Notre avis
Ce skill permet de créer des visualisations de données interactives avec pyecharts, générer des rapports HTML autonomes, et appliquer les bonnes pratiques de rendu.
Points forts
- Couverture complète des types de graphiques (barres, lignes, camemberts, heatmaps, scatter)
- Instructions précises pour éviter les problèmes de compatibilité navigateur (conversion en listes)
- Gestion des thèmes et de la mise en page pour des rapports professionnels
- Résolution des problèmes courants (graphiques vides, tailles, étiquettes)
Limites
- Limitée à la bibliothèque pyecharts, pas d'autres outils de visualisation
- Ne couvre pas l'analyse statistique avancée ni l'interactivité complexe
- Dépend de la connaissance préalable de Python et pandas
Utilisez ce skill pour générer rapidement des rapports de visualisation de données en HTML avec des graphiques interactifs variés.
Évitez ce skill si vous avez besoin de visualisations très personnalisées ou d'intégrations JavaScript complexes non supportées par pyecharts.
Analyse de sécurité
SûrThe skill is a documentation-only reference for pyecharts charting, containing no executable commands that could cause harm. It includes only safe code snippets and usage examples, with no network access, file deletion, or obfuscation.
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Exemples
Generate a bar chart using pyecharts showing cost by service for the top 10 services. Use the 'macarons' theme, rotate x-axis labels 45 degrees, and format y-axis as currency.Create a Python function that generates an HTML report with multiple charts (bar, line, pie) from a DataFrame, using Page layout and rendering to a file.My pyecharts chart renders blank in the browser. The data comes from a pandas DataFrame. What common mistakes could cause this? Provide corrected code.name: visualization description: Knowledge about pyecharts chart creation, HTML report generation, and visualization best practices
Visualization 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, professionalshine- Bright colorsroma- Muted, elegantvintage- Retro feeldark- Dark backgroundlight- 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
- Check browser console for JS errors
- Verify
.tolist()on all data - Hard refresh (Ctrl+Shift+R)
- 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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