Womens Rugby

library(tidyverse)

sevens <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-05-24/sevens.csv')
fifteens <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2022/2022-05-24/fifteens.csv')

my_df <- sevens%>%
  mutate(year_month=zoo::as.yearmon(date),.after=date) %>%
  filter(score_1=="L" | score_1=="W") %>%
  #select(-winner,-loser) %>%
  pivot_longer(cols = c("team_1","team_2"),names_to="teams",values_to="t_country")%>%
  relocate(teams,t_country,winner,loser) %>%
  distinct()%>%
  mutate(final=ifelse(t_country==winner,"Winner","Loser"))%>%
  relocate(final) 

my_df%>% # count(t_country)
  count(t_country,teams,final)%>%
  group_by(t_country)%>%
  summarize(final,teams,pct=round(n/sum(n)*100))%>%
  filter(!pct==100)

my_df%>% # count(t_country)
  count(t_country,teams,final)%>%
  group_by(t_country)%>%
  summarize(final,teams,pct=round(n/sum(n)*100))%>%
  filter(!pct==100)%>%
  ungroup()%>%
pivot_wider(names_from=teams,values_from=pct)

library(extrafont)
loadfonts()

library(ggbump)

my_df %>%
  select(row_id,date,year_month,teams,t_country,final) %>%
  mutate(t_country=case_when(t_country=="Arabian Gulf"~"* Arabian Gulf",
                             t_country=="Burkina Faso"~"* Burkina Faso",
                             t_country=="Cote d'Ivorie"~"* Cote d'Ivorie",
                             t_country=="Ghana"~"* Ghana",
                             t_country=="Hong Kong"~"* Hong Kong",
                             t_country=="Kazakhstan"~"* Kazakhstan",
                             TRUE~t_country))%>%
  ggplot(aes(x=1,y=t_country,color=teams)) +
  ggbump::geom_sigmoid(aes(x=1,y=t_country,
                           xend=year_month+1, yend=final),
                       key_glyph = draw_key_rect)+
  geom_text(aes(label=t_country,x=0),
            hjust=1,family="Comic Sans MS")+
  geom_text(aes(label=final,x=2000,y=final),family="Comic Sans MS",
            size=6,hjust=0) +#c("Winner","Loser")
  xlim(-300,2200)+
  labs(title="Women's Rugby - Countries without scores",
       subtitle = "from December 2000 to May 2010",
       caption="\n* 6 countries out of 21 shared a winner/loser position while being either in team 1 or team 2\nBurkina Faso is the only one who won being in Team 2 with 67% pct, most wins are from Team 1\nCote d'Ivorie won and lost 50%/50% pct in both teams\n\nDataSource: #TidyTuesday 2022 week21 - Women's Rugby - ScrumQueens\nDataViz: Federica Gazzelloni (@fgazzelloni)",
       color="")+
  viridis::scale_color_viridis(discrete=T,option="inferno",
                                alpha = 1,begin = 0.5,end = 0.8,
                               labels = c("Team 1", "Team 2"), breaks = c("team_1", "team_2"))+
  theme_void()+
  theme(text = element_text(family="Comic Sans MS",size=23,color="darkorange"),
    legend.position = c(0.8,0.2),
    plot.title = element_text(hjust = 0.1),
    plot.subtitle = element_text(hjust = 0.1,size=20),
    plot.caption = element_text(size=10,hjust=0,color="darkorange"),
    plot.background = element_rect(fill="beige",color="beige"),
    panel.background = element_rect(fill="beige",color="beige"),
    plot.margin = margin(5,5,5,5,unit = "pt"))

ggsave("w21_women_rugby.png",
       width = 8.5,
       height = 7,
       dpi=320)

fifteens%>%head