data-visualization

📁 spjoshis/claude-code-plugins 📅 5 days ago
2
总安装量
2
周安装量
#71870
全站排名
安装命令
npx skills add https://github.com/spjoshis/claude-code-plugins --skill data-visualization

Agent 安装分布

opencode 2
gemini-cli 2
claude-code 2
github-copilot 2
codex 2
kimi-cli 2

Skill 文档

Data Visualization

Create effective data visualizations and dashboards that communicate insights clearly and drive decision-making.

When to Use This Skill

  • Building dashboards
  • Presenting insights
  • Executive reporting
  • KPI tracking
  • Trend analysis
  • Comparative analysis
  • Geographic analysis
  • Time series visualization

Core Concepts

1. Chart Selection Guide

**Comparison**:
- Bar chart: Compare categories
- Column chart: Compare over time
- Grouped/stacked bar: Multiple series

**Trend**:
- Line chart: Show trends over time
- Area chart: Magnitude and trend
- Sparklines: Compact trends

**Part-to-Whole**:
- Pie chart: Few categories (<5)
- Stacked bar: Parts over time
- Treemap: Hierarchical data

**Distribution**:
- Histogram: Frequency distribution
- Box plot: Statistical distribution
- Scatter plot: Correlation

**Geographic**:
- Choropleth map: Regional data
- Symbol map: Point locations
- Heat map: Density visualization

2. Dashboard Design Principles

## KPI Dashboard Layout

+----------------------------------+
|  Title: Sales Performance        |
+----------------------------------+
|  KPI    |  KPI    |  KPI         |
|  $1.2M  |  +15%   |  95%         |
|  Revenue| Growth  | Goal         |
+----------------------------------+
|                                  |
|  Revenue Trend (Line Chart)      |
|  [Chart showing 12 months]       |
|                                  |
+----------------------------------+
|  By Region  |  By Product        |
|  [Bar Chart]|  [Bar Chart]       |
+----------------------------------+
|  Filters: Date Range, Region     |
+----------------------------------+

**Design Principles**:
1. Most important metric top-left
2. Trend charts show context
3. Filters at top or left
4. Consistent color scheme
5. Clear labels and units
6. White space for readability

Best Practices

  1. Choose right chart – Match data and purpose
  2. Simplify – Remove chartjunk, reduce clutter
  3. Use color purposefully – Highlight, categorize
  4. Clear labels – Title, axes, legends
  5. Start axis at zero – Avoid misleading scales
  6. Mobile-friendly – Responsive design
  7. Interactive – Filters, drill-down
  8. Tell a story – Guide viewer’s attention

Resources

  • Storytelling with Data: Cole Nussbaumer Knaflic
  • The Visual Display of Quantitative Information: Edward Tufte
  • Tableau Public: Free visualization tool