#' Map Traffic Accidents by State and Year
#'
#' A function that reads data from the US National Highway Traffic Safety
#' Administration's Fatality Analysis Reporting System and maps the number of fatalities
#' for one state for a particular year
#'
#' @title MapByState
#' @importFrom dplyr filter
#' @importFrom graphics points
#' @import maps
#' @param state.num State number as defined in the csv file - should be an integer
#' between 1 and 50
#' @param year Year to be queried for number of accidents - should be an integer
#' for the years 2013 through 2015
#' @details Will report an error if there is an invalid state number or if there are
#' no accidents in that state in the specified year or if multiple states or years
#' are chosen
#' @return A map of a state, with points notating accidents for that year
#' @examples
#' fars_map_state(12, 2015)
#' @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$STATE)))
stop("invalid STATE number: ", state.num)
data.sub <- dplyr::filter(data, STATE == state.num)
if(nrow(data.sub) == 0L) {
message("no accidents to plot")
return(invisible(NULL))
}
is.na(data.sub$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)
})
}
#' Summarize traffic fatalities by month and year
#'
#' A function that can summarize multiple years, by month. It takes the user input
#' of a year or multiple years and produces a table of traffic fatalities by month
#'
#' @title SummarizeByYears
#' @importFrom dplyr bind_rows group_by summarize
#' @importFrom tidyr spread
#' @param years User inputs the year needed - should be an integer
#' between 2013 and 2015
#' @return Returns a table with number of accidents, by month, in the
#' selected year
#' @examples
#' fars_summarize_years(2015)
#' @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)
}
#' Read data
#'
#' Takes the filename string and attempts to open the csv file as a data frame
#' Not user-facing
#'
#' @title ReadData
#' @importFrom readr read_csv
#' @importFrom dplyr tbl_df
#' @param filename Name of file to be input into the function. This is passed
#' from the make_filename function (and can have the .bz2 extension)
#' input should be a text string
#' @details will throw an error if the filename doesn't exist in the path
#' @return This function returns a data frame read from the input file
fars_read <- function(filename) {
filename <- system.file("extdata", filename, package = "FarsMap")
if(!file.exists(filename))
stop("file '", filename, "' does not exist")
data <- suppressMessages({
readr::read_csv(filename, progress = FALSE)
})
dplyr::tbl_df(data)
}
#' Creates a filename
#'
#' Take the year input by the user and creates a string to map to
#' the file to be read - for that year.
#' Not user-facing
#'
#' @title make_filename
#' @param year Parameter is passed from the fars_read_years function
#' input that is passed should be able to be converted to an integer
#' @return Creates a string for the filename
make_filename <- function(year) {
year <- as.integer(year)
sprintf("accident_%d.csv.bz2", year)
}
#' Gather data
#'
#' Compiles all of the months data for the year being selected by the user
#' Not user-facing
#'
#' @title SelectYearsFromData
#' @importFrom dplyr mutate select
#' @importFrom magrittr %>%
#' @param years Parameter is passed from the fars_summarize_years function - should be an integer
#' @details Will throw an error if the year being passed in not in the filenames available
#' @return Selects all of the months for the year being requested
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)
})
})
}
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