The data used in this assignment are from Numbersense, Kaiser Fung, McGraw Hill, 2013
Loading the data
flights_data<- data.frame(
Cities= c("Los Angeles", "Phoenix", "San Diego", "San Francisco", "Seattle"),
Alaska_on_time = c(497, 221, 212, 503, 1841),
Alaska_delayed= c(62, 12, 20, 102, 305),
Am_west_on_time = c(694, 4840, 383, 320, 201),
Am_west_delayed = c(117,415, 65, 129, 61)
)
data## function (..., list = character(), package = NULL, lib.loc = NULL,
## verbose = getOption("verbose"), envir = .GlobalEnv, overwrite = TRUE)
## {
## fileExt <- function(x) {
## db <- grepl("\\.[^.]+\\.(gz|bz2|xz)$", x)
## ans <- sub(".*\\.", "", x)
## ans[db] <- sub(".*\\.([^.]+\\.)(gz|bz2|xz)$", "\\1\\2",
## x[db])
## ans
## }
## my_read_table <- function(...) {
## lcc <- Sys.getlocale("LC_COLLATE")
## on.exit(Sys.setlocale("LC_COLLATE", lcc))
## Sys.setlocale("LC_COLLATE", "C")
## read.table(...)
## }
## stopifnot(is.character(list))
## names <- c(as.character(substitute(list(...))[-1L]), list)
## if (!is.null(package)) {
## if (!is.character(package))
## stop("'package' must be a character vector or NULL")
## }
## paths <- find.package(package, lib.loc, verbose = verbose)
## if (is.null(lib.loc))
## paths <- c(path.package(package, TRUE), if (!length(package)) getwd(),
## paths)
## paths <- unique(normalizePath(paths[file.exists(paths)]))
## paths <- paths[dir.exists(file.path(paths, "data"))]
## dataExts <- tools:::.make_file_exts("data")
## if (length(names) == 0L) {
## db <- matrix(character(), nrow = 0L, ncol = 4L)
## for (path in paths) {
## entries <- NULL
## packageName <- if (file_test("-f", file.path(path,
## "DESCRIPTION")))
## basename(path)
## else "."
## if (file_test("-f", INDEX <- file.path(path, "Meta",
## "data.rds"))) {
## entries <- readRDS(INDEX)
## }
## else {
## dataDir <- file.path(path, "data")
## entries <- tools::list_files_with_type(dataDir,
## "data")
## if (length(entries)) {
## entries <- unique(tools::file_path_sans_ext(basename(entries)))
## entries <- cbind(entries, "")
## }
## }
## if (NROW(entries)) {
## if (is.matrix(entries) && ncol(entries) == 2L)
## db <- rbind(db, cbind(packageName, dirname(path),
## entries))
## else warning(gettextf("data index for package %s is invalid and will be ignored",
## sQuote(packageName)), domain = NA, call. = FALSE)
## }
## }
## colnames(db) <- c("Package", "LibPath", "Item", "Title")
## footer <- if (missing(package))
## paste0("Use ", sQuote(paste("data(package =", ".packages(all.available = TRUE))")),
## "\n", "to list the data sets in all *available* packages.")
## else NULL
## y <- list(title = "Data sets", header = NULL, results = db,
## footer = footer)
## class(y) <- "packageIQR"
## return(y)
## }
## paths <- file.path(paths, "data")
## for (name in names) {
## found <- FALSE
## for (p in paths) {
## tmp_env <- if (overwrite)
## envir
## else new.env()
## if (file_test("-f", file.path(p, "Rdata.rds"))) {
## rds <- readRDS(file.path(p, "Rdata.rds"))
## if (name %in% names(rds)) {
## found <- TRUE
## if (verbose)
## message(sprintf("name=%s:\t found in Rdata.rds",
## name), domain = NA)
## thispkg <- sub(".*/([^/]*)/data$", "\\1", p)
## thispkg <- sub("_.*$", "", thispkg)
## thispkg <- paste0("package:", thispkg)
## objs <- rds[[name]]
## lazyLoad(file.path(p, "Rdata"), envir = tmp_env,
## filter = function(x) x %in% objs)
## break
## }
## else if (verbose)
## message(sprintf("name=%s:\t NOT found in names() of Rdata.rds, i.e.,\n\t%s\n",
## name, paste(names(rds), collapse = ",")),
## domain = NA)
## }
## if (file_test("-f", file.path(p, "Rdata.zip"))) {
## warning("zipped data found for package ", sQuote(basename(dirname(p))),
## ".