Benutzung öffentlicher Verkehrsmittel nach Bundesländer (https://twitter.com/matschnetzer/status/1063423205401071618)

publictransport.r

#### Code was adapted from https://github.com/ryantimpe/ChartOfTheDay ###
#### H/T to @ryantimpe!

library(tidyverse)
library(rvest)
library(png)
library(msthemes)

df <- tibble(geo=as.factor(c("Wien","Vorarlberg","Salzburg","Steiermark","Niederösterreich","Tirol","Oberösterreich","Kärnten","Burgenland")),
             public=c(92,66,61,58,57,55,50,42,36),
             ticket=as.factor(c("1","1","1","1","2","1","2","1","2")),
             preis=c(365,378,1539,2285,NA,499,NA,2420,NA))

# Download png from https://www.onlinewebfonts.com/icon/10417
pic.raw <- readPNG("bus-and-train-silhouettes.png")

pic <- pic.raw[,,4] %>% 
  as.data.frame() %>% 
  mutate(y = n()-row_number()) %>% 
  gather(x, value, 1:(ncol(.)-1)) %>% 
  mutate(x = as.numeric(str_remove_all(x, "V"))) %>% 
  filter(value > 0) %>% 
  #Rescale to 50% of coords
  group_by(x = x %/% 2, y = y %/% 2) %>% 
  summarize(value = max(value)) %>% 
  ungroup()

pic2 <- pic %>% 
  mutate(cluster = kmeans(.[, c(1:2)], 100)$cluster)

data <- df %>% 
  mutate(plot = map(public, function(public){
    keep_k <- sample(1:100, public)
    return(pic2 %>% filter(cluster %in% keep_k))
  })) %>% 
  unnest(plot)

# Change order of facets by relevel geo
data$geo <- factor(data$geo, levels=df$geo[order(df$public)])

pub.labels <- df %>% 
  mutate(label_p = paste0(round(public), "%"))

ticket.labels <- df %>% 
  mutate(label_t = ifelse(!is.na(preis),paste0("Jahreskarte: ", preis," Euro"),paste0(" ")))

data %>% 
  ggplot(aes(x=x, y=y,fill=ticket)) +
  geom_raster() +
  ylim(10,220) + 
  scale_fill_manual(values = c("#2dd49c", "#ff4040"),
                    labels = c(" Bundesland  "," Strecke  "),
                    name = "Jahreskarte für ") +
  coord_fixed() +
  geom_text(data = pub.labels, aes(label = label_p), 
            x = 30, y = 20, size = 4, 
            color = "#00436b", fontface = "bold") +
  geom_text(data = ticket.labels, aes(label = label_t),
            x = 170, y = 17, size = 2.5) +
  facet_wrap(~geo, ncol = 3) +
  labs(title = "Wie stark wird öffentlicher Verkehr genutzt?",
       subtitle = "Anteil der Bevölkerung, der öffentliche Verkehrsmittel nutzt",
       caption = "Preise für 2018. Daten: VCÖ, Verkehrsverbunde. Grafik: @matschnetzer") +
  theme_ms() +
  theme(
    axis.text = element_blank(),
    axis.title = element_blank(),
    panel.grid = element_blank(),
    strip.background = element_rect(fill = "#00436b"),
    strip.text = element_text(color = "white", face = "bold", hjust = 0.5, size=10),
    panel.background = element_rect(fill = "ivory"),
    legend.position = "bottom"
    ) +
  ggsave("publictrans.png", height = 6,width = 6, dpi = 300)