What multivariate EDA plots are most useful?

medium

Answer

$(1) Correlation heatmap: quick view of all pairwise linear relationships.$
$(2) Scatter plot matrix (pairs plot): all bivariate scatters, diagonal shows univariate — best for small-to-medium feature sets.$
$(3) Parallel coordinates: high-dim shape visualization.$
$(4) PCA / UMAP 2D projections: capture nonlinear structure.$
$(5) 2D density / hex bins: for many-point scatters.$
$(6) Facet grids: same plot across a categorical variable.$
$Choose based on dimensionality and hypothesis.$

Check yourself — multiple choice

Only one plot
Heatmap / pairs plot / parallel coords / PCA-UMAP / 2D density / facet grids — pick per dimension and question
Only histograms
None useful

Multivariate EDA: heatmap / pairs / parallel / PCA-UMAP / density / facets.

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