\nThat is defunct, so please re-install the package.",
## domain = NA)
## if (file_test("-f", fp <- file.path(p, "filelist")))
## files <- file.path(p, scan(fp, what = "", quiet = TRUE))
## else {
## warning(gettextf("file 'filelist' is missing for directory %s",
## sQuote(p)), domain = NA)
## next
## }
## }
## else {
## files <- list.files(p, full.names = TRUE)
## }
## files <- files[grep(name, files, fixed = TRUE)]
## if (length(files) > 1L) {
## o <- match(fileExt(files), dataExts, nomatch = 100L)
## paths0 <- dirname(files)
## paths0 <- factor(paths0, levels = unique(paths0))
## files <- files[order(paths0, o)]
## }
## if (length(files)) {
## for (file in files) {
## if (verbose)
## message("name=", name, ":\t file= ...", .Platform$file.sep,
## basename(file), "::\t", appendLF = FALSE,
## domain = NA)
## ext <- fileExt(file)
## if (basename(file) != paste0(name, ".", ext))
## found <- FALSE
## else {
## found <- TRUE
## zfile <- file
## zipname <- file.path(dirname(file), "Rdata.zip")
## if (file.exists(zipname)) {
## Rdatadir <- tempfile("Rdata")
## dir.create(Rdatadir, showWarnings = FALSE)
## topic <- basename(file)
## rc <- .External(C_unzip, zipname, topic,
## Rdatadir, FALSE, TRUE, FALSE, FALSE)
## if (rc == 0L)
## zfile <- file.path(Rdatadir, topic)
## }
## if (zfile != file)
## on.exit(unlink(zfile))
## switch(ext, R = , r = {
## library("utils")
## sys.source(zfile, chdir = TRUE, envir = tmp_env)
## }, RData = , rdata = , rda = load(zfile,
## envir = tmp_env), TXT = , txt = , tab = ,
## tab.gz = , tab.bz2 = , tab.xz = , txt.gz = ,
## txt.bz2 = , txt.xz = assign(name, my_read_table(zfile,
## header = TRUE, as.is = FALSE), envir = tmp_env),
## CSV = , csv = , csv.gz = , csv.bz2 = ,
## csv.xz = assign(name, my_read_table(zfile,
## header = TRUE, sep = ";", as.is = FALSE),
## envir = tmp_env), found <- FALSE)
## }
## if (found)
## break
## }
## if (verbose)
## message(if (!found)
## "*NOT* ", "found", domain = NA)
## }
## if (found)
## break
## }
## if (!found) {
## warning(gettextf("data set %s not found", sQuote(name)),
## domain = NA)
## }
## else if (!overwrite) {
## for (o in ls(envir = tmp_env, all.names = TRUE)) {
## if (exists(o, envir = envir, inherits = FALSE))
## warning(gettextf("an object named %s already exists and will not be overwritten",
## sQuote(o)))
## else assign(o, get(o, envir = tmp_env, inherits = FALSE),
## envir = envir)
## }
## rm(tmp_env)
## }
## }
## invisible(names)
## }
## <bytecode: 0x7fa9850cc860>
## <environment: namespace:utils>file_path <- "sample_data.csv"
write.csv(flights_data, file = file_path, row.names = FALSE)
file.exists(file_path)## [1] TRUEglimpse(flights_data)## Rows: 5
## Columns: 5
## $ Cities <chr> "Los Angeles", "Phoenix", "San Diego", "San Francisco"…
## $ Alaska_on_time <dbl> 497, 221, 212, 503, 1841
## $ Alaska_delayed <dbl> 62, 12, 20, 102, 305
## $ Am_west_on_time <dbl> 694, 4840, 383, 320, 201
## $ Am_west_delayed <dbl> 117, 415, 65, 129, 61Let’s add two new columns to the data set” arr_delays (delayed flights) and ontime_arr (flights that arrived on time):
flights_data |>
mutate(
arr_delays = Alaska_delayed + Am_west_delayed,
ontime_arr = Alaska_on_time + Am_west_on_time) ## Cities Alaska_on_time Alaska_delayed Am_west_on_time Am_west_delayed
