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Alternative ways to visualize a graph: Hive plots

Another method you can use to visualize graphs are hive plots. These visualize points along a set of axes that are defined by categories of data. The position on the axis is determined by a feature of the graph like centrality and edge width, and color can be set by graph properties. Unlike hairball plots, hive plots layout is determined by properties of the graph. It makes comparing and interpreting the visualization easier than other approaches. In this exercise, we’ll visualize some of the bike data by assigning each vertex to an axis by its geography (north, central, southern). Vertices are aligned by centrality, and then colored in a heat map by geographic distance. This is why we see more red lines (far distance) on vertices at the end of the axis (greater centrality).

This exercise is part of the course

Case Studies: Network Analysis in R

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Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Convert trip_df to hive object using edge2HPD()
bike_hive <- ___(___, axis.cols = rep("black", 3))
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