selectively color/size nodes in ggraph

Question

I'm using tidygraph and ggraph to plot a network. Is there a way to selectively manipulate nodes? Specifically, size and color, separately.

# example data
    rstat_nodes <- data.frame(name = c("Hadley", "David", "Romain", "Julia"))
    rstat_edges <- data.frame(from = c(1, 1, 1, 2, 3, 3, 4, 4, 4), 
                              to = c(2, 3, 4, 1, 1, 2, 1, 2, 3))
    gr <- tbl_graph(nodes = rstat_nodes, edges = rstat_edges)

    as_tbl_graph(gr) %>% 
      mutate(centrality = centrality_degree(normalized = T)) %>% 
      ggraph(layout = 'auto') + 
      #geom_edge_link() +
      geom_edge_arc(curvature=0.2,alpha=0.5) + 
      geom_node_point(aes(size = 0.2, colour = centrality)) + 
      scale_color_viridis(guide = 'legend') + 
      ggtitle("Network Degree Centrality (Normalized)") +
      theme_graph()

elliot · Accepted Answer · 2019-05-11 22:01:54Z

Yes, you can use activate from the tidygraph package to access the nodes and edges dataframes. You can then use dplyr to manipulate the data in each file. You can also pipe directly into a ggraph.

library(tidyverse)
library(igraph)
library(ggraph)
library(tidygraph)
library(graphlayouts)
library(scales)


# example data
rstat_nodes <-
  data.frame(name = c("Hadley", "David", "Romain", "Julia"))
rstat_edges <- data.frame(from = c(1, 1, 1, 2, 3, 3, 4, 4, 4),
                          to = c(2, 3, 4, 1, 1, 2, 1, 2, 3))

gr <- tbl_graph(nodes = rstat_nodes, edges = rstat_edges)

gr %>% 
  activate(nodes) %>% # use dplyr on nodes
  mutate(David = 
           case_when(name == 'David' ~ 2, T ~ 0), 
         David = as.character(David)) %>% 
  activate(edges) %>% # same on edge list
  mutate(David = case_when(from == 2 ~ 1, T ~ 0), 
         David = as.character(David)) %>% 
  ggraph(., layout = 'auto')+
  geom_edge_link(aes(color = David), 
                 width = 1)+
  geom_node_point(aes(color = David), 
                  size = 5)+
  geom_node_text(aes(label = name), 
                 nudge_x = .05, 
                 nudge_y = .05)

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