README.md
In a-antonopoulou/TestAssignment: Fatality Analysis Reporting (FAR) data functions

title: "TestAssignment" author: "Nancy" date: "8/14/2020" output: md_document

```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE, message=FALSE, warning=FALSE )


### TestAssignment Package - Overview

This is an R package which created as part of the last assignment for the coursera lesson "Building an R Package" which is a part of the "Mastering Software Development in R Specialization". 

This package includes the following functions:

+ fars_read
+ make_filename
+ fars_read_years
+ fars_summarize_years
+ fars_map_state
\
\

##### **Input Files**: 

As input for this assignment we are using data from the US National Highway Traffic Safety Administration's Fatality Analysis Reporting System, which is a nationwide census providing the American public yearly data regarding fatal injuries suffered in motor vehicle traffic crashes. 

A sample of the data are:

```{r sample_of_source_data, echo=FALSE, results=TRUE}

setwd("~/data")

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)
}

source <- fars_read("accident_2013.csv")

head(source)

\

Final Output:

The final output is given through the execution of the "fars_map_state". This function returns a plot of the incidences for the specified year and state. Specifically, it will return a map of the state specified including the incidences as dots.

Below you can find an example of the incidences for state 45 and year 2013:

```{r sample_of_output, echo=FALSE, results=TRUE}

setwd("~/data")

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

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(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(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) }) }

fars_map_state(45,2013)

```

I am working in Windows environment so Travis could not proceed with the testing, this is why I tested it also with appveyor which is the most suitable option for this operating system.