R/far_functions.R

In llafuenteDECIDE/FAR: Accidents data and analysis tool

#' fars_read function
#' read a csv file given a route to the file.
#'
#' @param filename an string indicating the complete route or relative route (from the working directory) to the file. The file can be compressed.
#'
#' @return  a table_df that contents the data of csv. If the file doesn?t exist returns an error.
#'
#' @importFrom readr read_csv
#' @importFrom dplyr tbl_df
#'
#' @examples
#'  \dontrun{
#' fars_read (accident_2013.csv.bz2)
#' fars_read (accident_2014.csv.bz2)
#' }
#'
#' @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_filename function
#'  given a year, makes the complete name of the "accident" filename. It has the form "accident_year.csv.bz2"
#'  where year is substituted by /code{"year"}
#'
#' @param year an integer or string indicating the year to which we want to obtain the filename
#'
#' @return  an string that represents the complete name of the filename.
#'
#' @examples
#' \dontrun{
#'  make_filename(2013)
#'  make_filename(2014)
#' }

make_filename <- function(year) {
  year <- as.integer(year)
  sprintf("accident_%d.csv.bz2", year)
}

#' fars_read_years fuction
#' given a list of years,  extracts for each  year the MONTH column
#'  and a year column of the accident data of that year.

#' @param years a vector or list of integers representing the years

#' @return a list of dataframes of the same length of /code {"year"}.
#' Each element of the list refers to a year of the list and si a dataframe that
#' includes the MONTH column of the accident data of the year and a column with the year.
#' If there is no data of the year the element of the list will be null.
#'
#' @importFrom dplyr mutate
#' @importFrom dplyr select
#' @importFrom magrittr "%>%"
#'
#' @examples
#' \dontrun{
#' fars_read_years(c(2013, 2014))
#' }
#'
#' @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)
    })
  })
}

#' fars_summarize_years function
#' given a list of years gives the number of accidents by month of each of the years
#'
#' @param years a vector or list of ints or strings  representing years
#'
#' @return a table which variables are the years on list and an unique
#' file that indicates the number of accidents by month of this year
#'
#' @examples
#' \dontrun{
#' fars_summarize_years(c(2013, 2014, 2015))
#'}
#'
#' @importFrom dplyr bind_rows
#' @importFrom dplyr group_by
#' @importFrom dplyr summarize
#' @importFrom tidyr spread
#' @importFrom dplyr n
#'
#' @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)
}

#' fars_map_state function
#'
#' given an state and a year plots the coordenates of the accidents in
#' this state an year
#'
#' @param state.num the number of the state for which we want
#' to draw the accident's coordinates.
#' @param year an integer indicating the year for which we want to draw the accident?s coordinates
#'
#' @return a plot with all accident's coordinates drawed of the /code{state.num}
#' and /code{year} or null if the /code{state.num} does not exist
#'
#' @importFrom dplyr filter
#' @importFrom maps  map
#' @importFrom graphics points
#'
#' @examples
#'\dontrun{
#'  fars_map_state(1,2013)
#'}
#' @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)
  })
}