## 1 Los Angeles 497 62 694 117
## 2 Phoenix 221 12 4840 415
## 3 San Diego 212 20 383 65
## 4 San Francisco 503 102 320 129
## 5 Seattle 1841 305 201 61
## arr_delays ontime_arr
## 1 179 1191
## 2 427 5061
## 3 85 595
## 4 231 823
## 5 366 2042Let’s also push the new variables or columns to the front of the data frame using the .before = 1
flights_data |>
mutate(
arr_delays = Alaska_delayed + Am_west_delayed,
ontime_arr = Alaska_on_time + Am_west_on_time,
.before = 1) ## arr_delays ontime_arr Cities Alaska_on_time Alaska_delayed
## 1 179 1191 Los Angeles 497 62
## 2 427 5061 Phoenix 221 12
## 3 85 595 San Diego 212 20
## 4 231 823 San Francisco 503 102
## 5 366 2042 Seattle 1841 305
## Am_west_on_time Am_west_delayed
## 1 694 117
## 2 4840 415
## 3 383 65
## 4 320 129
## 5 201 61Let’s push the new columns to the front of the data frame using the function relocate().
flights_data |>
mutate(
arr_delays = Alaska_delayed + Am_west_delayed,
ontime_arr = Alaska_on_time + Am_west_on_time) |>
relocate(arr_delays, ontime_arr)## arr_delays ontime_arr Cities Alaska_on_time Alaska_delayed
## 1 179 1191 Los Angeles 497 62
## 2 427 5061 Phoenix 221 12
## 3 85 595 San Diego 212 20
## 4 231 823 San Francisco 503 102
## 5 366 2042 Seattle 1841 305
## Am_west_on_time Am_west_delayed
## 1 694 117
## 2 4840 415
## 3 383 65
## 4 320 129
## 5 201 61flights_data2 <-flights_data |>
mutate(
arr_delays = Alaska_delayed + Am_west_delayed,
ontime_arr = Alaska_on_time + Am_west_on_time) |>
relocate(arr_delays, ontime_arr)Let’s now compare the arrival delays for the two airlines: Alaska delays
flights_data2 |>
group_by(Alaska_delayed) |>
summarize(Avg_delay = mean(Alaska_delayed, na.rm = TRUE))## # A tibble: 5 × 2
## Alaska_delayed Avg_delay
## <dbl> <dbl>
## 1 12 12
## 2 20 20
## 3 62 62
## 4 102 102
## 5 305 305Am_west_delays
flights_data2 |>
group_by(Am_west_delayed) |>
summarize(
Avg_delay = mean(Am_west_delayed, na.rm = TRUE))## # A tibble: 5 × 2
## Am_west_delayed Avg_delay
## <dbl> <dbl>
## 1 61 61
## 2 65 65
## 3 117 117
## 4 129 129
## 5 415 415Average delay for both airlines:
flights_data2 |>
group_by(arr_delays) |>
summarize(avg_delay = mean(arr_delays))## # A tibble: 5 × 2
## arr_delays avg_delay
## <dbl> <dbl>
## 1 85 85
## 2 179 179
## 3 231 231
## 4 366 366
## 5 427 427Let’s close with summary statistics for both airlines
flights_data2|>
summary(flights_data2)## arr_delays ontime_arr Cities Alaska_on_time
## Min. : 85.0 Min. : 595 Length:5 Min. : 212.0
## 1st Qu.:179.0 1st Qu.: 823 Class :character 1st Qu.: 221.0
## Median :231.0 Median :1191 Mode :character Median : 497.0
## Mean :257.6 Mean :1942 Mean : 654.8
## 3rd Qu.:366.0 3rd Qu.:2042 3rd Qu.: 503.0
## Max. :427.0 Max. :5061 Max. :1841.0
## Alaska_delayed Am_west_on_time Am_west_delayed
## Min. : 12.0 Min. : 201 Min. : 61.0
## 1st Qu.: 20.0 1st Qu.: 320 1st Qu.: 65.0
## Median : 62.0 Median : 383 Median :117.0
## Mean :100.2 Mean :1288 Mean :157.4
## 3rd Qu.:102.0 3rd Qu.: 694 3rd Qu.:129.0
## Max. :305.0 Max. :4840 Max. :415.0```