chartjs-generator（Chartjs 生成器）

Chart.js Generator

Overview

This skill generates professional, interactive charts using Chart.js, supporting all major chart types. Chart.js is a powerful, flexible JavaScript library for creating responsive data visualizations. The skill creates a complete MicroSim package suitable for embedding in educational content or documentation sites built with MkDocs. The default placement in a intelligent book uses an iframe with minimal padding and margins. Do not add any analysis or supporting documentation above or below the chart region.

Supported Chart Types

Chart.js supports the following chart types:

1. Line - Time series, trends, continuous data
2. Bar - Comparisons, categorical data, horizontal or vertical
3. Pie - Proportions, percentages, part-to-whole relationships
4. Doughnut - Similar to pie with central space for labels
5. Radar - Multi-dimensional data, spider/web charts
6. Polar Area - Similar to pie but with varying radius
7. Bubble - Three-dimensional data (x, y, size)
8. Scatter - Correlations, distributions, relationships

When to Use This Skill

Use this skill when users request:

• Data visualizations: Any chart or graph for presenting data
• Comparisons: Bar charts, grouped bars, stacked bars
• Trends: Line charts, area charts, multi-line charts
• Proportions: Pie charts, doughnut charts
• Distributions: Scatter plots, bubble charts
• Multi-dimensional data: Radar charts, bubble charts
• Interactive charts: Hover tooltips, clickable elements, animations

Common trigger phrases:

• "Create a [chart type] showing..."
• "Visualize [data] as a [chart type]..."
• "Build an interactive chart for..."
• "Generate a graph showing..."

Workflow

Step 1: Determine Chart Type

If the user doesn't specify a chart type, ask them to select from the supported types:

Use the AskUserQuestion tool with these options:

1. Line Chart - Best for trends over time, continuous data
2. Bar Chart - Best for comparing categories, discrete data
3. Pie/Doughnut Chart - Best for showing proportions and percentages
4. Bubble/Scatter Chart - Best for multi-dimensional or correlation data
5. Radar Chart - Best for comparing multiple variables across categories
6. Polar Area Chart - Best for showing proportions with emphasis on differences

Step 2: Gather Data and Requirements

Before generating the chart, gather information about:

1. Data structure: What data needs to be visualized?

- Data points/values - Labels/categories - Multiple datasets (if applicable) - Time periods or categories - Units of measurement

1. Chart configuration:

- Chart title - Axis labels (for bar, line, scatter, bubble charts) - Legend requirements - Color scheme preferences - Special features (stacked, grouped, filled areas, etc.)

1. Context: What is the purpose of the visualization?

- Educational content - Data analysis - Report or presentation - Dashboard component

1. Integration: Where will the chart be used?

- Standalone page - Embedded in documentation - MkDocs site integration

Step 3: Create Directory Structure

Create a new directory for the MicroSim following this pattern:

docs/sims/<chart-name>/
├── main.html         # Main visualization file
├── style.css         # Styling
└── index.md          # Documentation (if part of MkDocs)

Naming convention: Use kebab-case (lowercase with hyphens) for directory names that are descriptive and URL-friendly (e.g., sales-trend-chart, market-share-pie, student-performance-radar).

Step 4: Create main.html with Chart.js

Generate the main HTML file with the following structure:

1. HTML boilerplate with proper meta tags
2. Chart.js CDN import: https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js
3. Canvas element for the chart
4. Optional analysis/legend section do not any analysis or documentation unless requested
5. JavaScript implementation:

- Data array/object - Color scheme configuration - Chart.js configuration for the selected chart type - Custom plugins (if needed) - Interactive features (tooltips, legends, animations) - Tooltips should always be used

Key Chart.js configuration by type:

