data-visualization

# Data Visualization Skill

Chart selection guidance, Python visualization code patterns, design principles, and accessibility considerations for creating effective data visualizations.

## Chart Selection Guide

### Choose by Data Relationship

| What You're Showing | Best Chart | Alternatives |
|---|---|---|
| **Trend over time** | Line chart | Area chart (if showing cumulative or composition) |
| **Comparison across categories** | Vertical bar chart | Horizontal bar (many categories), lollipop chart |
| **Ranking** | Horizontal bar chart | Dot plot, slope chart (comparing two periods) |
| **Part-to-whole composition** | Stacked bar chart | Treemap (hierarchical), waffle chart |
| **Composition over time** | Stacked area chart | 100% stacked bar (for proportion focus) |
| **Distribution** | Histogram | Box plot (comparing groups), violin plot, strip plot |
| **Correlation (2 variables)** | Scatter plot | Bubble chart (add 3rd variable as size) |
| **Correlation (many variables)** | Heatmap (correlation matrix) | Pair plot |
| **Geographic patterns** | Choropleth map | Bubble map, hex map |
| **Flow / process** | Sankey diagram | Funnel chart (sequential stages) |
| **Relationship network** | Network graph | Chord diagram |
| **Performance vs. target** | Bullet chart | Gauge (single KPI only) |
| **Multiple KPIs at once** | Small multiples | Dashboard with separate charts |

### When NOT to Use Certain Charts

- **Pie charts**: Avoid unless <6 categories and exact proportions matter less than rough comparison. Humans are bad at comparing angles. Use bar charts instead.
- **3D charts**: Never. They distort perception and add no information.
- **Dual-axis charts**: Use cautiously. They can mislead by implying correlation. Clearly label both axes if used.
- **Stacked bar (many categories)**: Hard to compare middle segments. Use small multiples or grouped bars instead.
- **Donut charts**: Slightly better than pie charts but same fundamental issues. Use for single KPI d