chart-designer
设计高效数据可视化方案,推荐图表类型并生成主流图表库的配置代码
npx skills add claude-office-skills/skills --skill chart-designerBefore / After 效果对比
1 组面对数据不知道选择何种图表类型,手动编写图表库配置代码反复调试样式,可视化效果不佳导致数据洞察传达不清晰
根据数据特征自动推荐最佳图表类型,直接生成目标图表库的完整配置代码,可视化方案专业且开箱即用,数据洞察一目了然
description SKILL.md
chart-designer
Chart Designer Skill
Overview
I help you design effective data visualizations by recommending the right chart types, generating configurations for popular charting libraries, and applying data visualization best practices.
What I can do:
-
Recommend appropriate chart types for your data
-
Generate ECharts/Chart.js configurations
-
Design dashboard layouts
-
Apply visualization best practices
-
Create Excel chart specifications
-
Suggest color schemes and styling
What I cannot do:
-
Render charts directly (use generated configs in tools)
-
Create custom chart types from scratch
-
Access your data directly
How to Use Me
Step 1: Describe Your Data
Tell me:
-
What type of data you have
-
What story you want to tell
-
Your audience (technical, executive, public)
-
Where it will be displayed (presentation, dashboard, report)
Step 2: Get Recommendations
I'll suggest:
-
Best chart type(s) for your data
-
Configuration options
-
Color schemes
-
Layout considerations
Step 3: Receive Chart Configs
I'll provide:
-
ECharts JSON configuration
-
Chart.js configuration
-
Excel chart setup instructions
-
CSS/styling recommendations
Chart Selection Guide
Comparison Charts
Chart Type Best For Data Requirements
Bar Chart Comparing categories Categories + values
Grouped Bar Multiple series comparison Categories + multiple series
Stacked Bar Part-to-whole comparison Categories + component values
Trend Charts
Chart Type Best For Data Requirements
Line Chart Change over time Time series data
Area Chart Cumulative trends Time series (stacked optional)
Sparkline Compact trends Simple time series
Distribution Charts
Chart Type Best For Data Requirements
Histogram Value distribution Numeric values
Box Plot Distribution summary Numeric values with quartiles
Scatter Plot Correlation Two numeric variables
Part-to-Whole Charts
Chart Type Best For Data Requirements
Pie Chart Simple proportions (≤5 items) Categories + percentages
Donut Chart Proportions with total Categories + percentages
Treemap Hierarchical proportions Hierarchical data + values
Specialized Charts
Chart Type Best For Data Requirements
Funnel Process stages/conversion Stages + values
Gauge Single KPI vs target Current value + target
Heatmap Matrix comparisons Row + Column + Value
Radar Multi-dimensional comparison Multiple metrics per item
Sankey Flow/transitions Source + Target + Value
Decision Tree
What do you want to show?
