R/fars_functions.R

#' Reads FARS (Fatality Analysis Reporting System) data from cvs file.
#'
#' @export
#' @import readr
#' @import dplyr
#'
#' @param filename A string. Path to cvs data file.
#'
#' @section Warning:
#' Function will stop if provided file not found
#'
#' @return Loaded FARS data as \code{\link[dplyr]{tbl_df}}
#'
#' @examples
#' \dontrun{fars_read("accident_2014.csv.bz2")}
fars_read <- function(filename) {
        if(!file.exists(filename))
                stop("file '", filename, "' does not exist")
        data <- suppressMessages({
                readr::read_csv(filename, progress = FALSE, quote = "")
        })
        dplyr::tbl_df(data)
}

#' Genarates archive file name based on year value
#'
#' @export
#'
#' @param year A number.
#'
#' @return generated archive file as string
#'
#' @examples
#' \dontrun{make_filename("2011")}
#' \dontrun{make_filename(2011)}
make_filename <- function(year) {
        year <- as.integer(year)
        sprintf("accident_%d.csv.bz2", year)
}

#' Read FARS (Fatality Analysis Reporting System) data for years
#'
#' @export
#' @import dplyr
#'
#' @param years A vector of years values (numbers)
#'
#' @section Warning:
#' Function will skip year if file with data for year does not exists
#'
#' @return readed FARS data as \code{\link[dplyr]{tbl_df}}
#'
#' @examples
#' \dontrun{fars_read_years(c(2013:2015))}
#' \dontrun{fars_read_years(c(2013,2015))}
fars_read_years <- function(years) {
        lapply(years, function(year) {
                MONTH <- NULL
                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 accidents from FARS data by year and month
#'
#' @export
#' @import dplyr
#'
#' @param years A vector of years values (numbers) to summarize
#'
#' @section Warning:
#' Function will skip year if file with data for year does not exists
#'
#' @return Summarized informaion about accidents as \code{\link[dplyr]{tbl_df}}.
#'
#' @examples
#' \dontrun{fars_summarize_years(c(2001:2011))}
#' \dontrun{fars_summarize_years(c("2004, 2008"))}
fars_summarize_years <- function(years) {
        year <- NULL
        MONTH <- NULL
        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 state locations by year
#'
#' @export
#' @import dplyr
#' @import graphics
#' @import maps
#'
#' @param state.num US state index (string)
#' @param year A year value (number)
#'
#' @section Warning:
#' Function will skip year if file with data for year does not exists
#'
#' Function will stop if invalid state provided
#'
#' @return this function returns a US state map with dots representing the
#' fatalities in a given year for a FARS file
#'
fars_map_state <- function(state.num, year) {
  STATE <- MONTH <-  NULL
  LATITUDE <- LONGITUD <- NULL
  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)
  })
}
dratushnyy/rdrfars documentation built on May 20, 2019, 4:09 p.m.