knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(mtrostR)
Database on fatal injuries suffered in motor vehicle traffic crashes is produced by US National Highway Traffic Safety Administration. Data is provided on a yearly frequency.
Using functions from the mtrostR
package, one can import data from files disseminated by Administration, summarise it and plot fatal injuries by State on a map.
mtrostR
Package mtrostR
is only available on GitHub. It can be installed like:
# install.packages("devtools") devtools::install_github("Struya/mtrostR")
Using this package function make_filename
one can construct the filename string to be used for importing the dataset into R session. The user must only provide a number for a year (i.e. 2013) to be used by the function. Please note that in the package only dataset from 2013 to 2015 are included.
# choose a value for a year my_year <- 2013 # construct filename to be used for importing dataset into R my_filename <- make_filename(year = my_year)
Importing fatalities dataset is simple. Using fars_read
with filename string one can import a dataset for a chosen year.
# import datast into R using filename string my_df <- fars_read(my_filename) my_df
There is also a function fars_read_years
that imports datasets for all years at once but returns only two columns, month and year. The user only has to provide a vector of years.
# vector of years my_years <- 2013:2015 # import all datasets into R. my_list <- fars_read_years(my_years) my_list
Using fars_read_years
to import only columns months and years might be useful, however there is a function that calls it only to import datasets in order to summarise it by year and month. It is named fars_summarise_years
.
# vector of years my_years <- 2013:2015 # count number of fatalities by month and year count_by_year_and_month_df <- fars_summarize_years(my_years) count_by_year_and_month_df
Plotting fatalities on a map is a nice way of getting a feel for spatial distribution of fatalities accross United States. By providing the State ID number and a year, the function fars_map_state
will plot spatial distribution on a map of chosen State.
# choice of State my_state_id <- 1 my_year <- 2015 my_state_id_to_compare <- 10 # plot spatial distribution for a year fars_map_state(my_state_id, my_year) fars_map_state(my_state_id_to_compare, my_year)
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