# load packages
library(tidyverse)

Hello this is some text.

casualty_type = c("cat", "dog", "person")
casualty_age = seq(from = 20, to = 60, by = 20)
crashes = data.frame(casualty_type, casualty_age)
plot(crashes$casualty_age)

Subsetting.

crashes$casualty_type
crashes[[1]]
crashes[2,1]

crashes |>
  select(casualty_type)

crashes |> 
  filter(casualty_age > 35)

crashes |> 
  filter(casualty_age-20 > 35)

crashes |>
  ggplot() +
  geom_bar(aes(x = casualty_age, fill = casualty_type))

ac = stats19::get_stats19(year = 2020, type = "collision")
class(ac)
dim(ac)
ac_2021 = stats19::get_stats19(year = 2021, type = "collision")
nrow(ac)
nrow(ac_2021)
# # After googling "combine 2 data frames" let's try rbind
# ??combine
# ?rbind
ac = rbind(ac, ac_2021)
dim(ac)
ac_datetime = c(ac$datetime, ac_2021$datetime)
length(ac_datetime)
range(ac_datetime)

class(ac)
str(ac)
names(ac)
# aggregate this by day to show 
# how crash numbers varied over the year
ac_by_year = ac |>
  group_by(date) |>
  summarise(
    n_crashes = n()
  )
ac_by_year |>
  mutate(
    `N. crashes per year` = n_crashes,
    `Week average` = zoo::rollmean(n_crashes, 7, na.pad = TRUE),
    Date = date,
  ) |> 
  ggplot(aes(x = Date, y = `N. crashes per year`)) +
  geom_point(alpha = 0.1) +
  ylim(c(0, NA)) +
  # geom_smooth() +
  # weekly rolling average
  geom_line(aes(Date, `Week average`), colour = "red") +
  theme_minimal()

# Updated plot with title and legend...
ac_by_year |>
  mutate(
    `N. crashes per year` = n_crashes,
    `Week average` = zoo::rollmean(n_crashes, 7, na.pad = TRUE),
    Date = date,
  ) |> 
  ggplot(aes(x = Date, y = `N. crashes per year`)) +
  geom_point(alpha = 0.1) +
  ylim(c(0, NA)) +
  # geom_smooth() +
  # weekly rolling average
  geom_line(aes(Date, `Week average`, colour = "Week average")) +
  theme_minimal() +
  labs(
    colour = "Legend"
  ) +
  scale_colour_manual(values = c("Week average" = "red")) +
  ggtitle("Collions/day, 2020 to 2021") +
  theme(
    legend.position = "bottom"
  )

1 Python example

casualty_type_py = ["a", "B", "c"]
casualty_type_py