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README.md

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ozroaddeaths is a package that pulls data from the Australian Road Deaths Database, run by the Bureau of Infrastructure, Transport and Regional Economics (BITRE). This provides basic details of road transport crash fatalities in Australia as reported by the police each month to the State and Territory road safety authorities. The details provided in the database fall into two groups:

  1. The circumstances of the crash, for example, date, location, crash type

  2. Some details regarding the persons killed, for example, age, gender and road user group.

Installation

You can install ozroaddeaths from github with:

# install.packages("devtools")
devtools::install_github("ropenscilabs/ozroaddeaths")

This data is taken from the Australian Road Deaths Database, which provides basic details of road transport crash fatalities in Australia as reported by the police each month to the State and Territory road safety authorities, obtained from: https://data.gov.au/dataset/ds-dga-5b530fb8-526e-4fbf-b0f6-aa24e84e4277/details?q=crash

Details provided in the database fall into two groups:

  • the circumstances of the crash, for example, date, location, crash type

  • some details regarding the persons killed, for example, age, gender and road user group.

The fatality data is updated every month. The heavy vehicle flags (for articulated truck, heavy rigid truck and bus involvement) are only updated each quarter, and are current to within two months. Information for heavy rigid truck involvement in crashes earlier than 2004 is incomplete. There is no day of the month for the data, so we have imputed this as the first of the month.

Package Author’s Notes

Data was available at URL as at 13th December 2019. Data is imported into R and cleaned by removing redundant date columns and transforming into a tidy format.

Indemnity Statement:

The Bureau of Infrastructure, Transport and Regional Economics has taken due care in preparing this information. However, noting that data have been provided by third parties, the Commonwealth gives no warranty as to the accuracy, reliability, fitness for purpose, or otherwise of the information.

Copyright

© Commonwealth of Australia, 2017

This work is copyright and the data contained in this publication should not be reproduced or used in any form without acknowledgement.

Import data from the BITRE website into R

library(ozroaddeaths)
library(dplyr)
library(ggplot2)
library(lubridate)
library(ggridges)
crashes <- oz_road_fatal_crash() 
fatalities <- oz_road_fatalities()

Variables available

Crashes

knitr::kable(dplyr::as_data_frame(names(crashes)))
#> Warning: `as_data_frame()` is deprecated, use `as_tibble()` (but mind the new semantics).
#> This warning is displayed once per session.
value
crash_id
n_fatalities
month
year
weekday
time
state
crash_type
bus
heavy_rigid_truck
articulated_truck
speed_limit
date
date_time
knitr::kable(head(crashes))
crash_id n_fatalities month year weekday time state crash_type bus heavy_rigid_truck articulated_truck speed_limit date date_time
20193047 1 10 2019 Thursday 11:00:00 Qld Single No No No 100 2019-10-01 2019-10-01 11:00:00
20192202 1 10 2019 Thursday 21:06:00 Vic Pedestrian NA NA NA NA 2019-10-01 2019-10-01 21:06:00
20191179 1 10 2019 Wednesday 06:45:00 NSW Pedestrian No No No 50 2019-10-01 2019-10-01 06:45:00
20192073 1 10 2019 Wednesday 07:15:00 Vic Single NA NA NA NA 2019-10-01 2019-10-01 07:15:00
20193053 1 10 2019 Tuesday 15:00:00 Qld Multiple No Yes No 100 2019-10-01 2019-10-01 15:00:00
20192029 1 10 2019 Tuesday 12:03:00 Vic Multiple NA Yes NA 100 2019-10-01 2019-10-01 12:03:00

Fatalities

knitr::kable(dplyr::as_data_frame(names(fatalities)))
value
crash_id
month
year
weekday
time
state
crash_type
bus
heavy_rigid_truck
articulated_truck
speed_limit
road_user
gender
age
date
date_time
knitr::kable(head(fatalities))
crash_id month year weekday time state crash_type bus heavy_rigid_truck articulated_truck speed_limit road_user gender age date date_time
20193047 10 2019 Thursday 11:00:00 Qld Single No No No 100 Driver Male 25 2019-10-01 2019-10-01 11:00:00
20192202 10 2019 Thursday 21:06:00 Vic Pedestrian NA NA NA NA Pedestrian Female 64 2019-10-01 2019-10-01 21:06:00
20191179 10 2019 Wednesday 06:45:00 NSW Pedestrian No No No 50 Pedestrian Female 81 2019-10-01 2019-10-01 06:45:00
20192073 10 2019 Wednesday 07:15:00 Vic Single NA NA NA NA Passenger Male 25 2019-10-01 2019-10-01 07:15:00
20193053 10 2019 Tuesday 15:00:00 Qld Multiple No Yes No 100 Motorcycle rider Male 35 2019-10-01 2019-10-01 15:00:00
20191220 10 2019 Tuesday 06:40:00 NSW Multiple Yes No No 80 Motorcycle rider Male 28 2019-10-01 2019-10-01 06:40:00

Plot crashes by year

crash_plot <- ggplot(crashes,
                     aes(x = year,
                         fill = year)) +
  geom_line(stat = "count") +
  theme_minimal() +
  ggtitle("Annual number of fatal car accidents per year")

crash_plot

Plot crashes by year and state

crash_plot +
  scale_y_continuous(trans = "log2") +
  facet_wrap(~state) +
   ggtitle("Annual number of fatal car accidents per year and state",
           subtitle = "log2 scale" )

Fatalities by year

fatality_plot <- fatalities %>%
  mutate(year = lubridate::year(date_time)) %>%
  ggplot(aes(x =  year, 
             fill = year)) +
  geom_line(stat = "count") +
  theme_minimal() +
  ggtitle("Annual number of road fatalities")

fatality_plot

fatality_plot <- fatalities %>%
  filter(gender != "Unspecified") %>%
  mutate(year = lubridate::year(date_time)) %>%
  ggplot(aes(x = age, 
             fill = gender )) +
  geom_density() +
  facet_wrap(~gender) +
  theme_minimal() +
  ggtitle("Distribution of road fatalities by age 1989 to 2017")

fatality_plot
#> Warning: Removed 82 rows containing non-finite values (stat_density).

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Access data from Australian Road Deaths Database

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