Creates a graph of bike crashes by month, with September highlighted

september_crash_stats.R

library(pins)
library(sf)
library(tidyverse)
library(lubridate)
library(jsonlite)


board <- board_s3("vzpins", 
                  region = "us-east-1", 
                  access_key = "", 
                  secret_access_key = "")


crashes_all_dane <- pin_read(board = board, name = "crashes_all_dane")

crashes_all_dane |> 
  st_drop_geometry() |> 
  filter(bikeflag == "Y" & year < 2024) |> 
  group_by(month = month(date, label = T, abbr = T)) |> 
  summarise(n = n()) |> 
  ggplot(aes(month, n)) +
  geom_col() +
  xlab(element_blank()) +
  ylab("Number of reported crashes") +
  labs(title = "Drive carefully: September has the highest number of bike crashes in the year",
       subtitle =  "Police-reported motor vehicle crashes involving a bike rider in the City of Madison, 2017-2023",
       caption = "Data: Community Maps/TOPS Lab\nVisualization: Harald Kliems") +
  gghighlight::gghighlight(month == "Sep") +
  hrbrthemes::theme_ipsum() +
  theme(panel.grid.major.x = element_blank())