network graph of world cup players countries and clubs

wc_network.R

library(rvest)
library(tidyverse)
library(tidygraph)
library(ggraph)

wc_squads <- read_html("https://en.wikipedia.org/wiki/2018_FIFA_World_Cup_squads") %>% 
  html_table()

teams <- c("Egypt", "Russia", "Saudi Arabia", "Uruguay",
           "Iran", "Morocco", "Portugal", "Spain",
           "Australia", "Denmark", "France", "Peru",
           "Argentina", "Croatia", "Iceland", "Nigeria",
           "Brazil", "Costa Rica", "Serbia", "Switzerland",
           "Germany", "Mexico", "South Korea", "Sweden",
           "Belgium", "England", "Panama", "Tunisia",
           "Colombia", "Japan", "Poland", "Senegal")

df <- 
  map_df(1:32, ~ {
    wc_squads[[.x]] %>% 
      mutate(Country = teams[.x]) %>% 
      select(Player, Country, Club)
  }) %>% 
  rownames_to_column("id")

country_clubs <- df %>% 
  select(Country, Club) %>% 
  group_by_all() %>% 
  summarise(weight = n()) %>% 
  filter(Country %in% c("Brazil", "France", "Germany", "Spain", "Belgium")) 
  
wc_network <- as_tbl_graph(country_clubs) %>% 
  mutate(type = if_else(name %in% df$Country, "Country", "Club"))

ggraph(wc_network) + 
  geom_edge_arc(aes(width = weight), alpha = .25, colour = "white") + 
  scale_edge_width(range = c(0.2, 2)) +
  geom_node_point(aes(colour = type, size = type), show.legend = FALSE) + # 
  scale_size_manual(values = c(2, 10)) +
  geom_node_text(aes(label = name), family = "Iosevka", colour = "white",
                  repel = TRUE, size = 3, show.legend = FALSE) +
  theme_graph(background = "#2E3440", text_colour = "white", 
              base_family = "Iosevka", foreground = NA) +
  labs(title = "World Cup 2018 | Club Country Network",
       subtitle = "Belgium, Brazil, France, Germany, Spain",
       caption = "@paulcampbell91 | Source: Wikipedia",
       edge_width = "Players")

learn something new. thank you so much.