I’ve been working on ways to show the relationship between visualizing data using dimensionality reduction (e.g. UMAP, using deck.gl for interactive visualization) and hierarchically clustered heatmaps (e.g. using our library Clustergrammer-GL) as well as show the benefits of making linked visualizations.
This notebook shows how we can visualize a high-dimensional food nutrient dataset from the USDA (source Nutrient Explorer) ~7,000 foods and 14 nutrient dimensions. It works best when set to landscape and fullscreen.