#' read a csv text file
#'
#' This function reads a csv format file and stores in dataframe tbl_df. For this task uses package "readr" which allows to directly read comressed files
#'
#' @param filename A character chain containing the name of the file you want to read
#'
#' @return This function returns a dataframe tbl_df
#'
#' @examples
#'
#' ## fars_read("accident_2013.csv.bz2")
#'
#' fars_read( system.file("extdata", "accident_2014.csv.bz2", package = "farsUSA") )
#'
#' @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)
}
#' Creates a file name
#'
#' This function creates the apropriate name of the the file corresponding to accident data for the year 'year'
#'
#' @param year An integer indicating the year for filename creation
#'
#' @return This function returns a character variable containing a file name
#'
#' @examples
#' make_filename(2013)
#'
#' @export
make_filename <- function(year) {
year <- as.integer(year)
system.file("extdata",
sprintf("accident_%d.csv.bz2", year),
package = "farsUSA")
}
#' Reads several csv text files
#'
#' This function reads several csv format files and stores month and year into a list of dataframes tbl_df,
#' containing month and year of the accidents stored, one tbl_df for each csv file.
#'
#' @param years A list containing the years to estract information
#'
#' @return This function returns a list of tbl_df from all years in "years" with month and year information
#'
#' @examples
#' fars_read_years(list(2013,2014))
#'
#' @importFrom magrittr "%>%"
#'
#' @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)
})
})
}
#' Summarizes accidents by year and month
#'
#' This function summarizes the number of accidents occurred each month for a list of years
#'
#' @param years A list of years
#'
#' @return This function returns a tbl_df containing number of accidents by month
#' for the years included in the list parsed as parameter
#'
#' @examples
#' fars_summarize_years(list(2014,2015))
#'
#' @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)
}
#' Print a map of crash over year and state of U.S.
#'
#' This function prints a map with the position of every crash occurred over the state 'state.num' and the year 'year'
#'
#' @param state.num integer with the number of desired state, ranging 1:56
#' @param year An integert with the desired year
#'
#' @return This function returns a map
#'
#' @examples
#' 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)
})
}
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