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visualization
Knowledge about pyecharts chart creation, HTML report generation, and visualization best practices
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Knowledge about pyecharts chart creation, HTML report generation, and visualization best practices
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
This skill provides AI coding agents with the guidelines and reference material needed to contribute effectively to the Kader repository. Use this skill when writing code, fixing bugs, adding features, or making any modifications to the Kader project.
This skill provides AI coding agents with the guidelines and reference material needed to contribute effectively to the Kader repository. Use this skill when writing code, fixing bugs, adding features, or making any modifications to the Kader project.
GitHub operations via `gh` CLI: issues, PRs, CI runs, code review, API queries. Use when: (1) checking PR status or CI, (2) creating/commenting on issues, (3) listing/filtering PRs or issues, (4) viewing run logs. NOT for: complex web UI interactions requiring manual browser flows (use browser tooling when available), bulk operations across many repos (script with gh api), or when gh auth is not configured.
Skill for mathematical calculations
Skill for ALL greeting requests
Skill for ALL joke requests
| name | visualization |
| description | Knowledge about pyecharts chart creation, HTML report generation, and visualization best practices |
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)),
)
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"))
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"))
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),
)
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
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
Available themes in pyecharts:
macarons (default) - Colorful, professionalshine - Bright colorsroma - Muted, elegantvintage - Retro feeldark - Dark backgroundlight - Light, minimalUsage:
from pyecharts.globals import ThemeType
chart = Bar(init_opts=opts.InitOpts(theme=ThemeType.MACARONS))
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
# 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}")
)
.tolist() on all datainit_opts=opts.InitOpts(width="100%", height="400px")
xaxis_opts=opts.AxisOpts(
axislabel_opts=opts.LabelOpts(rotate=45, interval=0)
)
legend_opts=opts.LegendOpts(
type_="scroll",
orient="horizontal",
pos_bottom="0%"
)
# 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