Line Chart

{
    type: 'line',
    data: {
        labels: ['Jan', 'Feb', 'Mar', ...],
        datasets: [{
            label: 'Dataset 1',
            data: [12, 19, 3, 5, 2, 3],
            borderColor: 'rgb(75, 192, 192)',
            backgroundColor: 'rgba(75, 192, 192, 0.2)',
            tension: 0.1  // Curve smoothness
        }]
    },
    options: {
        responsive: true,
        scales: {
            y: { beginAtZero: true }
        }
    }
}

Bar Chart

{
    type: 'bar',
    data: {
        labels: ['Category A', 'Category B', ...],
        datasets: [{
            label: 'Dataset 1',
            data: [65, 59, 80, 81, 56, 55],
            backgroundColor: 'rgba(54, 162, 235, 0.8)',
            borderColor: 'rgb(54, 162, 235)',
            borderWidth: 1
        }]
    },
    options: {
        responsive: true,
        scales: {
            y: { beginAtZero: true }
        }
    }
}

Pie/Doughnut Chart

{
    type: 'pie',  // or 'doughnut'
    data: {
        labels: ['Red', 'Blue', 'Yellow', ...],
        datasets: [{
            data: [300, 50, 100],
            backgroundColor: [
                'rgba(255, 99, 132, 0.8)',
                'rgba(54, 162, 235, 0.8)',
                'rgba(255, 206, 86, 0.8)'
            ]
        }]
    },
    options: {
        responsive: true,
        plugins: {
            legend: { position: 'top' }
        }
    }
}

Radar Chart

{
    type: 'radar',
    data: {
        labels: ['Strength', 'Speed', 'Intelligence', ...],
        datasets: [{
            label: 'Player 1',
            data: [65, 59, 90, 81, 56],
            backgroundColor: 'rgba(255, 99, 132, 0.2)',
            borderColor: 'rgb(255, 99, 132)',
            pointBackgroundColor: 'rgb(255, 99, 132)'
        }]
    },
    options: {
        responsive: true,
        scales: {
            r: {
                beginAtZero: true,
                max: 100
            }
        }
    }
}

Bubble Chart

{
    type: 'bubble',
    data: {
        datasets: [{
            label: 'Dataset 1',
            data: [
                { x: 20, y: 30, r: 15 },  // r = bubble radius
                { x: 40, y: 10, r: 10 }
            ],
            backgroundColor: 'rgba(255, 99, 132, 0.8)'
        }]
    },
    options: {
        responsive: true,
        scales: {
            x: { min: 0, max: 100 },
            y: { min: 0, max: 100 }
        }
    }
}

Scatter Chart

{
    type: 'scatter',
    data: {
        datasets: [{
            label: 'Dataset 1',
            data: [
                { x: -10, y: 0 },
                { x: 0, y: 10 },
                { x: 10, y: 5 }
            ],
            backgroundColor: 'rgba(255, 99, 132, 0.8)'
        }]
    },
    options: {
        responsive: true,
        scales: {
            x: { type: 'linear', position: 'bottom' }
        }
    }
}

Important considerations:

• Responsive design: Set responsive: true and appropriate aspect ratio
• Color accessibility: Use distinguishable colors with good contrast
• Tooltips: Customize tooltips to show relevant information
• Legends: Position legends appropriately (top, bottom, left, right)
• Animations: Enable/disable based on use case
• Data labels: Use Chart.js plugins for data labels if needed

Step 5: Create style.css

Generate CSS with professional styling:

1. Reset and base styles: Clean defaults for cross-browser consistency
2. Chart container: Appropriate sizing, padding, box-shadow
3. Legend/analysis container: Styling for supplementary information
4. Interactive elements: Hover effects, transitions
5. Responsive design: Media queries for mobile/tablet
6. Print styles: Do not add additional CSS for printing

Key design principles:

• Use clean, modern aesthetics
• Assume placement of the chart in a book with narrow margins using a iframe
• Provide clear visual hierarchy
• Add subtle shadows and borders
• Include smooth transitions
• Ensure accessibility with sufficient contrast
• Make text readable at all sizes

Step 6: Create index.md Documentation

If the chart is part of a MkDocs site, create comprehensive documentation:

