In ricrossi/qfars: The qfars Training Pack

The FARStraining package provides functions to query 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. The FARStraining package is - obviously - a training package, thus it merely is an exercise in building up the structure of an R package and you're not probably going to need it!...)

How to read the data

Data can be read using the "fars_read" function. This function takes as only argument a filename and first check if the inputted filename exists. If the file does not exist in current working directory an error message is given, otherwise a connection to the file is created.

To read the content of the "accident_2013.csv.bz2" file and to store its content into the acc2013 object:

acc2013 <- fars_read("accident_2013.csv.bz2")

We are probably interested in a specific year: the filename relative to a specified year is cntructed according to FARS standard naming conventions. The "make_filename" command takes as argument a four digit number indicating a year to show the complete filename for that year. For example, the full name for the year 2014 is obtained as follows:

make_filename(2014)

We can also read more than one file at once. Guess you want to assess how many accidents are registered for the years 2013 and 2015: we can use the "fars_read_years" command:

multi_years <- fars_read_years(list(2013, 2015))

Summarizing and displaying data by months and years

The obtained "multi_years" object is a list of dataframes, one for yeach specified year. This function is internally used by the more useful summarize function, used to return a tabular display for the accidents occurred in a specific year, or a series of years, chopped down for each month.

To retrieve the summary for 2013 you can do:

summary2013 <- fars_summarize_years(2013)

To retrieve the summary for more than a single year the list of years must be used as the function's argument:

summary2013_2015 <- fars_summarize_years(list(2013, 2015))

Further geographical visualization of data

Data in the FARS database can also be visualized in their spatial distribution using maps overlays. the "fars_map_state" function exactly does this. Every State of the United States of America is identified by its numerical code. To print a density map for accidents in 2014 in California (State #06), the command is as follows:

fars_map_state(06, 2014)

Figures

The figure sizes have been customised so that you can easily put two images side-by-side.

plot(1:10)
plot(10:1)

You can enable figure captions by fig_caption: yes in YAML:

output:
  rmarkdown::html_vignette:
    fig_caption: yes

Then you can use the chunk option fig.cap = "Your figure caption." in knitr.

ricrossi/qfars documentation built on May 29, 2019, 1:19 p.m.