TidyTuesday_20200303

gistfile1.txt

library(readr)
library(tidyverse)
library(gganimate)
library(tidygraph)
library(igraph)
library(ggraph)

season_goals <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-03/season_goals.csv')

top_8 <- season_goals %>%
  select(player, total_goals) %>%
  distinct() %>%
  top_n(n = 8, wt = total_goals)
  
hockey_minder <- season_goals %>% 
  filter(season >= 1969) %>%
  mutate(top_player = if_else(player %in% top_8$player, player, "")) %>%
  mutate(season_start = as.numeric(str_sub(season, 1, 4))) %>%
  ggplot(mapping = aes(x = assists, 
                       y = goals, 
                       colour = team, 
                       size = penalty_min, 
                       label = top_player)) + 
  theme_bw() + 
  geom_point() + 
  geom_text(nudge_y = 12) + 
  guides(size = FALSE, colour = FALSE) +
  labs(title = "Season: {frame_time}", x = "Assists", y = "Goals") +
  transition_time(as.integer(season_start)) +
  ease_aes('linear')

anim_save("hockey_gif.gif", animate(hockey_minder, fps = 4))

#Load the data
season_goals <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-03-03/season_goals.csv')

#Prepare the edge list
edge_list <- season_goals %>%
  select(player, team) %>%
  distinct() %>%
  # from here the steps to getting an edge list are from https://stackoverflow.com/questions/34670145/generating-an-edge-list-from-id-and-grouping-vectors
  group_by(player) %>%
  filter(n()>=2) %>% 
  group_by(player) %>%
  do(data.frame(t(combn(.$team, 2)), stringsAsFactors=FALSE)) %>%
  ungroup() %>%
  select(-player) %>%
  rename(from = X1, to = X2) %>%
  # from here the steps to getting the edge weight are from: https://www.jessesadler.com/post/network-analysis-with-r/
  group_by(from, to) %>%
  summarise(weight = n()) %>% 
  ungroup()

#Graph it!

# Create graph using tidygraph
graph <- as_tbl_graph(edge_list)

# plot using ggraph
ggraph(graph, layout = 'kk') + 
  geom_edge_bend(aes(alpha = weight), show.legend = FALSE) + 
  scale_edge_width(range = c(0.2, 1.5)) + 
  geom_node_point() + 
  geom_node_label(aes(label = name), repel = TRUE) + 
  theme_graph()