1. YML Metadata: Add title, and description
2. Title and overview: Brief description of the visualization
3. Embedded iframe: Display the chart inline
4. Link to fullscreen: Markdown link to main.html with button "View MicroSim Fullscreen"
5. Interpretation guide: Explain how to read the chart
6. Features section: List interactive elements
7. Customization guide: Detailed instructions for modifying:

- Data structure - Colors and styling - Chart options - Responsive behavior - Animations

1. Technical details: Dependencies, browser compatibility, file structure
2. Use cases: Other applications for this chart type
3. References: Links to Chart.js docs and related resources

Documentation structure template:

---
title: [Chart Title]
description: [brief description of chart]
---

# [Chart Title]

[Brief description]

## Interactive Chart

<iframe src="main.html" width="100%" height="500" scrolling="no"></iframe>

[View Fullscreen](main.html){ .md-button .md-button--primary }

## Overview

[Detailed explanation of what the chart shows]

## Features

### Interactive Elements
- Hover tooltips showing detailed data
- Clickable legend items to show/hide datasets
- Smooth animations on load and update

### Visual Design
- Color-coded categories
- Clear axis labels and grid lines
- Responsive layout

## Customization Guide

### Changing the Data

To modify the chart data, edit the `data` object in `main.html`:

const data = { labels: ['Your', 'Labels', 'Here'], datasets: [{ label: 'Your Dataset', data: [10, 20, 30, 40] }] };

### Adjusting Colors

Customize the color scheme by modifying the `backgroundColor` and `borderColor` properties:

backgroundColor: [ 'rgba(255, 99, 132, 0.8)', 'rgba(54, 162, 235, 0.8)', // Add more colors... ]

### Chart Options

Modify chart behavior in the `options` object:

options: { responsive: true, maintainAspectRatio: true, aspectRatio: 2, // Width:height ratio plugins: { title: { display: true, text: 'Your Title' }, legend: { position: 'top' } } }

## Technical Details

- **Library**: Chart.js 4.4.0
- **Browser Compatibility**: All modern browsers (Chrome, Firefox, Safari, Edge)
- **Dependencies**: Chart.js (loaded from CDN)
- **Responsive**: Yes, adapts to container width

## Use Cases

This chart type is useful for:

- [List relevant use cases]

## References

• Chart.js Documentation
• Chart Type Guide

### Step 7: Integrate into Navigation (MkDocs)

Always add the chart to the navigation in `mkdocs.yml`:

• MicroSims:

- Introduction: sims/index.md - [Chart Name]: sims/[chart-name]/index.md - [Other sims...]: ...

Place the entry in a alphabetical order.

### Step 8: Test and Validate

Before considering the chart complete:

1. **Visual testing**:
  - Open `main.html` in a browser directly
  - Test with `mkdocs serve` if applicable
  - Check all breakpoints (desktop, tablet, mobile)
  - Verify data displays correctly
  - Confirm labels and legends are readable
2. **Interactive testing**:
  - Hover over chart elements to verify tooltips
  - Click legend items to show/hide datasets
  - Test animations (reload page)
  - Test on different browsers
3. **Documentation review**:
  - Verify all code examples are accurate
  - Test customization instructions
  - Check all internal and external links
4. **Data validation**:
  - Confirm all data points are plotted correctly
  - Verify calculations if applicable
  - Check that chart accurately represents the data

## Best Practices

### Data Preparation

1. **Consistent formatting**: Use consistent data types and formats
2. **Meaningful labels**: Use clear, descriptive labels
3. **Appropriate scale**: Choose scales that show data effectively
4. **Complete data**: Ensure all required fields are present

### Visual Design

1. **Color coding**: Use intuitive, accessible color schemes
2. **Contrast**: Ensure sufficient contrast for readability
3. **Labels**: Make all text readable at different sizes
4. **Spacing**: Prevent overlap with appropriate padding
5. **Consistency**: Use consistent styling across charts

