# LIB
{
library(readxl)
library(ggplot2)
library(dplyr)
library(ggflags)
library(stringr)
library(hrbrthemes)
}
# DATA
cup <- read.csv("cup.csv", sep=";", stringsAsFactors = FALSE)
cup <- cup[with(cup, order(-cup$WIN.WORLD.CUP)), ]
# ORDER
cup$TEAM <- gsub("\n","",cup$TEAM)
cup$TEAM <- gsub(" ","",cup$TEAM)
cup$TEAM <- str_replace_all(cup$TEAM," ", "")
cup$TEAM
cup <- head(cup,10)
names(cup)[12] = "Win"
new <- c(29.10, 12.00, 12.80,
12.90, 8.10, 0,
9.40, 6.00, 1.10, 0)
cup2 <- cbind(cup, new)
#PLOT
plot <- ggplot(data=cup2, aes(x= reorder(TEAM, -Win) , y=Win, group=1)) +
ggtitle("Winning the 2022 World Cup (Top 10 favourites)") +
xlab("Country") +
ylab("Percentage") +
geom_line(col="gray") +
geom_point() +
geom_line(data=cup2, aes(x= reorder(TEAM, -new) , y=new, group=1), col="blue") +
geom_point(data=cup2, aes(x= reorder(TEAM, -new) , y=new, group=1)) +
geom_text(data=cup2,aes(label=paste(Win, "%") ), vjust=2.3, color="gray", size=3.5)+
geom_text(data=cup2,
aes(x= reorder(TEAM, -new) , y=new, size=18),
label=paste(new, "%"), vjust=-1.6, color="blue", size=3.5)+
geom_flag(data=cup2, aes(x = reorder(TEAM, -Win) , y=-7, country = code), size=15) +
theme_ipsum(grid = F, base_family = "sans") +
labs(subtitle = "Data: Soccer Power Index (SPI)") +
geom_segment(aes(x="France",
xend = "Argentina",
y = 25,
yend = 25),
size = 4,
col = "blue") +
geom_segment(aes(x="France",
xend = "Argentina",
y = 23,
yend = 23),
size = 4,
col = "gray") +
annotate("text", x = "Germany", y = 23, label = "Prediction before the start of the World Cup") +
annotate("text", x = "Germany", y = 25, label = "Current forecast (Thu 1 Dec 22:18 GMT+1)")
# plot