Q&A 36 How do you visualize patterns and relationships in multivariate data?

36.1 Explanation

Once you’ve explored individual variables and group comparisons, the next step is to examine relationships across multiple variables. This helps uncover:

• Patterns in how features interact
• Clustering or separation between groups (e.g., species)
• Correlations that indicate redundancy or strong associations

These techniques help build intuition for: - Feature selection (which variables contribute useful info) - Model design (what patterns might be captured) - Data structure (whether groups are well-separated)

Common tools include: - Pair plots: All-vs-all scatter plots to spot trends - Heatmaps: Visualize correlations between numeric features - Facet plots: Compare distributions across groups or classes - Parallel coordinates: Explore high-dimensional feature behavior - Dimensionality reduction (e.g., PCA/UMAP): Visualize structure in fewer dimensions

We’ll begin by visualizing pairwise relationships using pair plots.