This morning I attacked my problem of showing hierarchical clusters without just making a dendrogram tree (left pic). Lots of plots were made in through the course of the day to get to the plot on the right, so I decided to show the whole process #dataviz 1/5 
First approach was putting the unclustered graph into Large Graph Layout. I have to consult my own blogpost to run the program, so I guess write for yourself clairemcwhite.github.io/lgl-guide/. The graph is too dense for even the magic bullet of LGL to get good separation w/o clustering 2/5
Next series of plots in R with ggraph, still using unclustered graph. The graph is too dense to all of these, but they look cool. 3/5
I was avoiding using the clustered data because I was stuck on converting the 'dendrogram' object (first tweet) to anything else. But it was definitely necessary to start reducing the complexity. This post on nested dataframe -> edgelist was the key: r-graph-gallery.com/334-basic-dend… 4/5
Circled back to the circlepack option in ggraph. It's reduced in complexity, and is starting to capture the hierarchical nature of the clusters. Definitely getting to where I want it to be, color scheme TBD. 5/5
Context for the key simplification step. Starting dendrogram is igraph clustering. I cut it at 5 intervals to gets clusters from rough to fine (pic, each row is a node w/ its cluster at different levels). Then follow code ex. from link two tweets up to get it formatted for ggraph
Thanks for the inspiration @IsabellaGhement, I got together at least the code to go from a dendrogram to my final plot into a gist. gist.github.com/clairemcwhite/…
@TraverHart The code's online now
@TraverHart The code's online now
