Chapter 15 Australian Open Winners
The following bar plot shows the Australian Open winners
getTournamentWinners = function(tournamentname,roundname ="All")
{
if(roundname == "All")
{
return(
matches %>%
filter(tourney_name == tournamentname) %>%
mutate(agediff = winner_age - loser_age) %>%
mutate(rankingdiff = loser_rank - winner_rank) %>%
mutate(htdiff = winner_ht - loser_ht)
)
}else
{
return(
matches %>%
filter(tourney_name == tournamentname) %>%
filter(round == roundname) %>%
mutate(agediff = winner_age - loser_age) %>%
mutate(rankingdiff = loser_rank - winner_rank) %>%
mutate(htdiff = winner_ht - loser_ht)
)
}
}
getGrandSlamWinners = function(roundname)
{
return(
matches %>%
filter(tourney_level == "G") %>%
filter(round == roundname) %>%
mutate(agediff = winner_age - loser_age) %>%
mutate(rankingdiff = loser_rank - winner_rank)
)
}
plotTournamentWinners = function(tournament,titleName)
{
tournament %>%
group_by(winner_name) %>%
summarise(Count = n()) %>%
arrange(desc(Count)) %>%
ungroup() %>%
mutate(winner_name = reorder(winner_name,Count)) %>%
ggplot(aes(x = winner_name,y = Count)) +
geom_bar(stat='identity',colour="white", fill = fillColor2) +
geom_text(aes(x = winner_name, y = 1, label = paste0("(",Count,")",sep="")),
hjust=0, vjust=.5, size = 4, colour = 'black',
fontface = 'bold') +
labs(x = 'Winner',
y = 'Count',
title = titleName) +
coord_flip() +
theme_bw()
}
ausopen = getTournamentWinners("Australian Open","F")
plotTournamentWinners(ausopen,'Aus Open Winners Count')
15.1 Distribution of Age of Australian Open Winners
summary(ausopen$winner_age)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 20.74 23.35 25.55 26.15 27.90 35.31
ausopen %>%
ggplot(aes(x = winner_age)) +
geom_histogram(binwidth = 1,fill = fillColor) +
labs(x= 'Winner Age',y = 'Count', title = paste("Distribution of", ' Winner Age ')) +
theme_bw()
The plot shows the Australian Open winners are mostly between 23 and 28.