### Documentation

1. **Code examples**: Provide exact, testable code snippets
2. **Before/after**: Show the effect of customizations
3. **Parameter ranges**: Suggest appropriate value ranges
4. **Common issues**: Address typical problems and solutions

### MkDocs Integration

1. **Iframe sizing**: Use appropriate height for chart type (typically 500-900px)
2. **Path references**: Use relative paths (`../sims/...`)
3. **Navigation placement**: Group with related MicroSims
4. **Responsive embedding**: Ensure iframe is responsive

## Chart Type Selection Guide

Help users choose the right chart type:

| Chart Type | Best For | Not Suitable For |
| --- | --- | --- |
| **Line** | Trends over time, continuous data | Categorical comparisons |
| **Bar** | Comparing categories, discrete data | Trends, continuous data |
| **Pie/Doughnut** | Part-to-whole, proportions (≤6 slices) | Precise comparisons, many categories |
| **Radar** | Comparing multiple variables, profiles | Single variable, continuous data |
| **Polar Area** | Proportions with emphasis on differences | Precise comparisons |
| **Bubble** | Three dimensions (x, y, size) | Simple 1D or 2D data |
| **Scatter** | Correlations, distributions | Categorical data |

## Common Variations

### Stacked Bar Chart

options: { scales: { x: { stacked: true }, y: { stacked: true } } }

### Horizontal Bar Chart

{ type: 'bar', options: { indexAxis: 'y' // Makes bars horizontal } }

### Multi-Line Chart

Add multiple datasets to a line chart:

data: { datasets: [ { label: 'Series 1', data: [...], borderColor: 'red' }, { label: 'Series 2', data: [...], borderColor: 'blue' } ] }

### Filled Area Chart

{ type: 'line', data: { datasets: [{ fill: true, // Fill area under line backgroundColor: 'rgba(75, 192, 192, 0.2)' }] } }

## Troubleshooting

### Chart Not Displaying

**Solution**: Check that Chart.js CDN is loading correctly and canvas element has an ID.

### Data Not Updating

**Solution**: Ensure `chart.update()` is called after modifying data:

chart.data.datasets[0].data = newData; chart.update();

### Labels Overlapping

**Solution**: Rotate labels or reduce font size:

scales: { x: { ticks: { maxRotation: 45, minRotation: 45 } } }

### Colors Not Showing

**Solution**: Verify color format (rgba, rgb, hex) and ensure arrays match data length.

### Responsive Issues

**Solution**: Set container dimensions and use `maintainAspectRatio`:

options: { responsive: true, maintainAspectRatio: true, aspectRatio: 2 }

## Advanced Features

### Data Labels Plugin

To show values on chart elements, use the Chart.js Data Labels plugin:

<script src="https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2"></script>

### Animations

Customize animation timing and easing:

options: { animation: { duration: 2000, easing: 'easeInOutQuart' } }

### Custom Tooltips

Create fully custom tooltip content:

plugins: { tooltip: { callbacks: { label: function(context) { return 'Custom: ' + context.parsed.y; } } } }

### Click Events

Handle click events on chart elements:

options: { onClick: (event, elements) => { if (elements.length > 0) { const dataIndex = elements[0].index; console.log('Clicked:', chart.data.labels[dataIndex]); } } }

## References

This skill uses the following assets and references:

### Assets

- **Chart.js CDN**: `https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js`
- **Optional Data Labels Plugin**: `https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2`
- No local assets required (Chart.js loaded from CDN)

### References

- [Chart.js Documentation](https://www.chartjs.org/docs/latest/)
- [Chart.js Samples](https://www.chartjs.org/docs/latest/samples/)
- [Chart.js GitHub](https://github.com/chartjs/Chart.js)
- [Chart Types Guide](https://www.chartjs.org/docs/latest/charts/)

### Example Implementations

See example charts in `/docs/sims/` directory for reference implementations of different chart types.