data-visualization

# Data Visualization Skill When creating data visualizations, follow these principles to ensure clear and effective communication: ## Core Principles ### 1. Choose the Right Chart Type - **Line Charts**: Trends over time, continuous data - **Bar Charts**: Comparing categories, discrete data - **Scatter Plots**: Relationships between variables, correlations - **Pie Charts**: Parts of a whole (use sparingly, max 5-6 segments) - **Heatmaps**: Patterns in large datasets, correlations - **Box Plots**: Distribution statistics, outlier detection ### 2. Design Guidelines **Clarity** - Use clear, descriptive titles and labels - Include units of measurement - Add a legend when multiple series are present - Ensure adequate contrast and readability **Accuracy** - Start y-axis at zero for bar charts (unless good reason) - Use consistent scales across related charts - Avoid distorting data through inappropriate scaling - Label data points when precision matters **Simplicity** - Remove chart junk and unnecessary decorations - Use color purposefully, not decoratively - Limit the number of colors (5-7 max) - Ensure accessibility (colorblind-friendly palettes) ### 3. Color Best Practices - **Sequential**: Use for ordered data (light to dark) - **Diverging**: Use for data with a meaningful midpoint - **Categorical**: Use for unordered categories - **Highlight**: Use accent colors to draw attention - Test accessibility with colorblind simulators ### 4. Storytelling with Data - Lead with...