│
├─ Comparison
│ ├─ Among items → Bar Chart
│ ├─ Over time → Line Chart
│ └─ Multiple series → Grouped/Stacked Bar
│
├─ Composition
│ ├─ Static → Pie/Donut (≤5) or Treemap
│ ├─ Over time → Stacked Area
│ └─ Hierarchical → Treemap/Sunburst
│
├─ Distribution
│ ├─ Single variable → Histogram
│ ├─ Multiple datasets → Box Plot
│ └─ Two variables → Scatter Plot
│
├─ Relationship
│ ├─ Two variables → Scatter Plot
│ ├─ Three variables → Bubble Chart
│ └─ Correlation matrix → Heatmap
│
└─ Flow/Process
├─ Sequential stages → Funnel
├─ Transitions → Sankey
└─ Single metric → Gauge
Output Format
# Chart Design: [Title]
**Data Type**: [Description]
**Purpose**: [What story to tell]
**Recommended Chart**: [Chart type]
---
## Chart Configuration
### ECharts
```javascript
const option = {
title: {
text: 'Chart Title',
left: 'center'
},
tooltip: {
trigger: 'axis'
},
legend: {
data: ['Series 1', 'Series 2'],
bottom: 10
},
xAxis: {
type: 'category',
data: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun']
},
yAxis: {
type: 'value'
},
series: [
{
name: 'Series 1',
type: 'bar',
data: [120, 200, 150, 80, 70, 110]
},
{
name: 'Series 2',
type: 'line',
data: [100, 180, 160, 90, 80, 100]
}
]
};
Chart.js
const config = {
type: 'bar',
data: {
labels: ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun'],
datasets: [{
label: 'Series 1',
data: [120, 200, 150, 80, 70, 110],
backgroundColor: 'rgba(54, 162, 235, 0.8)'
}]
},
options: {
responsive: true,
plugins: {
title: {
display: true,
text: 'Chart Title'
}
}
}
};
Styling Recommendations
Color Palette
-
Primary:
#5470c6 -
Secondary:
#91cc75 -
Accent:
#fac858 -
Neutral:
#73c0de
Typography
-
Title: 16px, bold
-
Labels: 12px, regular
-
Axis: 11px, light
Best Practices Applied
-
[Practice 1]
-
[Practice 2]
-
[Practice 3]
Alternative Charts
If this doesn't work well, consider:
-
[Alternative 1] - when [condition]
-
[Alternative 2] - when [condition]
---
## ECharts Common Configurations
### Bar Chart
```javascript
{
xAxis: { type: 'category', data: categories },
yAxis: { type: 'value' },
series: [{
type: 'bar',
data: values,
itemStyle: { color: '#5470c6' }
}]
}
Line Chart
{
xAxis: { type: 'category', data: categories },
yAxis: { type: 'value' },
series: [{
type: 'line',
data: values,
smooth: true,
areaStyle: {} // for area chart
}]
}
Pie Chart
{
series: [{
type: 'pie',
radius: ['40%', '70%'], // donut
data: [
{ value: 100, name: 'A' },
{ value: 200, name: 'B' }
]
}]
}
Scatter Plot
{
xAxis: { type: 'value' },
yAxis: { type: 'value' },
series: [{
type: 'scatter',
data: [[x1, y1], [x2, y2]],
symbolSize: 10
}]
}
Color Palettes
Professional
#5470c6, #91cc75, #fac858, #ee6666, #73c0de, #3ba272, #fc8452, #9a60b4
Cool
#1f77b4, #aec7e8, #17becf, #9edae5, #6baed6, #c6dbef, #08519c, #3182bd
Warm
#ff7f0e, #ffbb78, #d62728, #ff9896, #e377c2, #f7b6d2, #bcbd22, #dbdb8d
Accessible (colorblind-friendly)
#0077BB, #33BBEE, #009988, #EE7733, #CC3311, #EE3377, #BBBBBB
Best Practices
Data Ink Ratio
-
Remove unnecessary gridlines
-
Minimize chart junk
-
Let data be the focus
Clarity
-
Clear, descriptive titles
-
Labeled axes with units
-
Appropriate precision (not too many decimals)
Comparison
-
Start y-axis at zero for bar charts
-
Use consistent scales for comparison
-
Sort data logically
Color
-
Use color purposefully
-
Consider colorblind users
-
Don't use too many colors (≤7)
Interaction
-
Tooltips for details
-
Zoom for dense data
-
Drill-down for hierarchies
Tips for Better Charts
-
Know your audience - technical vs. executive
-
Start with the question - what are you trying to answer?
-
Choose the right chart - don't force data into wrong formats
-
Simplify - less is more
-
Label clearly - assume viewers have no context
-
Test with real users - is the message clear?
-
Consider accessibility - colors, contrast, alt text
Limitations
-
Cannot render charts directly
-
Configuration may need adjustment for specific tools
-
Complex custom visualizations may require code
-
Real-time data requires additional setup
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