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 proportion...