how to classify data inside a list file - r

Question

I have a data looks like this
df<- structure(list(14, FALSE, c(1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12,
13, 6), c(0, 0, 0, 0, 0, 6, 6, 6, 6, 6, 6, 6, 0), c(0, 1, 2,
3, 4, 12, 5, 6, 7, 8, 9, 10, 11), c(0, 1, 2, 3, 4, 12, 5, 6,
7, 8, 9, 10, 11), c(0, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13), c(0, 6, 6, 6, 6, 6, 6, 13, 13, 13, 13, 13, 13, 13, 13
), list(c(1, 0, 1), structure(list(), names = character(0)),
list(name = c("Bestman", "Tera1", "Tera2", "Tera3", "Tera4",
"Tera5", "Tetra", "Brownie1", "Brownie2", "Brownie3", "Brownie4",
"Brownie5", "Brownie6", "Brownie7")), list()), <environment>), class = "igraph")
I am trying to make a list and assign the two core as root
I can easily do this
as_tbl_graph(df) %>%
activate(nodes) %>%
mutate(type = ifelse(name %in% c("Bestman", "Tetra"), "root", "branch")) %>%
mutate(group = ifelse(name == "Bestman" | grepl("Tera", name),
"Bestman", "Tera"))
when the number of core grows, this method does not work, for example if I have more and I do the following
for example when my data becomes like this
df2<-structure(list(28, FALSE, c(1, 2, 3, 4, 5, 6, 1, 2, 8, 7, 9,
10, 11, 7, 7, 13, 14, 15, 16, 17, 19, 20, 21, 22, 23, 24, 26,
27, 7, 12, 18, 25, 12, 18, 25, 18, 25, 25), c(0, 0, 0, 0, 0,
0, 0, 0, 7, 6, 7, 7, 7, 2, 1, 12, 12, 12, 12, 12, 18, 18, 18,
18, 18, 18, 25, 25, 0, 0, 0, 0, 7, 7, 7, 12, 12, 18), c(6, 0,
7, 1, 2, 3, 4, 5, 28, 14, 13, 9, 8, 10, 11, 12, 29, 32, 15, 16,
17, 18, 19, 30, 33, 35, 20, 21, 22, 23, 24, 25, 31, 34, 36, 37,
26, 27), c(6, 0, 7, 1, 2, 3, 4, 5, 28, 29, 30, 31, 14, 13, 9,
8, 10, 11, 12, 32, 33, 34, 15, 16, 17, 18, 19, 35, 36, 20, 21,
22, 23, 24, 25, 37, 26, 27), c(0, 0, 2, 4, 5, 6, 7, 8, 12, 13,
14, 15, 16, 18, 19, 20, 21, 22, 23, 26, 27, 28, 29, 30, 31, 32,
36, 37, 38), c(0, 12, 13, 14, 14, 14, 14, 15, 22, 22, 22, 22,
22, 29, 29, 29, 29, 29, 29, 36, 36, 36, 36, 36, 36, 36, 38, 38,
38), list(c(1, 0, 1), structure(list(), names = character(0)),
list(name = c("Bestman", "Tera1", "Tera2", "Tera3", "Tera4",
"Tera5", "Brownie2", "Tetra", "Brownie1", "Brownie3", "Brownie4",
"Brownie5", "trueG", "ckage1", "ckage2", "ckage3", "ckage4",
"ckage5", "Carowner", "Hoghet1", "Hoghet2", "Hoghet3", "Hoghet4",
"Hoghet5", "Hoghet6", "Bestwomen", "Esme2", "Esme3")), list()),
<environment>), class = "igraph")
as_tbl_graph(df2) %>%
activate(nodes) %>%
mutate(type = ifelse(name %in% c("Bestman", "Tetra", "trueG", "Carowner","Bestwomen"), "root", "branch")) %>%
mutate(group = ifelse(name == "Bestman" | grepl("Tetra", name) | grepl("trueG",name) | grepl("Carowner", name) | grepl("Bestwomen", name) , "Bestman", "Tetra","trueG","Carowner","Bestwomen" ))
I get error, I want to know what I am doing wrong here ?

Answer 1

Your second graph is more complex than your first. Some of the 'peripheral' nodes join more than one central node, so it is not clear how they should be labelled / colored. However, tidygraph has various grouping functions which can be used to assign the nodes to groups based on their connectivity, and the centrality of a node can be calculated automatically to help with labelling and sizing.
library(tidygraph)
library(ggraph)
df2 %>%
as_tbl_graph() %>%
activate(nodes) %>%
mutate(is_central = centrality_hub() > 0.6) %>%
mutate(group = factor(group_label_prop())) %>%
ggraph(layout = "igraph", algorithm = "nicely") +
geom_edge_link(width = 2, alpha = 0.1) +
geom_node_circle(aes(r = ifelse(is_central, nchar(name)/12, 0.1), fill = group),
color = NA) +
geom_node_text(aes(label = ifelse(is_central, name, '')), size = 5,
color = "gray40", family = "Roboto Condensed", fontface = 2) +
theme_graph() +
coord_equal() +
scale_fill_brewer(palette = "Pastel2", guide = "none")

Answer 2

ifelse only allows for two options, try using dplyr::case_when instead.
https://dplyr.tidyverse.org/reference/case_when.html
Update to add requested code:
mutate(group = dplyr::case_when(name == "Bestman" ~ "Bestman",
grepl("Tetra", name) ~ "Tetra",
grepl("trueG",name) ~ "trueG",
grepl("Carowner", name) ~ "Carowner",
grepl("Bestwomen", name) ~ "Bestwomen"))