R/data-winery_cars.R

In openintro: Data Sets and Supplemental Functions from 'OpenIntro' Textbooks and Labs

#' Time Between Gondola Cars at Sterling Winery
#'
#' These times represent times between gondolas at Sterling Winery. The main
#' take-away: there are 7 cars, as evidenced by the somewhat regular increases
#' in splits between every 7 cars. The reason the times are slightly
#' non-constant is that the gondolas come off the tracks, so times will change
#' a little between each period.
#'
#' Important context: there was a sufficient line that people were leaving the
#' winery.
#'
#' So why is this data valuable? It indicates that the winery should add one
#' more car since it has a lot of time wasted every 7th car. By adding another
#' car, fewer visitors are likely to be turned away, resulting in increased
#' revenue.
#'
#' @name winery_cars
#' @docType data
#' @format A data frame with 52 observations on the following 2 variables.
#' \describe{
#'   \item{obs_number}{The observation number, e.g. observation 3 was immediately
#'   preceded by observation 2.}
#'   \item{time_until_next}{Time until this gondola car arrived since the last
#'   car had left.}
#'   }
#' @source In-person data collection by David Diez (OpenIntro) on 2013-07-04.
#' @keywords datasets
#' @examples
#'
#' winery_cars$car_number <- rep(1:7, 10)[1:nrow(winery_cars)]
#' col <- COL[ifelse(winery_cars$car_number == 3, 4, 1)]
#' plot(winery_cars[, c("obs_number", "time_until_next")],
#'   col = col, pch = 19
#' )
#' plot(winery_cars$car_number, winery_cars$time_until_next,
#'   col = fadeColor(col, "88"), pch = 19
#' )
"winery_cars"