In mmottahedi/coursera:

library(coursera)
library(dplyr)
library(maps)

This vignette gives a brief overview of the Coursera package functionality. The package contains a set of functions suited for analysis of data from Coursera - Fatality Analysis Reporting System. Coursera is a nationwide census providing NHTSA, Congress and the American public yearly data regarding fatal injuries suffered in motor vehicle traffic crashes. [1]

Package functions

There are three exported functions available to users:

• fars_read()
• fars_summarize_years()
• fars_map_state()

Further we give a short description with examples how to use the functions. For the purposes of these examples we will use data from Coursera, years 2013-2015, that can be found in the package directory under \extdata folder.

Read Coursera data files

The function fars_read() provides a way how to read data from a file path provided as an argument. It returns a tibble with loaded data:

filename <- system.file("extdata/accident_2013.csv.bz2", package = "coursera")
fars_read(filename)

Summarize number of accidents

The next function fars_summarize_years() takes a vector or list of years (numeric/integer values) as an argument and if the corresponding files with data are available, it returns a pivot table with number of accidents per year and month. The data files need to be located in the working directory.

setwd(system.file("extdata", package = "coursera"))
fars_summarize_years(2013:2015)

Plot accident locations

The last function available in the package, fars_map_state() takes a state index and year as arguments and returns a plot of the state with accident locations. The state indices need to correspond available indeces from the data set. Here are some examples:

setwd(system.file("extdata", package = "coursera"))
fars_map_state(45, 2015)

Note that again, the data file needs to be present in the working directory.

mmottahedi/coursera documentation built on May 23, 2019, 5:05 a.m.