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.
Hi @enjalot, I recently gave a talk where I tried to relate scatter plots, dimensionally reduction, parallel coordinates, and heatmaps in a few slides (video https://youtu.be/dSEy6XGoIi0 6-9 minute mark and slides bit.ly/nci-clustergrammer2) - I’m basically making the argument that heatmaps can be thought of as parallel coordinates and parallel data. I’ll probably try to make a notebook out of these intro slides later. Let me know if you have any comments
I would love to see a notebook based on those slides! It’s an interesting perspective I hadn’t seen in that way though I’ve thought about the various representations independently before. I wonder if having a toy example that could be played with interactively could help illustrate the concepts.
Some time ago I was playing with the idea of such a toy example around dimensionality reduction but couldn’t find a way to bring it home:
Yeah, I have been thinking about making a notebook on those slides. I agree that a single dataset with linked views (scatterplot, parallel-coords, dimensionality reduction, and heatmap) would be very nice. I just have to find a good dataset (e.g. Iris flowers or NBA stats or something), right plotting tools (deck.gl has been working well), and some time (I’ll update here once I have something working)
@enjalot Thanks for sharing the triangle world notebooks they look great and I look forward to checking them out in more detail.