London Marathon

To cite Federica’s work, please use: Gazzelloni F., 2023 Data Visualization London Marathon

library(tidyverse)
tuesdata <- tidytuesdayR::tt_load(2023, week = 17)
winners <- tuesdata$winners
london_marathon <- tuesdata$london_marathon

winners%>%count(Nationality)

london_marathon%>%head

london_marathon%>%
  mutate(ymon=zoo::as.yearmon(Date),.after=Date)%>%
  arrange(ymon)%>%
  pivot_longer(cols=c(Starters,Finishers))%>%
  select(ymon,name,value)%>%
  ggplot(aes(x=ymon,y=value,group=name,color=name))+
  geom_point()+
  geom_smooth(method="lm",
              linewidth=0.5,
              se=F)

time <- winners%>%
  count(Time)%>%
  mutate(time=hms(Time))
  

library(hms)

df <- winners%>%
  select(Year,Nationality,Time)%>%
  mutate(time=lubridate::hms(Time)) %>%
  group_by(Nationality)%>%
  mutate(mean=mean(Time),
          sd=sd(Time),
          max=max(Time),
          min=min(Time))%>%
  filter(!is.na(sd))
df

# Create multiple plots using facet_wrap()
ggplot(df, aes(x = Year, y = time)) +
  geom_point() +
  geom_errorbar(aes(ymin = mean - sd, ymax = mean + sd), color = "grey80") +
  scale_color_gradient(low = "blue", high = "red") +
  geom_smooth(method = "lm") +
  #scale_y_time()+
  facet_wrap(~Nationality,scales = "free_y")+
  theme(axis.text.y = element_blank())

london_marathon%>%
  pivot_longer(cols=c(Applicants,Accepted))%>%
  select(Year,name,value) %>%
   ggplot(aes(x=Year,y=value,group=name,color=name))+
  geom_point()+
  geom_smooth(method="lm",
              linewidth=0.5,
              se=F)

london_marathon%>%
  filter(!Year==2020)%>%
  select(Year,Applicants,Accepted)%>%
   ggplot(aes(x=Year))+
   geom_point(aes(y=Applicants))+
   geom_point(aes(y=Accepted))+
   geom_segment(aes(xend=Year,y=Accepted,yend=Applicants))

winners%>%
  group_by(Nationality)%>%
  mutate(n=n())%>%
  arrange(-n)%>%
  filter(Nationality%in%c("United Kingdom","Ireland","Kenya"))%>%
  ggplot(aes(x=Nationality,y=n))+
  geom_point()

london_marathon%>%
  filter(!is.na(Raised))%>%
  select(Year,Accepted,Raised)%>%
  inner_join(winners%>%count(Year,Nationality),by="Year")%>%
  arrange(Year)%>%
  mutate(Nationality=as.factor(Nationality))%>%
  filter(Nationality%in%c("Kenya","United Kingdom","United States"))
  ggplot(aes(Accepted,Raised,group=Nationality,color=Nationality))+
  geom_point()+
  geom_line()
  facet_wrap(~Nationality)

library(sysfonts)
sysfonts::font_add_google("Chelsea Market","Chelsea Market")
library(showtext)
showtext::showtext_auto()

london_marathon%>%
  filter(!is.na(Raised))%>%
  select(Year,Accepted,Raised)%>%
  inner_join(winners%>%count(Year,Nationality),by="Year")%>%
  arrange(Year)%>%
  mutate(Nationality=as.factor(Nationality))%>%
  filter(Nationality%in%c("Kenya","United Kingdom","United States"))%>%
  mutate(Accepted=scale(Accepted,
                        center = F, scale = TRUE),
         Raised=scale(Raised,
                      center = F, scale = TRUE)
         ) %>%
  # pivot_longer(cols = c("Accepted","Raised"))%>% #count(Year)
  ggplot(aes(x=Year)
             #group=name,
             #color=name,fill=name)
         )+
  geom_point(aes(y=Accepted),
             shape=21,stroke=0.5,
             size=2,
             color="white",
             fill="#910C00",
             key_glyph = draw_key_rect)+
    geom_point(aes(y=Raised),
             shape=21,stroke=0.5,
             size=2,
             fill="#00668F",
             color="white",
             key_glyph = draw_key_rect)+
  geom_line(aes(y=Accepted,color="Accepted"),
            linewidth=1,
            key_glyph = draw_key_rect)+
    geom_line(aes(y=Raised,color="Raised"),
              linewidth=1,
            key_glyph = draw_key_rect)+
  geom_segment(aes(xend=Year,y=Accepted,yend=Raised),
               color="grey80")+
  facet_wrap(~Nationality) +
  labs(title="Amount raised for charity based on acceptance",
       subtitle="scaled by the standard deviations without centering",
       caption="DataSource: #TidyTuesday Week 17 London Marathon\n#30DayChartChallenge Day 26 uncertanties: local change | DataViz: Federica Gazzelloni",
       color="")+
  scale_x_continuous(breaks = c(2007,2010,2014,2017))+
  scale_colour_manual("", 
                      breaks = c("Accepted", "Raised"),
                      values = c("#910C00", "#00668F")) +
  guides(fill="none")+
  ggthemes::theme_stata(base_family = "Chelsea Market",
                        scheme="s1rcolor")+
  theme(text=element_text(size=30),
        strip.background = element_rect(color="#910C00",fill="#910C00"),
        plot.caption = element_text(hjust = 0.5, size=30, lineheight = 0.5),
        plot.title = element_text(size=60),
        plot.subtitle = element_text(size=40),
        axis.title.y = element_blank())

showtext::showtext_auto(enable = T)
ggsave("w17_LM.png",
       dpi=320,
       width = 7,height = 5,
       bg="black")