In AlphaIgor/Test: Test Package

knitr::opts_chunk$set(echo = TRUE)

Introduction

This is an R Markdown document. Which explin in detail about the Accident data example package. This package contain some data from the US National Highway Traffic Safety Administration's Fatality Analysis Reporting System https://www.nhtsa.gov/ and some functions for extrapolating and summarizing the data.

Functions

This package contain five functions which will be explained above.

Create File name function

Returns a character vector containing a formatted combination of the year of the data, which is needed, and the full filename.

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

Import Data function

Takes a character vector, containing file name or path and load it.

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)
}

Read year function

Loads specified data about year and month.

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 year Function

Return the number of observations per month for a given year.

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)
}

Plot State map Function

Function for plotting an states accidentes map for given a state & year

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)
  })
}