#' Read file with FARS data
#'
#' This function reads data from .csv file, stored on disk, from the \strong{US
#' National Highway Traffic Safety Administration's} \emph{Fatality Analysis
#' Reporting System} (FARS), which is a nationwide census, providing the
#' American public yearly data, regarding fatal injuries suffered in motor
#' vehicle traffic crashes.
#'
#' @details For more information, see:
#' \itemize{
#' \item{\url{https://www.nhtsa.gov/research-data/fatality-analysis-reporting-system-fars}}
#' \item{\url{https://en.wikipedia.org/wiki/Fatality_Analysis_Reporting_System}}
#' }
#' @importFrom readr read_csv
#' @importFrom dplyr tbl_df
#'
#' @param filename A character string with the name of the file to read, see
#' notes.
#'
#' @return A data frame with data readed from the csv file, or an error if the
#' file does not exists.
#'
#' @note To generate file name use: \code{\link{make_filename}}
#' @seealso \link{make_filename}
#' @export
fars_read <- function(filename) {
if(!file.exists(filename))
stop("file '", filename, "' does not exist")
data <- suppressMessages({
readr::read_csv(filename, progress = FALSE)
})
dplyr::tbl_df(data)
}
#' Make data file name
#'
#' Make .csv data file name related to the given \code{year}
#' The function does not check if the file is available.
#'
#' @param year A string or an integer with the input \code{year}
#'
#' @return This function returns a string with the data file name for a given
#' year, and the file path within the package.
#'
#' @seealso \link{fars_read}
#' @export
make_filename <- function(year) {
year <- as.integer(year)
system.file("extdata",
sprintf("accident_%d.csv.bz2", year),
package = "fars",
mustWork = TRUE)
}
#' Read FARS years
#'
#' Ancillary function used by \code{fars_summarize_years}
#' @param years A vector with a list of years
#'
#' @importFrom dplyr mutate_
#' @importFrom dplyr select_
#' @importFrom magrittr "%>%"
#
#' @return A data.frame including entries in data by month, or NULL if the
#' \code{year} is not valid
#'
#' @seealso \link{fars_read}
#' @seealso \link{make_filename}
#' @seealso \link{fars_summarize_years}
#' @export
fars_read_years <- function(years) {
lapply(years, function(year) {
file <- make_filename(year)
tryCatch({
dat <- fars_read(file)
dplyr::mutate_(dat, year = "YEAR") %>%
dplyr::select_("MONTH", "year")
}, error = function(e) {
warning("invalid year: ", year)
return(NULL)
})
})
}
#' Summarize FARS data by years
#'
#' This function summarizes yearly accidents data, by month
#' @param years A vector with a list of years to summarize by.
#'
#' @return A data.frame with number of accidents by years summarized by month
#' @importFrom dplyr bind_rows
#' @importFrom dplyr group_by_
#' @importFrom dplyr summarize_
#' @importFrom tidyr spread_
#' @importFrom magrittr "%>%"
#' @seealso \link{fars_read_years}
#' @export
fars_summarize_years <- function(years) {
dat_list <- fars_read_years(years)
dplyr::bind_rows(dat_list) %>%
dplyr::group_by_("year", "MONTH") %>%
dplyr::summarize_(n = "n()") %>%
tidyr::spread_("year", "n")
}
#' Display accidents map by state and year
#'
#' Displays a plot with a state map including the accidents location by year
#' If the \code{state.num} is invalid the function shows an error
#' @param state.num An Integer with the State Code
#' \tabular{cc}{
#' \strong{State Code} \tab \strong{State Name} \cr
#' 01 \tab Alabama \cr
#' 02 \tab Alaska \cr
#' 04 \tab Arizona \cr
#' 05 \tab Arkansas \cr
#' 06 \tab California \cr
#' 08 \tab Colorado \cr
#' 09 \tab Connecticut \cr
#' 10 \tab Delaware \cr
#' 11 \tab District of Columbia \cr
#' 12 \tab Florida \cr
#' 13 \tab Georgia \cr
#' 15 \tab Hawaii \cr
#' 16 \tab Idaho \cr
#' 17 \tab Illinois \cr
#' 18 \tab Indiana \cr
#' 19 \tab Iowa \cr
#' 20 \tab Kansas \cr
#' 21 \tab Kentucky \cr
#' 22 \tab Louisiana \cr
#' 23 \tab Maine \cr
#' 24 \tab Maryland \cr
#' 25 \tab Massachusetts \cr
#' 26 \tab Michigan \cr
#' 27 \tab Minnesota \cr
#' 28 \tab Mississippi \cr
#' 29 \tab Missouri \cr
#' 30 \tab Montana \cr
#' 31 \tab Nebraska \cr
#' 32 \tab Nevada \cr
#' 33 \tab New Hampshire \cr
#' 34 \tab New Jersey \cr
#' 35 \tab New Mexico \cr
#' 36 \tab New York \cr
#' 37 \tab North Carolina \cr
#' 38 \tab North Dakota \cr
#' 39 \tab Ohio \cr
#' 40 \tab Oklahoma \cr
#' 41 \tab Oregon \cr
#' 42 \tab Pennsylvania \cr
#' 43 \tab Puerto Rico \cr
#' 44 \tab Rhode Island \cr
#' 45 \tab South Carolina \cr
#' 46 \tab South Dakota \cr
#' 47 \tab Tennessee \cr
#' 48 \tab Texas \cr
#' 49 \tab Utah \cr
#' 50 \tab Vermont \cr
#' 51 \tab Virginia \cr
#' 52 \tab Virgin Islands \cr
#' 53 \tab Washington \cr
#' 54 \tab West Virginia \cr
#' 55 \tab Wisconsin \cr
#' 56 \tab Wyoming
#' }
#' @param year A string, or an integer, with the input \code{year}
#'
#' @importFrom maps map
#' @importFrom dplyr filter_
#' @importFrom graphics points
#' @return None
#' @seealso \link{fars_read}
#' @seealso \link{make_filename}
#' @references 2014 FARS/NASS GES Coding and Validation Manual
#' @export
fars_map_state <- function(state.num, year) {
filename <- make_filename(year)
data <- fars_read(filename)
state.num <- as.integer(state.num)
if(!(state.num %in% unique(data$STATE))) {
stop("invalid STATE number: ", state.num)
}
data.sub <- dplyr::filter_(data, .dots = paste0("STATE==", state.num))
if(nrow(data.sub) == 0L) {
message("no accidents to plot")
return(invisible(NULL))
}
is.na(data.sub$LONGITUD) <- data.sub$LONGITUD > 900
is.na(data.sub$LATITUDE) <- data.sub$LATITUDE > 90
with(data.sub, {
maps::map("state", ylim = range(LATITUDE, na.rm = TRUE),
xlim = range(LONGITUD, na.rm = TRUE))
graphics::points(LONGITUD, LATITUDE, pch = 46)
})
}
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