opts(
    visualmap_opts=opts.VisualMapOpts(min_=0, max_=max_val),
)
Scatter Plots (for anomalies)
from pyecharts.charts import Scatter

chart = Scatter()
chart.add_xaxis(dates)
chart.add_yaxis("Cost", costs, symbol_size=10)
# Add anomaly markers with different color/size

Critical: Browser Compatibility

Always convert to lists for JavaScript:

# CORRECT
chart.add_xaxis(df['column'].tolist())
chart.add_yaxis("Label", df['values'].tolist())

# WRONG - causes rendering issues
chart.add_xaxis(df['column'].values)  # numpy array
chart.add_xaxis(df['column'])  # pandas Series

Theme Options

Available themes in pyecharts:

  • macarons (default) - Colorful, professional
  • shine - Bright colors
  • roma - Muted, elegant
  • vintage - Retro feel
  • dark - Dark background
  • light - Light, minimal

Usage:

from pyecharts.globals import ThemeType
chart = Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS))

HTML Report Structure

def generate_html_report(self, output_path: str, top_n: int = 10) -> str:
    # Create all charts
    charts = [
        self.create_cost_by_service_chart(top_n),
        self.create_cost_by_account_chart(),
        # ... more charts
    ]

    # Combine into page
    page = Page(layout=Page.SimplePageLayout)
    for chart in charts:
        page.add(chart)

    # Render to file
    page.render(output_path)
    return output_path

Formatting Numbers

# Currency formatting in tooltips
tooltip_opts=opts.TooltipOpts(
    trigger="axis",
    formatter="{b}: ${c:,.2f}"
)

# Axis label formatting
yaxis_opts=opts.AxisOpts(
    axislabel_opts=opts.LabelOpts(formatter="${value:,.0f}")
)

Common Issues & Solutions

Empty Charts
  1. Check browser console for JS errors
  2. Verify .tolist() on all data
  3. Hard refresh (Ctrl+Shift+R)
  4. Check data exists in HTML source
Chart Too Small
init_opts=opts.InitOpts(width="100%", height="400px")
Labels Overlapping
xaxis_opts=opts.AxisOpts(
    axislabel_opts=opts.LabelOpts(rotate=45, interval=0)
)
Legend Too Long
legend_opts=opts.LegendOpts(
    type_="scroll",
    orient="horizontal",
    pos_bottom="0%"
)

Testing Visualizations

# Test chart creation
uv run pytest tests/test_visualizer.py -v

# Regenerate example report
uv run pytest tests/test_examples.py -v -s

# View in browser
open examples/example_report.html

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