In bzunar/trafficSafety: Analyse data from the US 'Fatality Analysis Reporting System'

wd <- dirname(system.file("extdata", "accident_2013.csv.bz2", package = "trafficSafety"))

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

knitr::opts_knit$set(root.dir = wd)

Package 'trafficSafety' was primarily created for the Coursera's 'Building R Packages' course. It contains a number of functions that load, summarise, and visualise data from the US National Highway Traffic Safety Administration's 'Fatality Analysis Reporting System', which is a nationwide census providing the American public yearly data regarding fatal injuries suffered in motor vehicle traffic crashes.

Loading the Dataset

The package comes with three files that list fatalities throughout the years 2013-2015. They can be loaded with function fars_read which outputs a tibble. For the convenience, filenames can also be generated through a helper function make_filename.

library(trafficSafety)

# external data bundled with the package
y13 <- system.file("extdata", "accident_2013.csv.bz2", package = "trafficSafety")
y14 <- system.file("extdata", "accident_2014.csv.bz2", package = "trafficSafety")
y15 <- system.file("extdata", "accident_2015.csv.bz2", package = "trafficSafety")

# load the data
fars13 <- fars_read(y13)
head(fars13, 3)

# helper function
make_filename(2013)
system.file("extdata", make_filename(2013), package = "trafficSafety")

Several years worth of data can also be imported using the function fars_read_years which will extract only months and year, saving data from each file as a separate element of the list.

fars_read_years(c(2013, 2014))

Summarise Number of Accidents

One can summarise the number of accidents by using fars_summarize_years function.

fars_summarize_years(c(2013, 2014, 2015))

Visualise Loaction of the Accidents

Finally, one can visualise where the accidents occured for a specific state in the specified year using the fars_map_state function.

fars_map_state(1, 2014)

sessionInfo()

bzunar/trafficSafety documentation built on June 5, 2019, 7:57 a.m.