visualization

数据可视化设计、工具和故事讲述，用于打造有影响力的分析演示

SKILL.md

--- frontmatter

name: visualization
description: Data visualization design, tools, and storytelling for impactful analytics presentations
version: "2.0.0"
sasmp_version: "2.0.0"
bonded_agent: 04-visualization-architect
bond_type: PRIMARY_BOND

# Skill Configuration
config:
  atomic: true
  retry_enabled: true
  max_retries: 3
  backoff_strategy: exponential

# Parameter Validation
parameters:
  tool_focus:
    type: string
    required: true
    enum: [tableau, powerbi, python, r, all]
    default: all
  skill_level:
    type: string
    required: true
    enum: [beginner, intermediate, advanced]
    default: beginner
  audience_type:
    type: string
    required: false
    enum: [executive, technical, business, public]
    default: business

# Observability
observability:
  logging_level: info
  metrics: [dashboard_views, interaction_rate, load_time]

Data Visualization Skill

Overview

Master the art and science of data visualization to communicate insights effectively using modern tools and design principles.

Core Topics

Visualization Principles

•Chart selection guidelines
•Color theory for data visualization
•Visual hierarchy and attention
•Accessibility in visualization

Tools & Platforms

•Tableau (dashboards, calculated fields, LOD expressions)
•Power BI (DAX, data modeling, reports)
•Python (Matplotlib, Seaborn, Plotly)
•R (ggplot2, Shiny)

Chart Types

•Comparison charts (bar, column, dot plot)
•Trend charts (line, area, slope)
•Distribution charts (histogram, box plot, violin)
•Relationship charts (scatter, bubble, heatmap)
•Composition charts (pie, treemap, stacked bar)

Data Storytelling

•Narrative structure for data presentations
•Annotation and callout techniques
•Interactive dashboard design
•Executive presentation best practices

Learning Objectives

•Select appropriate visualization for data and audience
•Create professional dashboards in Tableau and Power BI
•Design effective data stories
•Apply visualization best practices

Error Handling

Error Type	Cause	Recovery
Data connection failed	Source unavailable	Check connection, use cached data
Slow dashboard	Too much data	Aggregate, filter, or use extracts
Chart unreadable	Poor design choice	Apply chart selection guidelines
Accessibility issue	Color/contrast	Use colorblind-safe palette
Mobile display broken	Non-responsive	Redesign for mobile-first

Related Skills

•statistics (for data to visualize)
•programming (for programmatic visualization)
•career (for presenting to stakeholders)