Chapter 6 Advanced Data Visualization

Learning Objectives

After completing this chapter, you will be able to:

  • Create jitter plots, count plots, and violin plots for comparing distributions
  • Add line segments and auxiliary lines to existing plots
  • Build heat maps using both base R and ggplot2
  • Visualize uncertainty with error bar plots
  • Convert static plots into interactive visualizations with plotly

In Chapter 5, we introduced the most commonly used plots. If you skipped the previous chapter, it may be worthwhile to briefly review Section 5.13.

In this chapter, we will introduce more types of plots and various customization.

At a glance – Chapter ROADMAP Section 6.1.2 & Section 6.1.3. Comparison Plots: Use jitter and count plots to address overplotting.
Section ??. Violin Plots: Visualize distribution density and statistics for comparing groups.
Section 6.3. Line Segments: Add horizontal, vertical, and custom line segments to plots.
Section 6.4. Heat Maps: Visualize magnitude across categories using tiled colors.
Section 6.5. Error Bars: Display uncertainty in statistical measurements.
Section 6.6. Interactive Plots: Transform static charts into interactive visualizations.

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