R/diamonds.R

In burrisk/midamix: Bayesian multiple imputation via mixtures

#' Prices of 1,000 round cut diamonds.
#'
#' A dataset containing the prices and other attributes of 1,000 diamonds.  This is a
#' subset of the diamonds dataset in ggplot2, where 20 percent of the data values are missing
#' completely at random
#'
#' @format A data frame with 1000 rows and 10 variables:
#' \describe{
#'   \item{carat}{weight of the diamond, in carats}
#'   \item{cut}{quality of the cut (Fair, Good, Very Good, Premium, Ideal)}
#'   \item{color}{color of the diamond, from J (worst) to D (best)}
#'   \item{clarity}{a measurement of how clear the diamond is from I1 (worst) to
#'   IF (best)}
#'   \item{table}{width of the top of the diamond relative to its widest point}
#'   \item{depth}{total depth percentage}
#'   \item{price}{price, in US dollars}
#'   \item{x}{length, in mm}
#'   \item{y}{width, in mm}
#'   \item{z}{depth, in mm}
#' }
"diamonds"