In haliyan/fars.functions: Process, Summarize, and Map FARS Data

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

library(fars.functions)
library(dplyr)
library(knitr)

fars.functions Package Overview

This package handles FARS (Fatality Analysis Reporting System) data. It contains several functions which can read in, summarize, and map FARS data.

The make_filename function creates a file name of the correct format for a specific year. The fars_read function can then be used to read in the FARS data corresponding to that file name. If a file name in the correct format is known, it can be directly inputted into fars_read.

For example, the following output can be obtained either via running make_filename("2014") %>% fars_read() %>% head(5) or fars_read("accident_2014.csv.bz2") %>% head(5).

make_filename("2014") %>% 
  fars_read() %>% 
  head(5)

The fars_read_years function and the fars_summarize_years function read in accident data from a list of years and summarize it, respectively.

fars_read_years(c("2013","2014")) %>% 
  lapply(head)

fars_summarize_years(c("2013","2014"))

Finally, the fars_map_state function creates a map of accident locations in a specified state in a specified year. For example, the following code generates a map of the accident locations in state 1 (Alabama) in 2015.

fars_map_state(1,2015)

Note that the fars_map_state function requires that a state number be inputted to produce the map.

A table of state numbers and names is shown below:

addtls<-c("American Samoa", "Canal Zone", "District of Columbia", "Guam", "Puerto Rico", "Virgin Islands")
state.name<-c(state.name, addtls) %>% 
  sort() %>% 
  replace(c(51,52), .[c(52,51)])



state.name<-data.frame(StateNumber = 1:56, StateName = state.name)
kable(state.name)

As shown above, some "state numbers" actually correspond to international territories of the US. Supplying these state numbers to the fars_map_state function will produce an invalid state number error. A table of these international territories and their numbers is shown below:

state.name %>% 
  filter(StateName %in% addtls & StateName != "District of Columbia") %>%
  kable(.)

There is also a state number assigned to the District of Columbia although it is not technically a state. This number will not generate an error if it is supplied to fars_map_state; as long as accident data is available for the given year, a map of DC's accidents will be printed.

Supplying the state numbers for Alaska and Hawaii will result in an error as these states fall out of bounds (since they aren't part of the contiguous United States).

Note on FARS Data

This package includes 3 files containing raw FARS data from the years 2013, 2014, and 2015.

FARS 2013 Data

accident_2013.csv.bz2 A tibble with 30,202 rows and 50 columns.

FARS 2014 Data

accident_2014.csv.bz2 A tibble with 30,056 rows and 50 columns.

FARS 2014 Data

accident_2015.csv.bz2 A tibble with 32,166 rows and 52 columns.

The FARS data from 2013 and 2014 contain the same columns:

sapply(fars_read("accident_2013.csv.bz2"), class) %>% 
  as.data.frame() %>% 
  kable(col.names="Class")

The FARS data from 2015 does not contain the ROAD_FNC column from the 2013 and 2014 data. It also contains 3 additional columns:

sapply(fars_read("accident_2015.csv.bz2"), class) %>% 
  as.data.frame() %>% 
  slice(c(19,20,21)) %>%
  kable(col.names = "Class")

Data are from the US National Highway Traffic Safety Administration's Fatality Analysis Reporting System (FARS).

haliyan/fars.functions documentation built on May 9, 2022, 8:30 p.m.