![]() Instead of displaying regions on a circle, they are duplicated and represented on both side of the graphic. Sankey diagram is another option to display weighted connection. See this blog post by Nadieh Bremer for more ideas on this topic. A good way to do so is to draw just a few connections in a first step, before displaying the whole graphic. ![]() Thus, it is advised to give a good amount of explanation to educate your audience. However chord diagram is not an usual way of displaying information. Moreover, for each continent it is quite easy to quantify the proportion of people leaving and arriving. Major flows are easy to detect, like the migration from South Asia towars Westa Asia, or Africa to Europe. In my opinion this is a powerful way to display information. # short names colnames(data) % rownames_to_column %>% gather( key = 'key', value = 'value', -rowname)Ĭircos.par( gree = 90, gap.degree = 4, track.margin = c( - 0.1, 0.1), = FALSE) It does not work for the other example on authors connections. Since this kind of graphic is used to display flows, it can be applied only on network where connection are weighted. Abel, who is also the author of the migration dataset used here. It works well if your data are directed and weighted like for migration flows between country.ĭisclaimer: this plot is made using the circlize library, and very strongly inspired from the Migest package from Gui J. Relationships can also be directed and unweightedĬhord diagram is a good way to represent the migration flows. Relationships can also be undirected and weighted # Load data #dataUU % head( 3) %>% select( 1 : 4) %>% kable() %>% kable_styling( bootstrap_options = "striped", full_width = F) ![]() ![]() The result is an adjacency matrix with about 100 researchers, filled with 1 if they have published a paper together, 0 otherwise. Data have been retrieved using the scholar package, the pipeline is describe in this github repository. I will consider all the co-authors of a researcher and study who is connected through a common publication. Relationships can be undirected and unweighted.Data % head( 3) %>% select( 1 : 3) %>% kable() %>% kable_styling( bootstrap_options = "striped", full_width = F) ![]()
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